diff --git a/.gitignore b/.gitignore index 075b254..5a473c7 100644 --- a/.gitignore +++ b/.gitignore @@ -1 +1,7 @@ -/.quarto/ +/.quarto/ +# macOS +.DS_Store + +# Windows +Thumbs.db +Desktop.ini diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..a490b61 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,5 @@ +{ + "githubPullRequests.ignoredPullRequestBranches": [ + "main" + ] +} \ No newline at end of file diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md index 10ba936..e9582e6 100644 --- a/CODE_OF_CONDUCT.md +++ b/CODE_OF_CONDUCT.md @@ -1,32 +1,32 @@ -# Cytometry In R Code of Conduct - -Like the flow cytometry community as a whole, the Cytometry In R team and community is made up of a mixture of professionals and volunteers from all over the world, working on every aspect of the mission - including mentorship, teaching, and connecting people. - -Diversity is one of our huge strengths, but it can also lead to communication issues and unhappiness. To that end, we have a few ground rules that we ask people to adhere to. This code applies equally to founders, mentors and those seeking help and guidance. - -This isn’t an exhaustive list of things that you can’t do. Rather, take it in the spirit in which it’s intended - a guide to make it easier to enrich all of us and the technical communities in which we participate. - -This code of conduct applies to all spaces managed by the UMGCCC FCSR's Cytometry In R course. This includes IRC, the mailing lists, the issue tracker, DSF events, and any other forums created by the project team which the community uses for communication. In addition, violations of this code outside these spaces may affect a person's ability to participate within them. - -If you believe someone is violating the code of conduct, we ask that you report it by emailing [flowcore@som.umaryland.edu](mailto:flowcore@som.umaryland.edu). - -- **Be friendly and patient.** -- **Be welcoming.** We strive to be a community that welcomes and supports people of all backgrounds and identities. This includes, but is not limited to members of any race, ethnicity, culture, national origin, colour, immigration status, social and economic class, educational level, sex, sexual orientation, gender identity and expression, age, size, family status, political belief, religion, and mental and physical ability. -- **Be considerate.** Your work will be used by other people, and you in turn will depend on the work of others. Any decision you take will affect users and colleagues, and you should take those consequences into account when making decisions. Remember that we're a world-wide community, so you might not be communicating in someone else's primary language. -- **Be respectful.** Not all of us will agree all the time, but disagreement is no excuse for poor behavior and poor manners. We might all experience some frustration now and then, but we cannot allow that frustration to turn into a personal attack. It’s important to remember that a community where people feel uncomfortable or threatened is not a productive one. Members of the Cytometry In R community should be respectful when dealing with other members as well as with people outside the Cytometry In R community. -- **Be careful in the words that you choose.** We are a community of professionals, and we conduct ourselves professionally. Be kind to others. Do not insult or put down other participants. Harassment and other exclusionary behavior aren't acceptable. This includes, but is not limited to: - - Violent threats or language directed against another person. - - Discriminatory jokes and language. - - Posting sexually explicit or violent material. - - Posting (or threatening to post) other people's personally identifying information ("doxing"). - - Personal insults, especially those using racist or sexist terms. - - Unwelcome sexual attention. - - Advocating for, or encouraging, any of the above behavior. - - Repeated harassment of others. In general, if someone asks you to stop, then stop. -- **When we disagree, try to understand why.** Disagreements, both social and technical, happen all the time and Cytometry In R is no exception. It is important that we resolve disagreements and differing views constructively. Remember that we’re different. The strength of Cytometry In R comes from its varied community, people from a wide range of backgrounds. Different people have different perspectives on issues. Being unable to understand why someone holds a viewpoint doesn’t mean that they’re wrong. Don’t forget that it is human to err and blaming each other doesn’t get us anywhere. Instead, focus on helping to resolve issues and learning from mistakes. - -Original text courtesy of the [Speak Up! project](http://web.archive.org/web/20141109123859/http://speakup.io/coc.html). - -## Questions? - -If you have any questions, feel free to [contact us](mailto:flowcore@som.umaryland.edu). +# Cytometry In R Code of Conduct + +Like the flow cytometry community as a whole, the Cytometry In R team and community is made up of a mixture of professionals and volunteers from all over the world, working on every aspect of the mission - including mentorship, teaching, and connecting people. + +Diversity is one of our huge strengths, but it can also lead to communication issues and unhappiness. To that end, we have a few ground rules that we ask people to adhere to. This code applies equally to founders, mentors and those seeking help and guidance. + +This isn’t an exhaustive list of things that you can’t do. Rather, take it in the spirit in which it’s intended - a guide to make it easier to enrich all of us and the technical communities in which we participate. + +This code of conduct applies to all spaces managed by the UMGCCC FCSR's Cytometry In R course. This includes IRC, the mailing lists, the issue tracker, DSF events, and any other forums created by the project team which the community uses for communication. In addition, violations of this code outside these spaces may affect a person's ability to participate within them. + +If you believe someone is violating the code of conduct, we ask that you report it by emailing [flowcore@som.umaryland.edu](mailto:flowcore@som.umaryland.edu). + +- **Be friendly and patient.** +- **Be welcoming.** We strive to be a community that welcomes and supports people of all backgrounds and identities. This includes, but is not limited to members of any race, ethnicity, culture, national origin, colour, immigration status, social and economic class, educational level, sex, sexual orientation, gender identity and expression, age, size, family status, political belief, religion, and mental and physical ability. +- **Be considerate.** Your work will be used by other people, and you in turn will depend on the work of others. Any decision you take will affect users and colleagues, and you should take those consequences into account when making decisions. Remember that we're a world-wide community, so you might not be communicating in someone else's primary language. +- **Be respectful.** Not all of us will agree all the time, but disagreement is no excuse for poor behavior and poor manners. We might all experience some frustration now and then, but we cannot allow that frustration to turn into a personal attack. It’s important to remember that a community where people feel uncomfortable or threatened is not a productive one. Members of the Cytometry In R community should be respectful when dealing with other members as well as with people outside the Cytometry In R community. +- **Be careful in the words that you choose.** We are a community of professionals, and we conduct ourselves professionally. Be kind to others. Do not insult or put down other participants. Harassment and other exclusionary behavior aren't acceptable. This includes, but is not limited to: + - Violent threats or language directed against another person. + - Discriminatory jokes and language. + - Posting sexually explicit or violent material. + - Posting (or threatening to post) other people's personally identifying information ("doxing"). + - Personal insults, especially those using racist or sexist terms. + - Unwelcome sexual attention. + - Advocating for, or encouraging, any of the above behavior. + - Repeated harassment of others. In general, if someone asks you to stop, then stop. +- **When we disagree, try to understand why.** Disagreements, both social and technical, happen all the time and Cytometry In R is no exception. It is important that we resolve disagreements and differing views constructively. Remember that we’re different. The strength of Cytometry In R comes from its varied community, people from a wide range of backgrounds. Different people have different perspectives on issues. Being unable to understand why someone holds a viewpoint doesn’t mean that they’re wrong. Don’t forget that it is human to err and blaming each other doesn’t get us anywhere. Instead, focus on helping to resolve issues and learning from mistakes. + +Original text courtesy of the [Speak Up! project](http://web.archive.org/web/20141109123859/http://speakup.io/coc.html). + +## Questions? + +If you have any questions, feel free to [contact us](mailto:flowcore@som.umaryland.edu). diff --git a/COMMIT_EDITMSG b/COMMIT_EDITMSG new file mode 100644 index 0000000..f74918f --- /dev/null +++ b/COMMIT_EDITMSG @@ -0,0 +1,188 @@ +Macbook sync + +# Conflicts: +# _quarto.yml +# docs/Schedule.html +# docs/course/00_BonusContent/Immport/images/index.html +# docs/course/00_BonusContent/index.html +# docs/course/00_Floreada/index.html +# docs/course/00_Git/index.html +# docs/course/00_GitHub/index.html +# docs/course/00_Homeworks/index.html +# docs/course/00_Positron/index.html +# docs/course/00_Quarto/index.html +# docs/course/00_WorkstationSetup/Linux.html +# docs/course/00_WorkstationSetup/MacOS.html +# docs/course/00_WorkstationSetup/Windows.html +# docs/course/00_WorkstationSetup/index.html +# docs/course/01_InstallingRPackages/index.html +# docs/course/02_FilePaths/Downsampler.html +# docs/course/02_FilePaths/index.html +# docs/course/03_InsideFCSFile/index.html +# docs/course/03_InsideFCSFile/slides.html +# docs/course/index.html +# docs/search.json + +# Please enter the commit message for your changes. 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a/CONTRIBUTING.md b/CONTRIBUTING.md index 1eff111..177e13a 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -1,32 +1,32 @@ -We gladly accept community contributions to make the project better. These typically take the form of improvements to either the text, code or both. - -# License - -In our commitment to open-science and open-source, the teaching materials for our mini-course are licensed under the CC-BY-SA license, while thc ode is licensed under the copyleft AGPL3-0 license. All community contributions to the project will fall under the same licenses. We ask that any contributions be your own words and code, and not verbatum copy-and-paste from a LLM. - -# Sign Your Work - -The _sign-off_ is a simple line at the end of the message for a commit. All commits in your pull request need to be signed. Your signature certifies that you wrote the patch or otherwise have the right to contribute the material (see [Developer Certificate of Origin](https://developercertificate.org)): - -``` -This is my commit message - -Signed-off-by: David Rach -``` - -Git has a [`-s`](https://git-scm.com/docs/git-commit#Documentation/git-commit.txt---signoff) command line option to append this automatically to your commit message: - -```bash -$ git commit -s -m "This is my commit message" -``` - -# Pull Request - -1) Open an issue, mention what you want to do. That way we can avoid misplaced effort of multiple people tackling the same issue separately. -2) Fork our repository. -3) Create your own branch. -4) Make your edits, keeping commit changes restricted to individual files. -5) Sign all your commits. -6) When ready, open a pull request from your branch to main. -7) We will reply with comments, update with any edits. -8) After review, we will merge or suggest additional changes. +We gladly accept community contributions to make the project better. These typically take the form of improvements to either the text, code or both. + +# License + +In our commitment to open-science and open-source, the teaching materials for our mini-course are licensed under the CC-BY-SA license, while thc ode is licensed under the copyleft AGPL3-0 license. All community contributions to the project will fall under the same licenses. We ask that any contributions be your own words and code, and not verbatum copy-and-paste from a LLM. + +# Sign Your Work + +The _sign-off_ is a simple line at the end of the message for a commit. All commits in your pull request need to be signed. Your signature certifies that you wrote the patch or otherwise have the right to contribute the material (see [Developer Certificate of Origin](https://developercertificate.org)): + +``` +This is my commit message + +Signed-off-by: David Rach +``` + +Git has a [`-s`](https://git-scm.com/docs/git-commit#Documentation/git-commit.txt---signoff) command line option to append this automatically to your commit message: + +```bash +$ git commit -s -m "This is my commit message" +``` + +# Pull Request + +1) Open an issue, mention what you want to do. That way we can avoid misplaced effort of multiple people tackling the same issue separately. +2) Fork our repository. +3) Create your own branch. +4) Make your edits, keeping commit changes restricted to individual files. +5) Sign all your commits. +6) When ready, open a pull request from your branch to main. +7) We will reply with comments, update with any edits. +8) After review, we will merge or suggest additional changes. diff --git a/ExistingResources.qmd b/ExistingResources.qmd index 22b65a5..67d6d3c 100644 --- a/ExistingResources.qmd +++ b/ExistingResources.qmd @@ -1,216 +1,216 @@ ---- -title: "Existing Resources" -format: html -toc: TRUE -toc-location: right -sidebar: false ---- - -![](images/WebsiteBanner.png) - -
-[![AGPL-3.0][agpl3-shield]][agpl3] -[![CC BY-SA 4.0][cc-by-sa-shield]][cc-by-sa] -
- -We are not the first "Cytometry in R" course, nor will we be the last. This page is linking to the already existant online Cytometry in R resources that we have encountered and benefited from during our own learning journey. May they prove useful to you as you progress your way through yours! - -
- ---- - -# Christopher Hall - Flow Cytometry Data Analysis in R - -[Cytometry-R-Scripts: R scripts to help with your flow cytometry analysis](https://github.com/hally166/Cytometry-R-scripts) - -[R_flowcytometry_course: The files and presentation from the Cytometry Core Facility flow cytometry data analysis course in R](https://github.com/hally166/R_flowcytometry_course) - -### Installation and Loading Data - -[(1) Flow Cytometry Data Analysis in R - Installation and Loading Data](https://youtu.be/2INqQNMNaV0?si=h_3Xa3bIBr0E9199) - - - -### Compensation, Cleaning, Transformation, Visualization - -[(2) Flow Cytometry Data Analysis in R: compensation, cleaning, transformation, visualization](https://www.youtube.com/watch?v=WWa7dwwiLvI&list=PLonl5DIJ0E5_nLR2iF9bILHB1W7a5LGqO&index=3) - - - -### Gating with flowWorkspace - -[(3) Flow Cytometry Data Analysis in R: gating with flowWorkspace](https://youtu.be/ijHOGHP82EY?si=87OB8t8wynJNnTf3) - - - - -### Visualization - -[(4) Flow Cytometry Data Analysis in R: Visualisation](https://youtu.be/Y7_ux9Py3Vg?si=2wG5WmI8n3IBCyHD) - - - -
- ---- - - -# Ozette Technologies - BioC 2023 Workshop - -Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew McDavid. - -[Workshop: Reproducible and programmatic analysis of flow cytometry experiments with the cytoverse](https://youtu.be/_8x-prIxJgw?si=Tm-QoBQ3qc568xXD) - - - -
- ---- - -# Pritam Kumar Panda - Flow Cytometry Data Analysis & Visualization in R using CytoExploreR - -[Flow-Cytometry-analysis-in-R](https://github.com/pritampanda15/Proteomics/tree/main/Flow-Cytometry-analysis-in-R-main) - -[CytoExploreR-Interactive-visualization](https://github.com/pritampanda15/Proteomics/tree/main/CytoExploreR-Interactive-visualization-main) - -### Complete Guide - -[Flow Cytometry Data Analysis & Visualization in R using CytoExploreR: Complete Guide](https://youtu.be/AvIvRorrh8c?si=MVViua5fSBrahtzv) - - - -
- ---- - - -# Bioinformatics DotCa - Introduction to Flow Cytometry in R - -### Introduction to Flow Cytometry in R - -[Introduction to Flow Cytometry in R](https://youtu.be/0_dN8VKhOJ0?si=Mn7UB0Gps5twqAqK) - - - -### Exploring FCM Data in R - -[Exploring FCM Data in R](https://youtu.be/IE8X32HVA9I?si=0xTVBGWanRele4WT) - - - -### Processing and Quality Assurance of FCM Data - -[Processing and Quality Assurance of FCM Data](https://youtu.be/OnAcZzBSc54?si=Z-RijMLvhvxqXvV2) - - - -### 1D Dynamic Gating - -[1D Dynamic Gating](https://youtu.be/Yd_IPMDFm4Y?si=9OikOeFnkEMCRURl) - - - -### Clustering and Additional FCM Tools - -[Clustering and Additional FCM Tools](https://youtu.be/xnvNCsu56Vo?si=botz0swIm31W5340) - - - -# Tulika Rai - Learn Innovatively With Me - -### flowAI Flow Cytometry Data Cleaning using R - -[flowAI Flow Cytometry Data Cleaning using R: A Step-by-step Tutorial](https://youtu.be/PvB37SEe7lI?si=X3iYcGT7A3G603oP) - - - -### tSNE UMAP TRIMAP colorization or Transformation using R script - -[tSNE UMAP TRIMAP colorization or Transformation using R script ](https://youtu.be/l9dg4QUYSOM?si=gW218zzDqQEtjtpY) - - - -
- ---- - -# Givanna Putri - Introduction to Cytometry Data Analysis in R workshop - -[ACS 2021 Workshops - Introduction to Cytometry Data Analysis in R workshop](https://youtu.be/-0QrXgk_NRw?si=GqcjU-_MQ3UvYwvI) - - - -
- ---- - -# Timothy Keyes - - -[{tidytof}: Predicting Patient Outcomes from Single-cell Data using Tidy Data Principles](https://youtu.be/5NhpC836aSc?si=QqoeW31cQcHFzu5W) - - - -
- ---- - -# Ryan Duggan - Cytometry on Air - -[Cytometry on Air: Analyzing Flow Cytometry Data in R](https://www.youtube.com/live/_B7mo6dB3BU?si=eW20X4YWgaCoYnfw) Presentation by TJ Chen and Greg Finak, - - - -
- ---- - - -# Guillaume Beyrend - Learn Cytometry - -[Learn Cytometry](https://learncytometry.com/videos/) Originally appeared to have been paywalled, doesn't currently appear to be the case. - -
- ---- - -# Hong Qin - flow analysis in R - -### Flow Analysis in R - -[flow analysis in R, bio125, Spring 2015](https://youtu.be/r7Mf6joCNzM?si=5j9Fy8fn6d7o0Z-u) - - - -### Flow Cytometer Data Analysis - -[BIO233 demo, flow cytometer data analysis, simple example](https://youtu.be/BN5Ldu1AFgk?si=FV2K7jJGe9H6na08) - - - - -
- ---- - -# Swayam Prabha - Flow cytometry data analysis in R/Bioconductor - -[Lecture 15 : Flow cytometry data analysis in R/Bioconductor](https://youtu.be/g-VUT3riwOM?si=SlX88J3HpsjYaqFI) - - - -
- ---- - - -
-[![AGPL-3.0][agpl3-image]][agpl3] -[![CC BY-SA 4.0][cc-by-sa-image]][cc-by-sa] -
- -[cc-by-sa]: http://creativecommons.org/licenses/by-sa/4.0/ -[cc-by-sa-image]: https://licensebuttons.net/l/by-sa/4.0/88x31.png -[cc-by-sa-shield]: https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg -[agpl3]: https://www.gnu.org/licenses/agpl-3.0.en.html -[agpl3-image]: https://www.gnu.org/graphics/agplv3-with-text-162x68.png +--- +title: "Existing Resources" +format: html +toc: TRUE +toc-location: right +sidebar: false +--- + +![](images/WebsiteBanner.png) + +
+[![AGPL-3.0][agpl3-shield]][agpl3] +[![CC BY-SA 4.0][cc-by-sa-shield]][cc-by-sa] +
+ +We are not the first "Cytometry in R" course, nor will we be the last. This page is linking to the already existant online Cytometry in R resources that we have encountered and benefited from during our own learning journey. May they prove useful to you as you progress your way through yours! + +
+ +--- + +# Christopher Hall - Flow Cytometry Data Analysis in R + +[Cytometry-R-Scripts: R scripts to help with your flow cytometry analysis](https://github.com/hally166/Cytometry-R-scripts) + +[R_flowcytometry_course: The files and presentation from the Cytometry Core Facility flow cytometry data analysis course in R](https://github.com/hally166/R_flowcytometry_course) + +### Installation and Loading Data + +[(1) Flow Cytometry Data Analysis in R - Installation and Loading Data](https://youtu.be/2INqQNMNaV0?si=h_3Xa3bIBr0E9199) + + + +### Compensation, Cleaning, Transformation, Visualization + +[(2) Flow Cytometry Data Analysis in R: compensation, cleaning, transformation, visualization](https://www.youtube.com/watch?v=WWa7dwwiLvI&list=PLonl5DIJ0E5_nLR2iF9bILHB1W7a5LGqO&index=3) + + + +### Gating with flowWorkspace + +[(3) Flow Cytometry Data Analysis in R: gating with flowWorkspace](https://youtu.be/ijHOGHP82EY?si=87OB8t8wynJNnTf3) + + + + +### Visualization + +[(4) Flow Cytometry Data Analysis in R: Visualisation](https://youtu.be/Y7_ux9Py3Vg?si=2wG5WmI8n3IBCyHD) + + + +
+ +--- + + +# Ozette Technologies - BioC 2023 Workshop + +Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew McDavid. + +[Workshop: Reproducible and programmatic analysis of flow cytometry experiments with the cytoverse](https://youtu.be/_8x-prIxJgw?si=Tm-QoBQ3qc568xXD) + + + +
+ +--- + +# Pritam Kumar Panda - Flow Cytometry Data Analysis & Visualization in R using CytoExploreR + +[Flow-Cytometry-analysis-in-R](https://github.com/pritampanda15/Proteomics/tree/main/Flow-Cytometry-analysis-in-R-main) + +[CytoExploreR-Interactive-visualization](https://github.com/pritampanda15/Proteomics/tree/main/CytoExploreR-Interactive-visualization-main) + +### Complete Guide + +[Flow Cytometry Data Analysis & Visualization in R using CytoExploreR: Complete Guide](https://youtu.be/AvIvRorrh8c?si=MVViua5fSBrahtzv) + + + +
+ +--- + + +# Bioinformatics DotCa - Introduction to Flow Cytometry in R + +### Introduction to Flow Cytometry in R + +[Introduction to Flow Cytometry in R](https://youtu.be/0_dN8VKhOJ0?si=Mn7UB0Gps5twqAqK) + + + +### Exploring FCM Data in R + +[Exploring FCM Data in R](https://youtu.be/IE8X32HVA9I?si=0xTVBGWanRele4WT) + + + +### Processing and Quality Assurance of FCM Data + +[Processing and Quality Assurance of FCM Data](https://youtu.be/OnAcZzBSc54?si=Z-RijMLvhvxqXvV2) + + + +### 1D Dynamic Gating + +[1D Dynamic Gating](https://youtu.be/Yd_IPMDFm4Y?si=9OikOeFnkEMCRURl) + + + +### Clustering and Additional FCM Tools + +[Clustering and Additional FCM Tools](https://youtu.be/xnvNCsu56Vo?si=botz0swIm31W5340) + + + +# Tulika Rai - Learn Innovatively With Me + +### flowAI Flow Cytometry Data Cleaning using R + +[flowAI Flow Cytometry Data Cleaning using R: A Step-by-step Tutorial](https://youtu.be/PvB37SEe7lI?si=X3iYcGT7A3G603oP) + + + +### tSNE UMAP TRIMAP colorization or Transformation using R script + +[tSNE UMAP TRIMAP colorization or Transformation using R script ](https://youtu.be/l9dg4QUYSOM?si=gW218zzDqQEtjtpY) + + + +
+ +--- + +# Givanna Putri - Introduction to Cytometry Data Analysis in R workshop + +[ACS 2021 Workshops - Introduction to Cytometry Data Analysis in R workshop](https://youtu.be/-0QrXgk_NRw?si=GqcjU-_MQ3UvYwvI) + + + +
+ +--- + +# Timothy Keyes - + +[{tidytof}: Predicting Patient Outcomes from Single-cell Data using Tidy Data Principles](https://youtu.be/5NhpC836aSc?si=QqoeW31cQcHFzu5W) + + + +
+ +--- + +# Ryan Duggan - Cytometry on Air + +[Cytometry on Air: Analyzing Flow Cytometry Data in R](https://www.youtube.com/live/_B7mo6dB3BU?si=eW20X4YWgaCoYnfw) Presentation by TJ Chen and Greg Finak, + + + +
+ +--- + + +# Guillaume Beyrend - Learn Cytometry + +[Learn Cytometry](https://learncytometry.com/videos/) Originally appeared to have been paywalled, doesn't currently appear to be the case. + +
+ +--- + +# Hong Qin - flow analysis in R + +### Flow Analysis in R + +[flow analysis in R, bio125, Spring 2015](https://youtu.be/r7Mf6joCNzM?si=5j9Fy8fn6d7o0Z-u) + + + +### Flow Cytometer Data Analysis + +[BIO233 demo, flow cytometer data analysis, simple example](https://youtu.be/BN5Ldu1AFgk?si=FV2K7jJGe9H6na08) + + + + +
+ +--- + +# Swayam Prabha - Flow cytometry data analysis in R/Bioconductor + +[Lecture 15 : Flow cytometry data analysis in R/Bioconductor](https://youtu.be/g-VUT3riwOM?si=SlX88J3HpsjYaqFI) + + + +
+ +--- + + +
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Distribution of +Creative Commons public licenses does not create a lawyer-client or +other relationship. Creative Commons makes its licenses and related +information available on an "as-is" basis. Creative Commons gives no +warranties regarding its licenses, any material licensed under their +terms and conditions, or any related information. Creative Commons +disclaims all liability for damages resulting from their use to the +fullest extent possible. + +Using Creative Commons Public Licenses + +Creative Commons public licenses provide a standard set of terms and +conditions that creators and other rights holders may use to share +original works of authorship and other material subject to copyright +and certain other rights specified in the public license below. The +following considerations are for informational purposes only, are not +exhaustive, and do not form part of our licenses. + + Considerations for licensors: Our public licenses are + intended for use by those authorized to give the public + permission to use material in ways otherwise restricted by + copyright and certain other rights. Our licenses are + irrevocable. Licensors should read and understand the terms + and conditions of the license they choose before applying it. + Licensors should also secure all rights necessary before + applying our licenses so that the public can reuse the + material as expected. Licensors should clearly mark any + material not subject to the license. This includes other CC- + licensed material, or material used under an exception or + limitation to copyright. 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Adapted Material means material subject to Copyright and Similar + Rights that is derived from or based upon the Licensed Material + and in which the Licensed Material is translated, altered, + arranged, transformed, or otherwise modified in a manner requiring + permission under the Copyright and Similar Rights held by the + Licensor. For purposes of this Public License, where the Licensed + Material is a musical work, performance, or sound recording, + Adapted Material is always produced where the Licensed Material is + synched in timed relation with a moving image. + + b. Adapter's License means the license You apply to Your Copyright + and Similar Rights in Your contributions to Adapted Material in + accordance with the terms and conditions of this Public License. + + c. BY-SA Compatible License means a license listed at + creativecommons.org/compatiblelicenses, approved by Creative + Commons as essentially the equivalent of this Public License. + + d. Copyright and Similar Rights means copyright and/or similar rights + closely related to copyright including, without limitation, + performance, broadcast, sound recording, and Sui Generis Database + Rights, without regard to how the rights are labeled or + categorized. For purposes of this Public License, the rights + specified in Section 2(b)(1)-(2) are not Copyright and Similar + Rights. + + e. Effective Technological Measures means those measures that, in the + absence of proper authority, may not be circumvented under laws + fulfilling obligations under Article 11 of the WIPO Copyright + Treaty adopted on December 20, 1996, and/or similar international + agreements. + + f. Exceptions and Limitations means fair use, fair dealing, and/or + any other exception or limitation to Copyright and Similar Rights + that applies to Your use of the Licensed Material. + + g. License Elements means the license attributes listed in the name + of a Creative Commons Public License. The License Elements of this + Public License are Attribution and ShareAlike. + + h. Licensed Material means the artistic or literary work, database, + or other material to which the Licensor applied this Public + License. + + i. Licensed Rights means the rights granted to You subject to the + terms and conditions of this Public License, which are limited to + all Copyright and Similar Rights that apply to Your use of the + Licensed Material and that the Licensor has authority to license. + + j. Licensor means the individual(s) or entity(ies) granting rights + under this Public License. + + k. Share means to provide material to the public by any means or + process that requires permission under the Licensed Rights, such + as reproduction, public display, public performance, distribution, + dissemination, communication, or importation, and to make material + available to the public including in ways that members of the + public may access the material from a place and at a time + individually chosen by them. + + l. Sui Generis Database Rights means rights other than copyright + resulting from Directive 96/9/EC of the European Parliament and of + the Council of 11 March 1996 on the legal protection of databases, + as amended and/or succeeded, as well as other essentially + equivalent rights anywhere in the world. + + m. You means the individual or entity exercising the Licensed Rights + under this Public License. Your has a corresponding meaning. + + +Section 2 -- Scope. + + a. License grant. + + 1. 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Except for the limited purpose of indicating that +material is shared under a Creative Commons public license or as +otherwise permitted by the Creative Commons policies published at +creativecommons.org/policies, Creative Commons does not authorize the +use of the trademark "Creative Commons" or any other trademark or logo +of Creative Commons without its prior written consent including, +without limitation, in connection with any unauthorized modifications +to any of its public licenses or any other arrangements, +understandings, or agreements concerning use of licensed material. For +the avoidance of doubt, this paragraph does not form part of the +public licenses. + +Creative Commons may be contacted at creativecommons.org. diff --git a/PackageWalkthroughs.qmd b/PackageWalkthroughs.qmd index 9819141..0a58ac6 100644 --- a/PackageWalkthroughs.qmd +++ b/PackageWalkthroughs.qmd @@ -1,179 +1,179 @@ ---- -title: "Package Walkthroughs" -format: html -toc: TRUE -toc-location: right -sidebar: false ---- - -![](images/WebsiteBanner.png) - -
-[![AGPL-3.0][agpl3-shield]][agpl3] -[![CC BY-SA 4.0][cc-by-sa-shield]][cc-by-sa] -
- - -# Background - -The purpose of this page is to host the Vignette writing challenge entries. There are a substantial number of R packages on both Bioconductor and GitHub that we will not be able to get to during the course. My goal for the off-weeks is to have the class assist in navigating through the existing vignettes/articles for each package, and write up a basic .qmd file to help anyone trying to use these packages have a simpler learning curve in doing so than they would have otherwise. - -# Bioconductor - -## flowCore - -## cytolib - -## flowWorkspace - -## ncdfFlow - -## flowViz - -## FlowSOM - -## ggcyto - -## openCyto - -## quantiseqr - -## flowStats - -## CytoML - -## CATALYST - -## flowAI - -## diffcyt - -## flowDensity - -## flowMeans - -## PeacoQC - -## flowFP - -## flowClean - -## flowPeaks - -## COMPASS - -## SamSPECTRAL - -## flowVS - -## cydar - -## flowMerge - -## flowTrans - -## distinct - -## flowCut - -## flowMatch - -## flowBeads - -## flowTime - -## sccomp - -## flowCHIC - -## flowSpecs - -## DepecheR - -## treekoR - -## flowBin - -## MetaCyto - -## immunoClust - -## scDataviz - -## cytoMEM - -## flowPloidy - -## plotGrouper - -## CytoDx - -## Sconify - -## flowPlots - -## GateFinder - -## flowGate - -## flowGraph - -## infinityFlow - -## cyanoFilter - -## optimalFlow - -## CytoGLMM - -## scifer - -## cytoKernel - -## CytoPipeline - -## censcyt - -## flowCyBar - -## reconsi - -## MACSQuantifyR - -## CytoMDS - -## CytoPipelineGUI - -## MAPFX - -## spillR - -## tidyFlowCore - -## CyTOFpower - -## tidytof - -## SuperCellCyto - -# GitHub - -## autospill - -## autospectral - -## flowMagic - - -
-[![AGPL-3.0][agpl3-image]][agpl3] -[![CC BY-SA 4.0][cc-by-sa-image]][cc-by-sa] -
- -[cc-by-sa]: http://creativecommons.org/licenses/by-sa/4.0/ -[cc-by-sa-image]: https://licensebuttons.net/l/by-sa/4.0/88x31.png -[cc-by-sa-shield]: https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg -[agpl3]: https://www.gnu.org/licenses/agpl-3.0.en.html -[agpl3-image]: https://www.gnu.org/graphics/agplv3-with-text-162x68.png -[agpl3-shield]: https://img.shields.io/badge/license-AGPLv3-blue - +--- +title: "Package Walkthroughs" +format: html +toc: TRUE +toc-location: right +sidebar: false +--- + +![](images/WebsiteBanner.png) + +
+[![AGPL-3.0][agpl3-shield]][agpl3] +[![CC BY-SA 4.0][cc-by-sa-shield]][cc-by-sa] +
+ + +# Background + +The purpose of this page is to host the Vignette writing challenge entries. There are a substantial number of R packages on both Bioconductor and GitHub that we will not be able to get to during the course. My goal for the off-weeks is to have the class assist in navigating through the existing vignettes/articles for each package, and write up a basic .qmd file to help anyone trying to use these packages have a simpler learning curve in doing so than they would have otherwise. + +# Bioconductor + +## flowCore + +## cytolib + +## flowWorkspace + +## ncdfFlow + +## flowViz + +## FlowSOM + +## ggcyto + +## openCyto + +## quantiseqr + +## flowStats + +## CytoML + +## CATALYST + +## flowAI + +## diffcyt + +## flowDensity + +## flowMeans + +## PeacoQC + +## flowFP + +## flowClean + +## flowPeaks + +## COMPASS + +## SamSPECTRAL + +## flowVS + +## cydar + +## flowMerge + +## flowTrans + +## distinct + +## flowCut + +## flowMatch + +## flowBeads + +## flowTime + +## sccomp + +## flowCHIC + +## flowSpecs + +## DepecheR + +## treekoR + +## flowBin + +## MetaCyto + +## immunoClust + +## scDataviz + +## cytoMEM + +## flowPloidy + +## plotGrouper + +## CytoDx + +## Sconify + +## flowPlots + +## GateFinder + +## flowGate + +## flowGraph + +## infinityFlow + +## cyanoFilter + +## optimalFlow + +## CytoGLMM + +## scifer + +## cytoKernel + +## CytoPipeline + +## censcyt + +## flowCyBar + +## reconsi + +## MACSQuantifyR + +## CytoMDS + +## CytoPipelineGUI + +## MAPFX + +## spillR + +## tidyFlowCore + +## CyTOFpower + +## tidytof + +## SuperCellCyto + +# GitHub + +## autospill + +## autospectral + +## flowMagic + + +
+[![AGPL-3.0][agpl3-image]][agpl3] +[![CC BY-SA 4.0][cc-by-sa-image]][cc-by-sa] +
+ +[cc-by-sa]: http://creativecommons.org/licenses/by-sa/4.0/ +[cc-by-sa-image]: https://licensebuttons.net/l/by-sa/4.0/88x31.png +[cc-by-sa-shield]: https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg +[agpl3]: https://www.gnu.org/licenses/agpl-3.0.en.html +[agpl3-image]: https://www.gnu.org/graphics/agplv3-with-text-162x68.png +[agpl3-shield]: https://img.shields.io/badge/license-AGPLv3-blue + diff --git a/README.md b/README.md index 48d8243..69261ff 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,44 @@ +<<<<<<< HEAD +![](images/WebsiteBanner.png) + +Cytometry in R is a free virtual mini-course being organized by the [Flow Cytometry Shared Resource](https://www.medschool.umaryland.edu/cibr/core/umgccc_flow/) Core at the [University of Maryland's Greenebaum Comprehensive Cancer Center](https://www.umms.org/umgccc). This course is a passion project arising from our desire to contribute back to the community. + +We are excited that so many individuals worldwide have chosen to take part, and we look forward to helping you get started on your own learning journeys. + +![](/images/WorldwideSignups.png){width=100%} + +Click here to go to our [Course Website](https://umgcccfcsr.github.io/CytometryInR) + +# Participating + +The course will start the first week of February, with Week #1 resources being released on Sunday, February 1st at 2200 EST (Monday 0300 GMT+0). See below for additional details. + +## Resources + +The pre-course learning materials are now [available](https://umgcccfcsr.github.io/CytometryInR/course/00_GitHub/) , providing walkthroughs of how to set up your workstations with the required software, and exercises to help you become more familiar with the various teaching and coding resources we will be using throughout the course. + +Narrated versions of the walk through materials will be available starting next week via [YouTube](https://www.youtube.com/@CytometryInR) + + +## In-Person (Baltimore) + +For those joining us in person, the class is being offered on Monday, Tuesday and Thursday from **4-5 pm EST** in Bressler Research Building Room 7-035. We invite you to make whichever session best fits your schedule. Monitors to plug your laptops in will be available on a first come, first served basis. These in-person sessions will not be recorded, but with the smaller class size you will have our undivided attention should you have any questions. + +## Virtual (Worldwide) + +For those joining us virtually, we will have three separate livestreams throughout the week on [YouTube](https://www.youtube.com/@CytometryInR). These will be offered on: + +- Tuesday 2200 EST (Wednesday 0300 GMT+0) +- Wednesday 1600 EST (Wednesday 2100 GMT+0) +- Thursday 1000 EST (Thursday 1500 GMT+0) + +All three livestreams will be recorded and available on YouTube immediately afterwards. + +## Discussion Forum + +We will be using the Cytometry in R [Discussions page](https://github.com/UMGCCCFCSR/CytometryInR/discussions) as a community forum, and a place to ask questions, celebrate wins, and provide feedback. After creating a a [GitHub](https://umgcccfcsr.github.io/CytometryInR/course/00_GitHub/) account, pleae go introduce yourself. +For additional details, please visit our [website](https://umgcccfcsr.github.io/CytometryInR/) +======= ![](images/WebsiteBanner.png) Cytometry in R is a free virtual mini-course being organized by the [Flow Cytometry Shared Resource](https://www.medschool.umaryland.edu/cibr/core/umgccc_flow/) Core at the [University of Maryland's Greenebaum Comprehensive Cancer Center](https://www.umms.org/umgccc). This course is a passion project arising from our desire to contribute back to the community. @@ -31,3 +72,4 @@ All three livestreams will be recorded and available on YouTube immediately afte We will be using the Cytometry in R [Discussions page](https://github.com/UMGCCCFCSR/CytometryInR/discussions) as a community forum, and a place to ask questions, celebrate wins, and provide feedback. After creating a a [GitHub](https://umgcccfcsr.github.io/CytometryInR/course/00_GitHub/) account, pleae go introduce yourself. For additional details, please visit our [website](https://umgcccfcsr.github.io/CytometryInR/) +>>>>>>> 23a81a59a64966e782d820f6b60f087d577c3b25 diff --git a/Schedule.qmd b/Schedule.qmd index cde0d6d..80d98d2 100644 --- a/Schedule.qmd +++ b/Schedule.qmd @@ -1,3 +1,342 @@ +<<<<<<< HEAD +--- +format: html +toc: TRUE +toc-location: right +toc-depth: 4 +toc-expand: true +sidebar: false +--- +![](images/WebsiteBanner.png) + +
+[![AGPL-3.0][agpl3-shield]][agpl3] +[![CC BY-SA 4.0][cc-by-sa-shield]][cc-by-sa] +
+ +### Cytometry in R: A Course for Beginners + +Cytometry in R is a free virtual mini-course being organized by the [Flow Cytometry Shared Resource](https://www.medschool.umaryland.edu/cibr/core/umgccc_flow/) core at the University of Maryland's [Greenebaum Comprehensive Cancer Center](https://www.umms.org/umgccc). This course is a passion project arising from our desire to contribute back to the community. We are excited that you have chosen to take part and look forward to helping you get started on your own learning journey. + +If you did not complete the original interest form, and would like to be added to our mailing list, please complete the form [here](https://docs.google.com/forms/d/e/1FAIpQLScPK4V_WNSgQvZNq7aIHpoiX8pi3kiuCfI0Tp7hQkVJS3HPtQ/viewform?usp=publish-editor) + +The pre-course learning materials are now [available](/course/00_GitHub/index.qmd) via the Course tab. They consist of walkthroughs of how to set up your workstations with the required software, and exercises to help you become more familiar with the various teaching and coding resources we will be using throughout the course. + +
+ +### Pre-Course Walkthroughs + +![](images/01_GitHub.png){width=25%} + +[**Week 0: January 26, 2026**]{.underline} In these pre-course [walk-throughs](/course/00_GitHub/index.qmd), we ensure that everyone creates a [GitHub](https://github.com/) account, and has their computer properly set up with the required software (including [R](https://cran.rstudio.com/), [Positron](https://positron.posit.co/), and [Git](https://git-scm.com/)). We then start to build individual participants familiarity with the software infrastructure that they will be using throughout the rest of the course. + +
+
+ +### Installing R Packages + +![](images/PopUpLab.jpeg){width=25%} + +[**Week 1: February 2, 2026**]{.underline} During this [first session](/course/01_InstallingRPackages/index.qmd), we learn how to install R packages from the various repositories ([CRAN](https://cran.r-project.org/), [Bioconductor](https://www.bioconductor.org/), [GitHub](https://github.com/r-lib/remotes)), and how to troubleshoot the more typical errors that occur during this process. + +
+
+ +### File Paths + +![](https://www.medschool.umaryland.edu/media/som/offices-of-the-dean/information-services/screenshots/mappedrives02.png){width=50%} + +[**Week 2: February 9, 2026**]{.underline} For this [second session](/course/02_FilePaths/index.qmd), we focus on how to programmatically tell your computer where to locate your experimental files, introducing the concept of [file paths](https://ytakemon.github.io/2019-10-22-R-BCCRC/02-filedir/). We explore how the various operating systems (Linux, MacOS, Windows) specify their respective folders and files, and how to identify where you are currently within the directory. Our goal by the end of this session is to have walked you through how to figure out where an .fcs file of interest is stored, and convey to your computer where you want it copied/moved to, without encountering the common pitfalls. + +
+
+ +### Inside an .FCS file + +![](https://www.researchgate.net/profile/John-Drakos/publication/5575630/figure/fig1/AS:202978347753476@1425405217571/The-structure-of-FCS-files-The-HEADER-is-a-fixed-size-58-bytes-ASCII-encoded-segment.png){width=50%} + +[**Week 3: February 16, 2026**]{.underline} In the course of this [third session](/course/03_InsideFCSFile/index.qmd) we will slice into an .FCS file and find out what the individual components that make it up are. In the process, we will cover the concepts of main [data structures](http://adv-r.had.co.nz/Data-structures.html) within R (vectors, matrices, data.frames, list) and how to identify what we are working with. Additionally, we will explore how various cytometry softwares store their metadata variables under various keywords that can be useful to know about. + +
+
+ +### Introduction to the Tidyverse + +![](images/histograms.png){width=75%} + +[**Week 4: February 23, 2026**]{.underline} Within this session, we explore how the various [tidyverse](https://tidyverse.org/) packages can be utilized to reorganize rows and columns of data in ways that are useful for data analysis. We will primarily work with the MFI expression data we isolated from within the .fcs file in the previous session, identifying and isolating events that meet certain criterias. We introduce the concepts behind ["tidy"](https://vita.had.co.nz/papers/tidy-data.pdf) data and how it can improve our workflows. + +
+
+ +### Gating Sets + +![](images/GatingSets.png){width=75%} + +[**Week 5: March 2, 2026**]{.underline} As part of this session, we learn about the two main flow cytometry infrastructure packages in R we will be working with during the course, [flowcore](https://www.bioconductor.org/packages/release/bioc/vignettes/flowCore/inst/doc/HowTo-flowCore.pdf) and [flowWorkspace](https://www.bioconductor.org/packages/release/bioc/vignettes/flowWorkspace/inst/doc/flowWorkspace-Introduction.html). Throughout the session, we will compare how they differ in naming, memory usage, and accessing .fcs file metadata. We additionally explore how to add keywords to their respective metadata for use in filtering specimens of interest from the larger set of .fcs files. + +
+
+ +### Visualizing with ggplot2 + +![](images/StatsIFNg.png){width=50%} + +[**Week 6: March 9, 2026**]{.underline} During this session we provide an introduction to the [ggplot2](https://ggplot2.tidyverse.org/) package. We will take the datasets we have collected from the previous sessions and see how in varying in different arguments at the respective plot layers we can produce and customize many different forms of plots, focusing on both cytometry and statistics plots. We close out providing links to [additional helpful resources](https://youtu.be/_indbXPXUw8?si=iZRFHzWvBZg-wu_X) and highlight the [TidyTuesday](https://github.com/rfordatascience/tidytuesday) project. + +
+
+ +### Applying Transformations and Compensation + +![](images/subsetting.png){width=75%} + +[**Week 7: March 16, 2026**]{.underline} For this seventh session, we take a closer look at the raw values of the data within our .fcs files, and explore the various ways to [transform](https://docs.flowjo.com/flowjo/graphs-and-gating/gw-transform-overview/) (ie. scale) flow cytometry data in R to better visualize "positive" and "negative populations". In the process, we visualize the differences resulting from applying different transformations commonly used by commercial software. Similarly, we learn how to apply and visualize compensation in context of conventional flow cytometry files. + +
+
+ +### Manual and Automated Gating + +![](images/openCyto.png){width=75%} + +[**Week 8: March 23, 2026**]{.underline} Within this session, we explore various ways to implement gating for flow cytometry files in R. We will explore manual approaches utilizing [flowGate](https://www.bioconductor.org/packages/release/bioc/html/flowGate.html), as well as automated options with [openCyto](https://www.bioconductor.org/packages/release/bioc/vignettes/openCyto/inst/doc/HowToAutoGating.html) and it's gating templates. We additionally will explore how to provide gate constraints and various ways to visually screen and evaluate the outcomes within the context of our own projects. + +
+
+ +### Conference Break 1 + +No class week of March 30, 2026. If you are attending the [ABRF conference](https://web.cvent.com/event/6aeb3907-0f0b-418d-a0d5-91f4de72c144/summary?RefId=ABRF%202026%20Annual%20Meeting%20Home%20Page), track me down at the [Complex Data Analysis in Flow Cytometry: Navigating the Landscape](https://web.cvent.com/event/6aeb3907-0f0b-418d-a0d5-91f4de72c144/websitePage:89d4bbd7-0f7c-4235-a335-97866af9506b) talk on Monday, March 30th at 4:30 PM. + +
+
+ +### It's Raining Functions! + +![](https://images2.minutemediacdn.com/image/upload/c_fill,w_720,ar_16:9,f_auto,q_auto,g_auto/shape/cover/sport/raining-monkeys-e3fa8001e4eb47433b1cc58e2017d2b8.png){width=75%} + +[**Week 9: April 6, 2026**]{.underline} In the course of this ninth session, we tackle one of the harder but most useful concepts to learn for a beginner, namely [functions](https://r4ds.had.co.nz/functions.html). We explore what they are, how their individual arguments work, how they differ from for-loops, and how to create our own to do useful work, reduce the number times code gets copied and pasted. Additionally, some functional programming best practices will be introduced, as well as provide introduction to how to use the walk and map functions from the [purrr](https://purrr.tidyverse.org/) package. + +
+
+ +### Downsampling and Concatenation + +![](https://www.ibm.com/content/dam/connectedassets-adobe-cms/worldwide-content/creative-assets/s-migr/ul/g/7d/10/downsampling-near-miss-v3.png){width=50%} + +[**Week 10: April 13, 2026**]{.underline} Within this session, we will expand on our growing understanding of GatingSets, functions and fcs file internals to write a script to downsample your fcs files to a desired number (or percentage) of cells for a given cell population. We will additionally learn how to concatenate these downsampled files together, and save them to a new .fcs file in ways that the metadata can be read by commercial software without the scaling being widely thrown off. + +
+
+ +### Retrieving data for Statistics + +![](images/TidyData.png){width=33%} + +[**Week 11: April 20, 2026**]{.underline} Leveraging the increased familiarity working with the various packages this far in the course, in this session we will retrieve summary statistics for the gates within our GatingSet, and programmatically derrive out tidy data.frames for use in statistical analyses typically used by many Immunologist. In the process, we add a couple additional plot types to our ggplot2 arsenal to hold in reserve should Prism prices go up again. + +
+
+ +### Spectral Signatures + +![](images/Signatures.png){width=75%} + +[**Week 12: April 27, 2026**]{.underline} As part of this session, we will explore how to extract fluorescent signatures from our raw spectral flow cytometry reference controls. Building on prior concepts, we will learn to isolate median signatures from positive and negative gates, and how to derrive and plot normalized signatures. We also introduce [plotly](https://plotly.com/r/) package and it's interactive plotting features, before showcasing various packages attempts at facilitating signature retrieval. + +
+
+ +### Similarities and Hotspots + +![](images/Hotspot.png){width=75%} + +[**Week 13: May 4, 2026**]{.underline} During this session, we will utilize the spectral signature matrix isolated from raw spectral flow cytometry controls and evaluate different ways of evaluating how similar different fluorescent signatures are to each other. In the process, we will gain better understanding of the metrics behind similarity (cosine), panel complexity (kappa), and unmixing-dependent spreading (collinearity). + +
+
+ +### Unmixing in R + +![](images/Unmixing.png){width=75%} + +[**Week 14: May 11, 2026**]{.underline} In the course of this session, we will attempt a reach goal of many, namely carry out unmixing of raw .fcs files using the spectral signatures we have isolated from our unmixing controls, and write to new .fcs files. After evaluating the necessary internals, we will explore how various current cytometry R packages have implemented their own unmixing functions, and the various limitations that each approach has encountered. + +
+
+ +### Cleaning Algorithms + +![](images/DegradingAPCFire810Signatures.png){width=75%} + +[**Week 15: May 18, 2026**]{.underline} In the span of this session, we will directly compare how various Bioconductor data cleanup algorithms (namely [PeacoQC](https://www.bioconductor.org/packages/release/bioc/vignettes/PeacoQC/inst/doc/PeacoQC_Vignette.pdf), [FlowAI](https://www.bioconductor.org/packages/release/bioc/vignettes/flowAI/inst/doc/flowAI.html), [FlowCut](https://www.bioconductor.org/packages/release/bioc/vignettes/flowCut/inst/doc/flowCut.html), and [FlowClean](https://www.bioconductor.org/packages/release/bioc/vignettes/flowClean/inst/doc/flowClean.pdf)) tackle distinguishing and removing bad quality events. We will see how they perform with previously identified good quality and horrific quality .fcs files. We will whether the implemented algorithmic decisions made sense, and how to customize them within our workflows to achieve our own desired goals. + +
+
+ +### Clustering Algorithms + +![](https://docs.flowjo.com/wp-content/uploads/2023/03/image-6-1024x1024.png){width=50%} + +[**Week 16: May 25, 2026**]{.underline} As part of this session, we venture away from supervised and semi-supervised analyses to explore unsupervised clustering approaches, namely [FlowSOM](https://onlinelibrary.wiley.com/doi/10.1002/cyto.a.22625) and [Phenograph](https://www.colibri-cytometry.com/post/the-peculiarities-of-phenograph). We will compare outcomes depending markers included, transformations applied, and panel used to gain a greater familiarity with how they work. We wrap up by investigating ways to visualize marker expression of cells ending up in each cluster, and how to backgate them to our manual gates. + +
+
+ +### Normalization: Batch Effect or Real Biology + +![](images/ridgeplots.png){width=75%} + +[**Week 17: June 1, 2026**]{.underline} During this session, we will dive into evaluating the performance of two commonly used normalization algorithms, [CytoNorm](https://github.com/saeyslab/CytoNorm) and [CyCombine](https://github.com/biosurf/cyCombine). We will utilize our ggplot2 and functional programming toolkits to create a customized workflow to visualize the differences for our respective cell populations before and after normalization, to better evaluate how the respective parameter choices can affect the process. + +
+
+ +### Conference Break 2 + +No class week of June 8, 2026. If you are attending the [Cyto conference](https://www.cytoconference.org/?gad_source=1&gad_campaignid=20633392465&gbraid=0AAAAADoJzsvHaLZAq9tqn_aTAQGEzIk_V&gclid=CjwKCAiA-sXMBhAOEiwAGGw6LJFFV69xaAU3s7bElL86RdnRNFwAYqOQO78MrIYQuG1qvRU6HTN3ZRoCGmAQAvD_BwE), track me down at my talks and posters. + +
+
+ + +### Dimensionality Visualization + +![](images/DimViz.png){width=75%} + +[**Week 18: June 15, 2026**]{.underline} For this session, we explore how dimensionality visualization algorithms perform [tSNE](https://github.com/lvdmaaten/bhtsne/) and [UMAP](https://github.com/jlmelville/uwot) in R using our raw and unmixed samples. In the process, we will explore how markers included, number of cells, and presence of bad quality events can impact the [final](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011288) visualizations. Finally, we will provide an overview of how to link to Python to additionally run [PaCMAP](https://github.com/YingfanWang/PaCMAP) and [PHATE](https://github.com/KrishnaswamyLab/PHATE) visualizations for use in R. + +
+
+ +### Annotating Unsupervised Clusters + +![](https://media.geeksforgeeks.org/wp-content/uploads/20230731175958/Bagging-classifier.png){width=50%} + +[**Week 19: June 22, 2026**]{.underline} In the course of this session, we explore ways to scale our efficiency in figuring out what an unsupervised cluster of cells may be, by employing several annotation packages. We explore how these work under the hood in their decision making process, and how to link them to reference data from external repositories for additional evaluation. + +
+
+ +### The Art of GitHub Diving + +![](https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTE3IHi5Y2itTmH60RF81y5b8JnSeeJvTTATA&s){width=100%} + +[**Week 20: June 29, 2026**]{.underline} Within this session, we delve into the art of investigating a new-to-you GitHub repository. We discuss the overall structure of R packages stored as source files within GitHub repositories, and how to leverage this knowledge when troubleshooting errors thrown by underdocumented R packages. We discuss how to modify identified functions, evaluate them, and process to submit helpful bug reports back to the original project to help fix the issue. + +
+
+ +### XML Files All The Way Down + +![](https://www.mssqltips.com/wp-content/images-tips/2899_img5.jpg){width=50%} + +[**Week 21: July 6, 2026**]{.underline} Breaking news alert, most of the experiment templates and worksheet layouts we work with as cytometrist are .xml files. In this session, we learn some additional coding tools to allow us to work with these types of files to extract useful data. In this session, we test out our new problem solving abilities to retrieve data from SpectroFlo and Diva .xml files to monitor how our core's flow cytometers behaved for various users last week. + +
+
+ +### Utilizing Bioconductor packages + +![](images/Bioconductor.svg){width=75%} + +[**Week 22: July 13, 2026**]{.underline} Many of the R packages for Flow Cytometry we have utilized in this course were packages from the [Bioconductor](https://www.bioconductor.org/) project. We take a look at what makes Bioconductor packages unique compared to packages found on GitHub and CRAN, explore some of their specific infrastructure types for flow cytometry data, and highlight some useful packages for downstream analysis that we haven't had time to properly explore. + +
+
+ +### Building your First R package + +![](images/R.png){width=33%} + +[**Week 23: July 20, 2026**]{.underline} For most of the course, we have been working with R packages that other individuals built and maintained. In this session, we leverage all your hard work from the rest of the course and corral the unwieldly arsenal of functions you wrote into your [first R package](https://r-pkgs.org/introduction.html) for easier use. We will discuss the individual pieces of an R package, the importance of a well-setup namespace file, and how to generate help page manuals to refer future-you back to what your individual function arguments actually do. + +
+
+ +### Everyone Get's a Quarto Website + +![](images/3L_V1_Gain_2024.png){width=75%} + +[**Week 24: July 27, 2026**]{.underline} In this session, we will extend the knowledge of .R and .qmd files you have gained from the course and extend them to create your own website using [Quarto](). We discuss the additional files that are required, how to customize and render the website locally, and finally set up [Quarto Pub](https://quartopub.com/) or [GitHub Pages](https://docs.github.com/en/pages) website that we are to access online. + +
+
+ + +### Reproducibility and Replicability + +![](https://media.springernature.com/lw1200/springer-static/image/art%3A10.1038%2F533452a/MediaObjects/41586_2016_BF533452a_Fige_HTML.jpg){width=50%} + +[**Week 25: August 3, 2026**]{.underline} Throughout the course, we emphasized the importance of making your workspaces and code reproducible and replicable. But what do we mean by these terms, and are there best practices we could add to our existing workflow to do this more efficiently? We explore a couple community-led efforts within the cytometry space and troubleshoot their implementation into a previously published pipeline. + +
+
+ +### Conference Break 3 + +No class week of August 10, 2026. If you are attending the [BioC conference](https://bioc2026.bioconductor.org/), track me down at my talk/poster. + +
+
+ +### Open Source Licenses + +![](https://cdn.media.amplience.net/i/epammarketplace/Software_Licenses_1?maxW=1200&qlt=80&fmt=jpg&bg=rgb(255,255,255)&v=1365581685114){width=50%} + +[**Week 26: August 17, 2026**]{.underline} For this course, we have relied extensively on open-source software to create our own data analysis pipelines. In the process, you may have some recollection of the various license names. But what impact do all these different names have in the end? We take a brief deep-dive into the ecosystem of [free and open-source licenses](https://en.wikipedia.org/wiki/Free_and_open-source_software), and evaluate what their respective license terms mean for us as individual users of the code, as well as potential developers extending existing codebases. + +
+
+ +### Validating Algorthmic Tools + +![](https://ecx.images-amazon.com/images/I/41f9FvgwgzL.jpg){width=50%} + +[**Week 27: August 24, 2026**]{.underline} We will be the first to admit, new implementations of algorithms as R packages are awesome! We appreciate the effort that went into them and making them available to the community at large. But what is the best way of evaluating whether they behave as promised, or work for our dataset? During this session, we share tips and tricks to gain better understanding of how a new R package works, and things to watch out for when evaluating complicated algortithms. We wrap with walkthrough of how to generate simulated datasets with known distributions for use in testing. + +
+
+ +### Databases and Repositories + +![](images/Database.png){width=50%} + +[**Week 28: August 31, 2026**]{.underline} During this session, we will learn how to identify and retrieve .fcs files from databases. While many of us are accustomed to working with large datasets of our own making, many of us are increasingly encountering larger-than-memory datasets, as well as files stored in large repositories. In this session, we will explore several database focused R [packages](https://arrow.apache.org/docs/r/), before investigating how to identify and retrieve .fcs files and associated metadata of interest from repositories, namely [ImmPort](https://www.immport.org/shared/) (and maybe [FlowRepository](https://flowrepository.org/) if it can be pinged that afternoon). + +
+
+ +### Assembling Web Data + +![](https://media.brightdata.com/2023/01/Web-scraping-with-R.png){width=50%} + +[**Week 29: September 7, 2026**]{.underline} In this session, we briefly delve into the concepts of web-scraping and APIs in general. We highlight useful packages, namely [httr2](https://httr2.r-lib.org/) and [rvest](https://rvest.tidyverse.org/), and best practices implemented to allow respectful retrieval of useful data without crashing someone's server like some AI startup bot. We finish by providing a list of additional useful resources for those interested in learning more. + +
+
+ +### Future Directions + +![](images/Future.jpg){width=75%} + +[**Week 30: September 14, 2026**]{.underline} In this final of the planned sessions, we revisit our solutions to the challenge problems set out during the beginning of the course. We also discuss potential future topics to visit in the future, and any additional resources that proved helpful throughout the course. + +
+
+ +
+[![AGPL-3.0][agpl3-image]][agpl3] +[![CC BY-SA 4.0][cc-by-sa-image]][cc-by-sa] +
+ +[cc-by-sa]: http://creativecommons.org/licenses/by-sa/4.0/ +[cc-by-sa-image]: https://licensebuttons.net/l/by-sa/4.0/88x31.png +[cc-by-sa-shield]: https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg +[agpl3]: https://www.gnu.org/licenses/agpl-3.0.en.html +[agpl3-image]: https://www.gnu.org/graphics/agplv3-with-text-162x68.png +======= --- format: html toc: TRUE @@ -335,4 +674,5 @@ No class week of August 10, 2026. If you are attending the [BioC conference](htt [cc-by-sa-shield]: https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg [agpl3]: https://www.gnu.org/licenses/agpl-3.0.en.html [agpl3-image]: https://www.gnu.org/graphics/agplv3-with-text-162x68.png +>>>>>>> 23a81a59a64966e782d820f6b60f087d577c3b25 [agpl3-shield]: https://img.shields.io/badge/license-AGPLv3-blue \ No newline at end of file diff --git a/_quarto.yml b/_quarto.yml index 0d4b92d..441afbd 100644 --- a/_quarto.yml +++ b/_quarto.yml @@ -1,3 +1,4 @@ +<<<<<<< HEAD project: type: website output-dir: docs @@ -63,7 +64,6 @@ website: - text: "00 - Floreada" href: course/00_Floreada/index.qmd - section: "Intro to R" - href: course/01_InstallingRPackages/index.qmd contents: - text: "01 - Installing R Packages" href: course/01_InstallingRPackages/index.qmd @@ -90,3 +90,91 @@ format: html: css: styles.css +======= +project: + type: website + output-dir: docs + render: + - index.qmd + - Schedule.qmd + - ExistingResources.qmd + - PackageWalkthroughs.qmd + - course/index.qmd + - 00_* + - 01_* + - 02_* + - 03_* +website: + google-analytics: "G-LZ35J3XE4D" + announcement: + icon: info-circle + dismissable: true + content: "See Course tab for Course Materials, see YouTube tab for livestream recordings" + type: info + position: below-navbar + page-navigation: true + title: "Cytometry in R" + navbar: + logo: images/hex.svg + background: white + left: + - text: "About" + href: index.qmd + - text: "Schedule" + href: Schedule.qmd + - text: "Course" + href: course/index.qmd + right: + - text: Discussions + href: https://github.com/UMGCCCFCSR/CytometryInR/discussions + - icon: youtube + href: https://www.youtube.com/@CytometryInR + aria-label: YouTube + - icon: github + href: https://github.com/UMGCCCFCSR/CytometryInR + aria-label: GitHub + sidebar: + style: floating + collapse-level: 1 + contents: + - section: "Getting Started" + contents: + - text: "00 - GitHub" + href: course/00_GitHub/index.qmd + - text: "00 - Workstation Setup" + href: course/00_WorkstationSetup/index.qmd + - text: "00 - Positron" + href: course/00_Positron/index.qmd + - text: "00 - Git" + href: course/00_Git/index.qmd + - text: "00 - Quarto" + href: course/00_Quarto/index.qmd + - text: "00 - Getting Help" + href: course/00_Homeworks/index.qmd + - text: "00 - Floreada" + href: course/00_Floreada/index.qmd + - section: "Intro to R" + href: course/01_InstallingRPackages/index.qmd + contents: + - text: "01 - Installing R Packages" + href: course/01_InstallingRPackages/index.qmd + - text: "02 - File Paths" + href: course/02_FilePaths/index.qmd + - text: "03 - Inside a .FCS file" + href: course/03_InsideFCSFile/index.qmd + - section: "Cytometry Core" + href: Schedule.qmd + - section: "Beyond the Sandbox" + href: Schedule.qmd + - section: "The World is your Oyster" + href: Schedule.qmd + page-footer: + left: Made with [Quarto](https://quarto.org/) + right: | + ![AGPL-3.0](/images/AGPL3.png) + ![CC-BY-SA](/images/CCBYSA.png) +format: + html: + css: styles.css + +>>>>>>> 052910a (Macbook sync) diff --git a/course/00_BonusContent/Immport/images/index.qmd b/course/00_BonusContent/Immport/images/index.qmd index 51d4412..4774754 100644 --- a/course/00_BonusContent/Immport/images/index.qmd +++ b/course/00_BonusContent/Immport/images/index.qmd @@ -1,14 +1,14 @@ ---- -title: "ImmPort - Downloading Datasets" -author: "David Rach" -date: 02-06-2026 -format: html -toc: true -toc-depth: 4 ---- - -To download data from the ImmPort Shared Data Repository, first navigate to the [website](https://www.immport.org/shared/home) - -![](images/) - +--- +title: "ImmPort - Downloading Datasets" +author: "David Rach" +date: 02-06-2026 +format: html +toc: true +toc-depth: 4 +--- + +To download data from the ImmPort Shared Data Repository, first navigate to the [website](https://www.immport.org/shared/home) + +![](images/) + For help setting up Aspera Connect, see the following [help documentation](https://www.immport.org/installAsperaHelp) \ No newline at end of file diff --git a/course/00_BonusContent/index.qmd b/course/00_BonusContent/index.qmd index b1442e5..d4c0202 100644 --- a/course/00_BonusContent/index.qmd +++ b/course/00_BonusContent/index.qmd @@ -1,88 +1,88 @@ ---- -title: "Bonus Content" -author: "David Rach" -date: 02-04-2026 -format: html -toc: true -toc-depth: 4 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -This is a miscellaneous page to host walk-throughs of topics that come up via the [Discussion Page](https://github.com/UMGCCCFCSR/CytometryInR/discussions). Rather than re-explain how to in the comments, I want to have a place to post short-walkthroughs to solve these issues, while avoiding incorporating it into the existing walk-throughs at this point in time. I hope you find it useful, and pardon the organized chaos of miscellaneous topics. - -# 00_WorkStationSetup - -## Windows Arm - -### Positron - -On the main Positron [installation page](https://positron.posit.co/download.html), only the installers for Windows Computers with x86 chips are currently shown. There is a beta (experimental) version of Positron for Windows ARM (ex. Snapdragons), but it needs to be installed from Positron's GitHub [releases page](https://github.com/posit-dev/positron/releases). - -![](/course/00_BonusContent/images/WindowsArm.png) - -Please note, you should download the most recent version that is available to you, as they continue to update it and fix bugs. As of February 04, 2026, you would also need to install Quarto separately. - -To install Quarto, first navigate to their [website](https://quarto.org/docs/get-started/). Quarto for Windows ARM was implemented in [2023](https://github.com/quarto-dev/quarto-cli/issues/190), so the regular installer should work. - -![](/course/00_BonusContent/images/WindowsArm.png) - -Also, you would need a Python arm64 installation installed if you decide you want to venture into using Python at any point. - -# 00_Positron - -## Visual Mode - -Within Positron, there exist a toggle button to switch between source and visual mode on Quarto documents. But what do you do when you can't find it? - -![](/course/00_BonusContent/images/ToggleAfika.png) - -Tuns out.... Visual Mode is currently broken, so the developers [removed it](https://github.com/posit-dev/positron/issues/1805#issuecomment-3792323435) about two weeks ago. - -The current way to switch to it is via right-click, then select edit visual mode. - -![](/course/00_BonusContent/images/EditVisualMode.png) - -Vice versa, once there, you can revert by right-clicking and selecting Edit Source Mode - -![](/course/00_BonusContent/images/EditSourceMode.png) - -The process of figuring what is going on highlights how to use a GitHub Discussion Page. This is [Positrons](https://github.com/posit-dev/positron/discussions?discussions_q=visual+button) when I searched for visual button. I then found that a similar question was asked 3 days ago that led me to the linked thread above. - -![](/course/00_BonusContent/images/DiscussionPageSearch.png) - -# 00_Git - -## Not Detecting Git - -If you leave the "Initialize Git Repository" option unclicked when setting up a New Folder from Template, Git will not be active within your project folder. - -![](/course/00_BonusContent/images/NoGitInitialized.png) - -As a result, when you try to use the `usethis` packages `use_github(private=true)` function, you will get an error that resembles the one below - -![](/course/00_BonusContent/images/NoGitDetected.png) - -To initiate a Git repository after the fact, you will need to go to the Version Control tab in the action bar, and select the option. - -![](/course/00_BonusContent/images/InitializeRepository.png) - -Then, you will need to stage the files you want to work with, and commit them. - -![](/course/00_BonusContent/images/SaveCommit.png) - -`use_github(private=TRUE)` should now be functional at that point. However, you can also choose to continue via Positron's interface instead by selecting Publish. - -![](/course/00_BonusContent/images/PublishBranch.png) - -It will then ask you whether you want to save it as either a Public or a Private repository. - -![](/course/00_BonusContent/images/PrivateRepository.png) - -And if all goes well, you will see the "Successs" pop-up in the lower-right - +--- +title: "Bonus Content" +author: "David Rach" +date: 02-04-2026 +format: html +toc: true +toc-depth: 4 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +This is a miscellaneous page to host walk-throughs of topics that come up via the [Discussion Page](https://github.com/UMGCCCFCSR/CytometryInR/discussions). Rather than re-explain how to in the comments, I want to have a place to post short-walkthroughs to solve these issues, while avoiding incorporating it into the existing walk-throughs at this point in time. I hope you find it useful, and pardon the organized chaos of miscellaneous topics. + +# 00_WorkStationSetup + +## Windows Arm + +### Positron + +On the main Positron [installation page](https://positron.posit.co/download.html), only the installers for Windows Computers with x86 chips are currently shown. There is a beta (experimental) version of Positron for Windows ARM (ex. Snapdragons), but it needs to be installed from Positron's GitHub [releases page](https://github.com/posit-dev/positron/releases). + +![](/course/00_BonusContent/images/WindowsArm.png) + +Please note, you should download the most recent version that is available to you, as they continue to update it and fix bugs. As of February 04, 2026, you would also need to install Quarto separately. + +To install Quarto, first navigate to their [website](https://quarto.org/docs/get-started/). Quarto for Windows ARM was implemented in [2023](https://github.com/quarto-dev/quarto-cli/issues/190), so the regular installer should work. + +![](/course/00_BonusContent/images/WindowsArm.png) + +Also, you would need a Python arm64 installation installed if you decide you want to venture into using Python at any point. + +# 00_Positron + +## Visual Mode + +Within Positron, there exist a toggle button to switch between source and visual mode on Quarto documents. But what do you do when you can't find it? + +![](/course/00_BonusContent/images/ToggleAfika.png) + +Tuns out.... Visual Mode is currently broken, so the developers [removed it](https://github.com/posit-dev/positron/issues/1805#issuecomment-3792323435) about two weeks ago. + +The current way to switch to it is via right-click, then select edit visual mode. + +![](/course/00_BonusContent/images/EditVisualMode.png) + +Vice versa, once there, you can revert by right-clicking and selecting Edit Source Mode + +![](/course/00_BonusContent/images/EditSourceMode.png) + +The process of figuring what is going on highlights how to use a GitHub Discussion Page. This is [Positrons](https://github.com/posit-dev/positron/discussions?discussions_q=visual+button) when I searched for visual button. I then found that a similar question was asked 3 days ago that led me to the linked thread above. + +![](/course/00_BonusContent/images/DiscussionPageSearch.png) + +# 00_Git + +## Not Detecting Git + +If you leave the "Initialize Git Repository" option unclicked when setting up a New Folder from Template, Git will not be active within your project folder. + +![](/course/00_BonusContent/images/NoGitInitialized.png) + +As a result, when you try to use the `usethis` packages `use_github(private=true)` function, you will get an error that resembles the one below + +![](/course/00_BonusContent/images/NoGitDetected.png) + +To initiate a Git repository after the fact, you will need to go to the Version Control tab in the action bar, and select the option. + +![](/course/00_BonusContent/images/InitializeRepository.png) + +Then, you will need to stage the files you want to work with, and commit them. + +![](/course/00_BonusContent/images/SaveCommit.png) + +`use_github(private=TRUE)` should now be functional at that point. However, you can also choose to continue via Positron's interface instead by selecting Publish. + +![](/course/00_BonusContent/images/PublishBranch.png) + +It will then ask you whether you want to save it as either a Public or a Private repository. + +![](/course/00_BonusContent/images/PrivateRepository.png) + +And if all goes well, you will see the "Successs" pop-up in the lower-right + ![](/course/00_BonusContent/images/SuccessToGitHub.png) \ No newline at end of file diff --git a/course/00_Floreada/.DS_Store b/course/00_Floreada/.DS_Store deleted file mode 100644 index 5152ac0..0000000 Binary files a/course/00_Floreada/.DS_Store and /dev/null differ diff --git a/course/00_Floreada/data/workspace.wsp b/course/00_Floreada/data/workspace.wsp index 429fcba..ef3cd19 100644 --- a/course/00_Floreada/data/workspace.wsp +++ b/course/00_Floreada/data/workspace.wsp @@ -1,166214 +1,166214 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/course/00_Floreada/index.qmd b/course/00_Floreada/index.qmd index 418d8a1..f13f653 100644 --- a/course/00_Floreada/index.qmd +++ b/course/00_Floreada/index.qmd @@ -1,375 +1,375 @@ ---- -title: "Using Floreada" -author: "David Rach" -date: 01-21-2026 -format: html -toc: true -toc-depth: 5 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -For the YouTube livestream recording, see [here](https://www.youtube.com/live/3jDed1gmq0M?si=ge-UPqQ6lbXAtn_Z) - - - -For screen-shot slides, click [here](/course/00_Floreada/slides.qmd) - -# Background - -As a "Cytometry in R" course, we will primarily be working in R. However, within our daily workflows and projects here at our flow cytometry core, we often use various flow cytometry softwares (like [FlowJo](https://flowjo.com/flowjo10/download) or [FCS Express](https://denovosoftware.com/)) for various tasks. Fortunately, R packages like [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) can allow us to import our manually drawn gates from existing FlowJo workspaces so that we can work with them in R. - -For this course, we are adamant about staying neutral in regards to both commercial software or instrument vendors as much as possible. If they have worked with the open-source community to make their files readable and accessible via R, we will showcase how to integrate those tools into your own workflows. At the same time, this being a [**free**]{.underline} course, it doesn't make sense to turn around and ask you to go and either free trial or buy an expensive software license just to see how a particular free R package works. - -Fortunately, for showing how to use this [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) functionality, we can use [Floreada.io](https://floreada.io/). It is a simple (but free) web-based analysis platform that can be used to draw manual gates for your .fcs files of interest. These can then be saved as Floreada workspaces for later use. We typically recommend it to users from labs that do flow experiments infrequently. Fortunately thanks to the hard work of its [developers](https://floreada.io/about), it can also save the gated files as [FlowJo](https://flowjo.com/flowjo10/download) v10 .wsp files, which with a small workaround become usable within the [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) pipeline. - -To facilitate this, we will provide a small walk-through of how to use it for those who want to create a .wsp with their own .fcs files for [Week 5](https://umgcccfcsr.github.io/CytometryInR/Schedule#gating-sets). - -# Walk-through - -## Floreada - -### Loading Dataset - -First, open your web browser and navigate to the [website](https://floreada.io/) - - -Click on Start to proceed to the next page. - -![](images/01_LandingPage.png) - -
- ---- - -![](images/02_InitialPage.png) - - -
- ---- - -Once that is done, select the File tab on the upper navigation bar. Then click on Open File(s). - -![](images/03_OpenFiles.png){fig-align="left"} - -
- ---- - -From there, select your .fcs files of interest, and click Open. - -![](images/04_SelectFCSFiles.png) - -
- ---- - -The .fcs files will now load in, and you should see a view similar to the one below. On the left side-bar, you have your gating options (Rectangle, Polygon, Range, Elipse, Quad, etc). Next to these on the right you have the FCS files that are loaded into the workspace. Then on the right, you have the visual display for your selected specimen. - -![](images/05_InitialFiles.png) - -
- ---- - -### Switching Axis Markers - - -If you left click on the axis name (SSC-H or FSC-H in this case), you will be able to select other markers by which to gate your specimen. For the provided example, we were using a raw spectral flow cytometry .fcs file, so the names of the detectors are present. - -![](images/06_LeftClick.png) - -
- ---- - -For now, I plan to start off by gating for singlets. I switch the y-axis to FSC-H, and then proceed to switch the x-axis to FSC-A. - -![](images/07_LeftClickXaxis.png) - -
- ---- - -### Creating Gates - -With this done, I can now select the Poly gate tab on the upper left. - -![](images/08_PolygonGateSelect.png) - -
- ---- - -Then manually click on the locations on the plot to add the individual gate nodes. - -![](images/08_PolygonGateStart.png) - -
- ---- - -To complete the gate, I click back to the original node point. At this point, the popup will allow you to name the gate. - -![](images/08_PolygonGateCreate.png) - -
- ---- - -To adjust the polygon gate, you can click on a node and drag it to expand or contract in a particular direction - -![](images/08_PolygonGateNode.png) - -
- ---- - -To move the entire gate, first click on a node to select the gate, then click in the center of the gate to adjust its location. - -![](images/08_PolygonGateCenter.png) - -
- ---- - - -### Additional Gates - -Unfortunately for those with the force-of-habit from using other softwares, double-clicking within the gate doesn't do anything. To continue gating on the selected cells, you will need to click on the newly created gate name on the left. This will result in visualizing the isolated cells. - -![](images/09_SecondLanding.png) - -
- ---- - -Once this is done, you can repeat the previous steps to change the axis markers and create a second gate. For this example, we went with a "Cells" gate to exclude debris from this particular sample. - -![](images/09_SecondGate.png) - -
- ---- - -Having created the "Cells" gate, we will be switching gating based on FSC and SSC to using the detector parameters. - -The samples in this example were acquired to derive the cell counts and concentration of various cell populations within cryopreserved cord and peripheral blood mononuclear cells (CBMC and PBMC) specimens after thawing. - -They were stained with CD19 BV421, CD45 PE, and CD14 APC on a [5-Laser Cytek Aurora](https://spectrum.cytekbio.com/), before unmixing, this would correspond respectively to V1, YG1/B4, R1/YG4 peaks respectively. - -
- ---- - -### Scaling/Transformation - -When we switch the axis, we can see that the scaling/transformation is not ideal, as the staining and not-staining populations are scrunched up together in the center of the plot. - -![](images/10_Untransformed.png) - -
- ---- - -To change the scaling/transformation, we need to click directly on the axis. - -![](images/10_ClickGrid.png) - -
- ---- - -From there, when we click on the drop-down, we see the various transformation options. We will select [Logicle](https://pubmed.ncbi.nlm.nih.gov/16604519/), given we are working with spectral flow cytometry files. - -![](images/10_SelectLogicle.png) - -
- ---- - -This y-axis values are subsequently visualized with the logicle transformation applied, increasing our resolution between the positive and negative population. - -![](images/10_LogicleY.png) - -
- ---- - -We can then repeat this for the x-axis, adjusting the fine-tune options for the scaling as needed. - -![](images/10_DoubleLogicleAxis.png) - -
- ---- - -### Navigating Gating Hierarchy - -With this done, let's first draw a rectangle gate for the CD45+ (B4-A) cells. - -![](images/10_CD45Gate.png) - -
- ---- - -And then selecting that population by clicking on the gate name, let's proceed and gate the CD19+ cells (V2-A). - -![](images/10_CD19Gate.png) - -
- ---- - -As you can see, we now have the various gates present in the gating hierarchy for the respective .fcs file. To return to a previous gated population, we would click on the parent population above it. - -![](images/11_ReturnToPrevious.png) - -
- ---- - -We can subsequently add an additional gate at this gating level for the likely debris population (the threshold setting was suboptimal for this experimental run). - -![](images/11_AdditionalGates.png) - -
- ---- - -### Copying Gates - -This was the process for gating for a single specimen. To copy gates over to the other specimens, we have two options. First, holding down your Ctrl (or equivalent) button, you can click on the individual gate names. - -![](images/11_ControlHighlight.png) - -
- ---- - -From there, you can drag them down to the next specimen and apply them. - -![](images/11_ApplyToNext.png) - -
- ---- - -Alternatively, you can drag down the highlighted gated to the Pipelines Tab, and apply to All Files. This will result in the gates being copied to all specimens in the experiment. - -![](images/11_ApplyAllViaPipelines.png) - -
- ---- - -![](images/13_PipelineAdjustAll.png) - - -
- ---- - -Adjustments within Pipelines will carry over to all other respective unmodified specimens that share it’s gates. - -![](images/13_PipelineAdjustCD19.png) - -
- ---- - -Once this is done, I recommend cycling through the gates for each specimen, just to ensure that the gates were positioned correctly before saving the workspace. - -![](images/12_ClickAdjust.png) - -
- ---- - -### Saving Workspace - -With everyone now "correctly" gated, we can proceed to save the workspace so that we can reopen it later from another browser. - -To do this we open the File tab from the upper navigation bar, and select Save Workspace. - -![](images/14_SaveWorkspace.png) - -
- ---- - -From there we have a couple options, for now let's select Floreada Workspace. Where it is saved at will depend on your individual browser settings, so watch for a popup. - -![](images/14_FloreadaWorkspace.png) - -
- ---- - -Alternatively (and crucially for the CytoML pipeline) we can also choose to save it as a FlowJo v10 .wsp file. - -![](images/14_FlowJoWorkspace.png) - -
- ---- - -In both cases, you will end up with Workspace files that can be used later to access your created gates - -![](images/WorkspaceFiles.png) - -
- ---- - -### Reopening Workspace - -To reopen the Floreada workspace within the browser, reopen the website, and select the Open File(s) option. - -![](images/15_Reopening.png) - -
- ---- - -From there, select both the Floreada Workspace file as well as the .fcs files - - -![](images/15_ReopeningSelectAll.png) - -
- ---- - -At which point you will now be back to the point you last saved at. - -![](images/15_ReopenedWorkspace.png) - -
- ---- - -## CytoML - -Due to a unknown formatting bug, the Floreada produced FlowJo v10 .wsp is not directly accessible by CytoML at the time of this course. However, the issue is resolved as soon as the file is opened the first time within FlowJo v10, regardless of whether you have a log in or not. Strange? Yes, but we will take the workaround. - -So, for anyone on Windows or MacOS, download [FlowJo v10](https://www.flowjo.com/flowjo10/overview). Once installed, open the software, and close the login popups. Once there, open the Floreada created FlowJo.wsp file. Since you haven't logged in, it won't show any events. But it will correct the formatting bug. Close the software, and return to R. Your Floreada sourced .WSP file should now be readable by CytoML. - -Odd? For sure. Fixable? Likely, I will set a reminder to work with the Floreada and CytoML devs to see if we can cut out the need for this workaround. - -# Wrap-up - - -# Additional Resources - -[Floreada Documentation](https://floreada.io/docs/) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Using Floreada" +author: "David Rach" +date: 01-21-2026 +format: html +toc: true +toc-depth: 5 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://www.youtube.com/live/3jDed1gmq0M?si=ge-UPqQ6lbXAtn_Z) + + + +For screen-shot slides, click [here](/course/00_Floreada/slides.qmd) + +# Background + +As a "Cytometry in R" course, we will primarily be working in R. However, within our daily workflows and projects here at our flow cytometry core, we often use various flow cytometry softwares (like [FlowJo](https://flowjo.com/flowjo10/download) or [FCS Express](https://denovosoftware.com/)) for various tasks. Fortunately, R packages like [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) can allow us to import our manually drawn gates from existing FlowJo workspaces so that we can work with them in R. + +For this course, we are adamant about staying neutral in regards to both commercial software or instrument vendors as much as possible. If they have worked with the open-source community to make their files readable and accessible via R, we will showcase how to integrate those tools into your own workflows. At the same time, this being a [**free**]{.underline} course, it doesn't make sense to turn around and ask you to go and either free trial or buy an expensive software license just to see how a particular free R package works. + +Fortunately, for showing how to use this [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) functionality, we can use [Floreada.io](https://floreada.io/). It is a simple (but free) web-based analysis platform that can be used to draw manual gates for your .fcs files of interest. These can then be saved as Floreada workspaces for later use. We typically recommend it to users from labs that do flow experiments infrequently. Fortunately thanks to the hard work of its [developers](https://floreada.io/about), it can also save the gated files as [FlowJo](https://flowjo.com/flowjo10/download) v10 .wsp files, which with a small workaround become usable within the [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) pipeline. + +To facilitate this, we will provide a small walk-through of how to use it for those who want to create a .wsp with their own .fcs files for [Week 5](https://umgcccfcsr.github.io/CytometryInR/Schedule#gating-sets). + +# Walk-through + +## Floreada + +### Loading Dataset + +First, open your web browser and navigate to the [website](https://floreada.io/) + + +Click on Start to proceed to the next page. + +![](images/01_LandingPage.png) + +
+ +--- + +![](images/02_InitialPage.png) + + +
+ +--- + +Once that is done, select the File tab on the upper navigation bar. Then click on Open File(s). + +![](images/03_OpenFiles.png){fig-align="left"} + +
+ +--- + +From there, select your .fcs files of interest, and click Open. + +![](images/04_SelectFCSFiles.png) + +
+ +--- + +The .fcs files will now load in, and you should see a view similar to the one below. On the left side-bar, you have your gating options (Rectangle, Polygon, Range, Elipse, Quad, etc). Next to these on the right you have the FCS files that are loaded into the workspace. Then on the right, you have the visual display for your selected specimen. + +![](images/05_InitialFiles.png) + +
+ +--- + +### Switching Axis Markers + + +If you left click on the axis name (SSC-H or FSC-H in this case), you will be able to select other markers by which to gate your specimen. For the provided example, we were using a raw spectral flow cytometry .fcs file, so the names of the detectors are present. + +![](images/06_LeftClick.png) + +
+ +--- + +For now, I plan to start off by gating for singlets. I switch the y-axis to FSC-H, and then proceed to switch the x-axis to FSC-A. + +![](images/07_LeftClickXaxis.png) + +
+ +--- + +### Creating Gates + +With this done, I can now select the Poly gate tab on the upper left. + +![](images/08_PolygonGateSelect.png) + +
+ +--- + +Then manually click on the locations on the plot to add the individual gate nodes. + +![](images/08_PolygonGateStart.png) + +
+ +--- + +To complete the gate, I click back to the original node point. At this point, the popup will allow you to name the gate. + +![](images/08_PolygonGateCreate.png) + +
+ +--- + +To adjust the polygon gate, you can click on a node and drag it to expand or contract in a particular direction + +![](images/08_PolygonGateNode.png) + +
+ +--- + +To move the entire gate, first click on a node to select the gate, then click in the center of the gate to adjust its location. + +![](images/08_PolygonGateCenter.png) + +
+ +--- + + +### Additional Gates + +Unfortunately for those with the force-of-habit from using other softwares, double-clicking within the gate doesn't do anything. To continue gating on the selected cells, you will need to click on the newly created gate name on the left. This will result in visualizing the isolated cells. + +![](images/09_SecondLanding.png) + +
+ +--- + +Once this is done, you can repeat the previous steps to change the axis markers and create a second gate. For this example, we went with a "Cells" gate to exclude debris from this particular sample. + +![](images/09_SecondGate.png) + +
+ +--- + +Having created the "Cells" gate, we will be switching gating based on FSC and SSC to using the detector parameters. + +The samples in this example were acquired to derive the cell counts and concentration of various cell populations within cryopreserved cord and peripheral blood mononuclear cells (CBMC and PBMC) specimens after thawing. + +They were stained with CD19 BV421, CD45 PE, and CD14 APC on a [5-Laser Cytek Aurora](https://spectrum.cytekbio.com/), before unmixing, this would correspond respectively to V1, YG1/B4, R1/YG4 peaks respectively. + +
+ +--- + +### Scaling/Transformation + +When we switch the axis, we can see that the scaling/transformation is not ideal, as the staining and not-staining populations are scrunched up together in the center of the plot. + +![](images/10_Untransformed.png) + +
+ +--- + +To change the scaling/transformation, we need to click directly on the axis. + +![](images/10_ClickGrid.png) + +
+ +--- + +From there, when we click on the drop-down, we see the various transformation options. We will select [Logicle](https://pubmed.ncbi.nlm.nih.gov/16604519/), given we are working with spectral flow cytometry files. + +![](images/10_SelectLogicle.png) + +
+ +--- + +This y-axis values are subsequently visualized with the logicle transformation applied, increasing our resolution between the positive and negative population. + +![](images/10_LogicleY.png) + +
+ +--- + +We can then repeat this for the x-axis, adjusting the fine-tune options for the scaling as needed. + +![](images/10_DoubleLogicleAxis.png) + +
+ +--- + +### Navigating Gating Hierarchy + +With this done, let's first draw a rectangle gate for the CD45+ (B4-A) cells. + +![](images/10_CD45Gate.png) + +
+ +--- + +And then selecting that population by clicking on the gate name, let's proceed and gate the CD19+ cells (V2-A). + +![](images/10_CD19Gate.png) + +
+ +--- + +As you can see, we now have the various gates present in the gating hierarchy for the respective .fcs file. To return to a previous gated population, we would click on the parent population above it. + +![](images/11_ReturnToPrevious.png) + +
+ +--- + +We can subsequently add an additional gate at this gating level for the likely debris population (the threshold setting was suboptimal for this experimental run). + +![](images/11_AdditionalGates.png) + +
+ +--- + +### Copying Gates + +This was the process for gating for a single specimen. To copy gates over to the other specimens, we have two options. First, holding down your Ctrl (or equivalent) button, you can click on the individual gate names. + +![](images/11_ControlHighlight.png) + +
+ +--- + +From there, you can drag them down to the next specimen and apply them. + +![](images/11_ApplyToNext.png) + +
+ +--- + +Alternatively, you can drag down the highlighted gated to the Pipelines Tab, and apply to All Files. This will result in the gates being copied to all specimens in the experiment. + +![](images/11_ApplyAllViaPipelines.png) + +
+ +--- + +![](images/13_PipelineAdjustAll.png) + + +
+ +--- + +Adjustments within Pipelines will carry over to all other respective unmodified specimens that share it’s gates. + +![](images/13_PipelineAdjustCD19.png) + +
+ +--- + +Once this is done, I recommend cycling through the gates for each specimen, just to ensure that the gates were positioned correctly before saving the workspace. + +![](images/12_ClickAdjust.png) + +
+ +--- + +### Saving Workspace + +With everyone now "correctly" gated, we can proceed to save the workspace so that we can reopen it later from another browser. + +To do this we open the File tab from the upper navigation bar, and select Save Workspace. + +![](images/14_SaveWorkspace.png) + +
+ +--- + +From there we have a couple options, for now let's select Floreada Workspace. Where it is saved at will depend on your individual browser settings, so watch for a popup. + +![](images/14_FloreadaWorkspace.png) + +
+ +--- + +Alternatively (and crucially for the CytoML pipeline) we can also choose to save it as a FlowJo v10 .wsp file. + +![](images/14_FlowJoWorkspace.png) + +
+ +--- + +In both cases, you will end up with Workspace files that can be used later to access your created gates + +![](images/WorkspaceFiles.png) + +
+ +--- + +### Reopening Workspace + +To reopen the Floreada workspace within the browser, reopen the website, and select the Open File(s) option. + +![](images/15_Reopening.png) + +
+ +--- + +From there, select both the Floreada Workspace file as well as the .fcs files + + +![](images/15_ReopeningSelectAll.png) + +
+ +--- + +At which point you will now be back to the point you last saved at. + +![](images/15_ReopenedWorkspace.png) + +
+ +--- + +## CytoML + +Due to a unknown formatting bug, the Floreada produced FlowJo v10 .wsp is not directly accessible by CytoML at the time of this course. However, the issue is resolved as soon as the file is opened the first time within FlowJo v10, regardless of whether you have a log in or not. Strange? Yes, but we will take the workaround. + +So, for anyone on Windows or MacOS, download [FlowJo v10](https://www.flowjo.com/flowjo10/overview). Once installed, open the software, and close the login popups. Once there, open the Floreada created FlowJo.wsp file. Since you haven't logged in, it won't show any events. But it will correct the formatting bug. Close the software, and return to R. Your Floreada sourced .WSP file should now be readable by CytoML. + +Odd? For sure. Fixable? Likely, I will set a reminder to work with the Floreada and CytoML devs to see if we can cut out the need for this workaround. + +# Wrap-up + + +# Additional Resources + +[Floreada Documentation](https://floreada.io/docs/) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_Floreada/slides.qmd b/course/00_Floreada/slides.qmd index 1c08ec9..357668a 100644 --- a/course/00_Floreada/slides.qmd +++ b/course/00_Floreada/slides.qmd @@ -1,535 +1,535 @@ ---- -title: "Using Floreada" -author: "David Rach" -date: 02-01-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - - -# Background - -::: {.fragment} -::: {.callout-tip title="."} -As a "Cytometry in R" course, we will primarily be working in R. However, within our daily workflows and projects here at our flow cytometry core, we often use various flow cytometry softwares (like [FlowJo](https://flowjo.com/flowjo10/download) or [FCS Express](https://denovosoftware.com/)) for various tasks. Fortunately, R packages like [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) can allow us to import our manually drawn gates from existing FlowJo workspaces so that we can work with them in R. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For this course, we are adamant about staying neutral in regards to both commercial software or instrument vendors as much as possible. If they have worked with the open-source community to make their files readable and accessible via R, we will showcase how to integrate those tools into your own workflows. At the same time, this being a [**free**]{.underline} course, it doesn't make sense to turn around and ask you to go and either free trial or buy an expensive software license just to see how a particular free R package works. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Fortunately, for showing how to use this [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) functionality, we can use [Floreada.io](https://floreada.io/). It is a simple (but free) web-based analysis platform that can be used to draw manual gates for your .fcs files of interest. These can then be saved as Floreada workspaces for later use. We typically recommend it to users from labs that do flow experiments infrequently. Fortunately thanks to the hard work of its [developers](https://floreada.io/about), it can also save the gated files as [FlowJo](https://flowjo.com/flowjo10/download) v10 .wsp files, which with a small workaround become usable within the [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) pipeline. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -To facilitate this, we will provide a small walk-through of how to use it for those who want to create a .wsp with their own .fcs files for [Week 5](https://umgcccfcsr.github.io/CytometryInR/Schedule#gating-sets). -::: -::: - ---- - -# Walk-through - -## Floreada - -### Loading Dataset - -::: {.fragment} -::: {.callout-tip title="."} -First, open your web browser and navigate to the [website](https://floreada.io/) - -Click on Start to proceed to the next page. -::: -::: - ---- - -![](images/01_LandingPage.png) - ---- - -![](images/02_InitialPage.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once that is done, select the File tab on the upper navigation bar. Then click on Open File(s). -::: -::: - ---- - -![](images/03_OpenFiles.png){fig-align="left"} - ---- - -::: {.fragment} -::: {.callout-tip title="."} -From there, select your .fcs files of interest, and click Open. -::: -::: - ---- - -![](images/04_SelectFCSFiles.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The .fcs files will now load in, and you should see a view similar to the one below. On the left side-bar, you have your gating options (Rectangle, Polygon, Range, Elipse, Quad, etc). Next to these on the right you have the FCS files that are loaded into the workspace. Then on the right, you have the visual display for your selected specimen. -::: -::: - ---- - -![](images/05_InitialFiles.png) - ---- - -### Switching Axis Markers - -::: {.fragment} -::: {.callout-tip title="."} -If you left click on the axis name (SSC-H or FSC-H in this case), you will be able to select other markers by which to gate your specimen. For the provided example, we were using a raw spectral flow cytometry .fcs file, so the names of the detectors are present. -::: -::: - ---- - -![](images/06_LeftClick.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For now, I plan to start off by gating for singlets. I switch the y-axis to FSC-H, and then proceed to switch the x-axis to FSC-A. -::: -::: - ---- - -![](images/07_LeftClickXaxis.png) - ---- - -### Creating Gates - -::: {.fragment} -::: {.callout-tip title="."} -With this done, I can now select the Poly gate tab on the upper left. -::: -::: - ---- - -![](images/08_PolygonGateSelect.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Then manually click on the locations on the plot to add the individual gate nodes. -::: -::: - ---- - -![](images/08_PolygonGateStart.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -To complete the gate, I click back to the original node point. At this point, the popup will allow you to name the gate. -::: -::: - ---- - -![](images/08_PolygonGateCreate.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -To adjust the polygon gate, you can click on a node and drag it to expand or contract in a particular direction -::: -::: - ---- - -![](images/08_PolygonGateNode.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -To move the entire gate, first click on a node to select the gate, then click in the center of the gate to adjust its location. -::: -::: - ---- - -![](images/08_PolygonGateCenter.png) - ---- - - -### Additional Gates - -::: {.fragment} -::: {.callout-tip title="."} -Unfortunately for those with the force-of-habit from using other softwares, double-clicking within the gate doesn't do anything. To continue gating on the selected cells, you will need to click on the newly created gate name on the left. This will result in visualizing the isolated cells. -::: -::: - ---- - -![](images/09_SecondLanding.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once this is done, you can repeat the previous steps to change the axis markers and create a second gate. For this example, we went with a "Cells" gate to exclude debris from this particular sample. -::: -::: - ---- - -![](images/09_SecondGate.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Having created the "Cells" gate, we will be switching gating based on FSC and SSC to using the detector parameters. - -The samples in this example were acquired to derive the cell counts and concentration of various cell populations within cryopreserved cord and peripheral blood mononuclear cells (CBMC and PBMC) specimens after thawing. - -They were stained with CD19 BV421, CD45 PE, and CD14 APC on a [5-Laser Cytek Aurora](https://spectrum.cytekbio.com/), before unmixing, this would correspond respectively to V1, YG1/B4, R1/YG4 peaks respectively. -::: -::: - ---- - -### Scaling/Transformation - -::: {.fragment} -::: {.callout-tip title="."} -When we switch the axis, we can see that the scaling/transformation is not ideal, as the staining and not-staining populations are scrunched up together in the center of the plot. -::: -::: - ---- - -![](images/10_Untransformed.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -To change the scaling/transformation, we need to click directly on the axis. -::: -::: - ---- - -![](images/10_ClickGrid.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -From there, when we click on the drop-down, we see the various transformation options. We will select [Logicle](https://pubmed.ncbi.nlm.nih.gov/16604519/), given we are working with spectral flow cytometry files. -::: -::: - ---- - -![](images/10_SelectLogicle.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -This y-axis values are subsequently visualized with the logicle transformation applied, increasing our resolution between the positive and negative population. -::: -::: - ---- - -![](images/10_LogicleY.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can then repeat this for the x-axis, adjusting the fine-tune options for the scaling as needed. -::: -::: - ---- - -![](images/10_DoubleLogicleAxis.png) - ---- - -### Navigating Gating Hierarchy - -::: {.fragment} -::: {.callout-tip title="."} -With this done, let's first draw a rectangle gate for the CD45+ (B4-A) cells. -::: -::: - ---- - -![](images/10_CD45Gate.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And then selecting that population by clicking on the gate name, let's proceed and gate the CD19+ cells (V2-A). -::: -::: - ---- - -![](images/10_CD19Gate.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -As you can see, we now have the various gates present in the gating hierarchy for the respective .fcs file. To return to a previous gated population, we would click on the parent population above it. -::: -::: - ---- - -![](images/11_ReturnToPrevious.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can subsequently add an additional gate at this gating level for the likely debris population (the threshold setting was suboptimal for this experimental run). -::: -::: - ---- - -![](images/11_AdditionalGates.png) - ---- - -### Copying Gates - -::: {.fragment} -::: {.callout-tip title="."} -This was the process for gating for a single specimen. To copy gates over to the other specimens, we have two options. First, holding down your Ctrl (or equivalent) button, you can click on the individual gate names. -::: -::: - ---- - -![](images/11_ControlHighlight.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -From there, you can drag them down to the next specimen and apply them. -::: -::: - ---- - -![](images/11_ApplyToNext.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Alternatively, you can drag down the highlighted gated to the Pipelines Tab, and apply to All Files. This will result in the gates being copied to all specimens in the experiment. -::: -::: - ---- - -![](images/11_ApplyAllViaPipelines.png) - ---- - -![](images/13_PipelineAdjustAll.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Adjustments within Pipelines will carry over to all other respective unmodified specimens that share it’s gates. -::: -::: - ---- - -![](images/13_PipelineAdjustCD19.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once this is done, I recommend cycling through the gates for each specimen, just to ensure that the gates were positioned correctly before saving the workspace. -::: -::: - ---- - -![](images/12_ClickAdjust.png) - ---- - -### Saving Workspace - -::: {.fragment} -::: {.callout-tip title="."} -With everyone now "correctly" gated, we can proceed to save the workspace so that we can reopen it later from another browser. - -To do this we open the File tab from the upper navigation bar, and select Save Workspace. -::: -::: - ---- - -![](images/14_SaveWorkspace.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -From there we have a couple options, for now let's select Floreada Workspace. Where it is saved at will depend on your individual browser settings, so watch for a popup. -::: -::: - ---- - -![](images/14_FloreadaWorkspace.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Alternatively (and crucially for the CytoML pipeline) we can also choose to save it as a FlowJo v10 .wsp file. -::: -::: - ---- - -![](images/14_FlowJoWorkspace.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In both cases, you will end up with Workspace files that can be used later to access your created gates -::: -::: - ---- - -![](images/WorkspaceFiles.png) - ---- - -### Reopening Workspace - -::: {.fragment} -::: {.callout-tip title="."} -To reopen the Floreada workspace within the browser, reopen the website, and select the Open File(s) option. -::: -::: - ---- - -![](images/15_Reopening.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -From there, select both the Floreada Workspace file as well as the .fcs files -::: -::: - ---- - -![](images/15_ReopeningSelectAll.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -At which point you will now be back to the point you last saved at. -::: -::: - ---- - -![](images/15_ReopenedWorkspace.png) - ---- - -## CytoML - -::: {.fragment} -::: {.callout-tip title="."} -Due to a unknown formatting bug, the Floreada produced FlowJo v10 .wsp is not directly accessible by CytoML at the time of this course. However, the issue is resolved as soon as the file is opened the first time within FlowJo v10, regardless of whether you have a log in or not. Strange? Yes, but we will take the workaround. - -So, for anyone on Windows or MacOS, download [FlowJo v10](https://www.flowjo.com/flowjo10/overview). Once installed, open the software, and close the login popups. Once there, open the Floreada created FlowJo.wsp file. Since you haven't logged in, it won't show any events. But it will correct the formatting bug. Close the software, and return to R. Your Floreada sourced .WSP file should now be readable by CytoML. - -Odd? For sure. Fixable? Likely, I will set a reminder to work with the Floreada and CytoML devs to see if we can cut out the need for this workaround. -::: -::: - -# Wrap-up - - -# Additional Resources - -[Floreada Documentation](https://floreada.io/docs/) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Using Floreada" +author: "David Rach" +date: 02-01-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + + +# Background + +::: {.fragment} +::: {.callout-tip title="."} +As a "Cytometry in R" course, we will primarily be working in R. However, within our daily workflows and projects here at our flow cytometry core, we often use various flow cytometry softwares (like [FlowJo](https://flowjo.com/flowjo10/download) or [FCS Express](https://denovosoftware.com/)) for various tasks. Fortunately, R packages like [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) can allow us to import our manually drawn gates from existing FlowJo workspaces so that we can work with them in R. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For this course, we are adamant about staying neutral in regards to both commercial software or instrument vendors as much as possible. If they have worked with the open-source community to make their files readable and accessible via R, we will showcase how to integrate those tools into your own workflows. At the same time, this being a [**free**]{.underline} course, it doesn't make sense to turn around and ask you to go and either free trial or buy an expensive software license just to see how a particular free R package works. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Fortunately, for showing how to use this [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) functionality, we can use [Floreada.io](https://floreada.io/). It is a simple (but free) web-based analysis platform that can be used to draw manual gates for your .fcs files of interest. These can then be saved as Floreada workspaces for later use. We typically recommend it to users from labs that do flow experiments infrequently. Fortunately thanks to the hard work of its [developers](https://floreada.io/about), it can also save the gated files as [FlowJo](https://flowjo.com/flowjo10/download) v10 .wsp files, which with a small workaround become usable within the [CytoML](https://www.bioconductor.org/packages/release/bioc/html/CytoML.html) pipeline. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To facilitate this, we will provide a small walk-through of how to use it for those who want to create a .wsp with their own .fcs files for [Week 5](https://umgcccfcsr.github.io/CytometryInR/Schedule#gating-sets). +::: +::: + +--- + +# Walk-through + +## Floreada + +### Loading Dataset + +::: {.fragment} +::: {.callout-tip title="."} +First, open your web browser and navigate to the [website](https://floreada.io/) + +Click on Start to proceed to the next page. +::: +::: + +--- + +![](images/01_LandingPage.png) + +--- + +![](images/02_InitialPage.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once that is done, select the File tab on the upper navigation bar. Then click on Open File(s). +::: +::: + +--- + +![](images/03_OpenFiles.png){fig-align="left"} + +--- + +::: {.fragment} +::: {.callout-tip title="."} +From there, select your .fcs files of interest, and click Open. +::: +::: + +--- + +![](images/04_SelectFCSFiles.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The .fcs files will now load in, and you should see a view similar to the one below. On the left side-bar, you have your gating options (Rectangle, Polygon, Range, Elipse, Quad, etc). Next to these on the right you have the FCS files that are loaded into the workspace. Then on the right, you have the visual display for your selected specimen. +::: +::: + +--- + +![](images/05_InitialFiles.png) + +--- + +### Switching Axis Markers + +::: {.fragment} +::: {.callout-tip title="."} +If you left click on the axis name (SSC-H or FSC-H in this case), you will be able to select other markers by which to gate your specimen. For the provided example, we were using a raw spectral flow cytometry .fcs file, so the names of the detectors are present. +::: +::: + +--- + +![](images/06_LeftClick.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For now, I plan to start off by gating for singlets. I switch the y-axis to FSC-H, and then proceed to switch the x-axis to FSC-A. +::: +::: + +--- + +![](images/07_LeftClickXaxis.png) + +--- + +### Creating Gates + +::: {.fragment} +::: {.callout-tip title="."} +With this done, I can now select the Poly gate tab on the upper left. +::: +::: + +--- + +![](images/08_PolygonGateSelect.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Then manually click on the locations on the plot to add the individual gate nodes. +::: +::: + +--- + +![](images/08_PolygonGateStart.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To complete the gate, I click back to the original node point. At this point, the popup will allow you to name the gate. +::: +::: + +--- + +![](images/08_PolygonGateCreate.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To adjust the polygon gate, you can click on a node and drag it to expand or contract in a particular direction +::: +::: + +--- + +![](images/08_PolygonGateNode.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To move the entire gate, first click on a node to select the gate, then click in the center of the gate to adjust its location. +::: +::: + +--- + +![](images/08_PolygonGateCenter.png) + +--- + + +### Additional Gates + +::: {.fragment} +::: {.callout-tip title="."} +Unfortunately for those with the force-of-habit from using other softwares, double-clicking within the gate doesn't do anything. To continue gating on the selected cells, you will need to click on the newly created gate name on the left. This will result in visualizing the isolated cells. +::: +::: + +--- + +![](images/09_SecondLanding.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once this is done, you can repeat the previous steps to change the axis markers and create a second gate. For this example, we went with a "Cells" gate to exclude debris from this particular sample. +::: +::: + +--- + +![](images/09_SecondGate.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Having created the "Cells" gate, we will be switching gating based on FSC and SSC to using the detector parameters. + +The samples in this example were acquired to derive the cell counts and concentration of various cell populations within cryopreserved cord and peripheral blood mononuclear cells (CBMC and PBMC) specimens after thawing. + +They were stained with CD19 BV421, CD45 PE, and CD14 APC on a [5-Laser Cytek Aurora](https://spectrum.cytekbio.com/), before unmixing, this would correspond respectively to V1, YG1/B4, R1/YG4 peaks respectively. +::: +::: + +--- + +### Scaling/Transformation + +::: {.fragment} +::: {.callout-tip title="."} +When we switch the axis, we can see that the scaling/transformation is not ideal, as the staining and not-staining populations are scrunched up together in the center of the plot. +::: +::: + +--- + +![](images/10_Untransformed.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To change the scaling/transformation, we need to click directly on the axis. +::: +::: + +--- + +![](images/10_ClickGrid.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +From there, when we click on the drop-down, we see the various transformation options. We will select [Logicle](https://pubmed.ncbi.nlm.nih.gov/16604519/), given we are working with spectral flow cytometry files. +::: +::: + +--- + +![](images/10_SelectLogicle.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This y-axis values are subsequently visualized with the logicle transformation applied, increasing our resolution between the positive and negative population. +::: +::: + +--- + +![](images/10_LogicleY.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can then repeat this for the x-axis, adjusting the fine-tune options for the scaling as needed. +::: +::: + +--- + +![](images/10_DoubleLogicleAxis.png) + +--- + +### Navigating Gating Hierarchy + +::: {.fragment} +::: {.callout-tip title="."} +With this done, let's first draw a rectangle gate for the CD45+ (B4-A) cells. +::: +::: + +--- + +![](images/10_CD45Gate.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And then selecting that population by clicking on the gate name, let's proceed and gate the CD19+ cells (V2-A). +::: +::: + +--- + +![](images/10_CD19Gate.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As you can see, we now have the various gates present in the gating hierarchy for the respective .fcs file. To return to a previous gated population, we would click on the parent population above it. +::: +::: + +--- + +![](images/11_ReturnToPrevious.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can subsequently add an additional gate at this gating level for the likely debris population (the threshold setting was suboptimal for this experimental run). +::: +::: + +--- + +![](images/11_AdditionalGates.png) + +--- + +### Copying Gates + +::: {.fragment} +::: {.callout-tip title="."} +This was the process for gating for a single specimen. To copy gates over to the other specimens, we have two options. First, holding down your Ctrl (or equivalent) button, you can click on the individual gate names. +::: +::: + +--- + +![](images/11_ControlHighlight.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +From there, you can drag them down to the next specimen and apply them. +::: +::: + +--- + +![](images/11_ApplyToNext.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, you can drag down the highlighted gated to the Pipelines Tab, and apply to All Files. This will result in the gates being copied to all specimens in the experiment. +::: +::: + +--- + +![](images/11_ApplyAllViaPipelines.png) + +--- + +![](images/13_PipelineAdjustAll.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Adjustments within Pipelines will carry over to all other respective unmodified specimens that share it’s gates. +::: +::: + +--- + +![](images/13_PipelineAdjustCD19.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once this is done, I recommend cycling through the gates for each specimen, just to ensure that the gates were positioned correctly before saving the workspace. +::: +::: + +--- + +![](images/12_ClickAdjust.png) + +--- + +### Saving Workspace + +::: {.fragment} +::: {.callout-tip title="."} +With everyone now "correctly" gated, we can proceed to save the workspace so that we can reopen it later from another browser. + +To do this we open the File tab from the upper navigation bar, and select Save Workspace. +::: +::: + +--- + +![](images/14_SaveWorkspace.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +From there we have a couple options, for now let's select Floreada Workspace. Where it is saved at will depend on your individual browser settings, so watch for a popup. +::: +::: + +--- + +![](images/14_FloreadaWorkspace.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively (and crucially for the CytoML pipeline) we can also choose to save it as a FlowJo v10 .wsp file. +::: +::: + +--- + +![](images/14_FlowJoWorkspace.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In both cases, you will end up with Workspace files that can be used later to access your created gates +::: +::: + +--- + +![](images/WorkspaceFiles.png) + +--- + +### Reopening Workspace + +::: {.fragment} +::: {.callout-tip title="."} +To reopen the Floreada workspace within the browser, reopen the website, and select the Open File(s) option. +::: +::: + +--- + +![](images/15_Reopening.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +From there, select both the Floreada Workspace file as well as the .fcs files +::: +::: + +--- + +![](images/15_ReopeningSelectAll.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +At which point you will now be back to the point you last saved at. +::: +::: + +--- + +![](images/15_ReopenedWorkspace.png) + +--- + +## CytoML + +::: {.fragment} +::: {.callout-tip title="."} +Due to a unknown formatting bug, the Floreada produced FlowJo v10 .wsp is not directly accessible by CytoML at the time of this course. However, the issue is resolved as soon as the file is opened the first time within FlowJo v10, regardless of whether you have a log in or not. Strange? Yes, but we will take the workaround. + +So, for anyone on Windows or MacOS, download [FlowJo v10](https://www.flowjo.com/flowjo10/overview). Once installed, open the software, and close the login popups. Once there, open the Floreada created FlowJo.wsp file. Since you haven't logged in, it won't show any events. But it will correct the formatting bug. Close the software, and return to R. Your Floreada sourced .WSP file should now be readable by CytoML. + +Odd? For sure. Fixable? Likely, I will set a reminder to work with the Floreada and CytoML devs to see if we can cut out the need for this workaround. +::: +::: + +# Wrap-up + + +# Additional Resources + +[Floreada Documentation](https://floreada.io/docs/) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_Git/.DS_Store b/course/00_Git/.DS_Store deleted file mode 100644 index 084a051..0000000 Binary files a/course/00_Git/.DS_Store and /dev/null differ diff --git a/course/00_Git/index.qmd b/course/00_Git/index.qmd index 6f44485..5835d1a 100644 --- a/course/00_Git/index.qmd +++ b/course/00_Git/index.qmd @@ -1,899 +1,899 @@ ---- -title: "Version Control with Git" -author: "David Rach" -date: 01-21-2026 -format: html -toc: true -toc-depth: 5 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -For the YouTube livestream recording, see [here](https://www.youtube.com/live/mw6Trvv3Pqg?si=vx6yEaXGpYbtq3DY) - - - -For screen-shot slides, click [here](/course/00_Git/slides.qmd) - - -# Background - -Now that we have created a [GitHub account](/course/00_GitHub/index.qmd), installed the required [software](/course/00_WorkstationSetup/index.qmd) and investigated [Positron's](/course/00_Positron/index.qmd) layout, we will start learning about version control software. - -When working with code, it is important to stay organized. Ideally, everything needed for your code to successfully run should be present and accounted for within the local environment. Likewise, if you make changes, and your code stops working (no longer returning the expected output, ie. breaks), it would be most useful to have a track record of what has changed since your last working version in order to fix the issue. For beginners, this is often a typo in a function name or a misplaced comma somewhere within your document. - -For this course, we will be using the version control software [Git](https://git-scm.com/). It is widely used by software developers and bioinformaticians worldwide, and is a very useful tool to have in your coding toolbox. - -Git works locally within your individual project folders to track changes to the documents within, allowing to save the current state of the folder along the way (ie. a commit). This allows you to compare to previous versions (other commits) and return the changes that have occured to the tracked files. - -As we saw during the [workstation setup](/course/00_WorkstationSetup/index.qmd) section, when you have a linked GitHub account, you can backup folders as repositories online. By leveraging the ability to send and receive changes, this allows you to modify a file on one computer, - - Individual repositories can be linked to a GitHub account, which permits them to be backed up online. Within our workflow, this allows to modify on one computer, back up (ie. push) the changes to GitHub, and then later on a different workstation, retrieve (ie. pull) these new changes and continue working. - - In this walk-through, we will set up a New Project Folder from a template, create a few folders and files, and work through how to use the main set of Git commands needed for this course. - - -# Getting Started - -For this walkthrough, we are going to create a brand new project folder. To do this, we can open the folder tab on the upper right. - -From here we can see we have two options, create a "New Folder from a Template", and create a "New Folder from Git" (which was the option we used during [workstation setup](/course/00_WorkstationSetup/index.qmd) to bring in the forked CytometryInR and README repository folders locally). - -We will go ahead and select "New Folder from a Template" for this example. - -![](images/1.png) - -
- ---- - -## New Folder from Template - -Since Positron can use multiple programming languages, when we select "New Folder from Template" we will be asked what kind of folder template we want to use. Since we are working in R, we will select the "R Project" option. - -![](images/2.png) - -
- ---- - -We will next be asked to name the new project folder and a storage location. - -One thing I would like to remind everyone who is just starting to code is that it is best to avoid using [special characters](https://en.wikipedia.org/wiki/Regular_expression) (ex. @ $ # ^ ! ; : ,) in any folder or file name. This is because when coding, these can be misinterpreted as commands. - -While spaces are generally okay, it is often to best stick to to stick to hyphens (-), underscores (_). We will explore naming conventions in more depth at a later time. - -![](https://pbs.twimg.com/media/FxVpCpqaIAE_iqU?format=jpg&name=small) - -
- ---- - -Another useful thing to know when getting started with version control, it is best to save your files within your local computer, avoid using OneDrive or other cloud storage options for the time reason. The reason behind is that permissions to write/save to the cloud locations can sometimes be quite finicky, and some autosave/indexing behaviors can cause issues. akes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. - -Having named our new Project Folder, and designated a storage location, go ahead and check the Initialize Git Repository option. This will indicate to version control to monitor content and changes to files within this folder. - -![](images/3.png) - -
- ---- - -The next setup screen will verify which version of R you wish to use. Since we are just getting started, your most recent version of R (usually system) should work. We will also leave the "renv" (reproducible environment setup) option unchecked for the time being (we will revisit the concept later in the course). - -![](images/4.png) - -
- ---- - -And if all goes well, we should see the "New Folder Created" popup. - -![](images/5.png) - -
- ---- - -## Creating SubFolders - -Once your new project folder has opened, you should be seeing the main layout elements that we briefly covered in the [Positron](/course/00_Positron/index.qmd) walk-through. - -For this section, we will primarily be focused on what is happening within the primary side bar on the left, where changes to the individual files within the folder since the last save/commit will be reflected by colored text. - -For my own projects, there are some elements of organization that I go ahead and add for each new folder. These include both a data and an images subfolders to help keep things a little more organized. - -To create these folders, we would click on the respective add folder (+) button on the side bar. Files and Folders can be clicked and dragged within the primary side bar to move things to new folder locations. - -![](images/6.png) - -
- ---- - -## Creating Files - -In context of this course, we will primarily be working with two types of files when coding: - -- R Scripts: These files end in .R. These contain only code (with occasional \# comment line). These are often used for self-contained code that once we get them working we rarely need to modify. - -- Quarto Markdowns: These files end in .qmd. They contain a .yaml header, followed by a mix of regular written text (often explanations or other documentation), and sections (ie. chunks) that contain code. These are used when we are still getting the code to work, when we need to modify inputs frequently, or simply when we need to document what and why we are doing something to make life easier for our future-self two months from now. - -
- ---- - -In this example, I will go ahead and select the new file icon - -![](images/7.png) - -
- ---- - -Thenn I will name the file, and designate it as a Quarto Markdown file by adding the .qmd at the end of the name to denote the file type. - -![](images/8.png) - -
- ---- - -## QMD Files - -Once this is done, we can now see we have a new .qmd file ("Example.qmd" in this case). - -### YAML - -As previously mentioned, the start of a [Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) file containg a [YAML](https://quarto.org/docs/authoring/front-matter.html) code chunk that is used to set formatting choices (we will explore this in-depth during the [next section](/course/00_Quarto/index.qmd)) - - -What designates the location of the YAML block are three hyphens at the start, and three hyphens at the end. For this example, we will also provide a "title:" and "format:" field for the time being (see additional options [here](https://quarto.org/docs/authoring/front-matter.html)). - -![](images/9.png) - -
- ---- - -### Text - -With a basic YAML formatting block now in place, we can build out other elements of our Quarto Markdown document. Unless otherwise specified, everything else in the document is assumed to be text, so I will go ahead and provide an initial text description of what I am trying to do. - -![](images/10.png) - -
- ---- - -### Code-Chunks - -Having provided some initial text for documentation, we can then add code-block chunks to start writing some code. - -The easiest way to do do this is to click the respective option on the upper-right of the Editor screen. Since Positron can handle multiple programming languages, so the chunk is inserted, we will need to select the language we use to be used within the code chunk (R in this case). - -![](images/11.png) - -
- ---- - -You will notice, that the inserted code block starts off with three backticks (\`) and then "{r}". The end of the code block is denoted by an additional three backticks. - -We can also add new code blocks by simply typing these elements into the location we want to place a code chunk (as long as we are careful to add 3 backticks also at the end). - -![](images/12.png) - -
- ---- - -![](images/13.png) - -
- ---- - -### Running Code - -Now that we have two code-chunks written, we can write lines of code within them. For this example, I will use two beginner friendly functions, print("Hello"), which will print the contents contained between the " " to the console, and getwd() which will return the location of the folder you are working within (ie. the working directory). - -To run/execute these lines of code, we have a couple options. We can click on the Run Cell option that appears on the upper-left side of the code chunk. Additionally, it has a companion option that will run all code chunks above it. - -![](images/14.png) - -
- ---- - -When a code block is successfully run, you will see within the console (lower bottom of the screen) the line of code be run, with any returned outputs appear directly after. - -![](images/15.png) - -
- ---- - -An alternative to clicking the Run Cell button is to click on the line of code you are interested in running, then press (Ctrl + Enter)/(Command + Enter). This will execute the line of code that you have clicked on. This can be useful in scenarios where you want to run a specific line, and not the entire code-chunk. - -![](images/16.png) - -
- ---- - -Using this approach, you can see the location (ie. file path) of the current working directory was returned to the Console. - -![](images/17.png) - -
- ---- - -## Local Version Control - -Having introduced the main elements of a [Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) file, let's turn our attention to the tab within the editor showing our newly created .qmd file. - -We can see there is a solid circle next to the file name, and it is appearing as green. The circle denotes unsaved changes, which we can correct by clicking on the Save Button to save the changes to our file. - -![](images/18.png) - -
- ---- - -### Untracked - -If we turn our attention to the left primary sidebar, we can see that within our GitPractie folder there are three files, our Example.qmd, and the default README.md and .gitignore files. These all show up in green text with U's to the right of the file names. - -This denotes that the version control tracking software Git is currently considering them as "Untracked" files. While saving the document via the Save button means we will still have our changes when we reopen Positron, we won't have any history of changes that we can use to revert back to the way all the files appeared at this exact point in time should something go wrong. - -We will next go the address bar on the very far left, and select the Git tab. - -![](images/19.png) - -
- ---- - -On the Git tab, we can see that each of the three files are shown underneath a "Changes" drop-down. This contains the files that have undergone changes since the last commit. In our case, since we haven't updated the save-state yet, this last commit would be the initial creation of the project folder. - -![](images/20.png) - -
- ---- - -To have version control track these individual files going forward, we can do so in two separate ways. We can add them individually by clicking the + symbol next to the individual names. - -![](images/21.png) - -
- ---- - -### Staged - -This will result in the files being moved to the "Staged" dropdown. This denotes files being tracked with the intention of being recorded as the next save-state or waypoint (ie. a commit). - -![](images/22.png) - -
- ---- - -### Commit - -To create a new commit (save-state or waypoint), once we have the files we want to track staged, we will write a commit message, and then press commit. - -A commit message is a brief description of the changes that have occurred to the files between this commit and the previous one. Make this short description informative enough that if you need to revert back in the future, you can quickly identify the commit you need to fall back to (more about this later). - -![](images/23.png) - -
- ---- - -If this your first time using version control, you will likely encounter the following pop-up asking that you provide a user.name and user.email. This is used to designate the author of the changes.If you get this popup, go ahead and select "Open Git Log" - -![](images/24.png) - -
- ---- - -### UserName and UserEmail - -The Output tab at the bottom of the screen will open, showing the messages that led to the popup. - -The important part to note is the commands that will be needed to provide your user name and email to the computer for authoring the commit. Typically, your email will be the same one you used for your GitHub account. - -![](images/25.png) - -
- ---- - -From the displayed message, go ahead and copy - -"git config –global user.email "you\@example.com"" - -Then click on the adjacent terminal tab. You will paste the command in, but do not hit enter just yet. - -Windows users, please note, depending on your settings, if trying to paste from the keyboard into the terminal, you may need to press "Ctrl + Shift + V" instead of the usual "Ctrl + V". - -![](images/26.png) - -
- ---- - -With the command now pasted (or typed), use your keyboard arrows to navigate to the email portion, and replace the generic email with your email address used for your GitHub account. - -Make sure that the quotation marks (") around the email address remain present, as they help the computer identify where your email address starts and ends. Once satisfied that your email address is correct, press enter. - -![](images/27.png) - -
- ---- - -Next up, repeat the process, this time copying over the command needed to set your user name to the terminal. Repeat the editing process to provide your name between the "" marks. Then press enter. - -![](images/28.png) - -
- ---- - -![](images/29.png) - -
- ---- - -### First Commit - -Now that your user.name and email address have been provided, Git should be able to provide an author to the commit message. Reattempt to press commit button. - -If this is successful, you will see your initial commit appear on the bottom half of the left primary side bar, under the Graph dropdown. Congrats! Your files are now being tracked by version control. - -![](images/30.png) - -
- ---- - -If you hover with your mouse arrow just over the commit, you can see the longer commit message and additional details appear. - -If you click on the commit tab, a new display will open in the editor, displaying the changes that occured in that commit compared to the previous one. In this case, since we added everything since the previous commit, nothing appears on the left side, while the entire documents contents appear highlighted in green on the right. - -Green highlighting is used to show additions, while red highlighting is used to show deletions. - -![](images/31.png) - -
- ---- - -Having completed this initial commit, for this example, let's imitate a typical workflow and make some additional changes to the file before we make a second commit. Within text portions of the .qmd file, use of \# denotes a section header in markdown, so let's add a header for Introduction and click save. - -![](images/32.png) - -
- ---- - -### Modified - -Within the left primary sidebar, we can see that the Git tracking has updated. Examples.qmd is visible once again. However, becuase it is now a tracked file, instead of showing up with the "U/Untracked" green highlight, it now appears as a brownish-red with a "M/Modified". - -Let's make an additional change to the .qmd file by adding another section (# Setup) and a code block with a commented out line (denoted by the \# at the line start), before pressing Save. - -![](images/33.png) - -
- ---- - -If we were now to click on the Example.qmd file in the left primary sidebar, it will open the same kind of tracking display we saw previously. This time, we can see changes since our last commit. These appear as the green highlights along the scroll-bar, corresponding to the \# Introduction and \# Setup headers that we have added in since the last commit. - -![](images/34.png) - -
- ---- - -For a larger document, we can scroll down to see the various highlighted regions. - -![](images/35.png) - -
- ---- - -We could now repeat the steps showed above, staging the file, writing a commit message, and commiting again by clicking on the designated buttons. - -An important question is how often should we commit, vs. just hit save? Well... it depends :D -Let's think about this in context of a video game. If you made commits at regular intervals throughout the day (or more frequently when doing something particularly risky), you are more likely to be close enough to a particular commit (waypoint/save-state) that you can quickly revert back to without loosing any progress. Alternatively, if your last commit was last week, you will not have any intermediate versions to fall back to. - -### Commit via Terminal - -Having demonstrated how to commit changes to Git via the left primary side-bar, for this second commit, let's do it the alternate way via the terminal (tab on the panel at the bottom of your screen). - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - -
- ---- - -After clicking on the terminal tab, click on blinking command line. - -The command to stage a file is "git add ", followed by the name of the file you want to stage. - -In this case, you would enter "git add Example.qmd" and press Enter. -![](images/36.png) - -
- ---- - -You will see after pressing enter a new blank terminal line appear. If you glance at the left-sidebar, you can see that Example.qmd now appears under the Staged Changes dropdown. - -![](images/37.png) - -
- ---- - -Next up, let's write the git commit via the terminal. In this case, the command would be "git commit -m " (-m denoting message). The commit text is then surrounded by "" marks. - -For example: "git commit -m "Added section headers to my QMD file"" - -Press enter to save the commit. - -![](images/38.png) - -
- ---- - -And you should see your second commit now appear in the left primary sidebar underneath the graphs dropdown. - -![](images/39.png) - -
- ---- - -## Remote Version Control - -### Copying Project Folder to GitHub - -While having local version control in place is helpful when you need to revert back after encountering issues, where Git shines is the ability to pass your changes to your online GitHub repository. - -Not only does this allow you to switch between computers, but should something disastrous happen to your main computer, you still have all your hard work backed up and readily assessible. - -For this subsection, first, double check that Positron is still connected to your GitHub account by checking the user tab on the bottom-left. If not, repeat the [connection setup](/course/00_WorkstationSetup/Windows.qmd#connecting-github-and-positron). - -![](images/40.png) - -
- ---- - -Since our project was created using the "New Folder from Template" option, it currently only exist locally. What we want to do next is to copy it to our GitHub account, creating a new repository in the process. - -To do this, we will first need to install the `usethis` R package. Within your console, you would run the following line of code: - -```{r} -#| eval: false -install.packages("usethis") -``` - -Depending on what R packages you already have installed on your computer, you may get a prompt asking if you want to update/install additional dependencies. Go ahead and type the number corresponding to Update All, and press enter. - -The package and all it's dependencies should then install. If an error message appears, read through it, and follow provided instructions. Go to [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) -if need help. - -
- ----- - -Once the `usethis` package is installed, we need to activate it within R by calling it with the library command. This makes all the tools (ie. functions) within an R package available for use within Positron. - -In your console, you would type: - -```{r} -#| eval: FALSE -library(usethis) -``` - -![](images/46.png) - -
- ---- - - -With library called, you now have access to the functions (tools) within the `usethis` R package. One of these is the `use_github()` function. - -In Positron, if you hover over a function, it will pull up the associated help file which will provide you information about the arguments the function expects to receive, and what they do. - -For `use_github()`, the main thing to remember for now is since this is a personal project being used for testing, we don't necessarily want to share it with the entire world, so we should set the "private" argument equal to TRUE when creating a new repository. - -![](images/46.png) - -
- ---- - -Taking this information that we have now gathered, we can now within our Quarto Markdown create a code chunk, write out the line of code calling the function, and providing the Private=TRUE argument within the (). - -Within a code chunk, adding a \# in front of a line of code, will comment it out, resulting in that line of code not being run. Since we have already installed the `usethis` package, and we don't want to reinstall it every single time, let's go ahead and comment out that line. Go ahead and press Enter. - -![](images/47.png) - -
- ---- - -We will see a message pop-up in the console. In this case, we had not saved before pressing enter, so there are uncommitted changes within the folder. The pop-up is asking whether you want to save these as well before sending the Folder to GitHub. - -In this case I will chose to ignore the uncommitted changes by entering 3 (for Definitely) in the console and hitting enter on my keyboard. - -![](images/48.png) - -
- ---- - -The `usethis` R package will then execute the series of git commands that are needed to set up a GitHub repository (ie. the messages being displayed in the console window), and when finished will open a pop-up asking whether you want to see your new repository in your default Web Browser. I will go ahead and select yes in this case. - -![](images/49.png) - -
- ---- - -After the browser opens, you can see that the elements I had staged and committed within Positron are now present within the GitHub repository. -Since I had only staged Example.qmd, it is the only file that was backed up. We can also see the commit history online by clicking on the commit clock. - - -![](images/50.png) - -
- ---- - -As we would expect, we only see our two commit messages. One important thing to note is the commit hash numbers, that denote a particular commit. If we decided to revert/fall back to a prior commit in the future, this would be the number we would need to provide to Git to return to that previous commit/save-state - -![](images/51.png) - -
- ---- - -Similarly, on GitHub, we have an option to Browse a Repository at a particular point in time. This will be quite useful later in the future when troubleshooting what major changes occurred between versions of an R package. - -![](images/52.png) - -
- ---- - -### Code Chunk Arguments - -Having successfully connected our local Project Folder to a remote GitHub repository, let's return to Positron. - -Before continuing, if we left the code chunk that created the GitHub repository as is, every time we ran all code chunks in the document, it would try to recreate the GitHub repository. We don't want this to happen, as the setup was a one-time operation. - -While we could add \# in front of every line of code (or delete the code chunk entirely) it is often useful to have these set-up code chunks around to remind us what arguments we need to provide next time we need to a similar setup and are mind blanking on what to do. - -Fortunately, Quarto allows us to set conditions on whether a chunk is run (ie. evaluated). We will discuss the conditiona arguments in more depth in the [next section](/course/00_Quarto/index.qmd), but for now, we can modify the code chunk as follows. - - -On the next line after the {r}, we will add a hashtag (\#), then a pipe (|), followed by a space. This is the setup for a code-chunk specific argument. We will then add "eval: FALSE", which signals that the particular code-chunk should not be evaluated (ie, should not be run). - -![](images/53.png) - -
- ---- - -### README - -Now that we have connected our local Project Folder to GitHub, and have gotten a basic introduction to the "git add", "git commit" arguments, let's turn our focus to the other files currently listed as untracked by Git within our folder, the README.md and the .gitignore files. - -When setting up our [GitHub]() account, we encounted an example of a README.md file. This file often provides a brief description of the project, and an outline of what the other files in the folder are for. As you may have gathered, even software developers are forgetful/under-caffenaited, and having notes to catch back up to speed is important. - -![](images/54.png) - -
- ---- - - -### .gitignore -We additionally have a .gitignore file. Within a project, there are often some files that we will never want version control to track. These could be files that are too large for GitHub (ex. really large .fcs files), or files containing sensitive information (passwords, history, credentials, etc.). - -When the names of these file (or the file type shothand) are added to the .gitignore file, they are ignored by version control, and no longer appear on the primary left side bar. - -![](images/54.png) - -
- ---- - -Let's proceed and stage both the README.md and .gitignore file, so that changes to these files will be tracked. We can of course select both from the primary left side bar and write a short commit message. - -![](images/55.png) - -
- ---- - -![](images/56.png) - -
- ---- - -Or alternatively, if we want to stage all uncommitted files present in a single step, we could in the terminal use the "git add ." - -We can then write our git commit using "git commit -m". - -Both approaches work, and you may switch between them based on preferrence. - -![](images/57.png) - -
- ---- - -You will notice after having committed, that if you look at the Graph dropdown on the bottom half of the primary left side-bar that something has changed. - -There are now separate icons denoted as main and origin/main. These correspond to the last commit present locally (main), and the last commit on remote (ie. GitHub, origin/main). - -Local is ahead since you just made the commit with the changes inactivating the code-chunk, and you have not passed these changes up to GitHub yet. - -![](images/58.png) - -
- ---- - - -### Pull - -Before sending (ie. pushing up) our updated commit to GitHub, especially if you are working on a project from multiple computers (or as part of a team) to bring in (ie. pull down) any changes that might be on GitHub that are not present locally. - -This ensures that everything is up to date, and you don't end up with mismatched commits that are incompatible with each other and trigger an error message. - -To pull in changes from GitHub, at the top of the primary left side-bar, you can select the ... button to open a drop-down menu of Git options. You would then select "Pull". - -Alternatively, you could do the same thing via the terminal by running the "git pull" command. - -![](images/59.png) - -
- ---- - -### Push - -In our case, there was no new material present on our GitHub repository that were not already present locally, so all that is returned is the "Already up to date" message. - -We are now good to proceed to push (ie. send) the updated commit up to our GitHub repository. - -We can do this by either pressing the Sync changes button, or via the terminal entering the "git push" command. - -![](images/60.png) - -
- ---- - -And now, if you glance down at left side-bar's graph section, you will see that both the main and origin/main icons are now present for the most recent commit. - -![](images/61.png) - -
- ---- - -If we switch to our Web browser, we can see that this is also now the case for our GitHub repository that now also has the most recent changes. - -![](images/62.png) - -
- ---- - -### Reverting to Prior Commit - -For most daily-workflows, you will only need the git commands that we have introduced above (git add, commit, pull, push). The next two areas (reverting to a prior commit, and branches) are more specialized, and will be covered in greater depth later in the course. We are briefly covering them here. If you are at the point where your last remaining neuron has disconnected, and you feel you need to take a break from version control, feel free to skip to the [next section](/course/00_Quarto/index.qmd) and we will revisit these topics later in the course. - -
- --- - -In most cases, if your code stops working, you can identify the issue and fix it in the existing version, never needing to resort to reverting to a previous commit (save-state). The times you would need to revert would be if you deleted important files, or the new files are hopeless mess that is not worth trying to sort through. In those cases, reverting back might be better approach. - -To imitate a falling back scenario, lets create and additional file, stage and commit it to end up a commit ahead of where we are currently at within the Project Folder. - -![](images/00_RevertTest.png) - - -
- ---- - -Now being one (or several) commits ahead, if we wanted to revert back, we would first need to identify the commit we want to revert back to and copy the commit hash number. - -![](images/00_CommitHash.png) - - -
- ---- - -Then, opening the terminal, we can enter "git reset " and paste the hash afterwards. We can then press enter. - - -![](images/00_GitReset.png) - - -
- ---- - -You will notice our additional commit has been removed, although the newer files we were working on subsequent last commit are still present. - - -![](images/00_GitResetExecuted.png) - - -
- ---- - -If however, we had wanted to return to the exact same state as the previous commit (removing all subsequent created files), we could do so by adding in the --hard argument. Before starting, save any newer files you want to keep in a completely different folder, because they will be permanently removed. - -Then, enter "git reset --hard thecommithashnumber" into the terminal, which would result in a "hard" return to the previous commits save-state. You may need to close and reopen Positron to see the changes reflected. - - -### Branches - -Branches are an useful Git feature that we will start using extensively later in the course. Branching allows you to create a parallel/carbon-copy of your existing repository, which you can then edit without affecting the main branch. This is particularly useful for projects that may get messy or drawn out. By isolating these edits to a parallel branch, if they don't work, your main branch remains safe. Alternatively, if you like the changes that occurred in the branch, you can pull these changes from the branch back to main, bringing the timelines back together. - -![](https://book.the-turing-way.org/build/sub-branch-491000deab04cb25ea703c007e2ebdd2.png) - ---- - -Within the terminal, entering "git branch" will show the existing branches. In this case, only main is present since we haven't yet created a new branch. - - -![](images/00_Branch.png) - -
- ---- - -We can create a new branch in the terminal by entering "git branch " followed by the name of our desired branch. In this case, we are creating a branch called Week1 - -![](images/00_Week1.png) - -
- ---- - -Now, when we check "git branch" again in the terminal, which returns the two branches, Week1 and main. The \* is located next to main, indicating that we are currently within the main branch. - -![](images/00_Branches.png) - -
- ---- - -Besides the terminal, we can also create a new branch via Positron. To do so, we first click on the Git tab in the Actions Bar. - -Once the left-side bar displays the version control display, we can click on the ... button (to the right of changes)to gain access to the Git options drop-down. - -From here, we click on Branch, and then select Create Branch. - -![](images/00_BranchesGUI.png) - -
- ---- - -Using Git branch, we saw that we were still within the main branch. In the terminal, we can switch over to the Week1 branch by using the "git checkout " command, followed by the branch we wish to switch to. - -![](images/00_Checkout.png) - -
- ---- - -This results in us switching over to the Week1 branch. - -![](images/00_CheckoutOutput.png) - -
- ---- - -Having switched (ie. checkout) to the Week 1 branch, let's create the file BranchTest.qmd, which will exist within this branch, but not yet in the main branch. - -![](images/00_BranchTest.png) - -
- ---- - -Having created the file, let's stage and then commit it. This will put the Week1 branch ahead of the main branch by a single commit. - -![](images/BranchCommit.png) - -
- ---- - -With our changes staged and committed, if we look at the left side-bar's graph section, our Week1 branch is now ahead of the origin/main branch by one commit. - -![](images/00_BranchToOrigin.png) - -
- ---- - -If we were to check on GitHub, we can see that no new files are present on the main branch, but can see the notification listing recent changes to Week1 branch. - -![](images/00_GitHub.png) - -
- ---- - -Using the drop-down, we can switch from displaying the main branch to the Week1 branch, where we can see the new file. - -![](images/00_GitHubWeek1.png) - -
- ---- - -If we click the green compare and pull request button, we end up on this screen. This compares how the two branches are different from each other. - -![](images/00_GithubWeek1Merge.png) - -
- ---- - -We will delve into branches again at a later point. For now, remember that by creating and prunning parallel branches, you can develop knowing that even if something goes wrong, your main branch remains safe. - - -# Wrap-Up - -In this section, we saw how to create a New Project Folder, create files and back up the project folder to GitHub. We also started learning about git, covering the basic commands (git add, commit, pull, push). If you feel a bit overwhelmed, please know, that is normal. Understanding how to leverage git takes time and practice, but is an incredibly valuable skillset to have in the long run. - -In the [next section](/course/00_Quarto/index.qmd), we will look at how by changing various elements within our .qmd file produce a variety of files, and how to leverage code-chunk arguments to fine-tune whether a code-chunk is utilized. - - -# Additional Resources - -[Git & GitHub Tutorial for Scientist: It's Not Only for Programmers](https://gitbookdown.dallasdatascience.com/) - -[Ten Simple Rules for Taking Advantage of Git and GitHub](https://pmc.ncbi.nlm.nih.gov/articles/PMC4945047/) - -[A brief introduction to Git for beginers](https://youtu.be/r8jQ9hVA2qs?si=IYe7JghJpVTz9Ht4) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Version Control with Git" +author: "David Rach" +date: 01-21-2026 +format: html +toc: true +toc-depth: 5 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://www.youtube.com/live/mw6Trvv3Pqg?si=vx6yEaXGpYbtq3DY) + + + +For screen-shot slides, click [here](/course/00_Git/slides.qmd) + + +# Background + +Now that we have created a [GitHub account](/course/00_GitHub/index.qmd), installed the required [software](/course/00_WorkstationSetup/index.qmd) and investigated [Positron's](/course/00_Positron/index.qmd) layout, we will start learning about version control software. + +When working with code, it is important to stay organized. Ideally, everything needed for your code to successfully run should be present and accounted for within the local environment. Likewise, if you make changes, and your code stops working (no longer returning the expected output, ie. breaks), it would be most useful to have a track record of what has changed since your last working version in order to fix the issue. For beginners, this is often a typo in a function name or a misplaced comma somewhere within your document. + +For this course, we will be using the version control software [Git](https://git-scm.com/). It is widely used by software developers and bioinformaticians worldwide, and is a very useful tool to have in your coding toolbox. + +Git works locally within your individual project folders to track changes to the documents within, allowing to save the current state of the folder along the way (ie. a commit). This allows you to compare to previous versions (other commits) and return the changes that have occured to the tracked files. + +As we saw during the [workstation setup](/course/00_WorkstationSetup/index.qmd) section, when you have a linked GitHub account, you can backup folders as repositories online. By leveraging the ability to send and receive changes, this allows you to modify a file on one computer, + + Individual repositories can be linked to a GitHub account, which permits them to be backed up online. Within our workflow, this allows to modify on one computer, back up (ie. push) the changes to GitHub, and then later on a different workstation, retrieve (ie. pull) these new changes and continue working. + + In this walk-through, we will set up a New Project Folder from a template, create a few folders and files, and work through how to use the main set of Git commands needed for this course. + + +# Getting Started + +For this walkthrough, we are going to create a brand new project folder. To do this, we can open the folder tab on the upper right. + +From here we can see we have two options, create a "New Folder from a Template", and create a "New Folder from Git" (which was the option we used during [workstation setup](/course/00_WorkstationSetup/index.qmd) to bring in the forked CytometryInR and README repository folders locally). + +We will go ahead and select "New Folder from a Template" for this example. + +![](images/1.png) + +
+ +--- + +## New Folder from Template + +Since Positron can use multiple programming languages, when we select "New Folder from Template" we will be asked what kind of folder template we want to use. Since we are working in R, we will select the "R Project" option. + +![](images/2.png) + +
+ +--- + +We will next be asked to name the new project folder and a storage location. + +One thing I would like to remind everyone who is just starting to code is that it is best to avoid using [special characters](https://en.wikipedia.org/wiki/Regular_expression) (ex. @ $ # ^ ! ; : ,) in any folder or file name. This is because when coding, these can be misinterpreted as commands. + +While spaces are generally okay, it is often to best stick to to stick to hyphens (-), underscores (_). We will explore naming conventions in more depth at a later time. + +![](https://pbs.twimg.com/media/FxVpCpqaIAE_iqU?format=jpg&name=small) + +
+ +--- + +Another useful thing to know when getting started with version control, it is best to save your files within your local computer, avoid using OneDrive or other cloud storage options for the time reason. The reason behind is that permissions to write/save to the cloud locations can sometimes be quite finicky, and some autosave/indexing behaviors can cause issues. akes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. + +Having named our new Project Folder, and designated a storage location, go ahead and check the Initialize Git Repository option. This will indicate to version control to monitor content and changes to files within this folder. + +![](images/3.png) + +
+ +--- + +The next setup screen will verify which version of R you wish to use. Since we are just getting started, your most recent version of R (usually system) should work. We will also leave the "renv" (reproducible environment setup) option unchecked for the time being (we will revisit the concept later in the course). + +![](images/4.png) + +
+ +--- + +And if all goes well, we should see the "New Folder Created" popup. + +![](images/5.png) + +
+ +--- + +## Creating SubFolders + +Once your new project folder has opened, you should be seeing the main layout elements that we briefly covered in the [Positron](/course/00_Positron/index.qmd) walk-through. + +For this section, we will primarily be focused on what is happening within the primary side bar on the left, where changes to the individual files within the folder since the last save/commit will be reflected by colored text. + +For my own projects, there are some elements of organization that I go ahead and add for each new folder. These include both a data and an images subfolders to help keep things a little more organized. + +To create these folders, we would click on the respective add folder (+) button on the side bar. Files and Folders can be clicked and dragged within the primary side bar to move things to new folder locations. + +![](images/6.png) + +
+ +--- + +## Creating Files + +In context of this course, we will primarily be working with two types of files when coding: + +- R Scripts: These files end in .R. These contain only code (with occasional \# comment line). These are often used for self-contained code that once we get them working we rarely need to modify. + +- Quarto Markdowns: These files end in .qmd. They contain a .yaml header, followed by a mix of regular written text (often explanations or other documentation), and sections (ie. chunks) that contain code. These are used when we are still getting the code to work, when we need to modify inputs frequently, or simply when we need to document what and why we are doing something to make life easier for our future-self two months from now. + +
+ +--- + +In this example, I will go ahead and select the new file icon + +![](images/7.png) + +
+ +--- + +Thenn I will name the file, and designate it as a Quarto Markdown file by adding the .qmd at the end of the name to denote the file type. + +![](images/8.png) + +
+ +--- + +## QMD Files + +Once this is done, we can now see we have a new .qmd file ("Example.qmd" in this case). + +### YAML + +As previously mentioned, the start of a [Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) file containg a [YAML](https://quarto.org/docs/authoring/front-matter.html) code chunk that is used to set formatting choices (we will explore this in-depth during the [next section](/course/00_Quarto/index.qmd)) + + +What designates the location of the YAML block are three hyphens at the start, and three hyphens at the end. For this example, we will also provide a "title:" and "format:" field for the time being (see additional options [here](https://quarto.org/docs/authoring/front-matter.html)). + +![](images/9.png) + +
+ +--- + +### Text + +With a basic YAML formatting block now in place, we can build out other elements of our Quarto Markdown document. Unless otherwise specified, everything else in the document is assumed to be text, so I will go ahead and provide an initial text description of what I am trying to do. + +![](images/10.png) + +
+ +--- + +### Code-Chunks + +Having provided some initial text for documentation, we can then add code-block chunks to start writing some code. + +The easiest way to do do this is to click the respective option on the upper-right of the Editor screen. Since Positron can handle multiple programming languages, so the chunk is inserted, we will need to select the language we use to be used within the code chunk (R in this case). + +![](images/11.png) + +
+ +--- + +You will notice, that the inserted code block starts off with three backticks (\`) and then "{r}". The end of the code block is denoted by an additional three backticks. + +We can also add new code blocks by simply typing these elements into the location we want to place a code chunk (as long as we are careful to add 3 backticks also at the end). + +![](images/12.png) + +
+ +--- + +![](images/13.png) + +
+ +--- + +### Running Code + +Now that we have two code-chunks written, we can write lines of code within them. For this example, I will use two beginner friendly functions, print("Hello"), which will print the contents contained between the " " to the console, and getwd() which will return the location of the folder you are working within (ie. the working directory). + +To run/execute these lines of code, we have a couple options. We can click on the Run Cell option that appears on the upper-left side of the code chunk. Additionally, it has a companion option that will run all code chunks above it. + +![](images/14.png) + +
+ +--- + +When a code block is successfully run, you will see within the console (lower bottom of the screen) the line of code be run, with any returned outputs appear directly after. + +![](images/15.png) + +
+ +--- + +An alternative to clicking the Run Cell button is to click on the line of code you are interested in running, then press (Ctrl + Enter)/(Command + Enter). This will execute the line of code that you have clicked on. This can be useful in scenarios where you want to run a specific line, and not the entire code-chunk. + +![](images/16.png) + +
+ +--- + +Using this approach, you can see the location (ie. file path) of the current working directory was returned to the Console. + +![](images/17.png) + +
+ +--- + +## Local Version Control + +Having introduced the main elements of a [Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) file, let's turn our attention to the tab within the editor showing our newly created .qmd file. + +We can see there is a solid circle next to the file name, and it is appearing as green. The circle denotes unsaved changes, which we can correct by clicking on the Save Button to save the changes to our file. + +![](images/18.png) + +
+ +--- + +### Untracked + +If we turn our attention to the left primary sidebar, we can see that within our GitPractie folder there are three files, our Example.qmd, and the default README.md and .gitignore files. These all show up in green text with U's to the right of the file names. + +This denotes that the version control tracking software Git is currently considering them as "Untracked" files. While saving the document via the Save button means we will still have our changes when we reopen Positron, we won't have any history of changes that we can use to revert back to the way all the files appeared at this exact point in time should something go wrong. + +We will next go the address bar on the very far left, and select the Git tab. + +![](images/19.png) + +
+ +--- + +On the Git tab, we can see that each of the three files are shown underneath a "Changes" drop-down. This contains the files that have undergone changes since the last commit. In our case, since we haven't updated the save-state yet, this last commit would be the initial creation of the project folder. + +![](images/20.png) + +
+ +--- + +To have version control track these individual files going forward, we can do so in two separate ways. We can add them individually by clicking the + symbol next to the individual names. + +![](images/21.png) + +
+ +--- + +### Staged + +This will result in the files being moved to the "Staged" dropdown. This denotes files being tracked with the intention of being recorded as the next save-state or waypoint (ie. a commit). + +![](images/22.png) + +
+ +--- + +### Commit + +To create a new commit (save-state or waypoint), once we have the files we want to track staged, we will write a commit message, and then press commit. + +A commit message is a brief description of the changes that have occurred to the files between this commit and the previous one. Make this short description informative enough that if you need to revert back in the future, you can quickly identify the commit you need to fall back to (more about this later). + +![](images/23.png) + +
+ +--- + +If this your first time using version control, you will likely encounter the following pop-up asking that you provide a user.name and user.email. This is used to designate the author of the changes.If you get this popup, go ahead and select "Open Git Log" + +![](images/24.png) + +
+ +--- + +### UserName and UserEmail + +The Output tab at the bottom of the screen will open, showing the messages that led to the popup. + +The important part to note is the commands that will be needed to provide your user name and email to the computer for authoring the commit. Typically, your email will be the same one you used for your GitHub account. + +![](images/25.png) + +
+ +--- + +From the displayed message, go ahead and copy + +"git config –global user.email "you\@example.com"" + +Then click on the adjacent terminal tab. You will paste the command in, but do not hit enter just yet. + +Windows users, please note, depending on your settings, if trying to paste from the keyboard into the terminal, you may need to press "Ctrl + Shift + V" instead of the usual "Ctrl + V". + +![](images/26.png) + +
+ +--- + +With the command now pasted (or typed), use your keyboard arrows to navigate to the email portion, and replace the generic email with your email address used for your GitHub account. + +Make sure that the quotation marks (") around the email address remain present, as they help the computer identify where your email address starts and ends. Once satisfied that your email address is correct, press enter. + +![](images/27.png) + +
+ +--- + +Next up, repeat the process, this time copying over the command needed to set your user name to the terminal. Repeat the editing process to provide your name between the "" marks. Then press enter. + +![](images/28.png) + +
+ +--- + +![](images/29.png) + +
+ +--- + +### First Commit + +Now that your user.name and email address have been provided, Git should be able to provide an author to the commit message. Reattempt to press commit button. + +If this is successful, you will see your initial commit appear on the bottom half of the left primary side bar, under the Graph dropdown. Congrats! Your files are now being tracked by version control. + +![](images/30.png) + +
+ +--- + +If you hover with your mouse arrow just over the commit, you can see the longer commit message and additional details appear. + +If you click on the commit tab, a new display will open in the editor, displaying the changes that occured in that commit compared to the previous one. In this case, since we added everything since the previous commit, nothing appears on the left side, while the entire documents contents appear highlighted in green on the right. + +Green highlighting is used to show additions, while red highlighting is used to show deletions. + +![](images/31.png) + +
+ +--- + +Having completed this initial commit, for this example, let's imitate a typical workflow and make some additional changes to the file before we make a second commit. Within text portions of the .qmd file, use of \# denotes a section header in markdown, so let's add a header for Introduction and click save. + +![](images/32.png) + +
+ +--- + +### Modified + +Within the left primary sidebar, we can see that the Git tracking has updated. Examples.qmd is visible once again. However, becuase it is now a tracked file, instead of showing up with the "U/Untracked" green highlight, it now appears as a brownish-red with a "M/Modified". + +Let's make an additional change to the .qmd file by adding another section (# Setup) and a code block with a commented out line (denoted by the \# at the line start), before pressing Save. + +![](images/33.png) + +
+ +--- + +If we were now to click on the Example.qmd file in the left primary sidebar, it will open the same kind of tracking display we saw previously. This time, we can see changes since our last commit. These appear as the green highlights along the scroll-bar, corresponding to the \# Introduction and \# Setup headers that we have added in since the last commit. + +![](images/34.png) + +
+ +--- + +For a larger document, we can scroll down to see the various highlighted regions. + +![](images/35.png) + +
+ +--- + +We could now repeat the steps showed above, staging the file, writing a commit message, and commiting again by clicking on the designated buttons. + +An important question is how often should we commit, vs. just hit save? Well... it depends :D +Let's think about this in context of a video game. If you made commits at regular intervals throughout the day (or more frequently when doing something particularly risky), you are more likely to be close enough to a particular commit (waypoint/save-state) that you can quickly revert back to without loosing any progress. Alternatively, if your last commit was last week, you will not have any intermediate versions to fall back to. + +### Commit via Terminal + +Having demonstrated how to commit changes to Git via the left primary side-bar, for this second commit, let's do it the alternate way via the terminal (tab on the panel at the bottom of your screen). + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + +
+ +--- + +After clicking on the terminal tab, click on blinking command line. + +The command to stage a file is "git add ", followed by the name of the file you want to stage. + +In this case, you would enter "git add Example.qmd" and press Enter. +![](images/36.png) + +
+ +--- + +You will see after pressing enter a new blank terminal line appear. If you glance at the left-sidebar, you can see that Example.qmd now appears under the Staged Changes dropdown. + +![](images/37.png) + +
+ +--- + +Next up, let's write the git commit via the terminal. In this case, the command would be "git commit -m " (-m denoting message). The commit text is then surrounded by "" marks. + +For example: "git commit -m "Added section headers to my QMD file"" + +Press enter to save the commit. + +![](images/38.png) + +
+ +--- + +And you should see your second commit now appear in the left primary sidebar underneath the graphs dropdown. + +![](images/39.png) + +
+ +--- + +## Remote Version Control + +### Copying Project Folder to GitHub + +While having local version control in place is helpful when you need to revert back after encountering issues, where Git shines is the ability to pass your changes to your online GitHub repository. + +Not only does this allow you to switch between computers, but should something disastrous happen to your main computer, you still have all your hard work backed up and readily assessible. + +For this subsection, first, double check that Positron is still connected to your GitHub account by checking the user tab on the bottom-left. If not, repeat the [connection setup](/course/00_WorkstationSetup/Windows.qmd#connecting-github-and-positron). + +![](images/40.png) + +
+ +--- + +Since our project was created using the "New Folder from Template" option, it currently only exist locally. What we want to do next is to copy it to our GitHub account, creating a new repository in the process. + +To do this, we will first need to install the `usethis` R package. Within your console, you would run the following line of code: + +```{r} +#| eval: false +install.packages("usethis") +``` + +Depending on what R packages you already have installed on your computer, you may get a prompt asking if you want to update/install additional dependencies. Go ahead and type the number corresponding to Update All, and press enter. + +The package and all it's dependencies should then install. If an error message appears, read through it, and follow provided instructions. Go to [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) +if need help. + +
+ +---- + +Once the `usethis` package is installed, we need to activate it within R by calling it with the library command. This makes all the tools (ie. functions) within an R package available for use within Positron. + +In your console, you would type: + +```{r} +#| eval: FALSE +library(usethis) +``` + +![](images/46.png) + +
+ +--- + + +With library called, you now have access to the functions (tools) within the `usethis` R package. One of these is the `use_github()` function. + +In Positron, if you hover over a function, it will pull up the associated help file which will provide you information about the arguments the function expects to receive, and what they do. + +For `use_github()`, the main thing to remember for now is since this is a personal project being used for testing, we don't necessarily want to share it with the entire world, so we should set the "private" argument equal to TRUE when creating a new repository. + +![](images/46.png) + +
+ +--- + +Taking this information that we have now gathered, we can now within our Quarto Markdown create a code chunk, write out the line of code calling the function, and providing the Private=TRUE argument within the (). + +Within a code chunk, adding a \# in front of a line of code, will comment it out, resulting in that line of code not being run. Since we have already installed the `usethis` package, and we don't want to reinstall it every single time, let's go ahead and comment out that line. Go ahead and press Enter. + +![](images/47.png) + +
+ +--- + +We will see a message pop-up in the console. In this case, we had not saved before pressing enter, so there are uncommitted changes within the folder. The pop-up is asking whether you want to save these as well before sending the Folder to GitHub. + +In this case I will chose to ignore the uncommitted changes by entering 3 (for Definitely) in the console and hitting enter on my keyboard. + +![](images/48.png) + +
+ +--- + +The `usethis` R package will then execute the series of git commands that are needed to set up a GitHub repository (ie. the messages being displayed in the console window), and when finished will open a pop-up asking whether you want to see your new repository in your default Web Browser. I will go ahead and select yes in this case. + +![](images/49.png) + +
+ +--- + +After the browser opens, you can see that the elements I had staged and committed within Positron are now present within the GitHub repository. +Since I had only staged Example.qmd, it is the only file that was backed up. We can also see the commit history online by clicking on the commit clock. + + +![](images/50.png) + +
+ +--- + +As we would expect, we only see our two commit messages. One important thing to note is the commit hash numbers, that denote a particular commit. If we decided to revert/fall back to a prior commit in the future, this would be the number we would need to provide to Git to return to that previous commit/save-state + +![](images/51.png) + +
+ +--- + +Similarly, on GitHub, we have an option to Browse a Repository at a particular point in time. This will be quite useful later in the future when troubleshooting what major changes occurred between versions of an R package. + +![](images/52.png) + +
+ +--- + +### Code Chunk Arguments + +Having successfully connected our local Project Folder to a remote GitHub repository, let's return to Positron. + +Before continuing, if we left the code chunk that created the GitHub repository as is, every time we ran all code chunks in the document, it would try to recreate the GitHub repository. We don't want this to happen, as the setup was a one-time operation. + +While we could add \# in front of every line of code (or delete the code chunk entirely) it is often useful to have these set-up code chunks around to remind us what arguments we need to provide next time we need to a similar setup and are mind blanking on what to do. + +Fortunately, Quarto allows us to set conditions on whether a chunk is run (ie. evaluated). We will discuss the conditiona arguments in more depth in the [next section](/course/00_Quarto/index.qmd), but for now, we can modify the code chunk as follows. + + +On the next line after the {r}, we will add a hashtag (\#), then a pipe (|), followed by a space. This is the setup for a code-chunk specific argument. We will then add "eval: FALSE", which signals that the particular code-chunk should not be evaluated (ie, should not be run). + +![](images/53.png) + +
+ +--- + +### README + +Now that we have connected our local Project Folder to GitHub, and have gotten a basic introduction to the "git add", "git commit" arguments, let's turn our focus to the other files currently listed as untracked by Git within our folder, the README.md and the .gitignore files. + +When setting up our [GitHub]() account, we encounted an example of a README.md file. This file often provides a brief description of the project, and an outline of what the other files in the folder are for. As you may have gathered, even software developers are forgetful/under-caffenaited, and having notes to catch back up to speed is important. + +![](images/54.png) + +
+ +--- + + +### .gitignore +We additionally have a .gitignore file. Within a project, there are often some files that we will never want version control to track. These could be files that are too large for GitHub (ex. really large .fcs files), or files containing sensitive information (passwords, history, credentials, etc.). + +When the names of these file (or the file type shothand) are added to the .gitignore file, they are ignored by version control, and no longer appear on the primary left side bar. + +![](images/54.png) + +
+ +--- + +Let's proceed and stage both the README.md and .gitignore file, so that changes to these files will be tracked. We can of course select both from the primary left side bar and write a short commit message. + +![](images/55.png) + +
+ +--- + +![](images/56.png) + +
+ +--- + +Or alternatively, if we want to stage all uncommitted files present in a single step, we could in the terminal use the "git add ." + +We can then write our git commit using "git commit -m". + +Both approaches work, and you may switch between them based on preferrence. + +![](images/57.png) + +
+ +--- + +You will notice after having committed, that if you look at the Graph dropdown on the bottom half of the primary left side-bar that something has changed. + +There are now separate icons denoted as main and origin/main. These correspond to the last commit present locally (main), and the last commit on remote (ie. GitHub, origin/main). + +Local is ahead since you just made the commit with the changes inactivating the code-chunk, and you have not passed these changes up to GitHub yet. + +![](images/58.png) + +
+ +--- + + +### Pull + +Before sending (ie. pushing up) our updated commit to GitHub, especially if you are working on a project from multiple computers (or as part of a team) to bring in (ie. pull down) any changes that might be on GitHub that are not present locally. + +This ensures that everything is up to date, and you don't end up with mismatched commits that are incompatible with each other and trigger an error message. + +To pull in changes from GitHub, at the top of the primary left side-bar, you can select the ... button to open a drop-down menu of Git options. You would then select "Pull". + +Alternatively, you could do the same thing via the terminal by running the "git pull" command. + +![](images/59.png) + +
+ +--- + +### Push + +In our case, there was no new material present on our GitHub repository that were not already present locally, so all that is returned is the "Already up to date" message. + +We are now good to proceed to push (ie. send) the updated commit up to our GitHub repository. + +We can do this by either pressing the Sync changes button, or via the terminal entering the "git push" command. + +![](images/60.png) + +
+ +--- + +And now, if you glance down at left side-bar's graph section, you will see that both the main and origin/main icons are now present for the most recent commit. + +![](images/61.png) + +
+ +--- + +If we switch to our Web browser, we can see that this is also now the case for our GitHub repository that now also has the most recent changes. + +![](images/62.png) + +
+ +--- + +### Reverting to Prior Commit + +For most daily-workflows, you will only need the git commands that we have introduced above (git add, commit, pull, push). The next two areas (reverting to a prior commit, and branches) are more specialized, and will be covered in greater depth later in the course. We are briefly covering them here. If you are at the point where your last remaining neuron has disconnected, and you feel you need to take a break from version control, feel free to skip to the [next section](/course/00_Quarto/index.qmd) and we will revisit these topics later in the course. + +
+ +-- + +In most cases, if your code stops working, you can identify the issue and fix it in the existing version, never needing to resort to reverting to a previous commit (save-state). The times you would need to revert would be if you deleted important files, or the new files are hopeless mess that is not worth trying to sort through. In those cases, reverting back might be better approach. + +To imitate a falling back scenario, lets create and additional file, stage and commit it to end up a commit ahead of where we are currently at within the Project Folder. + +![](images/00_RevertTest.png) + + +
+ +--- + +Now being one (or several) commits ahead, if we wanted to revert back, we would first need to identify the commit we want to revert back to and copy the commit hash number. + +![](images/00_CommitHash.png) + + +
+ +--- + +Then, opening the terminal, we can enter "git reset " and paste the hash afterwards. We can then press enter. + + +![](images/00_GitReset.png) + + +
+ +--- + +You will notice our additional commit has been removed, although the newer files we were working on subsequent last commit are still present. + + +![](images/00_GitResetExecuted.png) + + +
+ +--- + +If however, we had wanted to return to the exact same state as the previous commit (removing all subsequent created files), we could do so by adding in the --hard argument. Before starting, save any newer files you want to keep in a completely different folder, because they will be permanently removed. + +Then, enter "git reset --hard thecommithashnumber" into the terminal, which would result in a "hard" return to the previous commits save-state. You may need to close and reopen Positron to see the changes reflected. + + +### Branches + +Branches are an useful Git feature that we will start using extensively later in the course. Branching allows you to create a parallel/carbon-copy of your existing repository, which you can then edit without affecting the main branch. This is particularly useful for projects that may get messy or drawn out. By isolating these edits to a parallel branch, if they don't work, your main branch remains safe. Alternatively, if you like the changes that occurred in the branch, you can pull these changes from the branch back to main, bringing the timelines back together. + +![](https://book.the-turing-way.org/build/sub-branch-491000deab04cb25ea703c007e2ebdd2.png) + +--- + +Within the terminal, entering "git branch" will show the existing branches. In this case, only main is present since we haven't yet created a new branch. + + +![](images/00_Branch.png) + +
+ +--- + +We can create a new branch in the terminal by entering "git branch " followed by the name of our desired branch. In this case, we are creating a branch called Week1 + +![](images/00_Week1.png) + +
+ +--- + +Now, when we check "git branch" again in the terminal, which returns the two branches, Week1 and main. The \* is located next to main, indicating that we are currently within the main branch. + +![](images/00_Branches.png) + +
+ +--- + +Besides the terminal, we can also create a new branch via Positron. To do so, we first click on the Git tab in the Actions Bar. + +Once the left-side bar displays the version control display, we can click on the ... button (to the right of changes)to gain access to the Git options drop-down. + +From here, we click on Branch, and then select Create Branch. + +![](images/00_BranchesGUI.png) + +
+ +--- + +Using Git branch, we saw that we were still within the main branch. In the terminal, we can switch over to the Week1 branch by using the "git checkout " command, followed by the branch we wish to switch to. + +![](images/00_Checkout.png) + +
+ +--- + +This results in us switching over to the Week1 branch. + +![](images/00_CheckoutOutput.png) + +
+ +--- + +Having switched (ie. checkout) to the Week 1 branch, let's create the file BranchTest.qmd, which will exist within this branch, but not yet in the main branch. + +![](images/00_BranchTest.png) + +
+ +--- + +Having created the file, let's stage and then commit it. This will put the Week1 branch ahead of the main branch by a single commit. + +![](images/BranchCommit.png) + +
+ +--- + +With our changes staged and committed, if we look at the left side-bar's graph section, our Week1 branch is now ahead of the origin/main branch by one commit. + +![](images/00_BranchToOrigin.png) + +
+ +--- + +If we were to check on GitHub, we can see that no new files are present on the main branch, but can see the notification listing recent changes to Week1 branch. + +![](images/00_GitHub.png) + +
+ +--- + +Using the drop-down, we can switch from displaying the main branch to the Week1 branch, where we can see the new file. + +![](images/00_GitHubWeek1.png) + +
+ +--- + +If we click the green compare and pull request button, we end up on this screen. This compares how the two branches are different from each other. + +![](images/00_GithubWeek1Merge.png) + +
+ +--- + +We will delve into branches again at a later point. For now, remember that by creating and prunning parallel branches, you can develop knowing that even if something goes wrong, your main branch remains safe. + + +# Wrap-Up + +In this section, we saw how to create a New Project Folder, create files and back up the project folder to GitHub. We also started learning about git, covering the basic commands (git add, commit, pull, push). If you feel a bit overwhelmed, please know, that is normal. Understanding how to leverage git takes time and practice, but is an incredibly valuable skillset to have in the long run. + +In the [next section](/course/00_Quarto/index.qmd), we will look at how by changing various elements within our .qmd file produce a variety of files, and how to leverage code-chunk arguments to fine-tune whether a code-chunk is utilized. + + +# Additional Resources + +[Git & GitHub Tutorial for Scientist: It's Not Only for Programmers](https://gitbookdown.dallasdatascience.com/) + +[Ten Simple Rules for Taking Advantage of Git and GitHub](https://pmc.ncbi.nlm.nih.gov/articles/PMC4945047/) + +[A brief introduction to Git for beginers](https://youtu.be/r8jQ9hVA2qs?si=IYe7JghJpVTz9Ht4) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_Git/slides.qmd b/course/00_Git/slides.qmd index 247a262..6ddd2a5 100644 --- a/course/00_Git/slides.qmd +++ b/course/00_Git/slides.qmd @@ -1,1337 +1,1337 @@ ---- -title: "Version Control with Git" -author: "David Rach" -date: 02-01-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -# Background - -::: {.fragment} -::: {.callout-tip title="."} -Now that we have created a [GitHub account](/course/00_GitHub/index.qmd), installed the required [software](/course/00_WorkstationSetup/index.qmd) and investigated [Positron's](/course/00_Positron/index.qmd) layout, we will start learning about version control software. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When working with code, it is important to stay organized. Ideally, everything needed for your code to successfully run should be present and accounted for within the local environment. Likewise, if you make changes, and your code stops working (no longer returning the expected output, ie. breaks), it would be most useful to have a track record of what has changed since your last working version in order to fix the issue. For beginners, this is often a typo in a function name or a misplaced comma somewhere within your document. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For this course, we will be using the version control software [Git](https://git-scm.com/). It is widely used by software developers and bioinformaticians worldwide, and is a very useful tool to have in your coding toolbox. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Git works locally within your individual project folders to track changes to the documents within, allowing to save the current state of the folder along the way (ie. a commit). This allows you to compare to previous versions (other commits) and return the changes that have occured to the tracked files. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -As we saw during the [workstation setup](/course/00_WorkstationSetup/index.qmd) section, when you have a linked GitHub account, you can backup folders as repositories online. By leveraging the ability to send and receive changes, this allows you to modify a file on one computer, -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Individual repositories can be linked to a GitHub account, which permits them to be backed up online. Within our workflow, this allows to modify on one computer, back up (ie. push) the changes to GitHub, and then later on a different workstation, retrieve (ie. pull) these new changes and continue working. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In this walk-through, we will set up a New Project Folder from a template, create a few folders and files, and work through how to use the main set of Git commands needed for this course. -::: -::: - ---- - -# Getting Started - -::: {.fragment} -::: {.callout-tip title="."} -For this walkthrough, we are going to create a brand new project folder. To do this, we can open the folder tab on the upper right. - -From here we can see we have two options, create a "New Folder from a Template", and create a "New Folder from Git" (which was the option we used during [workstation setup](/course/00_WorkstationSetup/index.qmd) to bring in the forked CytometryInR and README repository folders locally). - -We will go ahead and select "New Folder from a Template" for this example. -::: -::: - ---- - -![](images/1.png) - - ---- - -## New Folder from Template - -::: {.fragment} -::: {.callout-tip title="."} -Since Positron can use multiple programming languages, when we select "New Folder from Template" we will be asked what kind of folder template we want to use. Since we are working in R, we will select the "R Project" option. -::: -::: - ---- - -![](images/2.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will next be asked to name the new project folder and a storage location. - -One thing I would like to remind everyone who is just starting to code is that it is best to avoid using [special characters](https://en.wikipedia.org/wiki/Regular_expression) (ex. @ $ # ^ ! ; : ,) in any folder or file name. This is because when coding, these can be misinterpreted as commands. - -While spaces are generally okay, it is often to best stick to to stick to hyphens (-), underscores (_). We will explore naming conventions in more depth at a later time. -::: -::: - -![](https://pbs.twimg.com/media/FxVpCpqaIAE_iqU?format=jpg&name=small) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Another useful thing to know when getting started with version control, it is best to save your files within your local computer, avoid using OneDrive or other cloud storage options for the time reason. The reason behind is that permissions to write/save to the cloud locations can sometimes be quite finicky, and some autosave/indexing behaviors can cause issues. akes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. - -Having named our new Project Folder, and designated a storage location, go ahead and check the Initialize Git Repository option. This will indicate to version control to monitor content and changes to files within this folder. -::: -::: ---- - -![](images/3.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The next setup screen will verify which version of R you wish to use. Since we are just getting started, your most recent version of R (usually system) should work. We will also leave the "renv" (reproducible environment setup) option unchecked for the time being (we will revisit the concept later in the course). -::: -::: - ---- - -![](images/4.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And if all goes well, we should see the "New Folder Created" popup. -::: -::: - ---- - -![](images/5.png) - - ---- - -## Creating SubFolders - -::: {.fragment} -::: {.callout-tip title="."} -Once your new project folder has opened, you should be seeing the main layout elements that we briefly covered in the [Positron](/course/00_Positron/index.qmd) walk-through. - -For this section, we will primarily be focused on what is happening within the primary side bar on the left, where changes to the individual files within the folder since the last save/commit will be reflected by colored text. - -For my own projects, there are some elements of organization that I go ahead and add for each new folder. These include both a data and an images subfolders to help keep things a little more organized. - -To create these folders, we would click on the respective add folder (+) button on the side bar. Files and Folders can be clicked and dragged within the primary side bar to move things to new folder locations. -::: -::: - ---- - -![](images/6.png) - - ---- - -## Creating Files - -::: {.fragment} -::: {.callout-tip title="."} -In context of this course, we will primarily be working with two types of files when coding: - -- R Scripts: These files end in .R. These contain only code (with occasional \# comment line). These are often used for self-contained code that once we get them working we rarely need to modify. - -- Quarto Markdowns: These files end in .qmd. They contain a .yaml header, followed by a mix of regular written text (often explanations or other documentation), and sections (ie. chunks) that contain code. These are used when we are still getting the code to work, when we need to modify inputs frequently, or simply when we need to document what and why we are doing something to make life easier for our future-self two months from now. -::: -::: - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In this example, I will go ahead and select the new file icon -::: -::: - ---- - -![](images/7.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Thenn I will name the file, and designate it as a Quarto Markdown file by adding the .qmd at the end of the name to denote the file type. -::: -::: - ---- - -![](images/8.png) - - ---- - -## QMD Files - -::: {.fragment} -::: {.callout-tip title="."} -Once this is done, we can now see we have a new .qmd file ("Example.qmd" in this case). -::: -::: - -### YAML - -::: {.fragment} -::: {.callout-tip title="."} -As previously mentioned, the start of a [Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) file containg a [YAML](https://quarto.org/docs/authoring/front-matter.html) code chunk that is used to set formatting choices (we will explore this in-depth during the [next section](/course/00_Quarto/index.qmd)) - - -What designates the location of the YAML block are three hyphens at the start, and three hyphens at the end. For this example, we will also provide a "title:" and "format:" field for the time being (see additional options [here](https://quarto.org/docs/authoring/front-matter.html)). -::: -::: - ---- - -![](images/9.png) - - ---- - -### Text - -::: {.fragment} -::: {.callout-tip title="."} -With a basic YAML formatting block now in place, we can build out other elements of our Quarto Markdown document. Unless otherwise specified, everything else in the document is assumed to be text, so I will go ahead and provide an initial text description of what I am trying to do. -::: -::: - ---- - -![](images/10.png) - - ---- - -### Code-Chunks - -::: {.fragment} -::: {.callout-tip title="."} -Having provided some initial text for documentation, we can then add code-block chunks to start writing some code. - -The easiest way to do do this is to click the respective option on the upper-right of the Editor screen. Since Positron can handle multiple programming languages, so the chunk is inserted, we will need to select the language we use to be used within the code chunk (R in this case). -::: -::: - ---- - -![](images/11.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will notice, that the inserted code block starts off with three backticks (\`) and then "{r}". The end of the code block is denoted by an additional three backticks. - -We can also add new code blocks by simply typing these elements into the location we want to place a code chunk (as long as we are careful to add 3 backticks also at the end). -::: -::: - ---- - -![](images/12.png) - ---- - -![](images/13.png) - - ---- - -### Running Code - -::: {.fragment} -::: {.callout-tip title="."} -Now that we have two code-chunks written, we can write lines of code within them. For this example, I will use two beginner friendly functions, print("Hello"), which will print the contents contained between the " " to the console, and getwd() which will return the location of the folder you are working within (ie. the working directory). - -To run/execute these lines of code, we have a couple options. We can click on the Run Cell option that appears on the upper-left side of the code chunk. Additionally, it has a companion option that will run all code chunks above it. -::: -::: - ---- - -![](images/14.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When a code block is successfully run, you will see within the console (lower bottom of the screen) the line of code be run, with any returned outputs appear directly after. -::: -::: - ---- - -![](images/15.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -An alternative to clicking the Run Cell button is to click on the line of code you are interested in running, then press (Ctrl + Enter)/(Command + Enter). This will execute the line of code that you have clicked on. This can be useful in scenarios where you want to run a specific line, and not the entire code-chunk. -::: -::: - ---- - -![](images/16.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Using this approach, you can see the location (ie. file path) of the current working directory was returned to the Console. -::: -::: - ---- - -![](images/17.png) - - ---- - -## Local Version Control - -::: {.fragment} -::: {.callout-tip title="."} -Having introduced the main elements of a [Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) file, let's turn our attention to the tab within the editor showing our newly created .qmd file. - -We can see there is a solid circle next to the file name, and it is appearing as green. The circle denotes unsaved changes, which we can correct by clicking on the Save Button to save the changes to our file. -::: -::: - ---- - -![](images/18.png) - - ---- - -### Untracked - -::: {.fragment} -::: {.callout-tip title="."} -If we turn our attention to the left primary sidebar, we can see that within our GitPractie folder there are three files, our Example.qmd, and the default README.md and .gitignore files. These all show up in green text with U's to the right of the file names. - -This denotes that the version control tracking software Git is currently considering them as "Untracked" files. While saving the document via the Save button means we will still have our changes when we reopen Positron, we won't have any history of changes that we can use to revert back to the way all the files appeared at this exact point in time should something go wrong. - -We will next go the address bar on the very far left, and select the Git tab. -::: -::: - ---- - -![](images/19.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -On the Git tab, we can see that each of the three files are shown underneath a "Changes" drop-down. This contains the files that have undergone changes since the last commit. In our case, since we haven't updated the save-state yet, this last commit would be the initial creation of the project folder. -::: -::: - ---- - -![](images/20.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -To have version control track these individual files going forward, we can do so in two separate ways. We can add them individually by clicking the + symbol next to the individual names. -::: -::: - ---- - -![](images/21.png) - - ---- - -### Staged - -::: {.fragment} -::: {.callout-tip title="."} -This will result in the files being moved to the "Staged" dropdown. This denotes files being tracked with the intention of being recorded as the next save-state or waypoint (ie. a commit). -::: -::: - ---- - -![](images/22.png) - - ---- - -### Commit - -::: {.fragment} -::: {.callout-tip title="."} -To create a new commit (save-state or waypoint), once we have the files we want to track staged, we will write a commit message, and then press commit. - -A commit message is a brief description of the changes that have occurred to the files between this commit and the previous one. Make this short description informative enough that if you need to revert back in the future, you can quickly identify the commit you need to fall back to (more about this later). -::: -::: - ---- - -![](images/23.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If this your first time using version control, you will likely encounter the following pop-up asking that you provide a user.name and user.email. This is used to designate the author of the changes.If you get this popup, go ahead and select "Open Git Log" -::: -::: - ---- - -![](images/24.png) - - ---- - -### UserName and UserEmail - -::: {.fragment} -::: {.callout-tip title="."} -The Output tab at the bottom of the screen will open, showing the messages that led to the popup. - -The important part to note is the commands that will be needed to provide your user name and email to the computer for authoring the commit. Typically, your email will be the same one you used for your GitHub account. -::: -::: - ---- - -![](images/25.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -From the displayed message, go ahead and copy - -"git config –global user.email "you\@example.com"" - -Then click on the adjacent terminal tab. You will paste the command in, but do not hit enter just yet. - -Windows users, please note, depending on your settings, if trying to paste from the keyboard into the terminal, you may need to press "Ctrl + Shift + V" instead of the usual "Ctrl + V". -::: -::: - ---- - -![](images/26.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -With the command now pasted (or typed), use your keyboard arrows to navigate to the email portion, and replace the generic email with your email address used for your GitHub account. - -Make sure that the quotation marks (") around the email address remain present, as they help the computer identify where your email address starts and ends. Once satisfied that your email address is correct, press enter. -::: -::: - ---- - -![](images/27.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next up, repeat the process, this time copying over the command needed to set your user name to the terminal. Repeat the editing process to provide your name between the "" marks. Then press enter. -::: -::: - ---- - -![](images/28.png) - ---- - -![](images/29.png) - - ---- - -### First Commit - -::: {.fragment} -::: {.callout-tip title="."} -Now that your user.name and email address have been provided, Git should be able to provide an author to the commit message. Reattempt to press commit button. - -If this is successful, you will see your initial commit appear on the bottom half of the left primary side bar, under the Graph dropdown. Congrats! Your files are now being tracked by version control. -::: -::: - ---- - -![](images/30.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If you hover with your mouse arrow just over the commit, you can see the longer commit message and additional details appear. - -If you click on the commit tab, a new display will open in the editor, displaying the changes that occured in that commit compared to the previous one. In this case, since we added everything since the previous commit, nothing appears on the left side, while the entire documents contents appear highlighted in green on the right. - -Green highlighting is used to show additions, while red highlighting is used to show deletions. -::: -::: - ---- - -![](images/31.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Having completed this initial commit, for this example, let's imitate a typical workflow and make some additional changes to the file before we make a second commit. Within text portions of the .qmd file, use of \# denotes a section header in markdown, so let's add a header for Introduction and click save. -::: -::: - ---- - -![](images/32.png) - - ---- - -### Modified - -::: {.fragment} -::: {.callout-tip title="."} -Within the left primary sidebar, we can see that the Git tracking has updated. Examples.qmd is visible once again. However, becuase it is now a tracked file, instead of showing up with the "U/Untracked" green highlight, it now appears as a brownish-red with a "M/Modified". - -Let's make an additional change to the .qmd file by adding another section (# Setup) and a code block with a commented out line (denoted by the \# at the line start), before pressing Save. -::: -::: - ---- - -![](images/33.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If we were now to click on the Example.qmd file in the left primary sidebar, it will open the same kind of tracking display we saw previously. This time, we can see changes since our last commit. These appear as the green highlights along the scroll-bar, corresponding to the \# Introduction and \# Setup headers that we have added in since the last commit. -::: -::: - ---- - -![](images/34.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For a larger document, we can scroll down to see the various highlighted regions. -::: -::: - ---- - -![](images/35.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We could now repeat the steps showed above, staging the file, writing a commit message, and commiting again by clicking on the designated buttons. - -An important question is how often should we commit, vs. just hit save? Well... it depends :D -Let's think about this in context of a video game. If you made commits at regular intervals throughout the day (or more frequently when doing something particularly risky), you are more likely to be close enough to a particular commit (waypoint/save-state) that you can quickly revert back to without loosing any progress. Alternatively, if your last commit was last week, you will not have any intermediate versions to fall back to. -::: -::: - -### Commit via Terminal - -::: {.fragment} -::: {.callout-tip title="."} -Having demonstrated how to commit changes to Git via the left primary side-bar, for this second commit, let's do it the alternate way via the terminal (tab on the panel at the bottom of your screen). -::: -::: - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -After clicking on the terminal tab, click on blinking command line. - -The command to stage a file is "git add ", followed by the name of the file you want to stage. - -In this case, you would enter "git add Example.qmd" and press Enter. -::: -::: - ---- - -![](images/36.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will see after pressing enter a new blank terminal line appear. If you glance at the left-sidebar, you can see that Example.qmd now appears under the Staged Changes dropdown. -::: -::: - ---- - -![](images/37.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next up, let's write the git commit via the terminal. In this case, the command would be "git commit -m " (-m denoting message). The commit text is then surrounded by "" marks. - -For example: "git commit -m "Added section headers to my QMD file"" - -Press enter to save the commit. -::: -::: - ---- - -![](images/38.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And you should see your second commit now appear in the left primary sidebar underneath the graphs dropdown. -::: -::: - ---- - -![](images/39.png) - - ---- - -## Remote Version Control - -### Copying Project Folder to GitHub - -::: {.fragment} -::: {.callout-tip title="."} -While having local version control in place is helpful when you need to revert back after encountering issues, where Git shines is the ability to pass your changes to your online GitHub repository. - -Not only does this allow you to switch between computers, but should something disastrous happen to your main computer, you still have all your hard work backed up and readily assessible. - -For this subsection, first, double check that Positron is still connected to your GitHub account by checking the user tab on the bottom-left. If not, repeat the [connection setup](/course/00_WorkstationSetup/Windows.qmd#connecting-github-and-positron). -::: -::: - ---- - -![](images/40.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Since our project was created using the "New Folder from Template" option, it currently only exist locally. What we want to do next is to copy it to our GitHub account, creating a new repository in the process. - -To do this, we will first need to install the `usethis` R package. Within your console, you would run the following line of code: -::: -::: - -```{r} -#| eval: false -install.packages("usethis") -``` - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Depending on what R packages you already have installed on your computer, you may get a prompt asking if you want to update/install additional dependencies. Go ahead and type the number corresponding to Update All, and press enter. - -The package and all it's dependencies should then install. If an error message appears, read through it, and follow provided instructions. Go to [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) -if need help. -::: -::: - - ----- - -::: {.fragment} -::: {.callout-tip title="."} -Once the `usethis` package is installed, we need to activate it within R by calling it with the library command. This makes all the tools (ie. functions) within an R package available for use within Positron. - -In your console, you would type: -::: -::: - -```{r} -#| eval: FALSE -library(usethis) -``` - ---- - -![](images/46.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -With library called, you now have access to the functions (tools) within the `usethis` R package. One of these is the `use_github()` function. - -In Positron, if you hover over a function, it will pull up the associated help file which will provide you information about the arguments the function expects to receive, and what they do. - -For `use_github()`, the main thing to remember for now is since this is a personal project being used for testing, we don't necessarily want to share it with the entire world, so we should set the "private" argument equal to TRUE when creating a new repository. -::: -::: - ---- - -![](images/46.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Taking this information that we have now gathered, we can now within our Quarto Markdown create a code chunk, write out the line of code calling the function, and providing the Private=TRUE argument within the (). - -Within a code chunk, adding a \# in front of a line of code, will comment it out, resulting in that line of code not being run. Since we have already installed the `usethis` package, and we don't want to reinstall it every single time, let's go ahead and comment out that line. Go ahead and press Enter. -::: -::: - ---- - -![](images/47.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will see a message pop-up in the console. In this case, we had not saved before pressing enter, so there are uncommitted changes within the folder. The pop-up is asking whether you want to save these as well before sending the Folder to GitHub. - -In this case I will chose to ignore the uncommitted changes by entering 3 (for Definitely) in the console and hitting enter on my keyboard. -::: -::: - ---- - -![](images/48.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The `usethis` R package will then execute the series of git commands that are needed to set up a GitHub repository (ie. the messages being displayed in the console window), and when finished will open a pop-up asking whether you want to see your new repository in your default Web Browser. I will go ahead and select yes in this case. -::: -::: - ---- - -![](images/49.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -After the browser opens, you can see that the elements I had staged and committed within Positron are now present within the GitHub repository. -Since I had only staged Example.qmd, it is the only file that was backed up. We can also see the commit history online by clicking on the commit clock. -::: -::: - ---- - -![](images/50.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -As we would expect, we only see our two commit messages. One important thing to note is the commit hash numbers, that denote a particular commit. If we decided to revert/fall back to a prior commit in the future, this would be the number we would need to provide to Git to return to that previous commit/save-state -::: -::: - ---- - -![](images/51.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Similarly, on GitHub, we have an option to Browse a Repository at a particular point in time. This will be quite useful later in the future when troubleshooting what major changes occurred between versions of an R package. -::: -::: - ---- - -![](images/52.png) - - ---- - -### Code Chunk Arguments - -::: {.fragment} -::: {.callout-tip title="."} -Having successfully connected our local Project Folder to a remote GitHub repository, let's return to Positron. - -Before continuing, if we left the code chunk that created the GitHub repository as is, every time we ran all code chunks in the document, it would try to recreate the GitHub repository. We don't want this to happen, as the setup was a one-time operation. - -While we could add \# in front of every line of code (or delete the code chunk entirely) it is often useful to have these set-up code chunks around to remind us what arguments we need to provide next time we need to a similar setup and are mind blanking on what to do. - -Fortunately, Quarto allows us to set conditions on whether a chunk is run (ie. evaluated). We will discuss the conditiona arguments in more depth in the [next section](/course/00_Quarto/index.qmd), but for now, we can modify the code chunk as follows. - - -On the next line after the {r}, we will add a hashtag (\#), then a pipe (|), followed by a space. This is the setup for a code-chunk specific argument. We will then add "eval: FALSE", which signals that the particular code-chunk should not be evaluated (ie, should not be run). -::: -::: - ---- - -![](images/53.png) - - ---- - -### README - -::: {.fragment} -::: {.callout-tip title="."} -Now that we have connected our local Project Folder to GitHub, and have gotten a basic introduction to the "git add", "git commit" arguments, let's turn our focus to the other files currently listed as untracked by Git within our folder, the README.md and the .gitignore files. - -When setting up our [GitHub]() account, we encounted an example of a README.md file. This file often provides a brief description of the project, and an outline of what the other files in the folder are for. As you may have gathered, even software developers are forgetful/under-caffenaited, and having notes to catch back up to speed is important. -::: -::: - ---- - -![](images/54.png) - - ---- - - -### .gitignore - -::: {.fragment} -::: {.callout-tip title="."} -We additionally have a .gitignore file. Within a project, there are often some files that we will never want version control to track. These could be files that are too large for GitHub (ex. really large .fcs files), or files containing sensitive information (passwords, history, credentials, etc.). - -When the names of these file (or the file type shothand) are added to the .gitignore file, they are ignored by version control, and no longer appear on the primary left side bar. -::: -::: - ---- - -![](images/54.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Let's proceed and stage both the README.md and .gitignore file, so that changes to these files will be tracked. We can of course select both from the primary left side bar and write a short commit message. -::: -::: - ---- - -![](images/55.png) - ---- - -![](images/56.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Or alternatively, if we want to stage all uncommitted files present in a single step, we could in the terminal use the "git add ." - -We can then write our git commit using "git commit -m". - -Both approaches work, and you may switch between them based on preferrence. -::: -::: - ---- - -![](images/57.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will notice after having committed, that if you look at the Graph dropdown on the bottom half of the primary left side-bar that something has changed. - -There are now separate icons denoted as main and origin/main. These correspond to the last commit present locally (main), and the last commit on remote (ie. GitHub, origin/main). - -Local is ahead since you just made the commit with the changes inactivating the code-chunk, and you have not passed these changes up to GitHub yet. -::: -::: - ---- - -![](images/58.png) - - ---- - - -### Pull - -::: {.fragment} -::: {.callout-tip title="."} -Before sending (ie. pushing up) our updated commit to GitHub, especially if you are working on a project from multiple computers (or as part of a team) to bring in (ie. pull down) any changes that might be on GitHub that are not present locally. - -This ensures that everything is up to date, and you don't end up with mismatched commits that are incompatible with each other and trigger an error message. - -To pull in changes from GitHub, at the top of the primary left side-bar, you can select the ... button to open a drop-down menu of Git options. You would then select "Pull". - -Alternatively, you could do the same thing via the terminal by running the "git pull" command. -::: -::: - ---- - -![](images/59.png) - - ---- - -### Push - -::: {.fragment} -::: {.callout-tip title="."} -In our case, there was no new material present on our GitHub repository that were not already present locally, so all that is returned is the "Already up to date" message. - -We are now good to proceed to push (ie. send) the updated commit up to our GitHub repository. - -We can do this by either pressing the Sync changes button, or via the terminal entering the "git push" command. -::: -::: - ---- - -![](images/60.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And now, if you glance down at left side-bar's graph section, you will see that both the main and origin/main icons are now present for the most recent commit. -::: -::: - ---- - -![](images/61.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If we switch to our Web browser, we can see that this is also now the case for our GitHub repository that now also has the most recent changes. -::: -::: - ---- - -![](images/62.png) - - ---- - -### Reverting to Prior Commit - -::: {.fragment} -::: {.callout-tip title="."} -For most daily-workflows, you will only need the git commands that we have introduced above (git add, commit, pull, push). The next two areas (reverting to a prior commit, and branches) are more specialized, and will be covered in greater depth later in the course. We are briefly covering them here. If you are at the point where your last remaining neuron has disconnected, and you feel you need to take a break from version control, feel free to skip to the [next section](/course/00_Quarto/index.qmd) and we will revisit these topics later in the course. -::: -::: - - --- - -::: {.fragment} -::: {.callout-tip title="."} -In most cases, if your code stops working, you can identify the issue and fix it in the existing version, never needing to resort to reverting to a previous commit (save-state). The times you would need to revert would be if you deleted important files, or the new files are hopeless mess that is not worth trying to sort through. In those cases, reverting back might be better approach. - -To imitate a falling back scenario, lets create and additional file, stage and commit it to end up a commit ahead of where we are currently at within the Project Folder. -::: -::: - ---- - -![](images/00_RevertTest.png) - - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Now being one (or several) commits ahead, if we wanted to revert back, we would first need to identify the commit we want to revert back to and copy the commit hash number. -::: -::: - ---- - -![](images/00_CommitHash.png) - - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Then, opening the terminal, we can enter "git reset " and paste the hash afterwards. We can then press enter. -::: -::: - ---- - -![](images/00_GitReset.png) - - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will notice our additional commit has been removed, although the newer files we were working on subsequent last commit are still present. -::: -::: - ---- - -![](images/00_GitResetExecuted.png) - - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If however, we had wanted to return to the exact same state as the previous commit (removing all subsequent created files), we could do so by adding in the --hard argument. Before starting, save any newer files you want to keep in a completely different folder, because they will be permanently removed. - -Then, enter "git reset --hard thecommithashnumber" into the terminal, which would result in a "hard" return to the previous commits save-state. You may need to close and reopen Positron to see the changes reflected. -::: -::: - ---- - -### Branches - -::: {.fragment} -::: {.callout-tip title="."} -Branches are an useful Git feature that we will start using extensively later in the course. Branching allows you to create a parallel/carbon-copy of your existing repository, which you can then edit without affecting the main branch. This is particularly useful for projects that may get messy or drawn out. By isolating these edits to a parallel branch, if they don't work, your main branch remains safe. Alternatively, if you like the changes that occurred in the branch, you can pull these changes from the branch back to main, bringing the timelines back together. -::: -::: - -![](https://book.the-turing-way.org/build/sub-branch-491000deab04cb25ea703c007e2ebdd2.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Within the terminal, entering "git branch" will show the existing branches. In this case, only main is present since we haven't yet created a new branch. -::: -::: - ---- - -![](images/00_Branch.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can create a new branch in the terminal by entering "git branch " followed by the name of our desired branch. In this case, we are creating a branch called Week1 -::: -::: - ---- - -![](images/00_Week1.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Now, when we check "git branch" again in the terminal, which returns the two branches, Week1 and main. The \* is located next to main, indicating that we are currently within the main branch. -::: -::: - ---- - -![](images/00_Branches.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Besides the terminal, we can also create a new branch via Positron. To do so, we first click on the Git tab in the Actions Bar. - -Once the left-side bar displays the version control display, we can click on the ... button (to the right of changes)to gain access to the Git options drop-down. - -From here, we click on Branch, and then select Create Branch. -::: -::: - ---- - -![](images/00_BranchesGUI.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Using Git branch, we saw that we were still within the main branch. In the terminal, we can switch over to the Week1 branch by using the "git checkout " command, followed by the branch we wish to switch to. -::: -::: - ---- - -![](images/00_Checkout.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -This results in us switching over to the Week1 branch. -::: -::: - ---- - -![](images/00_CheckoutOutput.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Having switched (ie. checkout) to the Week 1 branch, let's create the file BranchTest.qmd, which will exist within this branch, but not yet in the main branch. -::: -::: - ---- - -![](images/00_BranchTest.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Having created the file, let's stage and then commit it. This will put the Week1 branch ahead of the main branch by a single commit. -::: -::: - ---- - -![](images/BranchCommit.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -With our changes staged and committed, if we look at the left side-bar's graph section, our Week1 branch is now ahead of the origin/main branch by one commit. -::: -::: - ---- - -![](images/00_BranchToOrigin.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If we were to check on GitHub, we can see that no new files are present on the main branch, but can see the notification listing recent changes to Week1 branch. -::: -::: - ---- - -![](images/00_GitHub.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Using the drop-down, we can switch from displaying the main branch to the Week1 branch, where we can see the new file. -::: -::: - ---- - -![](images/00_GitHubWeek1.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If we click the green compare and pull request button, we end up on this screen. This compares how the two branches are different from each other. -::: -::: - ---- - -![](images/00_GithubWeek1Merge.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will delve into branches again at a later point. For now, remember that by creating and prunning parallel branches, you can develop knowing that even if something goes wrong, your main branch remains safe. -::: -::: - ---- - -# Wrap-Up - -::: {.fragment} -::: {.callout-tip title="."} -In this section, we saw how to create a New Project Folder, create files and back up the project folder to GitHub. We also started learning about git, covering the basic commands (git add, commit, pull, push). If you feel a bit overwhelmed, please know, that is normal. Understanding how to leverage git takes time and practice, but is an incredibly valuable skillset to have in the long run. - -In the [next section](/course/00_Quarto/index.qmd), we will look at how by changing various elements within our .qmd file produce a variety of files, and how to leverage code-chunk arguments to fine-tune whether a code-chunk is utilized. -::: -::: - -# Additional Resources - -[Git & GitHub Tutorial for Scientist: It's Not Only for Programmers](https://gitbookdown.dallasdatascience.com/) - -[Ten Simple Rules for Taking Advantage of Git and GitHub](https://pmc.ncbi.nlm.nih.gov/articles/PMC4945047/) - -[A brief introduction to Git for beginers](https://youtu.be/r8jQ9hVA2qs?si=IYe7JghJpVTz9Ht4) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Version Control with Git" +author: "David Rach" +date: 02-01-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +# Background + +::: {.fragment} +::: {.callout-tip title="."} +Now that we have created a [GitHub account](/course/00_GitHub/index.qmd), installed the required [software](/course/00_WorkstationSetup/index.qmd) and investigated [Positron's](/course/00_Positron/index.qmd) layout, we will start learning about version control software. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When working with code, it is important to stay organized. Ideally, everything needed for your code to successfully run should be present and accounted for within the local environment. Likewise, if you make changes, and your code stops working (no longer returning the expected output, ie. breaks), it would be most useful to have a track record of what has changed since your last working version in order to fix the issue. For beginners, this is often a typo in a function name or a misplaced comma somewhere within your document. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For this course, we will be using the version control software [Git](https://git-scm.com/). It is widely used by software developers and bioinformaticians worldwide, and is a very useful tool to have in your coding toolbox. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Git works locally within your individual project folders to track changes to the documents within, allowing to save the current state of the folder along the way (ie. a commit). This allows you to compare to previous versions (other commits) and return the changes that have occured to the tracked files. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As we saw during the [workstation setup](/course/00_WorkstationSetup/index.qmd) section, when you have a linked GitHub account, you can backup folders as repositories online. By leveraging the ability to send and receive changes, this allows you to modify a file on one computer, +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Individual repositories can be linked to a GitHub account, which permits them to be backed up online. Within our workflow, this allows to modify on one computer, back up (ie. push) the changes to GitHub, and then later on a different workstation, retrieve (ie. pull) these new changes and continue working. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this walk-through, we will set up a New Project Folder from a template, create a few folders and files, and work through how to use the main set of Git commands needed for this course. +::: +::: + +--- + +# Getting Started + +::: {.fragment} +::: {.callout-tip title="."} +For this walkthrough, we are going to create a brand new project folder. To do this, we can open the folder tab on the upper right. + +From here we can see we have two options, create a "New Folder from a Template", and create a "New Folder from Git" (which was the option we used during [workstation setup](/course/00_WorkstationSetup/index.qmd) to bring in the forked CytometryInR and README repository folders locally). + +We will go ahead and select "New Folder from a Template" for this example. +::: +::: + +--- + +![](images/1.png) + + +--- + +## New Folder from Template + +::: {.fragment} +::: {.callout-tip title="."} +Since Positron can use multiple programming languages, when we select "New Folder from Template" we will be asked what kind of folder template we want to use. Since we are working in R, we will select the "R Project" option. +::: +::: + +--- + +![](images/2.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will next be asked to name the new project folder and a storage location. + +One thing I would like to remind everyone who is just starting to code is that it is best to avoid using [special characters](https://en.wikipedia.org/wiki/Regular_expression) (ex. @ $ # ^ ! ; : ,) in any folder or file name. This is because when coding, these can be misinterpreted as commands. + +While spaces are generally okay, it is often to best stick to to stick to hyphens (-), underscores (_). We will explore naming conventions in more depth at a later time. +::: +::: + +![](https://pbs.twimg.com/media/FxVpCpqaIAE_iqU?format=jpg&name=small) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Another useful thing to know when getting started with version control, it is best to save your files within your local computer, avoid using OneDrive or other cloud storage options for the time reason. The reason behind is that permissions to write/save to the cloud locations can sometimes be quite finicky, and some autosave/indexing behaviors can cause issues. akes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. + +Having named our new Project Folder, and designated a storage location, go ahead and check the Initialize Git Repository option. This will indicate to version control to monitor content and changes to files within this folder. +::: +::: +--- + +![](images/3.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The next setup screen will verify which version of R you wish to use. Since we are just getting started, your most recent version of R (usually system) should work. We will also leave the "renv" (reproducible environment setup) option unchecked for the time being (we will revisit the concept later in the course). +::: +::: + +--- + +![](images/4.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And if all goes well, we should see the "New Folder Created" popup. +::: +::: + +--- + +![](images/5.png) + + +--- + +## Creating SubFolders + +::: {.fragment} +::: {.callout-tip title="."} +Once your new project folder has opened, you should be seeing the main layout elements that we briefly covered in the [Positron](/course/00_Positron/index.qmd) walk-through. + +For this section, we will primarily be focused on what is happening within the primary side bar on the left, where changes to the individual files within the folder since the last save/commit will be reflected by colored text. + +For my own projects, there are some elements of organization that I go ahead and add for each new folder. These include both a data and an images subfolders to help keep things a little more organized. + +To create these folders, we would click on the respective add folder (+) button on the side bar. Files and Folders can be clicked and dragged within the primary side bar to move things to new folder locations. +::: +::: + +--- + +![](images/6.png) + + +--- + +## Creating Files + +::: {.fragment} +::: {.callout-tip title="."} +In context of this course, we will primarily be working with two types of files when coding: + +- R Scripts: These files end in .R. These contain only code (with occasional \# comment line). These are often used for self-contained code that once we get them working we rarely need to modify. + +- Quarto Markdowns: These files end in .qmd. They contain a .yaml header, followed by a mix of regular written text (often explanations or other documentation), and sections (ie. chunks) that contain code. These are used when we are still getting the code to work, when we need to modify inputs frequently, or simply when we need to document what and why we are doing something to make life easier for our future-self two months from now. +::: +::: + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this example, I will go ahead and select the new file icon +::: +::: + +--- + +![](images/7.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Thenn I will name the file, and designate it as a Quarto Markdown file by adding the .qmd at the end of the name to denote the file type. +::: +::: + +--- + +![](images/8.png) + + +--- + +## QMD Files + +::: {.fragment} +::: {.callout-tip title="."} +Once this is done, we can now see we have a new .qmd file ("Example.qmd" in this case). +::: +::: + +### YAML + +::: {.fragment} +::: {.callout-tip title="."} +As previously mentioned, the start of a [Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) file containg a [YAML](https://quarto.org/docs/authoring/front-matter.html) code chunk that is used to set formatting choices (we will explore this in-depth during the [next section](/course/00_Quarto/index.qmd)) + + +What designates the location of the YAML block are three hyphens at the start, and three hyphens at the end. For this example, we will also provide a "title:" and "format:" field for the time being (see additional options [here](https://quarto.org/docs/authoring/front-matter.html)). +::: +::: + +--- + +![](images/9.png) + + +--- + +### Text + +::: {.fragment} +::: {.callout-tip title="."} +With a basic YAML formatting block now in place, we can build out other elements of our Quarto Markdown document. Unless otherwise specified, everything else in the document is assumed to be text, so I will go ahead and provide an initial text description of what I am trying to do. +::: +::: + +--- + +![](images/10.png) + + +--- + +### Code-Chunks + +::: {.fragment} +::: {.callout-tip title="."} +Having provided some initial text for documentation, we can then add code-block chunks to start writing some code. + +The easiest way to do do this is to click the respective option on the upper-right of the Editor screen. Since Positron can handle multiple programming languages, so the chunk is inserted, we will need to select the language we use to be used within the code chunk (R in this case). +::: +::: + +--- + +![](images/11.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will notice, that the inserted code block starts off with three backticks (\`) and then "{r}". The end of the code block is denoted by an additional three backticks. + +We can also add new code blocks by simply typing these elements into the location we want to place a code chunk (as long as we are careful to add 3 backticks also at the end). +::: +::: + +--- + +![](images/12.png) + +--- + +![](images/13.png) + + +--- + +### Running Code + +::: {.fragment} +::: {.callout-tip title="."} +Now that we have two code-chunks written, we can write lines of code within them. For this example, I will use two beginner friendly functions, print("Hello"), which will print the contents contained between the " " to the console, and getwd() which will return the location of the folder you are working within (ie. the working directory). + +To run/execute these lines of code, we have a couple options. We can click on the Run Cell option that appears on the upper-left side of the code chunk. Additionally, it has a companion option that will run all code chunks above it. +::: +::: + +--- + +![](images/14.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When a code block is successfully run, you will see within the console (lower bottom of the screen) the line of code be run, with any returned outputs appear directly after. +::: +::: + +--- + +![](images/15.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +An alternative to clicking the Run Cell button is to click on the line of code you are interested in running, then press (Ctrl + Enter)/(Command + Enter). This will execute the line of code that you have clicked on. This can be useful in scenarios where you want to run a specific line, and not the entire code-chunk. +::: +::: + +--- + +![](images/16.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Using this approach, you can see the location (ie. file path) of the current working directory was returned to the Console. +::: +::: + +--- + +![](images/17.png) + + +--- + +## Local Version Control + +::: {.fragment} +::: {.callout-tip title="."} +Having introduced the main elements of a [Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) file, let's turn our attention to the tab within the editor showing our newly created .qmd file. + +We can see there is a solid circle next to the file name, and it is appearing as green. The circle denotes unsaved changes, which we can correct by clicking on the Save Button to save the changes to our file. +::: +::: + +--- + +![](images/18.png) + + +--- + +### Untracked + +::: {.fragment} +::: {.callout-tip title="."} +If we turn our attention to the left primary sidebar, we can see that within our GitPractie folder there are three files, our Example.qmd, and the default README.md and .gitignore files. These all show up in green text with U's to the right of the file names. + +This denotes that the version control tracking software Git is currently considering them as "Untracked" files. While saving the document via the Save button means we will still have our changes when we reopen Positron, we won't have any history of changes that we can use to revert back to the way all the files appeared at this exact point in time should something go wrong. + +We will next go the address bar on the very far left, and select the Git tab. +::: +::: + +--- + +![](images/19.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +On the Git tab, we can see that each of the three files are shown underneath a "Changes" drop-down. This contains the files that have undergone changes since the last commit. In our case, since we haven't updated the save-state yet, this last commit would be the initial creation of the project folder. +::: +::: + +--- + +![](images/20.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To have version control track these individual files going forward, we can do so in two separate ways. We can add them individually by clicking the + symbol next to the individual names. +::: +::: + +--- + +![](images/21.png) + + +--- + +### Staged + +::: {.fragment} +::: {.callout-tip title="."} +This will result in the files being moved to the "Staged" dropdown. This denotes files being tracked with the intention of being recorded as the next save-state or waypoint (ie. a commit). +::: +::: + +--- + +![](images/22.png) + + +--- + +### Commit + +::: {.fragment} +::: {.callout-tip title="."} +To create a new commit (save-state or waypoint), once we have the files we want to track staged, we will write a commit message, and then press commit. + +A commit message is a brief description of the changes that have occurred to the files between this commit and the previous one. Make this short description informative enough that if you need to revert back in the future, you can quickly identify the commit you need to fall back to (more about this later). +::: +::: + +--- + +![](images/23.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If this your first time using version control, you will likely encounter the following pop-up asking that you provide a user.name and user.email. This is used to designate the author of the changes.If you get this popup, go ahead and select "Open Git Log" +::: +::: + +--- + +![](images/24.png) + + +--- + +### UserName and UserEmail + +::: {.fragment} +::: {.callout-tip title="."} +The Output tab at the bottom of the screen will open, showing the messages that led to the popup. + +The important part to note is the commands that will be needed to provide your user name and email to the computer for authoring the commit. Typically, your email will be the same one you used for your GitHub account. +::: +::: + +--- + +![](images/25.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +From the displayed message, go ahead and copy + +"git config –global user.email "you\@example.com"" + +Then click on the adjacent terminal tab. You will paste the command in, but do not hit enter just yet. + +Windows users, please note, depending on your settings, if trying to paste from the keyboard into the terminal, you may need to press "Ctrl + Shift + V" instead of the usual "Ctrl + V". +::: +::: + +--- + +![](images/26.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +With the command now pasted (or typed), use your keyboard arrows to navigate to the email portion, and replace the generic email with your email address used for your GitHub account. + +Make sure that the quotation marks (") around the email address remain present, as they help the computer identify where your email address starts and ends. Once satisfied that your email address is correct, press enter. +::: +::: + +--- + +![](images/27.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next up, repeat the process, this time copying over the command needed to set your user name to the terminal. Repeat the editing process to provide your name between the "" marks. Then press enter. +::: +::: + +--- + +![](images/28.png) + +--- + +![](images/29.png) + + +--- + +### First Commit + +::: {.fragment} +::: {.callout-tip title="."} +Now that your user.name and email address have been provided, Git should be able to provide an author to the commit message. Reattempt to press commit button. + +If this is successful, you will see your initial commit appear on the bottom half of the left primary side bar, under the Graph dropdown. Congrats! Your files are now being tracked by version control. +::: +::: + +--- + +![](images/30.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If you hover with your mouse arrow just over the commit, you can see the longer commit message and additional details appear. + +If you click on the commit tab, a new display will open in the editor, displaying the changes that occured in that commit compared to the previous one. In this case, since we added everything since the previous commit, nothing appears on the left side, while the entire documents contents appear highlighted in green on the right. + +Green highlighting is used to show additions, while red highlighting is used to show deletions. +::: +::: + +--- + +![](images/31.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Having completed this initial commit, for this example, let's imitate a typical workflow and make some additional changes to the file before we make a second commit. Within text portions of the .qmd file, use of \# denotes a section header in markdown, so let's add a header for Introduction and click save. +::: +::: + +--- + +![](images/32.png) + + +--- + +### Modified + +::: {.fragment} +::: {.callout-tip title="."} +Within the left primary sidebar, we can see that the Git tracking has updated. Examples.qmd is visible once again. However, becuase it is now a tracked file, instead of showing up with the "U/Untracked" green highlight, it now appears as a brownish-red with a "M/Modified". + +Let's make an additional change to the .qmd file by adding another section (# Setup) and a code block with a commented out line (denoted by the \# at the line start), before pressing Save. +::: +::: + +--- + +![](images/33.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we were now to click on the Example.qmd file in the left primary sidebar, it will open the same kind of tracking display we saw previously. This time, we can see changes since our last commit. These appear as the green highlights along the scroll-bar, corresponding to the \# Introduction and \# Setup headers that we have added in since the last commit. +::: +::: + +--- + +![](images/34.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For a larger document, we can scroll down to see the various highlighted regions. +::: +::: + +--- + +![](images/35.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We could now repeat the steps showed above, staging the file, writing a commit message, and commiting again by clicking on the designated buttons. + +An important question is how often should we commit, vs. just hit save? Well... it depends :D +Let's think about this in context of a video game. If you made commits at regular intervals throughout the day (or more frequently when doing something particularly risky), you are more likely to be close enough to a particular commit (waypoint/save-state) that you can quickly revert back to without loosing any progress. Alternatively, if your last commit was last week, you will not have any intermediate versions to fall back to. +::: +::: + +### Commit via Terminal + +::: {.fragment} +::: {.callout-tip title="."} +Having demonstrated how to commit changes to Git via the left primary side-bar, for this second commit, let's do it the alternate way via the terminal (tab on the panel at the bottom of your screen). +::: +::: + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +After clicking on the terminal tab, click on blinking command line. + +The command to stage a file is "git add ", followed by the name of the file you want to stage. + +In this case, you would enter "git add Example.qmd" and press Enter. +::: +::: + +--- + +![](images/36.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will see after pressing enter a new blank terminal line appear. If you glance at the left-sidebar, you can see that Example.qmd now appears under the Staged Changes dropdown. +::: +::: + +--- + +![](images/37.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next up, let's write the git commit via the terminal. In this case, the command would be "git commit -m " (-m denoting message). The commit text is then surrounded by "" marks. + +For example: "git commit -m "Added section headers to my QMD file"" + +Press enter to save the commit. +::: +::: + +--- + +![](images/38.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And you should see your second commit now appear in the left primary sidebar underneath the graphs dropdown. +::: +::: + +--- + +![](images/39.png) + + +--- + +## Remote Version Control + +### Copying Project Folder to GitHub + +::: {.fragment} +::: {.callout-tip title="."} +While having local version control in place is helpful when you need to revert back after encountering issues, where Git shines is the ability to pass your changes to your online GitHub repository. + +Not only does this allow you to switch between computers, but should something disastrous happen to your main computer, you still have all your hard work backed up and readily assessible. + +For this subsection, first, double check that Positron is still connected to your GitHub account by checking the user tab on the bottom-left. If not, repeat the [connection setup](/course/00_WorkstationSetup/Windows.qmd#connecting-github-and-positron). +::: +::: + +--- + +![](images/40.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Since our project was created using the "New Folder from Template" option, it currently only exist locally. What we want to do next is to copy it to our GitHub account, creating a new repository in the process. + +To do this, we will first need to install the `usethis` R package. Within your console, you would run the following line of code: +::: +::: + +```{r} +#| eval: false +install.packages("usethis") +``` + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Depending on what R packages you already have installed on your computer, you may get a prompt asking if you want to update/install additional dependencies. Go ahead and type the number corresponding to Update All, and press enter. + +The package and all it's dependencies should then install. If an error message appears, read through it, and follow provided instructions. Go to [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) +if need help. +::: +::: + + +---- + +::: {.fragment} +::: {.callout-tip title="."} +Once the `usethis` package is installed, we need to activate it within R by calling it with the library command. This makes all the tools (ie. functions) within an R package available for use within Positron. + +In your console, you would type: +::: +::: + +```{r} +#| eval: FALSE +library(usethis) +``` + +--- + +![](images/46.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +With library called, you now have access to the functions (tools) within the `usethis` R package. One of these is the `use_github()` function. + +In Positron, if you hover over a function, it will pull up the associated help file which will provide you information about the arguments the function expects to receive, and what they do. + +For `use_github()`, the main thing to remember for now is since this is a personal project being used for testing, we don't necessarily want to share it with the entire world, so we should set the "private" argument equal to TRUE when creating a new repository. +::: +::: + +--- + +![](images/46.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Taking this information that we have now gathered, we can now within our Quarto Markdown create a code chunk, write out the line of code calling the function, and providing the Private=TRUE argument within the (). + +Within a code chunk, adding a \# in front of a line of code, will comment it out, resulting in that line of code not being run. Since we have already installed the `usethis` package, and we don't want to reinstall it every single time, let's go ahead and comment out that line. Go ahead and press Enter. +::: +::: + +--- + +![](images/47.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will see a message pop-up in the console. In this case, we had not saved before pressing enter, so there are uncommitted changes within the folder. The pop-up is asking whether you want to save these as well before sending the Folder to GitHub. + +In this case I will chose to ignore the uncommitted changes by entering 3 (for Definitely) in the console and hitting enter on my keyboard. +::: +::: + +--- + +![](images/48.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The `usethis` R package will then execute the series of git commands that are needed to set up a GitHub repository (ie. the messages being displayed in the console window), and when finished will open a pop-up asking whether you want to see your new repository in your default Web Browser. I will go ahead and select yes in this case. +::: +::: + +--- + +![](images/49.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +After the browser opens, you can see that the elements I had staged and committed within Positron are now present within the GitHub repository. +Since I had only staged Example.qmd, it is the only file that was backed up. We can also see the commit history online by clicking on the commit clock. +::: +::: + +--- + +![](images/50.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As we would expect, we only see our two commit messages. One important thing to note is the commit hash numbers, that denote a particular commit. If we decided to revert/fall back to a prior commit in the future, this would be the number we would need to provide to Git to return to that previous commit/save-state +::: +::: + +--- + +![](images/51.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Similarly, on GitHub, we have an option to Browse a Repository at a particular point in time. This will be quite useful later in the future when troubleshooting what major changes occurred between versions of an R package. +::: +::: + +--- + +![](images/52.png) + + +--- + +### Code Chunk Arguments + +::: {.fragment} +::: {.callout-tip title="."} +Having successfully connected our local Project Folder to a remote GitHub repository, let's return to Positron. + +Before continuing, if we left the code chunk that created the GitHub repository as is, every time we ran all code chunks in the document, it would try to recreate the GitHub repository. We don't want this to happen, as the setup was a one-time operation. + +While we could add \# in front of every line of code (or delete the code chunk entirely) it is often useful to have these set-up code chunks around to remind us what arguments we need to provide next time we need to a similar setup and are mind blanking on what to do. + +Fortunately, Quarto allows us to set conditions on whether a chunk is run (ie. evaluated). We will discuss the conditiona arguments in more depth in the [next section](/course/00_Quarto/index.qmd), but for now, we can modify the code chunk as follows. + + +On the next line after the {r}, we will add a hashtag (\#), then a pipe (|), followed by a space. This is the setup for a code-chunk specific argument. We will then add "eval: FALSE", which signals that the particular code-chunk should not be evaluated (ie, should not be run). +::: +::: + +--- + +![](images/53.png) + + +--- + +### README + +::: {.fragment} +::: {.callout-tip title="."} +Now that we have connected our local Project Folder to GitHub, and have gotten a basic introduction to the "git add", "git commit" arguments, let's turn our focus to the other files currently listed as untracked by Git within our folder, the README.md and the .gitignore files. + +When setting up our [GitHub]() account, we encounted an example of a README.md file. This file often provides a brief description of the project, and an outline of what the other files in the folder are for. As you may have gathered, even software developers are forgetful/under-caffenaited, and having notes to catch back up to speed is important. +::: +::: + +--- + +![](images/54.png) + + +--- + + +### .gitignore + +::: {.fragment} +::: {.callout-tip title="."} +We additionally have a .gitignore file. Within a project, there are often some files that we will never want version control to track. These could be files that are too large for GitHub (ex. really large .fcs files), or files containing sensitive information (passwords, history, credentials, etc.). + +When the names of these file (or the file type shothand) are added to the .gitignore file, they are ignored by version control, and no longer appear on the primary left side bar. +::: +::: + +--- + +![](images/54.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Let's proceed and stage both the README.md and .gitignore file, so that changes to these files will be tracked. We can of course select both from the primary left side bar and write a short commit message. +::: +::: + +--- + +![](images/55.png) + +--- + +![](images/56.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Or alternatively, if we want to stage all uncommitted files present in a single step, we could in the terminal use the "git add ." + +We can then write our git commit using "git commit -m". + +Both approaches work, and you may switch between them based on preferrence. +::: +::: + +--- + +![](images/57.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will notice after having committed, that if you look at the Graph dropdown on the bottom half of the primary left side-bar that something has changed. + +There are now separate icons denoted as main and origin/main. These correspond to the last commit present locally (main), and the last commit on remote (ie. GitHub, origin/main). + +Local is ahead since you just made the commit with the changes inactivating the code-chunk, and you have not passed these changes up to GitHub yet. +::: +::: + +--- + +![](images/58.png) + + +--- + + +### Pull + +::: {.fragment} +::: {.callout-tip title="."} +Before sending (ie. pushing up) our updated commit to GitHub, especially if you are working on a project from multiple computers (or as part of a team) to bring in (ie. pull down) any changes that might be on GitHub that are not present locally. + +This ensures that everything is up to date, and you don't end up with mismatched commits that are incompatible with each other and trigger an error message. + +To pull in changes from GitHub, at the top of the primary left side-bar, you can select the ... button to open a drop-down menu of Git options. You would then select "Pull". + +Alternatively, you could do the same thing via the terminal by running the "git pull" command. +::: +::: + +--- + +![](images/59.png) + + +--- + +### Push + +::: {.fragment} +::: {.callout-tip title="."} +In our case, there was no new material present on our GitHub repository that were not already present locally, so all that is returned is the "Already up to date" message. + +We are now good to proceed to push (ie. send) the updated commit up to our GitHub repository. + +We can do this by either pressing the Sync changes button, or via the terminal entering the "git push" command. +::: +::: + +--- + +![](images/60.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And now, if you glance down at left side-bar's graph section, you will see that both the main and origin/main icons are now present for the most recent commit. +::: +::: + +--- + +![](images/61.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we switch to our Web browser, we can see that this is also now the case for our GitHub repository that now also has the most recent changes. +::: +::: + +--- + +![](images/62.png) + + +--- + +### Reverting to Prior Commit + +::: {.fragment} +::: {.callout-tip title="."} +For most daily-workflows, you will only need the git commands that we have introduced above (git add, commit, pull, push). The next two areas (reverting to a prior commit, and branches) are more specialized, and will be covered in greater depth later in the course. We are briefly covering them here. If you are at the point where your last remaining neuron has disconnected, and you feel you need to take a break from version control, feel free to skip to the [next section](/course/00_Quarto/index.qmd) and we will revisit these topics later in the course. +::: +::: + + +-- + +::: {.fragment} +::: {.callout-tip title="."} +In most cases, if your code stops working, you can identify the issue and fix it in the existing version, never needing to resort to reverting to a previous commit (save-state). The times you would need to revert would be if you deleted important files, or the new files are hopeless mess that is not worth trying to sort through. In those cases, reverting back might be better approach. + +To imitate a falling back scenario, lets create and additional file, stage and commit it to end up a commit ahead of where we are currently at within the Project Folder. +::: +::: + +--- + +![](images/00_RevertTest.png) + + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Now being one (or several) commits ahead, if we wanted to revert back, we would first need to identify the commit we want to revert back to and copy the commit hash number. +::: +::: + +--- + +![](images/00_CommitHash.png) + + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Then, opening the terminal, we can enter "git reset " and paste the hash afterwards. We can then press enter. +::: +::: + +--- + +![](images/00_GitReset.png) + + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will notice our additional commit has been removed, although the newer files we were working on subsequent last commit are still present. +::: +::: + +--- + +![](images/00_GitResetExecuted.png) + + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If however, we had wanted to return to the exact same state as the previous commit (removing all subsequent created files), we could do so by adding in the --hard argument. Before starting, save any newer files you want to keep in a completely different folder, because they will be permanently removed. + +Then, enter "git reset --hard thecommithashnumber" into the terminal, which would result in a "hard" return to the previous commits save-state. You may need to close and reopen Positron to see the changes reflected. +::: +::: + +--- + +### Branches + +::: {.fragment} +::: {.callout-tip title="."} +Branches are an useful Git feature that we will start using extensively later in the course. Branching allows you to create a parallel/carbon-copy of your existing repository, which you can then edit without affecting the main branch. This is particularly useful for projects that may get messy or drawn out. By isolating these edits to a parallel branch, if they don't work, your main branch remains safe. Alternatively, if you like the changes that occurred in the branch, you can pull these changes from the branch back to main, bringing the timelines back together. +::: +::: + +![](https://book.the-turing-way.org/build/sub-branch-491000deab04cb25ea703c007e2ebdd2.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Within the terminal, entering "git branch" will show the existing branches. In this case, only main is present since we haven't yet created a new branch. +::: +::: + +--- + +![](images/00_Branch.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can create a new branch in the terminal by entering "git branch " followed by the name of our desired branch. In this case, we are creating a branch called Week1 +::: +::: + +--- + +![](images/00_Week1.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Now, when we check "git branch" again in the terminal, which returns the two branches, Week1 and main. The \* is located next to main, indicating that we are currently within the main branch. +::: +::: + +--- + +![](images/00_Branches.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Besides the terminal, we can also create a new branch via Positron. To do so, we first click on the Git tab in the Actions Bar. + +Once the left-side bar displays the version control display, we can click on the ... button (to the right of changes)to gain access to the Git options drop-down. + +From here, we click on Branch, and then select Create Branch. +::: +::: + +--- + +![](images/00_BranchesGUI.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Using Git branch, we saw that we were still within the main branch. In the terminal, we can switch over to the Week1 branch by using the "git checkout " command, followed by the branch we wish to switch to. +::: +::: + +--- + +![](images/00_Checkout.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This results in us switching over to the Week1 branch. +::: +::: + +--- + +![](images/00_CheckoutOutput.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Having switched (ie. checkout) to the Week 1 branch, let's create the file BranchTest.qmd, which will exist within this branch, but not yet in the main branch. +::: +::: + +--- + +![](images/00_BranchTest.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Having created the file, let's stage and then commit it. This will put the Week1 branch ahead of the main branch by a single commit. +::: +::: + +--- + +![](images/BranchCommit.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +With our changes staged and committed, if we look at the left side-bar's graph section, our Week1 branch is now ahead of the origin/main branch by one commit. +::: +::: + +--- + +![](images/00_BranchToOrigin.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we were to check on GitHub, we can see that no new files are present on the main branch, but can see the notification listing recent changes to Week1 branch. +::: +::: + +--- + +![](images/00_GitHub.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Using the drop-down, we can switch from displaying the main branch to the Week1 branch, where we can see the new file. +::: +::: + +--- + +![](images/00_GitHubWeek1.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we click the green compare and pull request button, we end up on this screen. This compares how the two branches are different from each other. +::: +::: + +--- + +![](images/00_GithubWeek1Merge.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will delve into branches again at a later point. For now, remember that by creating and prunning parallel branches, you can develop knowing that even if something goes wrong, your main branch remains safe. +::: +::: + +--- + +# Wrap-Up + +::: {.fragment} +::: {.callout-tip title="."} +In this section, we saw how to create a New Project Folder, create files and back up the project folder to GitHub. We also started learning about git, covering the basic commands (git add, commit, pull, push). If you feel a bit overwhelmed, please know, that is normal. Understanding how to leverage git takes time and practice, but is an incredibly valuable skillset to have in the long run. + +In the [next section](/course/00_Quarto/index.qmd), we will look at how by changing various elements within our .qmd file produce a variety of files, and how to leverage code-chunk arguments to fine-tune whether a code-chunk is utilized. +::: +::: + +# Additional Resources + +[Git & GitHub Tutorial for Scientist: It's Not Only for Programmers](https://gitbookdown.dallasdatascience.com/) + +[Ten Simple Rules for Taking Advantage of Git and GitHub](https://pmc.ncbi.nlm.nih.gov/articles/PMC4945047/) + +[A brief introduction to Git for beginers](https://youtu.be/r8jQ9hVA2qs?si=IYe7JghJpVTz9Ht4) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_GitHub/index.qmd b/course/00_GitHub/index.qmd index 77e1bdd..f123e2a 100644 --- a/course/00_GitHub/index.qmd +++ b/course/00_GitHub/index.qmd @@ -1,406 +1,406 @@ ---- -title: "Using GitHub" -author: "David Rach" -date: 01-21-2026 -format: html -toc: true -toc-depth: 4 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -For the YouTube livestream recording, see [here](https://www.youtube.com/live/PDz0R9jdVfc?si=gtdIAye2q3ZWPJzs) - - - -For screen-shot slides, click [here](/course/00_GitHub/slides.qmd) - -# Background - -When working with code, it is very important to stay organized. You ultimately want to avoid being in a scenario where you need some code you wrote the previous month, and then having to search through multiple .R files, scattered across multiple folders, external hard-drives, and computers to find it. Likewise, you want to avoid ending up having identified multiple similarly-named copies of your original file that have all since diverged slightly from each other in some way that you have long since forgotten. - -![](https://phdcomics.com/comics/archive/phd101212s.gif){width=50%} - -Ideally, everything needed for your coding script to successfully run should be kept within a project-specific folder. This ensures, that should you transfer it to another computer (whether your own or a colleagues) that you would still be able to recreate the scripts output. - -Likewise, if you make changes to your script, and your code stops working (no longer returns the expected output, ie. breaks), having a record of what changes were made since the last working version would be very helpful in pinpointing what went wrong. For beginners, this often ends up being a typo in a function name, or an accidentally misplaced comma somewhere in your document. - -For these reasons, in this course, we will be extensively using the version control software [Git](https://git-scm.com/) from the very beginning. We will also have you create a [GitHub](https://github.com/) account, which will allow you to back-up your coding projects online as private repositories. Not only is this useful in case something happens to your computer, but it allows you to switch between separate computers while still having ready access to all your code, avoiding ending up with divergent copies on each computer. - -Additionally, since all the material for this course is being hosted on a public GitHub repository, once you have set up your GitHub account you will be able to retrieve all the new materials and changes by simply refreshing (ie. syncing) your version of the course folder (ie. fork) once a week. Your GitHub account will also be needed when posting or asking questions on the [Discussion Forum](https://github.com/UMGCCCFCSR/CytometryInR/discussions). - -In this walk-through, we will go through setting up a GitHub account, and make sure you are familiar with some of the elements and locations that we will be circling back to throughout the course. - ---- - -# Getting Started - - -## Creating an Account - -We will first navigate to the [GitHub homepage](). If you haven't previously created an account, click on the button to sign up for an account. - -![](images/01_GitHub.png) - -
- ---- - -On the sign-up page, you will fill in various details needed to create an account. Please remember that GitHub usernames are visible to others. Additionally, if you end up sharing code with others as part of a manuscript, or use GitHub to create a personal portfolio website in the future, your username will appear as part of the URL. - -For example, in my case, my user name is DavidRach, so my GitHub profile ends up as: [https://github.com/DavidRach](https://github.com/DavidRach). For our course, the core's GitHub user name is UMGCCCFCSR, so the github profile ends up as [https://github.com/UMGCCCFCSR](https://github.com/UMGCCCFCSR), while the course website ends up as [https://umgcccfcsr.github.io/CytometryInR/](https://umgcccfcsr.github.io/CytometryInR/) - -![](images/02_GithubSignup.png) - -
- ---- - -Once you have entered your new account information, you will need your account creation by entering the code sent to the email address that you provided. - -![](images/03_Github2Factor.png) - -
- ---- - -Once account creation has been confirmed, please proceed to login to GitHub for the first time. - -![](images/04_Login.png) - -
- ---- - -## GitHub Profile - -Upon creating a brand new account, your GitHub homepage will initially look rather empty, and can be intimidating to navigate for the first time. - -For now, on the upper right, go ahead and click on the default profile picture icon... - -![](images/05_YourIcon.png) - -
- ---- - -And then select Profile... - -![](images/05_Profile.png) - -
- ---- - -You are now on your public GitHub profile page. For a newly created account, it will look something like this: - -![](images/06_EditIcon.png) - -
- ---- - -For a more established account, this page will look a [little different](https://github.com/DrCytometer), and can be customized to highlight various projects that you are working on. - -For this course, we will have you set up a basic GitHub profile page for now, although you are free to customize and personalize it as much as you may want to in the future! - -To start, first select the edit profile button on the left below the default profile icon. - -![](images/06_EditIcon.png) - -
- ---- - -You can then proceed to fill in any details that you feel are relevant and are comfortable sharing. - -![](images/07_Basics.png) - -
- ---- - -With the quick access details filled in, it is now time to navigate to the Settings tab. You will return to the previous menu dropdown on the upper right, and instead of selecting Profile, click on the Settings option. - -![](images/05_Profile.png) - -
- ---- - -You should now end up within your Public Profile Settings page. - -Feel free to edit the default profile picture, and any other fields that you feel are relevant. Once done, continue to scroll down the page past ORCID ID. - -![](images/08_ProfileSetup.png) - -
- ---- - -When you reach Contributions and Activity, go ahead and select the option to include private repositories in the activity summary graphic. Then scroll down and click save. You will now be returned to your GitHub profile page. - -![](images/09_SelectThisOneSuggested.png) - -
- ---- - -At the top of the profile, you will see a "Your contributions" calendar graph. For a new account, it will look like this: - -![](images/10_UpdatedGitHubProfile.png) - -
- ---- - -If you are just starting out, this chart will be mostly empty, but will fill in as you work on projects, see [here](https://github.com/cararthompson) as an example. - -Every time you save your code (ie. make a commit), the activity will be reflected in this chart. By clicking the option in settings, code made within a private repository will remain private, but will count toward your contribution chart. As you progress through the course, this will provide a nice visual reminder of the progress you have made, and the obstacles that you have overcome. - -![](images/10_UpdatedGitHubProfile.png) - -
- ---- - -## GitHub ReadMe - -With this done, we modify your GitHub profile by adding one customized element, a ReadMe page. This will be used for a couple projects during the course, and can be personalized further in the future. - -To create a ReadMe page for your profile, we will navigate to the upper right of the screen and click on the + sign. - -![](images/11_UpdatedGitHubProfile2.png) - -
- ---- - -We will then select the Create New Repository option. - -![](images/12_NewRepository.png) - -
- ---- - -You will next create a repository (folder), naming it exactly the same as your username. This will be recognized by GitHub as being a special type of repository corresponding to the ReadMe section of your profile. - -For options, leave the visibility as Public, and Add README set to On. And proceed to Create Repository. - -![](images/13_ReadMe.png) - -
- ---- - -Having created the repository (folder), you will see it has been populated by a few default files. For now, you will be editing the README.md file. On a new repository, the easiest way to access it is by clicking the green option on the right side of your screen. - -![](images/14_EditButton.png) - -
- ---- - -With the README.md file now opened, you will be able to see generic filler text that is suggested by GitHub. - -For this course, I will ask you to add a couple elements for now. You are free to return and further personalize it later if you wish to do so. - -![](images/15_DefaultText.png) - -
- ---- - -The type of file that we are working with is a [Markdown](https://www.markdownguide.org/basic-syntax/) file, which can allow for a bunch of customizations which we will cover throughout the course. - -For now, please add and customize the following questions: - -**Cytometry In R** - -Location: Baltimore, Maryland, USA - -My Favorite Fluorophore/Metal-Isotope: Spark Blue 550 - -Previous Coding Experience: Repeatedly Calling IT - -What I Hope to Get From This Course: A faster way to match FlowSOM clusters to their likely cell type. - -![](images/16_ReadMeContent.png) - -
- ---- - -Next, to save you will select the green "Commit changes" button. We will cover the meaning of "Commit" more in-depth during the [Git](/course/00_Git/index.qmd) section. - -For now, write a short summary of the change you made to the file in the "Commit message", and any additional details within the "Extended description" field. When ready, click the green "Commit changes" button. - -![](images/17_ReadMeCommit.png) - -
- ---- - -You will now be able to see the updated README.md file, as you can see in our example below. To make additional edits, you would select the pencil icon on the right-center side of the screen. - -![](images/18_ReadMeRendered.png) - -
- ---- - -Next, navigate back to your profile page (by clicking on either your username or the Overview option on the tabs). - -You will see that the README file contents are now displayed on the upper portion of your GitHub profile. Feel free to circle back and customize this further to your liking. - -In this last example, we created your first repository (folder). Since this is public, it is now shown below the README section of the profile under your repositories. You can also see that your commits made in the process of making the changes are now shown both in the Contributions graph, and under the Contributor Activity summary at the bottom of the page. - -![](images/19_UpdatedProfile.png) - -
- ---- - -## GitHub Repository - -Having set up your GitHub profile, it now is time to make sure you have access to our course materials. We will have you navigate to our course's [GitHub profile](https://github.com/UMGCCCFCSR) - -On the profile page, you will be able to see our version of the README, our repositories, and the Contributions graph and Contribution activity sections. - -Please click on the [CytometryInR](https://github.com/UMGCCCFCSR/CytometryInR) to navigate to its repository (folder) - -![](images/20_ToCourseProfile.png) - -
- ---- - -On this page, you will see several elements that you will be circling back to throughout the course. - -For our course, we will be extentsively ussing the [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page as a community forum. If you have any questions, are looking for feedback, or want to show off something that you worked on, this is the place for it. This will also help make sure - -![](images/21_Discussions.png) - -
- ---- - -The [Issues](https://github.com/UMGCCCFCSR/CytometryInR/issues) tab is where you will need to go to open an Issue if you encounter a bug (or major documentation typo), so that I can cicle back and correct them when I have the chance. - -![](images/21_BugReports.png) - -
- ---- - -To submit the optional take-home problems, you would turn in these problems by going to the [Pull Request](https://github.com/UMGCCCFCSR/CytometryInR/pulls) tab, and initiating a pull request between your forked version of the project and our "homework" branch (more details on this later). - -![](images/21_HomeworkPullRequest.png) - -
- ---- - -Optionally, you can "Star" a repository. This is basically the GitHub equivalent of liking a project. In our case, we will often star a repository since it will be saved under the Stars tab of our profile, which makes finding it again significantly easier a few weeks later after forgetting the repository name. - -![](images/21_Stars.png) - -
- ---- - -To see projects that you have starred, you can select the Stars option from the same dropdown you used to get to Settings. - -![](images/22_Stars.png) - -
- ---- - -Or from your GitHub profile, you can see these under [Stars](https://github.com/DavidRach?tab=stars) tab. - -![](images/22_YourStarredRepositories.png) - -
- ---- - - -## Forking CytometryInR - -Before we go further, we will need you to make your own copy of the [course repository](https://github.com/UMGCCCFCSR/CytometryInR/) (ie. fork it). This will allow you to quickly retrieve all the new materials and code corrections by simply rereshing (ie. syncing) your forked version with our upstream parent branch once a week. - -
- ---- - -To fork the [course repository](https://github.com/UMGCCCFCSR/CytometryInR/), you will select the "Fork repository" option on the upper-center portion of your screen. - -![](images/23_ForkIt.png) - -
- ---- - -By "Fork-ing" a repository, you are basically copying the contents from that repository to a newly created repository on your own GitHub. Forked projects are still linked to the original (parent) fork, and can retrieve any updates via syncing, as well as return changes via a pull request. - -For this course, when you create the fork, keep the existing repository name ("CytometryInR"). Importantly, select the copy main branch option. This will ensure you only get the code and data needed for the course copied over, and don't end up with your entire hard-drive filled will website elements, or other people's solutions to the take-home problems. - -![](images/24_ForkMainBranch.png) - -
- ---- - -Once you have created the fork, you will see your copy of the forked repository under your own username. Seeing as you have just now forked the project, you will see the notification that you are up to date with the existing version of the CytometryInR course repository. - -As we go through the course, and new material is released each week on Sunday at 2200 EST (Monday 0300 GMT+0), you will see this changed to behind the main branch by a number of commits, and have the option to sync in the changes to your fork to gain access to that week's material. - -![](images/25_YourForkedBranch.png) - -
- ---- - - -If you remember, previously under your GitHub profile, the Repositories tab only contained the repository corresponding to your ReadMe section. - -![](images/YourRepositories.png) - -
- ---- - -You should however now be able to see your fork of the CytometryInR repository. As you add project specific repositories throughout the course, they will also appear here. - -![](images/YourUpdatedRepos.png) - -
- ---- - -# Wrap-Up - -We have now completed our walk-through of setting up a GitHub account. At this point, you should have modified your GitHub profile, added a README section, and most importantly, forked the [CytometryInR](https://github.com/UMGCCCFCSR/CytometryInR/) repository so that you can easily retrieve the new course materials each week. - -Next up, we will have you proceed to installing the required software to your computer that will be needed throughout the course. Installation instructions will vary depending on your computer's operating system, so please follow the appropiate walkthrough. - -# Additional Resources - -[Git & GitHub Tutorial for Scientist: It's Not Only for Programmers](https://gitbookdown.dallasdatascience.com/) - -[Ten Simple Rules for Taking Advantage of Git and GitHub](https://pmc.ncbi.nlm.nih.gov/articles/PMC4945047/) - -[A brief introduction to Git for beginers](https://youtu.be/r8jQ9hVA2qs?si=IYe7JghJpVTz9Ht4) - -[How to Use GitHub for Beginners](https://youtu.be/a9u2yZvsqHA?si=lbKBogzjEZ1YehpQ) - - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Using GitHub" +author: "David Rach" +date: 01-21-2026 +format: html +toc: true +toc-depth: 4 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://www.youtube.com/live/PDz0R9jdVfc?si=gtdIAye2q3ZWPJzs) + + + +For screen-shot slides, click [here](/course/00_GitHub/slides.qmd) + +# Background + +When working with code, it is very important to stay organized. You ultimately want to avoid being in a scenario where you need some code you wrote the previous month, and then having to search through multiple .R files, scattered across multiple folders, external hard-drives, and computers to find it. Likewise, you want to avoid ending up having identified multiple similarly-named copies of your original file that have all since diverged slightly from each other in some way that you have long since forgotten. + +![](https://phdcomics.com/comics/archive/phd101212s.gif){width=50%} + +Ideally, everything needed for your coding script to successfully run should be kept within a project-specific folder. This ensures, that should you transfer it to another computer (whether your own or a colleagues) that you would still be able to recreate the scripts output. + +Likewise, if you make changes to your script, and your code stops working (no longer returns the expected output, ie. breaks), having a record of what changes were made since the last working version would be very helpful in pinpointing what went wrong. For beginners, this often ends up being a typo in a function name, or an accidentally misplaced comma somewhere in your document. + +For these reasons, in this course, we will be extensively using the version control software [Git](https://git-scm.com/) from the very beginning. We will also have you create a [GitHub](https://github.com/) account, which will allow you to back-up your coding projects online as private repositories. Not only is this useful in case something happens to your computer, but it allows you to switch between separate computers while still having ready access to all your code, avoiding ending up with divergent copies on each computer. + +Additionally, since all the material for this course is being hosted on a public GitHub repository, once you have set up your GitHub account you will be able to retrieve all the new materials and changes by simply refreshing (ie. syncing) your version of the course folder (ie. fork) once a week. Your GitHub account will also be needed when posting or asking questions on the [Discussion Forum](https://github.com/UMGCCCFCSR/CytometryInR/discussions). + +In this walk-through, we will go through setting up a GitHub account, and make sure you are familiar with some of the elements and locations that we will be circling back to throughout the course. + +--- + +# Getting Started + + +## Creating an Account + +We will first navigate to the [GitHub homepage](). If you haven't previously created an account, click on the button to sign up for an account. + +![](images/01_GitHub.png) + +
+ +--- + +On the sign-up page, you will fill in various details needed to create an account. Please remember that GitHub usernames are visible to others. Additionally, if you end up sharing code with others as part of a manuscript, or use GitHub to create a personal portfolio website in the future, your username will appear as part of the URL. + +For example, in my case, my user name is DavidRach, so my GitHub profile ends up as: [https://github.com/DavidRach](https://github.com/DavidRach). For our course, the core's GitHub user name is UMGCCCFCSR, so the github profile ends up as [https://github.com/UMGCCCFCSR](https://github.com/UMGCCCFCSR), while the course website ends up as [https://umgcccfcsr.github.io/CytometryInR/](https://umgcccfcsr.github.io/CytometryInR/) + +![](images/02_GithubSignup.png) + +
+ +--- + +Once you have entered your new account information, you will need your account creation by entering the code sent to the email address that you provided. + +![](images/03_Github2Factor.png) + +
+ +--- + +Once account creation has been confirmed, please proceed to login to GitHub for the first time. + +![](images/04_Login.png) + +
+ +--- + +## GitHub Profile + +Upon creating a brand new account, your GitHub homepage will initially look rather empty, and can be intimidating to navigate for the first time. + +For now, on the upper right, go ahead and click on the default profile picture icon... + +![](images/05_YourIcon.png) + +
+ +--- + +And then select Profile... + +![](images/05_Profile.png) + +
+ +--- + +You are now on your public GitHub profile page. For a newly created account, it will look something like this: + +![](images/06_EditIcon.png) + +
+ +--- + +For a more established account, this page will look a [little different](https://github.com/DrCytometer), and can be customized to highlight various projects that you are working on. + +For this course, we will have you set up a basic GitHub profile page for now, although you are free to customize and personalize it as much as you may want to in the future! + +To start, first select the edit profile button on the left below the default profile icon. + +![](images/06_EditIcon.png) + +
+ +--- + +You can then proceed to fill in any details that you feel are relevant and are comfortable sharing. + +![](images/07_Basics.png) + +
+ +--- + +With the quick access details filled in, it is now time to navigate to the Settings tab. You will return to the previous menu dropdown on the upper right, and instead of selecting Profile, click on the Settings option. + +![](images/05_Profile.png) + +
+ +--- + +You should now end up within your Public Profile Settings page. + +Feel free to edit the default profile picture, and any other fields that you feel are relevant. Once done, continue to scroll down the page past ORCID ID. + +![](images/08_ProfileSetup.png) + +
+ +--- + +When you reach Contributions and Activity, go ahead and select the option to include private repositories in the activity summary graphic. Then scroll down and click save. You will now be returned to your GitHub profile page. + +![](images/09_SelectThisOneSuggested.png) + +
+ +--- + +At the top of the profile, you will see a "Your contributions" calendar graph. For a new account, it will look like this: + +![](images/10_UpdatedGitHubProfile.png) + +
+ +--- + +If you are just starting out, this chart will be mostly empty, but will fill in as you work on projects, see [here](https://github.com/cararthompson) as an example. + +Every time you save your code (ie. make a commit), the activity will be reflected in this chart. By clicking the option in settings, code made within a private repository will remain private, but will count toward your contribution chart. As you progress through the course, this will provide a nice visual reminder of the progress you have made, and the obstacles that you have overcome. + +![](images/10_UpdatedGitHubProfile.png) + +
+ +--- + +## GitHub ReadMe + +With this done, we modify your GitHub profile by adding one customized element, a ReadMe page. This will be used for a couple projects during the course, and can be personalized further in the future. + +To create a ReadMe page for your profile, we will navigate to the upper right of the screen and click on the + sign. + +![](images/11_UpdatedGitHubProfile2.png) + +
+ +--- + +We will then select the Create New Repository option. + +![](images/12_NewRepository.png) + +
+ +--- + +You will next create a repository (folder), naming it exactly the same as your username. This will be recognized by GitHub as being a special type of repository corresponding to the ReadMe section of your profile. + +For options, leave the visibility as Public, and Add README set to On. And proceed to Create Repository. + +![](images/13_ReadMe.png) + +
+ +--- + +Having created the repository (folder), you will see it has been populated by a few default files. For now, you will be editing the README.md file. On a new repository, the easiest way to access it is by clicking the green option on the right side of your screen. + +![](images/14_EditButton.png) + +
+ +--- + +With the README.md file now opened, you will be able to see generic filler text that is suggested by GitHub. + +For this course, I will ask you to add a couple elements for now. You are free to return and further personalize it later if you wish to do so. + +![](images/15_DefaultText.png) + +
+ +--- + +The type of file that we are working with is a [Markdown](https://www.markdownguide.org/basic-syntax/) file, which can allow for a bunch of customizations which we will cover throughout the course. + +For now, please add and customize the following questions: + +**Cytometry In R** + +Location: Baltimore, Maryland, USA + +My Favorite Fluorophore/Metal-Isotope: Spark Blue 550 + +Previous Coding Experience: Repeatedly Calling IT + +What I Hope to Get From This Course: A faster way to match FlowSOM clusters to their likely cell type. + +![](images/16_ReadMeContent.png) + +
+ +--- + +Next, to save you will select the green "Commit changes" button. We will cover the meaning of "Commit" more in-depth during the [Git](/course/00_Git/index.qmd) section. + +For now, write a short summary of the change you made to the file in the "Commit message", and any additional details within the "Extended description" field. When ready, click the green "Commit changes" button. + +![](images/17_ReadMeCommit.png) + +
+ +--- + +You will now be able to see the updated README.md file, as you can see in our example below. To make additional edits, you would select the pencil icon on the right-center side of the screen. + +![](images/18_ReadMeRendered.png) + +
+ +--- + +Next, navigate back to your profile page (by clicking on either your username or the Overview option on the tabs). + +You will see that the README file contents are now displayed on the upper portion of your GitHub profile. Feel free to circle back and customize this further to your liking. + +In this last example, we created your first repository (folder). Since this is public, it is now shown below the README section of the profile under your repositories. You can also see that your commits made in the process of making the changes are now shown both in the Contributions graph, and under the Contributor Activity summary at the bottom of the page. + +![](images/19_UpdatedProfile.png) + +
+ +--- + +## GitHub Repository + +Having set up your GitHub profile, it now is time to make sure you have access to our course materials. We will have you navigate to our course's [GitHub profile](https://github.com/UMGCCCFCSR) + +On the profile page, you will be able to see our version of the README, our repositories, and the Contributions graph and Contribution activity sections. + +Please click on the [CytometryInR](https://github.com/UMGCCCFCSR/CytometryInR) to navigate to its repository (folder) + +![](images/20_ToCourseProfile.png) + +
+ +--- + +On this page, you will see several elements that you will be circling back to throughout the course. + +For our course, we will be extentsively ussing the [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page as a community forum. If you have any questions, are looking for feedback, or want to show off something that you worked on, this is the place for it. This will also help make sure + +![](images/21_Discussions.png) + +
+ +--- + +The [Issues](https://github.com/UMGCCCFCSR/CytometryInR/issues) tab is where you will need to go to open an Issue if you encounter a bug (or major documentation typo), so that I can cicle back and correct them when I have the chance. + +![](images/21_BugReports.png) + +
+ +--- + +To submit the optional take-home problems, you would turn in these problems by going to the [Pull Request](https://github.com/UMGCCCFCSR/CytometryInR/pulls) tab, and initiating a pull request between your forked version of the project and our "homework" branch (more details on this later). + +![](images/21_HomeworkPullRequest.png) + +
+ +--- + +Optionally, you can "Star" a repository. This is basically the GitHub equivalent of liking a project. In our case, we will often star a repository since it will be saved under the Stars tab of our profile, which makes finding it again significantly easier a few weeks later after forgetting the repository name. + +![](images/21_Stars.png) + +
+ +--- + +To see projects that you have starred, you can select the Stars option from the same dropdown you used to get to Settings. + +![](images/22_Stars.png) + +
+ +--- + +Or from your GitHub profile, you can see these under [Stars](https://github.com/DavidRach?tab=stars) tab. + +![](images/22_YourStarredRepositories.png) + +
+ +--- + + +## Forking CytometryInR + +Before we go further, we will need you to make your own copy of the [course repository](https://github.com/UMGCCCFCSR/CytometryInR/) (ie. fork it). This will allow you to quickly retrieve all the new materials and code corrections by simply rereshing (ie. syncing) your forked version with our upstream parent branch once a week. + +
+ +--- + +To fork the [course repository](https://github.com/UMGCCCFCSR/CytometryInR/), you will select the "Fork repository" option on the upper-center portion of your screen. + +![](images/23_ForkIt.png) + +
+ +--- + +By "Fork-ing" a repository, you are basically copying the contents from that repository to a newly created repository on your own GitHub. Forked projects are still linked to the original (parent) fork, and can retrieve any updates via syncing, as well as return changes via a pull request. + +For this course, when you create the fork, keep the existing repository name ("CytometryInR"). Importantly, select the copy main branch option. This will ensure you only get the code and data needed for the course copied over, and don't end up with your entire hard-drive filled will website elements, or other people's solutions to the take-home problems. + +![](images/24_ForkMainBranch.png) + +
+ +--- + +Once you have created the fork, you will see your copy of the forked repository under your own username. Seeing as you have just now forked the project, you will see the notification that you are up to date with the existing version of the CytometryInR course repository. + +As we go through the course, and new material is released each week on Sunday at 2200 EST (Monday 0300 GMT+0), you will see this changed to behind the main branch by a number of commits, and have the option to sync in the changes to your fork to gain access to that week's material. + +![](images/25_YourForkedBranch.png) + +
+ +--- + + +If you remember, previously under your GitHub profile, the Repositories tab only contained the repository corresponding to your ReadMe section. + +![](images/YourRepositories.png) + +
+ +--- + +You should however now be able to see your fork of the CytometryInR repository. As you add project specific repositories throughout the course, they will also appear here. + +![](images/YourUpdatedRepos.png) + +
+ +--- + +# Wrap-Up + +We have now completed our walk-through of setting up a GitHub account. At this point, you should have modified your GitHub profile, added a README section, and most importantly, forked the [CytometryInR](https://github.com/UMGCCCFCSR/CytometryInR/) repository so that you can easily retrieve the new course materials each week. + +Next up, we will have you proceed to installing the required software to your computer that will be needed throughout the course. Installation instructions will vary depending on your computer's operating system, so please follow the appropiate walkthrough. + +# Additional Resources + +[Git & GitHub Tutorial for Scientist: It's Not Only for Programmers](https://gitbookdown.dallasdatascience.com/) + +[Ten Simple Rules for Taking Advantage of Git and GitHub](https://pmc.ncbi.nlm.nih.gov/articles/PMC4945047/) + +[A brief introduction to Git for beginers](https://youtu.be/r8jQ9hVA2qs?si=IYe7JghJpVTz9Ht4) + +[How to Use GitHub for Beginners](https://youtu.be/a9u2yZvsqHA?si=lbKBogzjEZ1YehpQ) + + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_GitHub/slides.qmd b/course/00_GitHub/slides.qmd index 914fdf1..11561e1 100644 --- a/course/00_GitHub/slides.qmd +++ b/course/00_GitHub/slides.qmd @@ -1,594 +1,594 @@ ---- -title: "Using GitHub" -author: "David Rach" -date: 02-01-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -# Background - -::: {.fragment} -::: {.callout-tip title="."} - -When working with code, it is very important to stay organized. You ultimately want to avoid being in a scenario where you need some code you wrote the previous month, and then having to search through multiple .R files, scattered across multiple folders, external hard-drives, and computers to find it. Likewise, you want to avoid ending up having identified multiple similarly-named copies of your original file that have all since diverged slightly from each other in some way that you have long since forgotten. - -::: -::: - ---- - -![](https://phdcomics.com/comics/archive/phd101212s.gif){width=50%} - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Ideally, everything needed for your coding script to successfully run should be kept within a project-specific folder. This ensures, that should you transfer it to another computer (whether your own or a colleagues) that you would still be able to recreate the scripts output. - -Likewise, if you make changes to your script, and your code stops working (no longer returns the expected output, ie. breaks), having a record of what changes were made since the last working version would be very helpful in pinpointing what went wrong. For beginners, this often ends up being a typo in a function name, or an accidentally misplaced comma somewhere in your document. - -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} - -For these reasons, in this course, we will be extensively using the version control software [Git](https://git-scm.com/) from the very beginning. We will also have you create a [GitHub](https://github.com/) account, which will allow you to back-up your coding projects online as private repositories. Not only is this useful in case something happens to your computer, but it allows you to switch between separate computers while still having ready access to all your code, avoiding ending up with divergent copies on each computer. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Additionally, since all the material for this course is being hosted on a public GitHub repository, once you have set up your GitHub account you will be able to retrieve all the new materials and changes by simply refreshing (ie. syncing) your version of the course folder (ie. fork) once a week. Your GitHub account will also be needed when posting or asking questions on the [Discussion Forum](https://github.com/UMGCCCFCSR/CytometryInR/discussions). - -In this walk-through, we will go through setting up a GitHub account, and make sure you are familiar with some of the elements and locations that we will be circling back to throughout the course. - -::: -::: - ---- - -![](/images/Placeholder.png) - ---- - -# Getting Started - - -## Creating an Account - -::: {.fragment} -::: {.callout-tip title="."} -We will first navigate to the [GitHub homepage](). If you haven't previously created an account, click on the button to sign up for an account. -::: -::: - ---- - -![](images/01_GitHub.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -On the sign-up page, you will fill in various details needed to create an account. Please remember that GitHub usernames are visible to others. Additionally, if you end up sharing code with others as part of a manuscript, or use GitHub to create a personal portfolio website in the future, your username will appear as part of the URL. - -For example, in my case, my user name is DavidRach, so my GitHub profile ends up as: [https://github.com/DavidRach](https://github.com/DavidRach). For our course, the core's GitHub user name is UMGCCCFCSR, so the github profile ends up as [https://github.com/UMGCCCFCSR](https://github.com/UMGCCCFCSR), while the course website ends up as [https://umgcccfcsr.github.io/CytometryInR/](https://umgcccfcsr.github.io/CytometryInR/) -::: -::: - ---- - -![](images/02_GithubSignup.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once you have entered your new account information, you will need your account creation by entering the code sent to the email address that you provided. -::: -::: ---- - -![](images/03_Github2Factor.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once account creation has been confirmed, please proceed to login to GitHub for the first time. -::: -::: ---- - -![](images/04_Login.png) - ---- - -## GitHub Profile - -::: {.fragment} -::: {.callout-tip title="."} -Upon creating a brand new account, your GitHub homepage will initially look rather empty, and can be intimidating to navigate for the first time. - -For now, on the upper right, go ahead and click on the default profile picture icon... -::: -::: ---- - -![](images/05_YourIcon.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And then select Profile... -::: -::: ---- - -![](images/05_Profile.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You are now on your public GitHub profile page. For a newly created account, it will look something like this: -::: -::: ---- - -![](images/06_EditIcon.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For a more established account, this page will look a [little different](https://github.com/DrCytometer), and can be customized to highlight various projects that you are working on. - -For this course, we will have you set up a basic GitHub profile page for now, although you are free to customize and personalize it as much as you may want to in the future! - -To start, first select the edit profile button on the left below the default profile icon. -::: -::: ---- - -![](images/06_EditIcon.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You can then proceed to fill in any details that you feel are relevant and are comfortable sharing. -::: -::: ---- - -![](images/07_Basics.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -With the quick access details filled in, it is now time to navigate to the Settings tab. You will return to the previous menu dropdown on the upper right, and instead of selecting Profile, click on the Settings option. -::: -::: ---- - -![](images/05_Profile.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You should now end up within your Public Profile Settings page. - -Feel free to edit the default profile picture, and any other fields that you feel are relevant. Once done, continue to scroll down the page past ORCID ID. -::: -::: ---- - -![](images/08_ProfileSetup.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When you reach Contributions and Activity, go ahead and select the option to include private repositories in the activity summary graphic. Then scroll down and click save. You will now be returned to your GitHub profile page. -::: -::: ---- - -![](images/09_SelectThisOneSuggested.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -At the top of the profile, you will see a "Your contributions" calendar graph. For a new account, it will look like this: -::: -::: ---- - -![](images/10_UpdatedGitHubProfile.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If you are just starting out, this chart will be mostly empty, but will fill in as you work on projects, see [here](https://github.com/cararthompson) as an example. - -Every time you save your code (ie. make a commit), the activity will be reflected in this chart. By clicking the option in settings, code made within a private repository will remain private, but will count toward your contribution chart. As you progress through the course, this will provide a nice visual reminder of the progress you have made, and the obstacles that you have overcome. -::: -::: ---- - -![](images/10_UpdatedGitHubProfile.png) - ---- - -## GitHub ReadMe - -::: {.fragment} -::: {.callout-tip title="."} - -With this done, we modify your GitHub profile by adding one customized element, a ReadMe page. This will be used for a couple projects during the course, and can be personalized further in the future. - -To create a ReadMe page for your profile, we will navigate to the upper right of the screen and click on the + sign. - -::: -::: - ---- - -![](images/11_UpdatedGitHubProfile2.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -We will then select the Create New Repository option. - -::: -::: ---- - -![](images/12_NewRepository.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -You will next create a repository (folder), naming it exactly the same as your username. This will be recognized by GitHub as being a special type of repository corresponding to the ReadMe section of your profile. - -For options, leave the visibility as Public, and Add README set to On. And proceed to Create Repository. - -::: -::: ---- - -![](images/13_ReadMe.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Having created the repository (folder), you will see it has been populated by a few default files. For now, you will be editing the README.md file. On a new repository, the easiest way to access it is by clicking the green option on the right side of your screen. - -::: -::: ---- - -![](images/14_EditButton.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -With the README.md file now opened, you will be able to see generic filler text that is suggested by GitHub. - -For this course, I will ask you to add a couple elements for now. You are free to return and further personalize it later if you wish to do so. - -::: -::: ---- - -![](images/15_DefaultText.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -The type of file that we are working with is a [Markdown](https://www.markdownguide.org/basic-syntax/) file, which can allow for a bunch of customizations which we will cover throughout the course. - -For now, please add and customize the following questions: - -Cytometry In R - -Location: Baltimore, Maryland, USA - -My Favorite Fluorophore/Metal-Isotope: Spark Blue 550 - -Previous Coding Experience: Repeatedly Calling IT - -What I Hope to Get From This Course: A faster way to match FlowSOM clusters to their likely cell type. - -::: -::: ---- - -![](images/16_ReadMeContent.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Next, to save you will select the green "Commit changes" button. We will cover the meaning of "Commit" more in-depth during the [Git](/course/00_Git/index.qmd) section. - -For now, write a short summary of the change you made to the file in the "Commit message", and any additional details within the "Extended description" field. When ready, click the green "Commit changes" button. - -::: -::: ---- - -![](images/17_ReadMeCommit.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -You will now be able to see the updated README.md file, as you can see in our example below. To make additional edits, you would select the pencil icon on the right-center side of the screen. - -::: -::: ---- - -![](images/18_ReadMeRendered.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Next, navigate back to your profile page (by clicking on either your username or the Overview option on the tabs). - -You will see that the README file contents are now displayed on the upper portion of your GitHub profile. Feel free to circle back and customize this further to your liking. - -In this last example, we created your first repository (folder). Since this is public, it is now shown below the README section of the profile under your repositories. You can also see that your commits made in the process of making the changes are now shown both in the Contributions graph, and under the Contributor Activity summary at the bottom of the page. - -::: -::: ---- - -![](images/19_UpdatedProfile.png) - ---- - -## GitHub Repository - -::: {.fragment} -::: {.callout-tip title="."} - -Having set up your GitHub profile, it now is time to make sure you have access to our course materials. We will have you navigate to our course's [GitHub profile](https://github.com/UMGCCCFCSR) - -On the profile page, you will be able to see our version of the README, our repositories, and the Contributions graph and Contribution activity sections. - -Please click on the [CytometryInR](https://github.com/UMGCCCFCSR/CytometryInR) to navigate to its repository (folder) - -::: -::: ---- - -![](images/20_ToCourseProfile.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -On this page, you will see several elements that you will be circling back to throughout the course. - -For our course, we will be extentsively ussing the [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page as a community forum. If you have any questions, are looking for feedback, or want to show off something that you worked on, this is the place for it. This will also help make sure - -::: -::: ---- - -![](images/21_Discussions.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -The [Issues](https://github.com/UMGCCCFCSR/CytometryInR/issues) tab is where you will need to go to open an Issue if you encounter a bug (or major documentation typo), so that I can cicle back and correct them when I have the chance. - -::: -::: ---- - -![](images/21_BugReports.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To submit the optional take-home problems, you would turn in these problems by going to the [Pull Request](https://github.com/UMGCCCFCSR/CytometryInR/pulls) tab, and initiating a pull request between your forked version of the project and our "homework" branch (more details on this later). - -::: -::: ---- - -![](images/21_HomeworkPullRequest.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Optionally, you can "Star" a repository. This is basically the GitHub equivalent of liking a project. In our case, we will often star a repository since it will be saved under the Stars tab of our profile, which makes finding it again significantly easier a few weeks later after forgetting the repository name. - -::: -::: ---- - -![](images/21_Stars.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To see projects that you have starred, you can select the Stars option from the same dropdown you used to get to Settings. - -::: -::: ---- - -![](images/22_Stars.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Or from your GitHub profile, you can see these under [Stars](https://github.com/DavidRach?tab=stars) tab. - -::: -::: ---- - -![](images/22_YourStarredRepositories.png) - ---- - - -## Forking CytometryInR - -::: {.fragment} -::: {.callout-tip title="."} - -Before we go further, we will need you to make your own copy of the [course repository](https://github.com/UMGCCCFCSR/CytometryInR/) (ie. fork it). This will allow you to quickly retrieve all the new materials and code corrections by simply rereshing (ie. syncing) your forked version with our upstream parent branch once a week. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To fork the [course repository](https://github.com/UMGCCCFCSR/CytometryInR/), you will select the "Fork repository" option on the upper-center portion of your screen. - -::: -::: ---- - -![](images/23_ForkIt.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -By "Fork-ing" a repository, you are basically copying the contents from that repository to a newly created repository on your own GitHub. Forked projects are still linked to the original (parent) fork, and can retrieve any updates via syncing, as well as return changes via a pull request. - -For this course, when you create the fork, keep the existing repository name ("CytometryInR"). Importantly, select the copy main branch option. This will ensure you only get the code and data needed for the course copied over, and don't end up with your entire hard-drive filled will website elements, or other people's solutions to the take-home problems. - -::: -::: ---- - -![](images/24_ForkMainBranch.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Once you have created the fork, you will see your copy of the forked repository under your own username. Seeing as you have just now forked the project, you will see the notification that you are up to date with the existing version of the CytometryInR course repository. - -As we go through the course, and new material is released each week on Sunday at 2200 EST (Monday 0300 GMT+0), you will see this changed to behind the main branch by a number of commits, and have the option to sync in the changes to your fork to gain access to that week's material. - -::: -::: ---- - -![](images/25_YourForkedBranch.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If you remember, previously under your GitHub profile, the Repositories tab only contained the repository corresponding to your ReadMe section. -::: -::: ---- - -![](images/YourRepositories.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You should however now be able to see your fork of the CytometryInR repository. As you add project specific repositories throughout the course, they will also appear here. -::: -::: ---- - -![](images/YourUpdatedRepos.png) - ---- - -# Wrap-Up - -::: {.fragment} -::: {.callout-tip title="."} -We have now completed our walk-through of setting up a GitHub account. At this point, you should have modified your GitHub profile, added a README section, and most importantly, forked the [CytometryInR](https://github.com/UMGCCCFCSR/CytometryInR/) repository so that you can easily retrieve the new course materials each week. - -Next up, we will have you proceed to installing the required software to your computer that will be needed throughout the course. Installation instructions will vary depending on your computer's operating system, so please follow the appropiate walkthrough. -::: -::: - -# Additional Resources - -[Git & GitHub Tutorial for Scientist: It's Not Only for Programmers](https://gitbookdown.dallasdatascience.com/) - -[Ten Simple Rules for Taking Advantage of Git and GitHub](https://pmc.ncbi.nlm.nih.gov/articles/PMC4945047/) - -[A brief introduction to Git for beginers](https://youtu.be/r8jQ9hVA2qs?si=IYe7JghJpVTz9Ht4) - -[How to Use GitHub for Beginners](https://youtu.be/a9u2yZvsqHA?si=lbKBogzjEZ1YehpQ) - - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Using GitHub" +author: "David Rach" +date: 02-01-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +# Background + +::: {.fragment} +::: {.callout-tip title="."} + +When working with code, it is very important to stay organized. You ultimately want to avoid being in a scenario where you need some code you wrote the previous month, and then having to search through multiple .R files, scattered across multiple folders, external hard-drives, and computers to find it. Likewise, you want to avoid ending up having identified multiple similarly-named copies of your original file that have all since diverged slightly from each other in some way that you have long since forgotten. + +::: +::: + +--- + +![](https://phdcomics.com/comics/archive/phd101212s.gif){width=50%} + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Ideally, everything needed for your coding script to successfully run should be kept within a project-specific folder. This ensures, that should you transfer it to another computer (whether your own or a colleagues) that you would still be able to recreate the scripts output. + +Likewise, if you make changes to your script, and your code stops working (no longer returns the expected output, ie. breaks), having a record of what changes were made since the last working version would be very helpful in pinpointing what went wrong. For beginners, this often ends up being a typo in a function name, or an accidentally misplaced comma somewhere in your document. + +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} + +For these reasons, in this course, we will be extensively using the version control software [Git](https://git-scm.com/) from the very beginning. We will also have you create a [GitHub](https://github.com/) account, which will allow you to back-up your coding projects online as private repositories. Not only is this useful in case something happens to your computer, but it allows you to switch between separate computers while still having ready access to all your code, avoiding ending up with divergent copies on each computer. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Additionally, since all the material for this course is being hosted on a public GitHub repository, once you have set up your GitHub account you will be able to retrieve all the new materials and changes by simply refreshing (ie. syncing) your version of the course folder (ie. fork) once a week. Your GitHub account will also be needed when posting or asking questions on the [Discussion Forum](https://github.com/UMGCCCFCSR/CytometryInR/discussions). + +In this walk-through, we will go through setting up a GitHub account, and make sure you are familiar with some of the elements and locations that we will be circling back to throughout the course. + +::: +::: + +--- + +![](/images/Placeholder.png) + +--- + +# Getting Started + + +## Creating an Account + +::: {.fragment} +::: {.callout-tip title="."} +We will first navigate to the [GitHub homepage](). If you haven't previously created an account, click on the button to sign up for an account. +::: +::: + +--- + +![](images/01_GitHub.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +On the sign-up page, you will fill in various details needed to create an account. Please remember that GitHub usernames are visible to others. Additionally, if you end up sharing code with others as part of a manuscript, or use GitHub to create a personal portfolio website in the future, your username will appear as part of the URL. + +For example, in my case, my user name is DavidRach, so my GitHub profile ends up as: [https://github.com/DavidRach](https://github.com/DavidRach). For our course, the core's GitHub user name is UMGCCCFCSR, so the github profile ends up as [https://github.com/UMGCCCFCSR](https://github.com/UMGCCCFCSR), while the course website ends up as [https://umgcccfcsr.github.io/CytometryInR/](https://umgcccfcsr.github.io/CytometryInR/) +::: +::: + +--- + +![](images/02_GithubSignup.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once you have entered your new account information, you will need your account creation by entering the code sent to the email address that you provided. +::: +::: +--- + +![](images/03_Github2Factor.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once account creation has been confirmed, please proceed to login to GitHub for the first time. +::: +::: +--- + +![](images/04_Login.png) + +--- + +## GitHub Profile + +::: {.fragment} +::: {.callout-tip title="."} +Upon creating a brand new account, your GitHub homepage will initially look rather empty, and can be intimidating to navigate for the first time. + +For now, on the upper right, go ahead and click on the default profile picture icon... +::: +::: +--- + +![](images/05_YourIcon.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And then select Profile... +::: +::: +--- + +![](images/05_Profile.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You are now on your public GitHub profile page. For a newly created account, it will look something like this: +::: +::: +--- + +![](images/06_EditIcon.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For a more established account, this page will look a [little different](https://github.com/DrCytometer), and can be customized to highlight various projects that you are working on. + +For this course, we will have you set up a basic GitHub profile page for now, although you are free to customize and personalize it as much as you may want to in the future! + +To start, first select the edit profile button on the left below the default profile icon. +::: +::: +--- + +![](images/06_EditIcon.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You can then proceed to fill in any details that you feel are relevant and are comfortable sharing. +::: +::: +--- + +![](images/07_Basics.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +With the quick access details filled in, it is now time to navigate to the Settings tab. You will return to the previous menu dropdown on the upper right, and instead of selecting Profile, click on the Settings option. +::: +::: +--- + +![](images/05_Profile.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You should now end up within your Public Profile Settings page. + +Feel free to edit the default profile picture, and any other fields that you feel are relevant. Once done, continue to scroll down the page past ORCID ID. +::: +::: +--- + +![](images/08_ProfileSetup.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When you reach Contributions and Activity, go ahead and select the option to include private repositories in the activity summary graphic. Then scroll down and click save. You will now be returned to your GitHub profile page. +::: +::: +--- + +![](images/09_SelectThisOneSuggested.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +At the top of the profile, you will see a "Your contributions" calendar graph. For a new account, it will look like this: +::: +::: +--- + +![](images/10_UpdatedGitHubProfile.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If you are just starting out, this chart will be mostly empty, but will fill in as you work on projects, see [here](https://github.com/cararthompson) as an example. + +Every time you save your code (ie. make a commit), the activity will be reflected in this chart. By clicking the option in settings, code made within a private repository will remain private, but will count toward your contribution chart. As you progress through the course, this will provide a nice visual reminder of the progress you have made, and the obstacles that you have overcome. +::: +::: +--- + +![](images/10_UpdatedGitHubProfile.png) + +--- + +## GitHub ReadMe + +::: {.fragment} +::: {.callout-tip title="."} + +With this done, we modify your GitHub profile by adding one customized element, a ReadMe page. This will be used for a couple projects during the course, and can be personalized further in the future. + +To create a ReadMe page for your profile, we will navigate to the upper right of the screen and click on the + sign. + +::: +::: + +--- + +![](images/11_UpdatedGitHubProfile2.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +We will then select the Create New Repository option. + +::: +::: +--- + +![](images/12_NewRepository.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +You will next create a repository (folder), naming it exactly the same as your username. This will be recognized by GitHub as being a special type of repository corresponding to the ReadMe section of your profile. + +For options, leave the visibility as Public, and Add README set to On. And proceed to Create Repository. + +::: +::: +--- + +![](images/13_ReadMe.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Having created the repository (folder), you will see it has been populated by a few default files. For now, you will be editing the README.md file. On a new repository, the easiest way to access it is by clicking the green option on the right side of your screen. + +::: +::: +--- + +![](images/14_EditButton.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +With the README.md file now opened, you will be able to see generic filler text that is suggested by GitHub. + +For this course, I will ask you to add a couple elements for now. You are free to return and further personalize it later if you wish to do so. + +::: +::: +--- + +![](images/15_DefaultText.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +The type of file that we are working with is a [Markdown](https://www.markdownguide.org/basic-syntax/) file, which can allow for a bunch of customizations which we will cover throughout the course. + +For now, please add and customize the following questions: + +Cytometry In R + +Location: Baltimore, Maryland, USA + +My Favorite Fluorophore/Metal-Isotope: Spark Blue 550 + +Previous Coding Experience: Repeatedly Calling IT + +What I Hope to Get From This Course: A faster way to match FlowSOM clusters to their likely cell type. + +::: +::: +--- + +![](images/16_ReadMeContent.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Next, to save you will select the green "Commit changes" button. We will cover the meaning of "Commit" more in-depth during the [Git](/course/00_Git/index.qmd) section. + +For now, write a short summary of the change you made to the file in the "Commit message", and any additional details within the "Extended description" field. When ready, click the green "Commit changes" button. + +::: +::: +--- + +![](images/17_ReadMeCommit.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +You will now be able to see the updated README.md file, as you can see in our example below. To make additional edits, you would select the pencil icon on the right-center side of the screen. + +::: +::: +--- + +![](images/18_ReadMeRendered.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Next, navigate back to your profile page (by clicking on either your username or the Overview option on the tabs). + +You will see that the README file contents are now displayed on the upper portion of your GitHub profile. Feel free to circle back and customize this further to your liking. + +In this last example, we created your first repository (folder). Since this is public, it is now shown below the README section of the profile under your repositories. You can also see that your commits made in the process of making the changes are now shown both in the Contributions graph, and under the Contributor Activity summary at the bottom of the page. + +::: +::: +--- + +![](images/19_UpdatedProfile.png) + +--- + +## GitHub Repository + +::: {.fragment} +::: {.callout-tip title="."} + +Having set up your GitHub profile, it now is time to make sure you have access to our course materials. We will have you navigate to our course's [GitHub profile](https://github.com/UMGCCCFCSR) + +On the profile page, you will be able to see our version of the README, our repositories, and the Contributions graph and Contribution activity sections. + +Please click on the [CytometryInR](https://github.com/UMGCCCFCSR/CytometryInR) to navigate to its repository (folder) + +::: +::: +--- + +![](images/20_ToCourseProfile.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +On this page, you will see several elements that you will be circling back to throughout the course. + +For our course, we will be extentsively ussing the [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page as a community forum. If you have any questions, are looking for feedback, or want to show off something that you worked on, this is the place for it. This will also help make sure + +::: +::: +--- + +![](images/21_Discussions.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +The [Issues](https://github.com/UMGCCCFCSR/CytometryInR/issues) tab is where you will need to go to open an Issue if you encounter a bug (or major documentation typo), so that I can cicle back and correct them when I have the chance. + +::: +::: +--- + +![](images/21_BugReports.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To submit the optional take-home problems, you would turn in these problems by going to the [Pull Request](https://github.com/UMGCCCFCSR/CytometryInR/pulls) tab, and initiating a pull request between your forked version of the project and our "homework" branch (more details on this later). + +::: +::: +--- + +![](images/21_HomeworkPullRequest.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Optionally, you can "Star" a repository. This is basically the GitHub equivalent of liking a project. In our case, we will often star a repository since it will be saved under the Stars tab of our profile, which makes finding it again significantly easier a few weeks later after forgetting the repository name. + +::: +::: +--- + +![](images/21_Stars.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To see projects that you have starred, you can select the Stars option from the same dropdown you used to get to Settings. + +::: +::: +--- + +![](images/22_Stars.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Or from your GitHub profile, you can see these under [Stars](https://github.com/DavidRach?tab=stars) tab. + +::: +::: +--- + +![](images/22_YourStarredRepositories.png) + +--- + + +## Forking CytometryInR + +::: {.fragment} +::: {.callout-tip title="."} + +Before we go further, we will need you to make your own copy of the [course repository](https://github.com/UMGCCCFCSR/CytometryInR/) (ie. fork it). This will allow you to quickly retrieve all the new materials and code corrections by simply rereshing (ie. syncing) your forked version with our upstream parent branch once a week. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To fork the [course repository](https://github.com/UMGCCCFCSR/CytometryInR/), you will select the "Fork repository" option on the upper-center portion of your screen. + +::: +::: +--- + +![](images/23_ForkIt.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +By "Fork-ing" a repository, you are basically copying the contents from that repository to a newly created repository on your own GitHub. Forked projects are still linked to the original (parent) fork, and can retrieve any updates via syncing, as well as return changes via a pull request. + +For this course, when you create the fork, keep the existing repository name ("CytometryInR"). Importantly, select the copy main branch option. This will ensure you only get the code and data needed for the course copied over, and don't end up with your entire hard-drive filled will website elements, or other people's solutions to the take-home problems. + +::: +::: +--- + +![](images/24_ForkMainBranch.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Once you have created the fork, you will see your copy of the forked repository under your own username. Seeing as you have just now forked the project, you will see the notification that you are up to date with the existing version of the CytometryInR course repository. + +As we go through the course, and new material is released each week on Sunday at 2200 EST (Monday 0300 GMT+0), you will see this changed to behind the main branch by a number of commits, and have the option to sync in the changes to your fork to gain access to that week's material. + +::: +::: +--- + +![](images/25_YourForkedBranch.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If you remember, previously under your GitHub profile, the Repositories tab only contained the repository corresponding to your ReadMe section. +::: +::: +--- + +![](images/YourRepositories.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You should however now be able to see your fork of the CytometryInR repository. As you add project specific repositories throughout the course, they will also appear here. +::: +::: +--- + +![](images/YourUpdatedRepos.png) + +--- + +# Wrap-Up + +::: {.fragment} +::: {.callout-tip title="."} +We have now completed our walk-through of setting up a GitHub account. At this point, you should have modified your GitHub profile, added a README section, and most importantly, forked the [CytometryInR](https://github.com/UMGCCCFCSR/CytometryInR/) repository so that you can easily retrieve the new course materials each week. + +Next up, we will have you proceed to installing the required software to your computer that will be needed throughout the course. Installation instructions will vary depending on your computer's operating system, so please follow the appropiate walkthrough. +::: +::: + +# Additional Resources + +[Git & GitHub Tutorial for Scientist: It's Not Only for Programmers](https://gitbookdown.dallasdatascience.com/) + +[Ten Simple Rules for Taking Advantage of Git and GitHub](https://pmc.ncbi.nlm.nih.gov/articles/PMC4945047/) + +[A brief introduction to Git for beginers](https://youtu.be/r8jQ9hVA2qs?si=IYe7JghJpVTz9Ht4) + +[How to Use GitHub for Beginners](https://youtu.be/a9u2yZvsqHA?si=lbKBogzjEZ1YehpQ) + + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_Homeworks/index.qmd b/course/00_Homeworks/index.qmd index 4dae069..f017577 100644 --- a/course/00_Homeworks/index.qmd +++ b/course/00_Homeworks/index.qmd @@ -1,3 +1,405 @@ +<<<<<<< HEAD +--- +title: "Getting Help" +author: "David Rach" +date: 01-21-2026 +format: html +toc: true +toc-depth: 4 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://www.youtube.com/live/QFaYpckzTEs?si=m9zEO9nPk6dvOL08) + + + +For screen-shot slides, click [here](/course/00_Homeworks/slides.qmd) + + +# Background + +In the previous sections, we set up our [GitHub](/course/00_GitHub/index.qmd) account, installed the required [software](/course/00_WorkstationSetup/index.qmd), and further explored various elements of [Positron](/course/00_Positron/index.qmd), [Git](/course/00_Git/index.qmd) and [Quarto](/course/00_Quarto/index.qmd) that we will be using throughout the course. + +This is our first year offering the course. Although we can and will answer questions during the livestreams, given the number of people signed up that might have a question, we want to make sure to provide multiple avenues by which you can get help and feedback throughout. These include the [Discussions Forum](https://github.com/UMGCCCFCSR/CytometryInR/discussions), where you can ask questions, discuss topics, get feedback and celebrate wins; and 2) turning in optional take-home problems via a pull request, in which the course instructors will take a look and provide additional feedback. + +In this walk-through, we go over how to use these resources. + +
+ +--- + +# Getting Started + + +## Discussions Forum + +On the course's [GitHub repository](https://github.com/UMGCCCFCSR/CytometryInR), we have opened up a [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page that we plan to use as a community forum. We hope that it will serve multiple functions, from providing a better sense of community for the online participants, to facilitating asking and receiving help on something that is not clear, provide feedback about something that it not working out, as well as a place to celebrate and show off your coding wins. + +![](images/Discussion.png) + +To keep the Discussions forum semi-organized, we have set up several categories, please select the appropiate category when opening a new discussion! + +
+ +--- + +### Code of Conduct + +![](images/CodeOfConduct.png) + +We ask that all course participants read and adhere to the spirit of our [Code of Conduct](https://github.com/UMGCCCFCSR/CytometryInR?tab=coc-ov-file). We are all human, at different points in our learning journeys, so what may be obvious to you at your point of your learning journey may have necessarily be obvious to someone just getting started. This course is our giving back to those in the community, but is on a voluntary basis in addition to our regular workload. While we try to reply quickly, sometimes our cell sorters fully melt down sending everything into chaos. We will reply when we can. + +
+ +--- + +### Announcements + +![](images/Announcements.png) + +When we send out an email to all participants, we will also repost it as an announcement. This ensures that even if you are not on our mailing list, you will still be able to have access to important information and course updates. + +
+ +--- + +![](images/000_Announcements.png) + +
+ +--- + +### General + +![](images/General.png) + +This section category can be used for any discussions that you think are worth having, that don't fall under any of the other category. Good examples are continuing a discussion that was held during one of the livestreams; wanting to discuss and dive further into a given week's topic; or bringing in additional resources that you found useful to understandingn something that didn't click initially. This space is for the community to shape as they see best. + + +
+ +--- + +![](images/000_General.png) + +
+ +--- + +### Ideas + +![](images/Ideas.png) + +Have an idea for a new topic or a way to improve the course? We would love to hear them. Provide as many details, and ideally, an example, and if it is doable, we will try to implement them. + +
+ +--- + +![](images/000_Ideas.png) + +
+ +--- + +### Introductions + +![](images/Introductions.png) + +Online courses can be odd in terms of replicating in-person dynamics. Fortunately, we have gathered the largest cohort of "cytometrist with no-to-little flow experience trying to learn R at the same time" that the world has ever seen, so best to take advantage of this while we can. Treat this section as if we had just met at a conference, tell us about yourself, what brings you here, and what you want to hopefully be able to do after the course ends. + +
+ +--- + +![](images/000_Introductions.png) + +
+ +--- + +## Polls + +![](images/Polls.png) + +Occasionally, we will need to gather community feedback on what is working and what is not working. We will sporadically post Polls for this purpose. + +
+ +--- + +![](images/000_Polls.png) + +
+ +--- + +### Q&A + +![](images/Q&A.png) + +The Questions and Answers (Q&A) section is where you go if something is not clear, not working, and you are trying to troubleshoot your way through it. First thing before posting, search! to see if someone has already asked the question. If you don't find anything, go ahead and open a new discussion. + +Since we are not at your computer, and don't have your dataset, when troubleshooting it is best to include a minimal reproducible example of the issuen you are encountering, slimming down the number of files needed to be transferred, and generalizing down the code so that other course participants and instructors can follow along. If this is not doable, or if the problem requires added context (and larger files), create a new repository on your GitHub, make it public, and share the links to it in your post. The goal would be to download the folder and be able to replicate the issue that you are encountering. + +
+ +--- + +![](images/000_QandA.png) + +
+ +--- + +![](images/000_QandAExample.png) + +
+ +--- + +### Show and Tell + +![](images/ShowAndTell.png) + +Where Q&A section is for getting help on code that is frustratingly not working, Show and Tell is where to go and celebrate when you finally get things to work. Share your wins, show us the extra pretty graphs, bizarre autofluorescence signatures, or odd outputs that just make you laugh. + +
+ +--- + +![](images/000_ShowAndTell.png) + +
+ +--- + +![](images/Timeline.png) + +
+ +--- + +## Issues + +Most of the time, if you are having trouble getting you code to run, you should first stop after some initial troubleshooting should be to open a new [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) under the Q&A category. Here you will be able to get both community and instructor help and suggestions to hopefully resolve whatever is going on. + +![](images/Issues.png) + +The Issues page is primarily meant for course-specific problems that require the course instructor intervention to fix. For example, we release a new week of material, and while it runs fine for both Windows and Linux, the code fails to run for all MacOS users. While you may be able to find workarounds on your own, it's ultimately our responsibility to help provide a solution so that everyone can move forward. This is the situation where opening an Issue is appropiate. + +
+ +--- + +![](images/000_IssuesExample.png) + + +Similarly, if our code contains a wrong argument, is returning a deprecation warning, etc. open an issue to let us know. While we may not be able to fix something that is not directly related to our code, we can redirect it to the package maintainers so that they can fix the issue. + +And likewise, if you find multiple typos in the documentation, you can open an issue and propose carrying out a pull-request to fix them. + + +
+ +--- + +## Submitting Take-Home Problems + +Each week, during the course, we introduce and cover the main concepts for the particular concept. Our goal is to provide you with the necessary code and enough code to be able to get the jist. However, to become comfortable and be able to apply what you have learned, you will need to explore beyond our examples, try it with your own datasets, encounter things that don't work, and troubleshoot your way through them. It's this cycle of venturing into the unknown that develops strong coding skills that are needed to overcome any barrier you encounter. The goal of the take-home questions is to provide some less curated problems that will take a little longer to answer to help get you started on your own exploration of the topic. + +As previously mentioned, these take-home problems are completely **optional**. If you are in the middle of solving them and want to seek feedback from then community and course instructors, open a [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) under the general category is the way to go. + +However, if you have completed them, and want course instructor feedback, you can submit them to us in the form of a pull-request to the CytometryInR repo's homework branch. We will take a look, offer constructive suggestions, and when ready merge the solution. This will also result in GitHub listing you as a contributor to the course. + +We will outline the basic steps of how to set up and open a pull-request, to help simplify the process. + +### Sync your Fork + +First off, make sure to Sync your fork of the Cytometry in R project. That makes sure that all the commits present are up-to-date and simplifies the process of having the pull-request being merged. + + +![](images/00_Sync.png) + +
+ +--- + +![](images/00_Compare.png) + +
+ +--- + +![](images/02_Synced.png) + +
+ +--- + +### Pull to Local + +Having Synced your branch on GitHub, return to your computer, open the CytometryInR repository and [pull](/course/00_Git/index.qmd#pull) in the changes locally. + +
+ +--- + +### Create own Folder under Homeworks + +Under the course folder, you will find folders for each week. Within these folders find the homework folder. This will appear empty except for a README file with ionstructions. It is within this folder you will need to create your own folder. + +To ensure there are no conflicts on the pull-request merge, please use your GitHub username as the folder name. + +![](images/09_Homework.png) + +
+ +--- + +Once you have your folder inside homework, go ahead and copy anything you are turning in from their respective working project folders. Remember, the goal is minimal reproducible example is the goal. Rendered Quarto Documents are preferred, but we will also accept scripts and small data files and images. a README.MD file with anything you want me to know, + +![](images/10_TakeHomeReturnStructure.png) + +
+ +--- + + +![](images/11_SelfContained.png) + + +
+ +--- + +### Sign off Commit + +Now that everything is present, Sign Off and Commit the change. + +![](images/12_Commit.png) + +
+ +--- + +### Push Branch to GitHub. + +Proceed to push the branch to GitHub. + +![](images/13_Sync.png) + +
+ +--- + +# Re-sync if necessary + +If additional changes have occured to the parent CytometryInR repository, go ahead and update your branch. As long as your edits occurred within your folder inside homework folders, they should still be able to merge. + +![](images/17_SyncMaybe.png) + +
+ +--- + +![](images/18_Update.png) + +
+ +--- + +### Open a pull-request + +To start a pull request, click to see how your commit is ahead by + +![](images/14_Ahead.png) + +
+ +--- + +Next, switch from the parent CytometryInR main branch (used for the website and course) to the homework branch for that respective week (used for the take-home problems). + +![](images/15_BranchSwitch.png) + +
+ +--- + +Once this is done, select Pull request + +![](images/16_PullRequest.png) + +
+ +--- + +Make sure to triple check it's bound for the homeworks branch. If you see that it is not capable of merging, verify that your commit only contains files within your respective homework username folder. Fill in the required fields of the pull request. + +![](images/20_PullRequestHomeworks.png) + +
+ +--- + +And when ready, create the pull request. + +
+ +--- + +### Wait for Feedback + +On our end, once you have created a pull request, we will review your work, offer constructive suggestions, etc. If I ask for revisions, all you would need to do is update your files, commit again on your side of the local forked repository. + +![](images/22_StartReviewProcess.png) + +
+ +--- + +### Final Review and Merge + +If all is good, we will merge the pull request and your solution to the take-home problems will now be available on the homework branch. + +![](images/23_Merge.png) + +
+ +--- + +### After course + +After the course completes, we will merge homework branch with the main branch, making the community solutions to the take-home problems additional coding examples that can be used by others following along after the course concludes. + +
+ +--- + +# Wrap-up + +In this walk-through, we covered the [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) Forum, mentioned appropiate use cases for the [Issues](https://github.com/UMGCCCFCSR/CytometryInR/issues) page and provided the logistics of how to submit take-home problems as a pull request to the homework branch. We have now covered all the major elements that you will be using throughout the course. + +The next couple sections cover our thoughts [on AI use]() in a course for coding beginners, and an optional walkthrough of how to use [Floreada](/course/00_Floreada/index.qmd) in preparation for some topics starting around Week 5. + + +# Additional Resources + +[Create a Home for Your Community With GitHub Discussions](https://github.blog/open-source/maintainers/create-a-home-for-your-community-with-github-discussions/) + +[GitHub for Beginners: How to create a pull request in 4 minutes](https://youtu.be/nCKdihvneS0?si=PaM7QmylZiGfU9v4) + +[Five tips for Reviewing a GitHub pull request](https://www.youtube.com/watch?v=nP9Y72HQNaA) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +======= --- title: "Getting Help" author: "David Rach" @@ -398,4 +800,5 @@ The next couple sections cover our thoughts [on AI use]() in a course for coding ::: {style="text-align: right;"} [![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +>>>>>>> 23a81a59a64966e782d820f6b60f087d577c3b25 ::: \ No newline at end of file diff --git a/course/00_Homeworks/slides.qmd b/course/00_Homeworks/slides.qmd index 22e913b..231d3a8 100644 --- a/course/00_Homeworks/slides.qmd +++ b/course/00_Homeworks/slides.qmd @@ -1,539 +1,539 @@ ---- -title: "Getting Help" -author: "David Rach" -date: 02-01-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - ---- - -# Background - -::: {.fragment} -::: {.callout-tip title="."} -In the previous sections, we set up our [GitHub](/course/00_GitHub/index.qmd) account, installed the required [software](/course/00_WorkstationSetup/index.qmd), and further explored various elements of [Positron](/course/00_Positron/index.qmd), [Git](/course/00_Git/index.qmd) and [Quarto](/course/00_Quarto/index.qmd) that we will be using throughout the course. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -This is our first year offering the course. Although we can and will answer questions during the livestreams, given the number of people signed up that might have a question, we want to make sure to provide multiple avenues by which you can get help and feedback throughout. These include the [Discussions Forum](https://github.com/UMGCCCFCSR/CytometryInR/discussions), where you can ask questions, discuss topics, get feedback and celebrate wins; and 2) turning in optional take-home problems via a pull request, in which the course instructors will take a look and provide additional feedback. - -In this walk-through, we go over how to use these resources. -::: -::: - ---- - -# Getting Started - - -## Discussions Forum - - -::: {.fragment} -::: {.callout-tip title="."} -On the course's [GitHub repository](https://github.com/UMGCCCFCSR/CytometryInR), we have opened up a [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page that we plan to use as a community forum. We hope that it will serve multiple functions, from providing a better sense of community for the online participants, to facilitating asking and receiving help on something that is not clear, provide feedback about something that it not working out, as well as a place to celebrate and show off your coding wins. -::: -::: - ---- - -![](images/Discussion.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -To keep the Discussions forum semi-organized, we have set up several categories, please select the appropiate category when opening a new discussion! -::: -::: - ---- - -### Code of Conduct - -::: {.fragment} -::: {.callout-tip title="."} -We ask that all course participants read and adhere to the spirit of our [Code of Conduct](https://github.com/UMGCCCFCSR/CytometryInR?tab=coc-ov-file). We are all human, at different points in our learning journeys, so what may be obvious to you at your point of your learning journey may have necessarily be obvious to someone just getting started. This course is our giving back to those in the community, but is on a voluntary basis in addition to our regular workload. While we try to reply quickly, sometimes our cell sorters fully melt down sending everything into chaos. We will reply when we can. -::: -::: - ---- - -![](images/CodeOfConduct.png) - ---- - -### Announcements - -![](images/Announcements.png) - -::: {.fragment} -::: {.callout-tip title="."} -When we send out an email to all participants, we will also repost it as an announcement. This ensures that even if you are not on our mailing list, you will still be able to have access to important information and course updates. -::: -::: - ---- - -![](images/000_Announcements.png) - ---- - -### General - -![](images/General.png) - -::: {.fragment} -::: {.callout-tip title="."} -This section category can be used for any discussions that you think are worth having, that don't fall under any of the other category. Good examples are continuing a discussion that was held during one of the livestreams; wanting to discuss and dive further into a given week's topic; or bringing in additional resources that you found useful to understandingn something that didn't click initially. This space is for the community to shape as they see best. -::: -::: - ---- - -![](images/000_General.png) - ---- - -### Ideas - -![](images/Ideas.png) - -::: {.fragment} -::: {.callout-tip title="."} -Have an idea for a new topic or a way to improve the course? We would love to hear them. Provide as many details, and ideally, an example, and if it is doable, we will try to implement them. -::: -::: - ---- - -![](images/000_Ideas.png) - ---- - -### Introductions - -![](images/Introductions.png) - -::: {.fragment} -::: {.callout-tip title="."} -Online courses can be odd in terms of replicating in-person dynamics. Fortunately, we have gathered the largest cohort of "cytometrist with no-to-little flow experience trying to learn R at the same time" that the world has ever seen, so best to take advantage of this while we can. Treat this section as if we had just met at a conference, tell us about yourself, what brings you here, and what you want to hopefully be able to do after the course ends. -::: -::: - ---- - -![](images/000_Introductions.png) - ---- - -## Polls - -![](images/Polls.png) - -::: {.fragment} -::: {.callout-tip title="."} -Occasionally, we will need to gather community feedback on what is working and what is not working. We will sporadically post Polls for this purpose. -::: -::: - ---- - -![](images/000_Polls.png) - ---- - -### Q&A - -![](images/Q&A.png) - -::: {.fragment} -::: {.callout-tip title="."} -The Questions and Answers (Q&A) section is where you go if something is not clear, not working, and you are trying to troubleshoot your way through it. First thing before posting, search! to see if someone has already asked the question. If you don't find anything, go ahead and open a new discussion. -::: -::: - ---- - -![](images/000_QandA.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Since we are not at your computer, and don't have your dataset, when troubleshooting it is best to include a minimal reproducible example of the issuen you are encountering, slimming down the number of files needed to be transferred, and generalizing down the code so that other course participants and instructors can follow along. If this is not doable, or if the problem requires added context (and larger files), create a new repository on your GitHub, make it public, and share the links to it in your post. The goal would be to download the folder and be able to replicate the issue that you are encountering. -::: -::: - ---- - -![](images/000_QandAExample.png) - ---- - -### Show and Tell - -![](images/ShowAndTell.png) - -::: {.fragment} -::: {.callout-tip title="."} -Where Q&A section is for getting help on code that is frustratingly not working, Show and Tell is where to go and celebrate when you finally get things to work. Share your wins, show us the extra pretty graphs, bizarre autofluorescence signatures, or odd outputs that just make you laugh. -::: -::: - ---- - -![](images/000_ShowAndTell.png) - ---- - -![](images/Timeline.png) - ---- - -## Issues - -![](images/Issues.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Most of the time, if you are having trouble getting you code to run, you should first stop after some initial troubleshooting should be to open a new [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) under the Q&A category. Here you will be able to get both community and instructor help and suggestions to hopefully resolve whatever is going on. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The Issues page is primarily meant for course-specific problems that require the course instructor intervention to fix. For example, we release a new week of material, and while it runs fine for both Windows and Linux, the code fails to run for all MacOS users. While you may be able to find workarounds on your own, it's ultimately our responsibility to help provide a solution so that everyone can move forward. This is the situation where opening an Issue is appropiate. -::: -::: - ---- - -![](images/000_IssuesExample.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Similarly, if our code contains a wrong argument, is returning a deprecation warning, etc. open an issue to let us know. While we may not be able to fix something that is not directly related to our code, we can redirect it to the package maintainers so that they can fix the issue. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And likewise, if you find multiple typos in the documentation, you can open an issue and propose carrying out a pull-request to fix them. -::: -::: - ---- - -## Submitting Take-Home Problems - - -::: {.fragment} -::: {.callout-tip title="."} -Each week, during the course, we introduce and cover the main concepts for the particular concept. Our goal is to provide you with the necessary code and enough code to be able to get the jist. However, to become comfortable and be able to apply what you have learned, you will need to explore beyond our examples, try it with your own datasets, encounter things that don't work, and troubleshoot your way through them. It's this cycle of venturing into the unknown that develops strong coding skills that are needed to overcome any barrier you encounter. The goal of the take-home questions is to provide some less curated problems that will take a little longer to answer to help get you started on your own exploration of the topic. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -As previously mentioned, these take-home problems are completely **optional**. If you are in the middle of solving them and want to seek feedback from then community and course instructors, open a [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) under the general category is the way to go. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -However, if you have completed them, and want course instructor feedback, you can submit them to us in the form of a pull-request to the CytometryInR repo's homework branch. We will take a look, offer constructive suggestions, and when ready merge the solution. This will also result in GitHub listing you as a contributor to the course. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will outline the basic steps of how to set up and open a pull-request, to help simplify the process. -::: -::: - ---- - -### Sync your Fork - - -::: {.fragment} -::: {.callout-tip title="."} -First off, make sure to Sync your fork of the Cytometry in R project. That makes sure that all the commits present are up-to-date and simplifies the process of having the pull-request being merged. -::: -::: - ---- - -![](images/00_Sync.png) - - ---- - -![](images/00_Compare.png) - - ---- - -![](images/02_Synced.png) - - ---- - -### Pull to Local - -::: {.fragment} -::: {.callout-tip title="."} -Having Synced your branch on GitHub, return to your computer, open the CytometryInR repository and [pull](/course/00_Git/index.qmd#pull) in the changes locally. -::: -::: - ---- - -### Create own Folder under Homeworks - - -::: {.fragment} -::: {.callout-tip title="."} -Under the course folder, you will find folders for each week. Within these folders find the homework folder. This will appear empty except for a README file with ionstructions. It is within this folder you will need to create your own folder. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -To ensure there are no conflicts on the pull-request merge, please use your GitHub username as the folder name. -::: -::: - ---- - -![](images/09_Homework.png) - ---- - - -::: {.fragment} -::: {.callout-tip title="."} -Once you have your folder inside homework, go ahead and copy anything you are turning in from their respective working project folders. Remember, the goal is minimal reproducible example is the goal. Rendered Quarto Documents are preferred, but we will also accept scripts and small data files and images. a README.MD file with anything you want me to know, -::: -::: - ---- - -![](images/10_TakeHomeReturnStructure.png) - ---- - -![](images/11_SelfContained.png) - ---- - -### Sign off Commit - - -::: {.fragment} -::: {.callout-tip title="."} -Now that everything is present, Sign Off and Commit the change. -::: -::: - ---- - -![](images/12_Commit.png) - ---- - -### Push Branch to GitHub. - -::: {.fragment} -::: {.callout-tip title="."} -Proceed to push the branch to GitHub. -::: -::: - ---- - -![](images/13_Sync.png) - ---- - -# Re-sync if necessary - - -::: {.fragment} -::: {.callout-tip title="."} -If additional changes have occured to the parent CytometryInR repository, go ahead and update your branch. As long as your edits occurred within your folder inside homework folders, they should still be able to merge. -::: -::: - ---- - -![](images/17_SyncMaybe.png) - ---- - -![](images/18_Update.png) - ---- - -### Open a pull-request - - -::: {.fragment} -::: {.callout-tip title="."} -To start a pull request, click to see how your commit is ahead by -::: -::: - ---- - -![](images/14_Ahead.png) - ---- - - -::: {.fragment} -::: {.callout-tip title="."} -Next, switch from the parent CytometryInR main branch (used for the website and course) to the homework branch for that respective week (used for the take-home problems). -::: -::: - ---- - -![](images/15_BranchSwitch.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once this is done, select Pull request -::: -::: - ---- - -![](images/16_PullRequest.png) - ---- - - -::: {.fragment} -::: {.callout-tip title="."} -Make sure to triple check it's bound for the homeworks branch. If you see that it is not capable of merging, verify that your commit only contains files within your respective homework username folder. Fill in the required fields of the pull request. -::: -::: - ---- - -![](images/20_PullRequestHomeworks.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And when ready, create the pull request. -::: -::: - ---- - -### Wait for Feedback - -::: {.fragment} -::: {.callout-tip title="."} -On our end, once you have created a pull request, we will review your work, offer constructive suggestions, etc. If I ask for revisions, all you would need to do is update your files, commit again on your side of the local forked repository. -::: -::: - ---- - -![](images/22_StartReviewProcess.png) - ---- - -### Final Review and Merge - -::: {.fragment} -::: {.callout-tip title="."} -If all is good, we will merge the pull request and your solution to the take-home problems will now be available on the homework branch. -::: -::: - ---- - -![](images/23_Merge.png) - ---- - -### After course - -::: {.fragment} -::: {.callout-tip title="."} -After the course completes, we will merge homework branch with the main branch, making the community solutions to the take-home problems additional coding examples that can be used by others following along after the course concludes. -::: -::: - ---- - -# Wrap-up - -::: {.fragment} -::: {.callout-tip title="."} -In this walk-through, we covered the [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) Forum, mentioned appropiate use cases for the [Issues](https://github.com/UMGCCCFCSR/CytometryInR/issues) page and provided the logistics of how to submit take-home problems as a pull request to the homework branch. We have now covered all the major elements that you will be using throughout the course. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The next couple sections cover our thoughts [on AI use]() in a course for coding beginners, and an optional walkthrough of how to use [Floreada](/course/00_Floreada/index.qmd) in preparation for some topics starting around Week 5. -::: -::: - -# Additional Resources - -[Create a Home for Your Community With GitHub Discussions](https://github.blog/open-source/maintainers/create-a-home-for-your-community-with-github-discussions/) - -[GitHub for Beginners: How to create a pull request in 4 minutes](https://youtu.be/nCKdihvneS0?si=PaM7QmylZiGfU9v4) - -[Five tips for Reviewing a GitHub pull request](https://www.youtube.com/watch?v=nP9Y72HQNaA) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Getting Help" +author: "David Rach" +date: 02-01-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +--- + +# Background + +::: {.fragment} +::: {.callout-tip title="."} +In the previous sections, we set up our [GitHub](/course/00_GitHub/index.qmd) account, installed the required [software](/course/00_WorkstationSetup/index.qmd), and further explored various elements of [Positron](/course/00_Positron/index.qmd), [Git](/course/00_Git/index.qmd) and [Quarto](/course/00_Quarto/index.qmd) that we will be using throughout the course. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This is our first year offering the course. Although we can and will answer questions during the livestreams, given the number of people signed up that might have a question, we want to make sure to provide multiple avenues by which you can get help and feedback throughout. These include the [Discussions Forum](https://github.com/UMGCCCFCSR/CytometryInR/discussions), where you can ask questions, discuss topics, get feedback and celebrate wins; and 2) turning in optional take-home problems via a pull request, in which the course instructors will take a look and provide additional feedback. + +In this walk-through, we go over how to use these resources. +::: +::: + +--- + +# Getting Started + + +## Discussions Forum + + +::: {.fragment} +::: {.callout-tip title="."} +On the course's [GitHub repository](https://github.com/UMGCCCFCSR/CytometryInR), we have opened up a [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page that we plan to use as a community forum. We hope that it will serve multiple functions, from providing a better sense of community for the online participants, to facilitating asking and receiving help on something that is not clear, provide feedback about something that it not working out, as well as a place to celebrate and show off your coding wins. +::: +::: + +--- + +![](images/Discussion.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To keep the Discussions forum semi-organized, we have set up several categories, please select the appropiate category when opening a new discussion! +::: +::: + +--- + +### Code of Conduct + +::: {.fragment} +::: {.callout-tip title="."} +We ask that all course participants read and adhere to the spirit of our [Code of Conduct](https://github.com/UMGCCCFCSR/CytometryInR?tab=coc-ov-file). We are all human, at different points in our learning journeys, so what may be obvious to you at your point of your learning journey may have necessarily be obvious to someone just getting started. This course is our giving back to those in the community, but is on a voluntary basis in addition to our regular workload. While we try to reply quickly, sometimes our cell sorters fully melt down sending everything into chaos. We will reply when we can. +::: +::: + +--- + +![](images/CodeOfConduct.png) + +--- + +### Announcements + +![](images/Announcements.png) + +::: {.fragment} +::: {.callout-tip title="."} +When we send out an email to all participants, we will also repost it as an announcement. This ensures that even if you are not on our mailing list, you will still be able to have access to important information and course updates. +::: +::: + +--- + +![](images/000_Announcements.png) + +--- + +### General + +![](images/General.png) + +::: {.fragment} +::: {.callout-tip title="."} +This section category can be used for any discussions that you think are worth having, that don't fall under any of the other category. Good examples are continuing a discussion that was held during one of the livestreams; wanting to discuss and dive further into a given week's topic; or bringing in additional resources that you found useful to understandingn something that didn't click initially. This space is for the community to shape as they see best. +::: +::: + +--- + +![](images/000_General.png) + +--- + +### Ideas + +![](images/Ideas.png) + +::: {.fragment} +::: {.callout-tip title="."} +Have an idea for a new topic or a way to improve the course? We would love to hear them. Provide as many details, and ideally, an example, and if it is doable, we will try to implement them. +::: +::: + +--- + +![](images/000_Ideas.png) + +--- + +### Introductions + +![](images/Introductions.png) + +::: {.fragment} +::: {.callout-tip title="."} +Online courses can be odd in terms of replicating in-person dynamics. Fortunately, we have gathered the largest cohort of "cytometrist with no-to-little flow experience trying to learn R at the same time" that the world has ever seen, so best to take advantage of this while we can. Treat this section as if we had just met at a conference, tell us about yourself, what brings you here, and what you want to hopefully be able to do after the course ends. +::: +::: + +--- + +![](images/000_Introductions.png) + +--- + +## Polls + +![](images/Polls.png) + +::: {.fragment} +::: {.callout-tip title="."} +Occasionally, we will need to gather community feedback on what is working and what is not working. We will sporadically post Polls for this purpose. +::: +::: + +--- + +![](images/000_Polls.png) + +--- + +### Q&A + +![](images/Q&A.png) + +::: {.fragment} +::: {.callout-tip title="."} +The Questions and Answers (Q&A) section is where you go if something is not clear, not working, and you are trying to troubleshoot your way through it. First thing before posting, search! to see if someone has already asked the question. If you don't find anything, go ahead and open a new discussion. +::: +::: + +--- + +![](images/000_QandA.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Since we are not at your computer, and don't have your dataset, when troubleshooting it is best to include a minimal reproducible example of the issuen you are encountering, slimming down the number of files needed to be transferred, and generalizing down the code so that other course participants and instructors can follow along. If this is not doable, or if the problem requires added context (and larger files), create a new repository on your GitHub, make it public, and share the links to it in your post. The goal would be to download the folder and be able to replicate the issue that you are encountering. +::: +::: + +--- + +![](images/000_QandAExample.png) + +--- + +### Show and Tell + +![](images/ShowAndTell.png) + +::: {.fragment} +::: {.callout-tip title="."} +Where Q&A section is for getting help on code that is frustratingly not working, Show and Tell is where to go and celebrate when you finally get things to work. Share your wins, show us the extra pretty graphs, bizarre autofluorescence signatures, or odd outputs that just make you laugh. +::: +::: + +--- + +![](images/000_ShowAndTell.png) + +--- + +![](images/Timeline.png) + +--- + +## Issues + +![](images/Issues.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Most of the time, if you are having trouble getting you code to run, you should first stop after some initial troubleshooting should be to open a new [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) under the Q&A category. Here you will be able to get both community and instructor help and suggestions to hopefully resolve whatever is going on. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The Issues page is primarily meant for course-specific problems that require the course instructor intervention to fix. For example, we release a new week of material, and while it runs fine for both Windows and Linux, the code fails to run for all MacOS users. While you may be able to find workarounds on your own, it's ultimately our responsibility to help provide a solution so that everyone can move forward. This is the situation where opening an Issue is appropiate. +::: +::: + +--- + +![](images/000_IssuesExample.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Similarly, if our code contains a wrong argument, is returning a deprecation warning, etc. open an issue to let us know. While we may not be able to fix something that is not directly related to our code, we can redirect it to the package maintainers so that they can fix the issue. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And likewise, if you find multiple typos in the documentation, you can open an issue and propose carrying out a pull-request to fix them. +::: +::: + +--- + +## Submitting Take-Home Problems + + +::: {.fragment} +::: {.callout-tip title="."} +Each week, during the course, we introduce and cover the main concepts for the particular concept. Our goal is to provide you with the necessary code and enough code to be able to get the jist. However, to become comfortable and be able to apply what you have learned, you will need to explore beyond our examples, try it with your own datasets, encounter things that don't work, and troubleshoot your way through them. It's this cycle of venturing into the unknown that develops strong coding skills that are needed to overcome any barrier you encounter. The goal of the take-home questions is to provide some less curated problems that will take a little longer to answer to help get you started on your own exploration of the topic. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As previously mentioned, these take-home problems are completely **optional**. If you are in the middle of solving them and want to seek feedback from then community and course instructors, open a [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) under the general category is the way to go. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +However, if you have completed them, and want course instructor feedback, you can submit them to us in the form of a pull-request to the CytometryInR repo's homework branch. We will take a look, offer constructive suggestions, and when ready merge the solution. This will also result in GitHub listing you as a contributor to the course. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will outline the basic steps of how to set up and open a pull-request, to help simplify the process. +::: +::: + +--- + +### Sync your Fork + + +::: {.fragment} +::: {.callout-tip title="."} +First off, make sure to Sync your fork of the Cytometry in R project. That makes sure that all the commits present are up-to-date and simplifies the process of having the pull-request being merged. +::: +::: + +--- + +![](images/00_Sync.png) + + +--- + +![](images/00_Compare.png) + + +--- + +![](images/02_Synced.png) + + +--- + +### Pull to Local + +::: {.fragment} +::: {.callout-tip title="."} +Having Synced your branch on GitHub, return to your computer, open the CytometryInR repository and [pull](/course/00_Git/index.qmd#pull) in the changes locally. +::: +::: + +--- + +### Create own Folder under Homeworks + + +::: {.fragment} +::: {.callout-tip title="."} +Under the course folder, you will find folders for each week. Within these folders find the homework folder. This will appear empty except for a README file with ionstructions. It is within this folder you will need to create your own folder. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To ensure there are no conflicts on the pull-request merge, please use your GitHub username as the folder name. +::: +::: + +--- + +![](images/09_Homework.png) + +--- + + +::: {.fragment} +::: {.callout-tip title="."} +Once you have your folder inside homework, go ahead and copy anything you are turning in from their respective working project folders. Remember, the goal is minimal reproducible example is the goal. Rendered Quarto Documents are preferred, but we will also accept scripts and small data files and images. a README.MD file with anything you want me to know, +::: +::: + +--- + +![](images/10_TakeHomeReturnStructure.png) + +--- + +![](images/11_SelfContained.png) + +--- + +### Sign off Commit + + +::: {.fragment} +::: {.callout-tip title="."} +Now that everything is present, Sign Off and Commit the change. +::: +::: + +--- + +![](images/12_Commit.png) + +--- + +### Push Branch to GitHub. + +::: {.fragment} +::: {.callout-tip title="."} +Proceed to push the branch to GitHub. +::: +::: + +--- + +![](images/13_Sync.png) + +--- + +# Re-sync if necessary + + +::: {.fragment} +::: {.callout-tip title="."} +If additional changes have occured to the parent CytometryInR repository, go ahead and update your branch. As long as your edits occurred within your folder inside homework folders, they should still be able to merge. +::: +::: + +--- + +![](images/17_SyncMaybe.png) + +--- + +![](images/18_Update.png) + +--- + +### Open a pull-request + + +::: {.fragment} +::: {.callout-tip title="."} +To start a pull request, click to see how your commit is ahead by +::: +::: + +--- + +![](images/14_Ahead.png) + +--- + + +::: {.fragment} +::: {.callout-tip title="."} +Next, switch from the parent CytometryInR main branch (used for the website and course) to the homework branch for that respective week (used for the take-home problems). +::: +::: + +--- + +![](images/15_BranchSwitch.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once this is done, select Pull request +::: +::: + +--- + +![](images/16_PullRequest.png) + +--- + + +::: {.fragment} +::: {.callout-tip title="."} +Make sure to triple check it's bound for the homeworks branch. If you see that it is not capable of merging, verify that your commit only contains files within your respective homework username folder. Fill in the required fields of the pull request. +::: +::: + +--- + +![](images/20_PullRequestHomeworks.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And when ready, create the pull request. +::: +::: + +--- + +### Wait for Feedback + +::: {.fragment} +::: {.callout-tip title="."} +On our end, once you have created a pull request, we will review your work, offer constructive suggestions, etc. If I ask for revisions, all you would need to do is update your files, commit again on your side of the local forked repository. +::: +::: + +--- + +![](images/22_StartReviewProcess.png) + +--- + +### Final Review and Merge + +::: {.fragment} +::: {.callout-tip title="."} +If all is good, we will merge the pull request and your solution to the take-home problems will now be available on the homework branch. +::: +::: + +--- + +![](images/23_Merge.png) + +--- + +### After course + +::: {.fragment} +::: {.callout-tip title="."} +After the course completes, we will merge homework branch with the main branch, making the community solutions to the take-home problems additional coding examples that can be used by others following along after the course concludes. +::: +::: + +--- + +# Wrap-up + +::: {.fragment} +::: {.callout-tip title="."} +In this walk-through, we covered the [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) Forum, mentioned appropiate use cases for the [Issues](https://github.com/UMGCCCFCSR/CytometryInR/issues) page and provided the logistics of how to submit take-home problems as a pull request to the homework branch. We have now covered all the major elements that you will be using throughout the course. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The next couple sections cover our thoughts [on AI use]() in a course for coding beginners, and an optional walkthrough of how to use [Floreada](/course/00_Floreada/index.qmd) in preparation for some topics starting around Week 5. +::: +::: + +# Additional Resources + +[Create a Home for Your Community With GitHub Discussions](https://github.blog/open-source/maintainers/create-a-home-for-your-community-with-github-discussions/) + +[GitHub for Beginners: How to create a pull request in 4 minutes](https://youtu.be/nCKdihvneS0?si=PaM7QmylZiGfU9v4) + +[Five tips for Reviewing a GitHub pull request](https://www.youtube.com/watch?v=nP9Y72HQNaA) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_Positron/index.qmd b/course/00_Positron/index.qmd index 6827205..47108dd 100644 --- a/course/00_Positron/index.qmd +++ b/course/00_Positron/index.qmd @@ -1,350 +1,350 @@ ---- -title: "Using Positron" -author: "David Rach" -date: 01-21-2026 -format: html -toc: true -toc-depth: 4 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -For the YouTube livestream recording, see [here](https://www.youtube.com/live/FSXsgaeM9Xo?si=kUZx9tn3KByDniEv) - - - -For screen-shot slides, click [here](/course/00_Positron/slides.qmd) - -# Background - -In this course, we are creating and working with code from the programming language [R](https://www.r-project.org/). However, in practice, we are not running the code directly using just the base R software. Typically, we are running an integrated development environment (IDE), which is an additional software running on top of base R. - -An IDE has the responsibility to help organize and manage the projects folders, pass along lines of code being executed (run) to the underlying R software, and then return and visualize the outputs in a manner that leads to increased producitivity. Examples of IDEs include [Positron](https://positron.posit.co/), [Visual Studio Code](https://code.visualstudio.com/) and [Rstudio](https://posit.co/downloads/). - -For this course, we will be using [Positron](https://positron.posit.co/) as our primary IDE. For those of you who have previous R experience, you are likely more familiar with [Rstudio](https://posit.co/downloads/) which is also made by Posit, and is the older of the two IDEs. Why use Positron for this course then? - -There are several reasons. First, Positron combines the best elements of both Rstudio (which preceeded it) and VS code (from which it's base infrastructure was [forked](https://posit.co/blog/positron-product-announcement-aug-2025/)). In a course aimed at coding beginners, this combination is immensely helpful in bringing important elements that had been previously hidden behind several menus in Rstudio out into the open where they are immediately available, reducing complicated workarounds. In my recent experience, it has been easier to teach beginners to code well with Positron than it was previously with Rstudio. - -Second, Data Science (and Bioinformatics) is increasingly moving in a multi-lingual programming direction. Flow Cytometry is not immune to this trend, [Python](https://www.python.org/), [Julia](https://julialang.org/) and [Rust](https://rust-lang.org/) are appearing more in [Cyto posters](https://www.cytoconference.org/index.html) each year. Positron is built to handle this, allowing us to bring in and use cool packages regardless of what language they are written, avoiding additional complicated workarounds to get them to work in Rstudio. - -And finally, having placed so much effort into making these resources available to the wider community, I don't want to provide all my examples using Rstudio only to find out two years from now that maintenance has been discontinued by Posit and everything needs to be remade. - -Consequently, I decided to use Positron for the course. This walk-through will cover some of the main layout elements to help start build some initial familiarity with the IDE, which we will continue to build on throughout the course. - - -# Getting Started - -When opening Positron for the first time, you will see something like this. Let's work our way around the screen, covering the major items in turn. - -![](images/01_PositronOpen.png) - -
- ---- - -# Interpreter - -On the upper right, above Session/Variables tab, you have the option to select the coding language (interpreter) being used by the project folder. For most of this course, you will likely see this set to R 4.5.2 (or your current R version). If your computer has Python installed, you may also see these versions appear within the interpreter drop-down menu. - -![](images/30_Session.png) - -
- ---- - -# Folders - -As [briefly covered](/course/00_WorkstationSetup/index.qmd) at the end of WorkStation walkthrough, the folders button to the right of the interpretor button allows us to open and work with Project Folders. From the drop-down, we can also Create New Folder from a template (which we will cover in the next section), or bring them in from existing GitHub repositories (as we did last section). You will also find the option to open other project folders that have been opened recently. - -![](images/31_ProjectFolderAccess.png) - -
- ---- - -# Panel - -At the bottom-center of the screen you will find the Panel region. This contains several tabs (Console, Terminal, etc). - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - - -## Console - -At the bottom of the sceen, you will first see the Console Tab. This is the tab where your lines of code when executed (run) will appear, as well as any messages, warnings or errors that get returned. On the right side of the console, you can find several buttons, among them restart R and delete session (for when you need a fresh start), and clear console (which keeps all previously run outputs and objects, but clears away the displayed text within the console). - -![](images/02_Console.png) - -
- ---- - -## Terminal -Right next to the Console tab is your Terminal tab. While the console tab is primarily used to run R code within Positron, the terminal is the interface where code containing system commands directed at at your computer is entered. We will use this less frequently, primarily in two context: 1) rendering Quarto documents, and 2) commiting changes to version control. Among the buttons on the right-side of the terminal to make note of are the + button to add a new terminal, and the trash/garbage can button to kill (stop) the terminal. - -![](images/03_Terminal.png) - -
- ---- - -The other tabs (Problems, Output, Ports, Debug Console) are used less frequently. I usually will Problems and Debug when something goes wrong with the code, as various warning and error messages will end up being displayed there. - -![](images/03_Terminal.png) - -
- ---- - -# Editor - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - -Located above the panel section (ie, just above the console window) is the main area known as the Editor. It is typically where you end up writing your code. It displays any and all the files that you open. - -For example, when I open a .png for one of my projects, the image will appear within the editor area in the middle of my screen. - - -![](images/04_VisualizedPNG.png) - -
- ---- - -When the file I open is an .R script, I will be able to see and edit the code contained within that same area. - -![](images/05_R.png) - -
- ---- - -Should I open a Quarto markdown file (.qmd), I can see and edit both the written as well as the code chunks contained within. - -![](images/06_QMD.png) - -
- ---- - -Looking below the tabs of the opened files, I can see the file.path (location) for the file I currently have open and am working on. This is denoted by the \> \> \> interspersed with the parent folder names. - -![](images/07_FilePath.png) - -
- ---- - -Just above the file path, and below the tabs, we find a couple buttons. Preview is used to render a Quarto document into various types of documents (including .html, .pdf or .docx) as long as no errors are encountered. - -![](images/08_Preview.png) - -
- ---- - -Source tab will normally be the active view, which will show everything as code/[markdown](https://www.markdownguide.org/getting-started/) - -![](images/09_Source.png) - -
- ---- - -However, we can also switch to Visual mode (by right clicking and selecting Edit Visual Mode) which will visualize it in a similar manner as if we had rendered the document as an .html webpage. - -![](images/EditVisualMode.png) - -
- ---- - -![](images/10_Visual.png) - -
- ---- - -As more files are opened, they will appear as individual tabs. These can be opened and closed as need be. The color of the text also displays their saved status. - -![](images/11_NavigatingBetween.png) - -
- ---- - -## Help - -When trying to evaluate how a particular function is working in R, you can hover over it and positron will open up the documentation for that particular function if available, alternatively, you can enter ?theParticularFunctionsName in the console and hit enter to similarly view what is occuring. - -![](images/Help.png) - -# Primary Side Bar - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - -To open a file, several options exist. If they are present within your Project folder, you can click on the pages tab on the activity bar (far upper left) and then click on the file of interest shown within the primary side bar (between the activity bar and the editor). Alternatively, the Open Folder icon on the upper-left or entering "Ctrl + O"/"Command + O" will open a pop-up to allow you to navigate and select a folder elsewhere on your computer. - -![](images/OpenFile.png) - -
- ---- - -Unsaved changes to an open file are reflected by on the tab the change in color of the text, and the appearance of a dot. We can click the Save changes button to change this. - -![](images/SaveChanges.png) - -
- ---- - -# Secondary Side Bar - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - -The secondary side bar is found on the right-side of the screen, to the right of the Editor and Panel windows. It is divided between an upper, and a lower portion. - -## Variables -On the upper-portion of the Secondary Side Bar, we can find the Session window, containing the Variables tab. As you run (execute) lines of code, and different variables, objects and functions are created, these become visible under the variables tab on the upper right. - -![](images/SessionVariables.png) - -
- ---- - -For some types of objects (generally data.frames and other matrix-like objects), you can click on their listing under variables to expand to see additional details about the object (column names, etc.) as well as view a larger version which will appear within the Editor window. - -## Plots - -Similarly, any generated Plots or Documents will appear within the Secondary Side Bar, either under Plots (bottom) or Viewer (top) tabs. - -![](images/SessionPlots.png) - -
- ---- - -## View - -On the upper bar multiple tabs can be found, which we will explore in due time. Most useful to point out is the View tab. If you accidentally close your console, session or plots window, and are trying to get them to reapper, you would need to reselect them from this tab. - -![](images/28_View.png) - -
- ---- - -# Activity Bar - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - -At the far-left side of the screen, you will find the activity bar, which contains several tabs. Depending on which one you have opened, the contents will be displayed on the primary side bar next to it. - - -## Pages - -The pages tab and the left-side bar show you everything that is currently within your project folder, including all the folders, and files. Once version control with Git is initiated, new files are relected showing up as green text and a dot, while modified tracked files are reflected by light brown text and a dot. - -![](images/27_ChangesSinceLastCommit.png) - -
- ---- - -The dropdown arrows can be used to open and close specific folders to allow for better organization. There is also a scrollbar on the right-side of the side-bar to scroll through the entire folders contents. - -![](images/26_MainTab.png) - -
- ---- - -## Search - -The search tab on the left side bar is something that I use routinely. - -![](images/24_SearchTab.png) - -
- ---- - -It can help locate code that you had been working on, but have since forgotten where it is at. Here is an example of finding the files where I had used a function that needed modifying within a local project folder's files. - -![](images/25_SearchResults.png) - -
- ---- - -Similarly, if you need to replace a particular character string with another, the replace with field below can help simplify the task without having to track down and change 20 lines across 5 files. - -![](images/24_SearchTab.png) - -
- ---- - -## Extensions - -On the far-left side we can find the Activity bar, which contains several tabs. Which tab you have selected will then dictate the contents of your left side-bar. - -Occupying the left side bar are several tabs. One of these is Extensions, which shows "Plugins" (or the VScode equivalent) that extend the functionality of Positron further. The ones you have installed may vary, but the main ones in context of this course are Air (provides color and highlights syntax for R code to make interpretation easier) as well as Quarto (for rendering the various document types). - - -![](images/29_ExtensionsTab.png) - -
- ---- - -## Git - -The Git tab on the left side bar is where once version control is initiated for the project folder, we can see changes that have occurred to the individual files since the last commit. These changes can be added to a new commit by clicking on the + sign. This will be covered more extensively in the [next section](/course/00_Git/index.qmd) - -![](images/20_SaveChanges.png) - -
- ---- - -Similarly, if you want to discard a change that has occured, the circular arrow will revert to the last commited version. Selecting and pressing the delete button will similarly work. - -![](images/21_DiscardChanges.png) - -
- ---- - -Selecting the ... options will highlight all the various git functions, some of which we will cover more extensively in the [next section](/course/00_Git/index.qmd) and throughout the course. - -![](images/23_AdditionalGitOptions.png) - -
- ---- - - -# Wrap-up - -In this walk-through, we looked at some of the elements within Positron. Don't worry, you don't need to remember them all or what they do at this point of time, these will come with practice over the first few weeks of the course. - -In the [next section](/course/00_Git/index.qmd), we will take a closer look at using the version control software Git that we have previewed here. - -# Additional Resources - -[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) - -[A brief tour of Positron (YouTube)](https://youtu.be/4Ir_HX4riHw?si=awSUVjdzBPDVR4Iw) - -[Welcome to Positron](https://positron.posit.co/welcome.html) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Using Positron" +author: "David Rach" +date: 01-21-2026 +format: html +toc: true +toc-depth: 4 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://www.youtube.com/live/FSXsgaeM9Xo?si=kUZx9tn3KByDniEv) + + + +For screen-shot slides, click [here](/course/00_Positron/slides.qmd) + +# Background + +In this course, we are creating and working with code from the programming language [R](https://www.r-project.org/). However, in practice, we are not running the code directly using just the base R software. Typically, we are running an integrated development environment (IDE), which is an additional software running on top of base R. + +An IDE has the responsibility to help organize and manage the projects folders, pass along lines of code being executed (run) to the underlying R software, and then return and visualize the outputs in a manner that leads to increased producitivity. Examples of IDEs include [Positron](https://positron.posit.co/), [Visual Studio Code](https://code.visualstudio.com/) and [Rstudio](https://posit.co/downloads/). + +For this course, we will be using [Positron](https://positron.posit.co/) as our primary IDE. For those of you who have previous R experience, you are likely more familiar with [Rstudio](https://posit.co/downloads/) which is also made by Posit, and is the older of the two IDEs. Why use Positron for this course then? + +There are several reasons. First, Positron combines the best elements of both Rstudio (which preceeded it) and VS code (from which it's base infrastructure was [forked](https://posit.co/blog/positron-product-announcement-aug-2025/)). In a course aimed at coding beginners, this combination is immensely helpful in bringing important elements that had been previously hidden behind several menus in Rstudio out into the open where they are immediately available, reducing complicated workarounds. In my recent experience, it has been easier to teach beginners to code well with Positron than it was previously with Rstudio. + +Second, Data Science (and Bioinformatics) is increasingly moving in a multi-lingual programming direction. Flow Cytometry is not immune to this trend, [Python](https://www.python.org/), [Julia](https://julialang.org/) and [Rust](https://rust-lang.org/) are appearing more in [Cyto posters](https://www.cytoconference.org/index.html) each year. Positron is built to handle this, allowing us to bring in and use cool packages regardless of what language they are written, avoiding additional complicated workarounds to get them to work in Rstudio. + +And finally, having placed so much effort into making these resources available to the wider community, I don't want to provide all my examples using Rstudio only to find out two years from now that maintenance has been discontinued by Posit and everything needs to be remade. + +Consequently, I decided to use Positron for the course. This walk-through will cover some of the main layout elements to help start build some initial familiarity with the IDE, which we will continue to build on throughout the course. + + +# Getting Started + +When opening Positron for the first time, you will see something like this. Let's work our way around the screen, covering the major items in turn. + +![](images/01_PositronOpen.png) + +
+ +--- + +# Interpreter + +On the upper right, above Session/Variables tab, you have the option to select the coding language (interpreter) being used by the project folder. For most of this course, you will likely see this set to R 4.5.2 (or your current R version). If your computer has Python installed, you may also see these versions appear within the interpreter drop-down menu. + +![](images/30_Session.png) + +
+ +--- + +# Folders + +As [briefly covered](/course/00_WorkstationSetup/index.qmd) at the end of WorkStation walkthrough, the folders button to the right of the interpretor button allows us to open and work with Project Folders. From the drop-down, we can also Create New Folder from a template (which we will cover in the next section), or bring them in from existing GitHub repositories (as we did last section). You will also find the option to open other project folders that have been opened recently. + +![](images/31_ProjectFolderAccess.png) + +
+ +--- + +# Panel + +At the bottom-center of the screen you will find the Panel region. This contains several tabs (Console, Terminal, etc). + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + + +## Console + +At the bottom of the sceen, you will first see the Console Tab. This is the tab where your lines of code when executed (run) will appear, as well as any messages, warnings or errors that get returned. On the right side of the console, you can find several buttons, among them restart R and delete session (for when you need a fresh start), and clear console (which keeps all previously run outputs and objects, but clears away the displayed text within the console). + +![](images/02_Console.png) + +
+ +--- + +## Terminal +Right next to the Console tab is your Terminal tab. While the console tab is primarily used to run R code within Positron, the terminal is the interface where code containing system commands directed at at your computer is entered. We will use this less frequently, primarily in two context: 1) rendering Quarto documents, and 2) commiting changes to version control. Among the buttons on the right-side of the terminal to make note of are the + button to add a new terminal, and the trash/garbage can button to kill (stop) the terminal. + +![](images/03_Terminal.png) + +
+ +--- + +The other tabs (Problems, Output, Ports, Debug Console) are used less frequently. I usually will Problems and Debug when something goes wrong with the code, as various warning and error messages will end up being displayed there. + +![](images/03_Terminal.png) + +
+ +--- + +# Editor + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + +Located above the panel section (ie, just above the console window) is the main area known as the Editor. It is typically where you end up writing your code. It displays any and all the files that you open. + +For example, when I open a .png for one of my projects, the image will appear within the editor area in the middle of my screen. + + +![](images/04_VisualizedPNG.png) + +
+ +--- + +When the file I open is an .R script, I will be able to see and edit the code contained within that same area. + +![](images/05_R.png) + +
+ +--- + +Should I open a Quarto markdown file (.qmd), I can see and edit both the written as well as the code chunks contained within. + +![](images/06_QMD.png) + +
+ +--- + +Looking below the tabs of the opened files, I can see the file.path (location) for the file I currently have open and am working on. This is denoted by the \> \> \> interspersed with the parent folder names. + +![](images/07_FilePath.png) + +
+ +--- + +Just above the file path, and below the tabs, we find a couple buttons. Preview is used to render a Quarto document into various types of documents (including .html, .pdf or .docx) as long as no errors are encountered. + +![](images/08_Preview.png) + +
+ +--- + +Source tab will normally be the active view, which will show everything as code/[markdown](https://www.markdownguide.org/getting-started/) + +![](images/09_Source.png) + +
+ +--- + +However, we can also switch to Visual mode (by right clicking and selecting Edit Visual Mode) which will visualize it in a similar manner as if we had rendered the document as an .html webpage. + +![](images/EditVisualMode.png) + +
+ +--- + +![](images/10_Visual.png) + +
+ +--- + +As more files are opened, they will appear as individual tabs. These can be opened and closed as need be. The color of the text also displays their saved status. + +![](images/11_NavigatingBetween.png) + +
+ +--- + +## Help + +When trying to evaluate how a particular function is working in R, you can hover over it and positron will open up the documentation for that particular function if available, alternatively, you can enter ?theParticularFunctionsName in the console and hit enter to similarly view what is occuring. + +![](images/Help.png) + +# Primary Side Bar + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + +To open a file, several options exist. If they are present within your Project folder, you can click on the pages tab on the activity bar (far upper left) and then click on the file of interest shown within the primary side bar (between the activity bar and the editor). Alternatively, the Open Folder icon on the upper-left or entering "Ctrl + O"/"Command + O" will open a pop-up to allow you to navigate and select a folder elsewhere on your computer. + +![](images/OpenFile.png) + +
+ +--- + +Unsaved changes to an open file are reflected by on the tab the change in color of the text, and the appearance of a dot. We can click the Save changes button to change this. + +![](images/SaveChanges.png) + +
+ +--- + +# Secondary Side Bar + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + +The secondary side bar is found on the right-side of the screen, to the right of the Editor and Panel windows. It is divided between an upper, and a lower portion. + +## Variables +On the upper-portion of the Secondary Side Bar, we can find the Session window, containing the Variables tab. As you run (execute) lines of code, and different variables, objects and functions are created, these become visible under the variables tab on the upper right. + +![](images/SessionVariables.png) + +
+ +--- + +For some types of objects (generally data.frames and other matrix-like objects), you can click on their listing under variables to expand to see additional details about the object (column names, etc.) as well as view a larger version which will appear within the Editor window. + +## Plots + +Similarly, any generated Plots or Documents will appear within the Secondary Side Bar, either under Plots (bottom) or Viewer (top) tabs. + +![](images/SessionPlots.png) + +
+ +--- + +## View + +On the upper bar multiple tabs can be found, which we will explore in due time. Most useful to point out is the View tab. If you accidentally close your console, session or plots window, and are trying to get them to reapper, you would need to reselect them from this tab. + +![](images/28_View.png) + +
+ +--- + +# Activity Bar + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + +At the far-left side of the screen, you will find the activity bar, which contains several tabs. Depending on which one you have opened, the contents will be displayed on the primary side bar next to it. + + +## Pages + +The pages tab and the left-side bar show you everything that is currently within your project folder, including all the folders, and files. Once version control with Git is initiated, new files are relected showing up as green text and a dot, while modified tracked files are reflected by light brown text and a dot. + +![](images/27_ChangesSinceLastCommit.png) + +
+ +--- + +The dropdown arrows can be used to open and close specific folders to allow for better organization. There is also a scrollbar on the right-side of the side-bar to scroll through the entire folders contents. + +![](images/26_MainTab.png) + +
+ +--- + +## Search + +The search tab on the left side bar is something that I use routinely. + +![](images/24_SearchTab.png) + +
+ +--- + +It can help locate code that you had been working on, but have since forgotten where it is at. Here is an example of finding the files where I had used a function that needed modifying within a local project folder's files. + +![](images/25_SearchResults.png) + +
+ +--- + +Similarly, if you need to replace a particular character string with another, the replace with field below can help simplify the task without having to track down and change 20 lines across 5 files. + +![](images/24_SearchTab.png) + +
+ +--- + +## Extensions + +On the far-left side we can find the Activity bar, which contains several tabs. Which tab you have selected will then dictate the contents of your left side-bar. + +Occupying the left side bar are several tabs. One of these is Extensions, which shows "Plugins" (or the VScode equivalent) that extend the functionality of Positron further. The ones you have installed may vary, but the main ones in context of this course are Air (provides color and highlights syntax for R code to make interpretation easier) as well as Quarto (for rendering the various document types). + + +![](images/29_ExtensionsTab.png) + +
+ +--- + +## Git + +The Git tab on the left side bar is where once version control is initiated for the project folder, we can see changes that have occurred to the individual files since the last commit. These changes can be added to a new commit by clicking on the + sign. This will be covered more extensively in the [next section](/course/00_Git/index.qmd) + +![](images/20_SaveChanges.png) + +
+ +--- + +Similarly, if you want to discard a change that has occured, the circular arrow will revert to the last commited version. Selecting and pressing the delete button will similarly work. + +![](images/21_DiscardChanges.png) + +
+ +--- + +Selecting the ... options will highlight all the various git functions, some of which we will cover more extensively in the [next section](/course/00_Git/index.qmd) and throughout the course. + +![](images/23_AdditionalGitOptions.png) + +
+ +--- + + +# Wrap-up + +In this walk-through, we looked at some of the elements within Positron. Don't worry, you don't need to remember them all or what they do at this point of time, these will come with practice over the first few weeks of the course. + +In the [next section](/course/00_Git/index.qmd), we will take a closer look at using the version control software Git that we have previewed here. + +# Additional Resources + +[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) + +[A brief tour of Positron (YouTube)](https://youtu.be/4Ir_HX4riHw?si=awSUVjdzBPDVR4Iw) + +[Welcome to Positron](https://positron.posit.co/welcome.html) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_Positron/slides.qmd b/course/00_Positron/slides.qmd index 149a1f9..47eee0d 100644 --- a/course/00_Positron/slides.qmd +++ b/course/00_Positron/slides.qmd @@ -1,554 +1,554 @@ ---- -title: "Using Positron" -author: "David Rach" -date: 02-01-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -# Background - -::: {.fragment} -::: {.callout-tip title="."} -In this course, we are creating and working with code from the programming language [R](https://www.r-project.org/). However, in practice, we are not running the code directly using just the base R software. Typically, we are running an integrated development environment (IDE), which is an additional software running on top of base R. -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} -An IDE has the responsibility to help organize and manage the projects folders, pass along lines of code being executed (run) to the underlying R software, and then return and visualize the outputs in a manner that leads to increased producitivity. Examples of IDEs include [Positron](https://positron.posit.co/), [Visual Studio Code](https://code.visualstudio.com/) and [Rstudio](https://posit.co/downloads/). -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For this course, we will be using [Positron](https://positron.posit.co/) as our primary IDE. For those of you who have previous R experience, you are likely more familiar with [Rstudio](https://posit.co/downloads/) which is also made by Posit, and is the older of the two IDEs. Why use Positron for this course then? -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -There are several reasons. First, Positron combines the best elements of both Rstudio (which preceeded it) and VS code (from which it's base infrastructure was [forked](https://posit.co/blog/positron-product-announcement-aug-2025/)). In a course aimed at coding beginners, this combination is immensely helpful in bringing important elements that had been previously hidden behind several menus in Rstudio out into the open where they are immediately available, reducing complicated workarounds. In my recent experience, it has been easier to teach beginners to code well with Positron than it was previously with Rstudio. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Second, Data Science (and Bioinformatics) is increasingly moving in a multi-lingual programming direction. Flow Cytometry is not immune to this trend, [Python](https://www.python.org/), [Julia](https://julialang.org/) and [Rust](https://rust-lang.org/) are appearing more in [Cyto posters](https://www.cytoconference.org/index.html) each year. Positron is built to handle this, allowing us to bring in and use cool packages regardless of what language they are written, avoiding additional complicated workarounds to get them to work in Rstudio. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And finally, having placed so much effort into making these resources available to the wider community, I don't want to provide all my examples using Rstudio only to find out two years from now that maintenance has been discontinued by Posit and everything needs to be remade. -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} -Consequently, I decided to use Positron for the course. This walk-through will cover some of the main layout elements to help start build some initial familiarity with the IDE, which we will continue to build on throughout the course. -::: -::: - -# Getting Started - -::: {.fragment} -::: {.callout-tip title="."} -When opening Positron for the first time, you will see something like this. Let's work our way around the screen, covering the major items in turn. -::: -::: - ---- - -![](images/01_PositronOpen.png) - - ---- - -# Interpreter - -::: {.fragment} -::: {.callout-tip title="."} -On the upper right, above Session/Variables tab, you have the option to select the coding language (interpreter) being used by the project folder. For most of this course, you will likely see this set to R 4.5.2 (or your current R version). If your computer has Python installed, you may also see these versions appear within the interpreter drop-down menu. -::: -::: - ---- - -![](images/30_Session.png) - - ---- - -# Folders - -::: {.fragment} -::: {.callout-tip title="."} -As [briefly covered](/course/00_WorkstationSetup/index.qmd) at the end of WorkStation walkthrough, the folders button to the right of the interpretor button allows us to open and work with Project Folders. From the drop-down, we can also Create New Folder from a template (which we will cover in the next section), or bring them in from existing GitHub repositories (as we did last section). You will also find the option to open other project folders that have been opened recently. -::: -::: - ---- - -![](images/31_ProjectFolderAccess.png) - - ---- - -# Panel - -::: {.fragment} -::: {.callout-tip title="."} -At the bottom-center of the screen you will find the Panel region. This contains several tabs (Console, Terminal, etc). -::: -::: - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - - -## Console - -::: {.fragment} -::: {.callout-tip title="."} -At the bottom of the sceen, you will first see the Console Tab. This is the tab where your lines of code when executed (run) will appear, as well as any messages, warnings or errors that get returned. On the right side of the console, you can find several buttons, among them restart R and delete session (for when you need a fresh start), and clear console (which keeps all previously run outputs and objects, but clears away the displayed text within the console). -::: -::: - ---- - -![](images/02_Console.png) - - ---- - -## Terminal - -::: {.fragment} -::: {.callout-tip title="."} -Right next to the Console tab is your Terminal tab. While the console tab is primarily used to run R code within Positron, the terminal is the interface where code containing system commands directed at at your computer is entered. We will use this less frequently, primarily in two context: 1) rendering Quarto documents, and 2) commiting changes to version control. Among the buttons on the right-side of the terminal to make note of are the + button to add a new terminal, and the trash/garbage can button to kill (stop) the terminal. -::: -::: - ---- - -![](images/03_Terminal.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The other tabs (Problems, Output, Ports, Debug Console) are used less frequently. I usually will Problems and Debug when something goes wrong with the code, as various warning and error messages will end up being displayed there. -::: -::: - ---- - -![](images/03_Terminal.png) - - ---- - -# Editor - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Located above the panel section (ie, just above the console window) is the main area known as the Editor. It is typically where you end up writing your code. It displays any and all the files that you open. - -For example, when I open a .png for one of my projects, the image will appear within the editor area in the middle of my screen. -::: -::: - ---- - -![](images/04_VisualizedPNG.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When the file I open is an .R script, I will be able to see and edit the code contained within that same area. -::: -::: - ---- - -![](images/05_R.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Should I open a Quarto markdown file (.qmd), I can see and edit both the written as well as the code chunks contained within. -::: -::: - ---- - -![](images/06_QMD.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Looking below the tabs of the opened files, I can see the file.path (location) for the file I currently have open and am working on. This is denoted by the \> \> \> interspersed with the parent folder names. -::: -::: - ---- - -![](images/07_FilePath.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Just above the file path, and below the tabs, we find a couple buttons. Preview is used to render a Quarto document into various types of documents (including .html, .pdf or .docx) as long as no errors are encountered. -::: -::: - ---- - -![](images/08_Preview.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Source tab will normally be the active view, which will show everything as code/[markdown](https://www.markdownguide.org/getting-started/) -::: -::: - ---- - -![](images/09_Source.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -However, we can also switch to Visual mode (by right clicking and selecting Edit Visual Mode) which will visualize it in a similar manner as if we had rendered the document as an .html webpage. -::: -::: - ---- - -![](images/EditVisualMode.png) - ---- - -![](images/10_Visual.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -As more files are opened, they will appear as individual tabs. These can be opened and closed as need be. The color of the text also displays their saved status. -::: -::: - ---- - -![](images/11_NavigatingBetween.png) - - ---- - -## Help - -::: {.fragment} -::: {.callout-tip title="."} -When trying to evaluate how a particular function is working in R, you can hover over it and positron will open up the documentation for that particular function if available, alternatively, you can enter ?theParticularFunctionsName in the console and hit enter to similarly view what is occuring. -::: -::: - ---- - -![](images/Help.png) - -# Primary Side Bar - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -To open a file, several options exist. If they are present within your Project folder, you can click on the pages tab on the activity bar (far upper left) and then click on the file of interest shown within the primary side bar (between the activity bar and the editor). Alternatively, the Open Folder icon on the upper-left or entering "Ctrl + O"/"Command + O" will open a pop-up to allow you to navigate and select a folder elsewhere on your computer. -::: -::: - ---- - -![](images/OpenFile.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Unsaved changes to an open file are reflected by on the tab the change in color of the text, and the appearance of a dot. We can click the Save changes button to change this. -::: -::: - ---- - -![](images/SaveChanges.png) - - ---- - -# Secondary Side Bar - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - -::: {.fragment} -::: {.callout-tip title="."} -The secondary side bar is found on the right-side of the screen, to the right of the Editor and Panel windows. It is divided between an upper, and a lower portion. -::: -::: - -## Variables - -::: {.fragment} -::: {.callout-tip title="."} -On the upper-portion of the Secondary Side Bar, we can find the Session window, containing the Variables tab. As you run (execute) lines of code, and different variables, objects and functions are created, these become visible under the variables tab on the upper right. -::: -::: - ---- - -![](images/SessionVariables.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For some types of objects (generally data.frames and other matrix-like objects), you can click on their listing under variables to expand to see additional details about the object (column names, etc.) as well as view a larger version which will appear within the Editor window. -::: -::: - -## Plots - -::: {.fragment} -::: {.callout-tip title="."} -Similarly, any generated Plots or Documents will appear within the Secondary Side Bar, either under Plots (bottom) or Viewer (top) tabs. -::: -::: - ---- - -![](images/SessionPlots.png) - - ---- - -## View - -::: {.fragment} -::: {.callout-tip title="."} -On the upper bar multiple tabs can be found, which we will explore in due time. Most useful to point out is the View tab. If you accidentally close your console, session or plots window, and are trying to get them to reapper, you would need to reselect them from this tab. -::: -::: - ---- - -![](images/28_View.png) - - ---- - -# Activity Bar - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - -::: {.fragment} -::: {.callout-tip title="."} -At the far-left side of the screen, you will find the activity bar, which contains several tabs. Depending on which one you have opened, the contents will be displayed on the primary side bar next to it. -::: -::: - -## Pages - -::: {.fragment} -::: {.callout-tip title="."} -The pages tab and the left-side bar show you everything that is currently within your project folder, including all the folders, and files. Once version control with Git is initiated, new files are relected showing up as green text and a dot, while modified tracked files are reflected by light brown text and a dot. -::: -::: - ---- - -![](images/27_ChangesSinceLastCommit.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The dropdown arrows can be used to open and close specific folders to allow for better organization. There is also a scrollbar on the right-side of the side-bar to scroll through the entire folders contents. -::: -::: - ---- - -![](images/26_MainTab.png) - - ---- - -## Search - -::: {.fragment} -::: {.callout-tip title="."} -The search tab on the left side bar is something that I use routinely. -::: -::: - ---- - -![](images/24_SearchTab.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -It can help locate code that you had been working on, but have since forgotten where it is at. Here is an example of finding the files where I had used a function that needed modifying within a local project folder's files. -::: -::: - ---- - -![](images/25_SearchResults.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Similarly, if you need to replace a particular character string with another, the replace with field below can help simplify the task without having to track down and change 20 lines across 5 files. -::: -::: - ---- - -![](images/24_SearchTab.png) - - ---- - -## Extensions - -::: {.fragment} -::: {.callout-tip title="."} -On the far-left side we can find the Activity bar, which contains several tabs. Which tab you have selected will then dictate the contents of your left side-bar. - -Occupying the left side bar are several tabs. One of these is Extensions, which shows "Plugins" (or the VScode equivalent) that extend the functionality of Positron further. The ones you have installed may vary, but the main ones in context of this course are Air (provides color and highlights syntax for R code to make interpretation easier) as well as Quarto (for rendering the various document types). -::: -::: - ---- - -![](images/29_ExtensionsTab.png) - - ---- - -## Git - -::: {.fragment} -::: {.callout-tip title="."} -The Git tab on the left side bar is where once version control is initiated for the project folder, we can see changes that have occurred to the individual files since the last commit. These changes can be added to a new commit by clicking on the + sign. This will be covered more extensively in the [next section](/course/00_Git/index.qmd) -::: -::: - ---- - -![](images/20_SaveChanges.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Similarly, if you want to discard a change that has occured, the circular arrow will revert to the last commited version. Selecting and pressing the delete button will similarly work. -::: -::: - ---- - -![](images/21_DiscardChanges.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Selecting the ... options will highlight all the various git functions, some of which we will cover more extensively in the [next section](/course/00_Git/index.qmd) and throughout the course. -::: -::: - ---- - -![](images/23_AdditionalGitOptions.png) - - ---- - - -# Wrap-up - -::: {.fragment} -::: {.callout-tip title="."} -In this walk-through, we looked at some of the elements within Positron. Don't worry, you don't need to remember them all or what they do at this point of time, these will come with practice over the first few weeks of the course. - -In the [next section](/course/00_Git/index.qmd), we will take a closer look at using the version control software Git that we have previewed here. -::: -::: - -# Additional Resources - -[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) - -[A brief tour of Positron (YouTube)](https://youtu.be/4Ir_HX4riHw?si=awSUVjdzBPDVR4Iw) - -[Welcome to Positron](https://positron.posit.co/welcome.html) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Using Positron" +author: "David Rach" +date: 02-01-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +# Background + +::: {.fragment} +::: {.callout-tip title="."} +In this course, we are creating and working with code from the programming language [R](https://www.r-project.org/). However, in practice, we are not running the code directly using just the base R software. Typically, we are running an integrated development environment (IDE), which is an additional software running on top of base R. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +An IDE has the responsibility to help organize and manage the projects folders, pass along lines of code being executed (run) to the underlying R software, and then return and visualize the outputs in a manner that leads to increased producitivity. Examples of IDEs include [Positron](https://positron.posit.co/), [Visual Studio Code](https://code.visualstudio.com/) and [Rstudio](https://posit.co/downloads/). +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For this course, we will be using [Positron](https://positron.posit.co/) as our primary IDE. For those of you who have previous R experience, you are likely more familiar with [Rstudio](https://posit.co/downloads/) which is also made by Posit, and is the older of the two IDEs. Why use Positron for this course then? +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +There are several reasons. First, Positron combines the best elements of both Rstudio (which preceeded it) and VS code (from which it's base infrastructure was [forked](https://posit.co/blog/positron-product-announcement-aug-2025/)). In a course aimed at coding beginners, this combination is immensely helpful in bringing important elements that had been previously hidden behind several menus in Rstudio out into the open where they are immediately available, reducing complicated workarounds. In my recent experience, it has been easier to teach beginners to code well with Positron than it was previously with Rstudio. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Second, Data Science (and Bioinformatics) is increasingly moving in a multi-lingual programming direction. Flow Cytometry is not immune to this trend, [Python](https://www.python.org/), [Julia](https://julialang.org/) and [Rust](https://rust-lang.org/) are appearing more in [Cyto posters](https://www.cytoconference.org/index.html) each year. Positron is built to handle this, allowing us to bring in and use cool packages regardless of what language they are written, avoiding additional complicated workarounds to get them to work in Rstudio. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And finally, having placed so much effort into making these resources available to the wider community, I don't want to provide all my examples using Rstudio only to find out two years from now that maintenance has been discontinued by Posit and everything needs to be remade. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +Consequently, I decided to use Positron for the course. This walk-through will cover some of the main layout elements to help start build some initial familiarity with the IDE, which we will continue to build on throughout the course. +::: +::: + +# Getting Started + +::: {.fragment} +::: {.callout-tip title="."} +When opening Positron for the first time, you will see something like this. Let's work our way around the screen, covering the major items in turn. +::: +::: + +--- + +![](images/01_PositronOpen.png) + + +--- + +# Interpreter + +::: {.fragment} +::: {.callout-tip title="."} +On the upper right, above Session/Variables tab, you have the option to select the coding language (interpreter) being used by the project folder. For most of this course, you will likely see this set to R 4.5.2 (or your current R version). If your computer has Python installed, you may also see these versions appear within the interpreter drop-down menu. +::: +::: + +--- + +![](images/30_Session.png) + + +--- + +# Folders + +::: {.fragment} +::: {.callout-tip title="."} +As [briefly covered](/course/00_WorkstationSetup/index.qmd) at the end of WorkStation walkthrough, the folders button to the right of the interpretor button allows us to open and work with Project Folders. From the drop-down, we can also Create New Folder from a template (which we will cover in the next section), or bring them in from existing GitHub repositories (as we did last section). You will also find the option to open other project folders that have been opened recently. +::: +::: + +--- + +![](images/31_ProjectFolderAccess.png) + + +--- + +# Panel + +::: {.fragment} +::: {.callout-tip title="."} +At the bottom-center of the screen you will find the Panel region. This contains several tabs (Console, Terminal, etc). +::: +::: + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + + +## Console + +::: {.fragment} +::: {.callout-tip title="."} +At the bottom of the sceen, you will first see the Console Tab. This is the tab where your lines of code when executed (run) will appear, as well as any messages, warnings or errors that get returned. On the right side of the console, you can find several buttons, among them restart R and delete session (for when you need a fresh start), and clear console (which keeps all previously run outputs and objects, but clears away the displayed text within the console). +::: +::: + +--- + +![](images/02_Console.png) + + +--- + +## Terminal + +::: {.fragment} +::: {.callout-tip title="."} +Right next to the Console tab is your Terminal tab. While the console tab is primarily used to run R code within Positron, the terminal is the interface where code containing system commands directed at at your computer is entered. We will use this less frequently, primarily in two context: 1) rendering Quarto documents, and 2) commiting changes to version control. Among the buttons on the right-side of the terminal to make note of are the + button to add a new terminal, and the trash/garbage can button to kill (stop) the terminal. +::: +::: + +--- + +![](images/03_Terminal.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The other tabs (Problems, Output, Ports, Debug Console) are used less frequently. I usually will Problems and Debug when something goes wrong with the code, as various warning and error messages will end up being displayed there. +::: +::: + +--- + +![](images/03_Terminal.png) + + +--- + +# Editor + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Located above the panel section (ie, just above the console window) is the main area known as the Editor. It is typically where you end up writing your code. It displays any and all the files that you open. + +For example, when I open a .png for one of my projects, the image will appear within the editor area in the middle of my screen. +::: +::: + +--- + +![](images/04_VisualizedPNG.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When the file I open is an .R script, I will be able to see and edit the code contained within that same area. +::: +::: + +--- + +![](images/05_R.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Should I open a Quarto markdown file (.qmd), I can see and edit both the written as well as the code chunks contained within. +::: +::: + +--- + +![](images/06_QMD.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Looking below the tabs of the opened files, I can see the file.path (location) for the file I currently have open and am working on. This is denoted by the \> \> \> interspersed with the parent folder names. +::: +::: + +--- + +![](images/07_FilePath.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Just above the file path, and below the tabs, we find a couple buttons. Preview is used to render a Quarto document into various types of documents (including .html, .pdf or .docx) as long as no errors are encountered. +::: +::: + +--- + +![](images/08_Preview.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Source tab will normally be the active view, which will show everything as code/[markdown](https://www.markdownguide.org/getting-started/) +::: +::: + +--- + +![](images/09_Source.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +However, we can also switch to Visual mode (by right clicking and selecting Edit Visual Mode) which will visualize it in a similar manner as if we had rendered the document as an .html webpage. +::: +::: + +--- + +![](images/EditVisualMode.png) + +--- + +![](images/10_Visual.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As more files are opened, they will appear as individual tabs. These can be opened and closed as need be. The color of the text also displays their saved status. +::: +::: + +--- + +![](images/11_NavigatingBetween.png) + + +--- + +## Help + +::: {.fragment} +::: {.callout-tip title="."} +When trying to evaluate how a particular function is working in R, you can hover over it and positron will open up the documentation for that particular function if available, alternatively, you can enter ?theParticularFunctionsName in the console and hit enter to similarly view what is occuring. +::: +::: + +--- + +![](images/Help.png) + +# Primary Side Bar + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To open a file, several options exist. If they are present within your Project folder, you can click on the pages tab on the activity bar (far upper left) and then click on the file of interest shown within the primary side bar (between the activity bar and the editor). Alternatively, the Open Folder icon on the upper-left or entering "Ctrl + O"/"Command + O" will open a pop-up to allow you to navigate and select a folder elsewhere on your computer. +::: +::: + +--- + +![](images/OpenFile.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Unsaved changes to an open file are reflected by on the tab the change in color of the text, and the appearance of a dot. We can click the Save changes button to change this. +::: +::: + +--- + +![](images/SaveChanges.png) + + +--- + +# Secondary Side Bar + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + +::: {.fragment} +::: {.callout-tip title="."} +The secondary side bar is found on the right-side of the screen, to the right of the Editor and Panel windows. It is divided between an upper, and a lower portion. +::: +::: + +## Variables + +::: {.fragment} +::: {.callout-tip title="."} +On the upper-portion of the Secondary Side Bar, we can find the Session window, containing the Variables tab. As you run (execute) lines of code, and different variables, objects and functions are created, these become visible under the variables tab on the upper right. +::: +::: + +--- + +![](images/SessionVariables.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For some types of objects (generally data.frames and other matrix-like objects), you can click on their listing under variables to expand to see additional details about the object (column names, etc.) as well as view a larger version which will appear within the Editor window. +::: +::: + +## Plots + +::: {.fragment} +::: {.callout-tip title="."} +Similarly, any generated Plots or Documents will appear within the Secondary Side Bar, either under Plots (bottom) or Viewer (top) tabs. +::: +::: + +--- + +![](images/SessionPlots.png) + + +--- + +## View + +::: {.fragment} +::: {.callout-tip title="."} +On the upper bar multiple tabs can be found, which we will explore in due time. Most useful to point out is the View tab. If you accidentally close your console, session or plots window, and are trying to get them to reapper, you would need to reselect them from this tab. +::: +::: + +--- + +![](images/28_View.png) + + +--- + +# Activity Bar + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + +::: {.fragment} +::: {.callout-tip title="."} +At the far-left side of the screen, you will find the activity bar, which contains several tabs. Depending on which one you have opened, the contents will be displayed on the primary side bar next to it. +::: +::: + +## Pages + +::: {.fragment} +::: {.callout-tip title="."} +The pages tab and the left-side bar show you everything that is currently within your project folder, including all the folders, and files. Once version control with Git is initiated, new files are relected showing up as green text and a dot, while modified tracked files are reflected by light brown text and a dot. +::: +::: + +--- + +![](images/27_ChangesSinceLastCommit.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The dropdown arrows can be used to open and close specific folders to allow for better organization. There is also a scrollbar on the right-side of the side-bar to scroll through the entire folders contents. +::: +::: + +--- + +![](images/26_MainTab.png) + + +--- + +## Search + +::: {.fragment} +::: {.callout-tip title="."} +The search tab on the left side bar is something that I use routinely. +::: +::: + +--- + +![](images/24_SearchTab.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +It can help locate code that you had been working on, but have since forgotten where it is at. Here is an example of finding the files where I had used a function that needed modifying within a local project folder's files. +::: +::: + +--- + +![](images/25_SearchResults.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Similarly, if you need to replace a particular character string with another, the replace with field below can help simplify the task without having to track down and change 20 lines across 5 files. +::: +::: + +--- + +![](images/24_SearchTab.png) + + +--- + +## Extensions + +::: {.fragment} +::: {.callout-tip title="."} +On the far-left side we can find the Activity bar, which contains several tabs. Which tab you have selected will then dictate the contents of your left side-bar. + +Occupying the left side bar are several tabs. One of these is Extensions, which shows "Plugins" (or the VScode equivalent) that extend the functionality of Positron further. The ones you have installed may vary, but the main ones in context of this course are Air (provides color and highlights syntax for R code to make interpretation easier) as well as Quarto (for rendering the various document types). +::: +::: + +--- + +![](images/29_ExtensionsTab.png) + + +--- + +## Git + +::: {.fragment} +::: {.callout-tip title="."} +The Git tab on the left side bar is where once version control is initiated for the project folder, we can see changes that have occurred to the individual files since the last commit. These changes can be added to a new commit by clicking on the + sign. This will be covered more extensively in the [next section](/course/00_Git/index.qmd) +::: +::: + +--- + +![](images/20_SaveChanges.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Similarly, if you want to discard a change that has occured, the circular arrow will revert to the last commited version. Selecting and pressing the delete button will similarly work. +::: +::: + +--- + +![](images/21_DiscardChanges.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Selecting the ... options will highlight all the various git functions, some of which we will cover more extensively in the [next section](/course/00_Git/index.qmd) and throughout the course. +::: +::: + +--- + +![](images/23_AdditionalGitOptions.png) + + +--- + + +# Wrap-up + +::: {.fragment} +::: {.callout-tip title="."} +In this walk-through, we looked at some of the elements within Positron. Don't worry, you don't need to remember them all or what they do at this point of time, these will come with practice over the first few weeks of the course. + +In the [next section](/course/00_Git/index.qmd), we will take a closer look at using the version control software Git that we have previewed here. +::: +::: + +# Additional Resources + +[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) + +[A brief tour of Positron (YouTube)](https://youtu.be/4Ir_HX4riHw?si=awSUVjdzBPDVR4Iw) + +[Welcome to Positron](https://positron.posit.co/welcome.html) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_Quarto/index.qmd b/course/00_Quarto/index.qmd index 1f111d9..2d07a6e 100644 --- a/course/00_Quarto/index.qmd +++ b/course/00_Quarto/index.qmd @@ -1,370 +1,370 @@ ---- -title: "Introduction to Quarto" -author: "David Rach" -date: 01-21-2026 -format: html -toc: true -toc-depth: 4 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -For the YouTube livestream recording, see [here](https://www.youtube.com/live/VQNFWzKxgdk?si=Lbg1mbbnhYAqjSyZ) - - - -For screen-shot slides, click [here](/course/00_Quarto/slides.qmd) - -# Background - -In the [previous section](/course/00_Git/index.qmd), we briefly introduced Quarto Markdown Documents (.qmd) while working our way through version control concepts. Since we will be using .qmd files extensively throughout this course, this section will explore how we can build on these concepts to modify these files to create a variety of outputs (ranging from Word documents, pdfs, html webpages). We will also take a look at how to use code-chunk arguments to control what code is run or displayed within. - -# Getting Started - -We will start off by creating a a new .QMD document within our GitPractice repository. As we saw in the [previous section](/course/00_Git/index.qmd), the basic elements include: - -1) A [YAML]() header, that dictates formatting -2) The text body, where we can include documentation -3) Code-block chunks, in which we can write code that can be executed, as well as # comments - -![](images/00_BasicQMD.png) - -
- ---- - -## Render/Preview - -The preview button, at the upper-left end of the Editor, is used to render/knit a quarto document. This triggers the process by which code-chunks are run, and then the outputs are cobbled together into the file format type designated by the YAML header. - - -![](images/01_Preview.png) - -
- ---- - -### HTML - -In this case, the YAML header's format argument is set to html. After clicking preview, we can see the various rendering steps appear in the console below. Since no errors occured, the html document was formed succesfully and appears as a file in the left side-bar. Additional, a preview of the document appears in the View tab of the right side-bar, allowing for quick visual inspection. - -![](images/03_Preview.png) - -
- ---- - -Alternatively, we can render a document via the terminal, by entering "quarto render ", followed by the name of the document. - -![](images/02_Preview.png) - -
- ---- - -This results similar process as what we saw with the preview button - -![](images/04_Preview.png) - -
- ---- - -We can also open the .html document via our File Explorer, which will open it within our web browser. - -![](images/05_HTML.png) - -
- ---- - -Quarto documents can be rendered (previewed) in other formats besides html. These include pdf, Word documents (docx), and slides (revealjs). This is set by the format argument within the YAML header. - -### PDF - -By switching the format argument from html to pdf, we can render the document as a pdf - -![](images/06_PDF.png) - -
- ---- - -We can see the pdf is now listed in the list of files, with a preview shown on the right side-bar. - -![](images/06_PDFOutput.png) - -
- ---- - -### Docx - -We can also generate Word documents (.docx) as well. - -![](images/07_Docx.png) - -
- ---- - -In this case, we can see that a Word document file was created, but nothing appears in the View tab. This is because the format is not yet supported for the View tab. We can however open and view the Word document via our File explorer. - -![](images/07_DocxRender.png) - -
- ---- - -Which shows a Word Document style output. - -![](images/07_DocxOutput.png) - -
- ---- - -## YAML - -We can additionally provide additional custom inputs to the YAML header. A couple examples include providing the document author and date. - -![](images/08_Yaml.png) - -
- ---- - -Which we can see are updated after we preview/render. - -![](images/08_Yaml2.png) - -
- ---- - - -## Table of Contents - -In the previous section, we saw that we could provide headings and subheadings to our .qmd file by placing a \# at the start of a line in the text portion of the document. A subheading was designated by a \#\#, with additional hierarchy being designated by appending an additional \#. - - -![](images/09_Headers.png) - -
- ---- - -We can use the heading information to generate a table of contents for our document. To do this, we add a toc argument to the yaml header, and set it to TRUE. -After rendering, it appears on the upper-right side of the document. - -![](images/10_TOC.png) - -
- ---- - -Notice, that the subheaders do not appear currently within the TOC. - -![](images/11_HeaderSubs.png) - -
- ---- - -We can fix this by setting a toc-expand argument in the YAML to true. - -![](images/12_TOCexpanded.png) - -
- ---- - - -## Code Chunk Arguments - -As we briefly touched on in the [last section](/course/00_Git/index.qmd), code-chunks can be modified by including arguments, which affect whether a particular code chunk gets evaluated. In that example, we included a "#| eval: FALSE" to the install commands since we did not want them to be re-run subsequently. We will take a closer look at the other arguments in this section. - -### Eval - -The code-chunk argument, "Eval", is used to determine when a code-chunk get's evaluated. When set to true (or by default if no eval argument is included), the code-chunks contents will be run/executed, and the output will appear. We can see this in the html output, as below the code block, we get back the address of my working directory. - -![](images/13_EvalTRUE.png) - -
- ---- - -When we switch the Eval argument to FALSE, and then render the document, we can see that the code block remains, but we do not get any output for the code contained within. - -In every-day practice, we will "use eval: FALSE" arguments when we want to keep the code for later use, but want to manually run the code contained within ourselves. - -![](images/14_EvalFALSE.png) - -
- ---- - -### Echo - -The code-block argument "echo" dictates whether the code within the code-block is displayed within the document. So in the case when "echo: true", we get both the code displayed, as well as the output that gets returned by the code. - -![](images/16_EchoTRUE.png) - -
- ---- - -By contrast, when "echo: FALSE", we do not have the code displayed, but do get the output of that code being run. - -In daily-practice, "echo: FALSE" gets often used when generating plots that we want to include in the report, without the code that generated them being displayed. - -![](images/17_EchoFALSE.png) - -
- ---- - -### Include - -The next code-chunk argument is include. Unlike echo, which focuses on whether the code is displayed, but still returns the output, include dictates behavior of both the code-block and it's output. Unlike eval however, it will still run the code, which allows it to be available for the next code-chunk that might need it. When we set "include: false", no trace of that code-chunk is present in the document. This is useful when making reports where we do not want to include the code used to generate a particular figure. - -![](images/15_IncludeFALSE.png) - -
- ---- - -By contrast, when we set "include: true", the code block and it's output is once again included within the rendered document. - -![](images/15_IncludeTRUE.png) - -
- ---- - -### Code-Fold - -One of my favorites is "code-fold". When we set it as "code-fold: show", it displays the code, but provides a drop-down arrow that can be closed to compress the code. - -![](images/18_CodeFoldShow.png) - -
- ---- - -In contrast, if we want to make the code-available for those that are interested, but not directly visible, we can set as "code-fold: true" - -![](images/19_CodeFoldTRUE.png) - -
- ---- - - -### Warnings - -Within R, when code is executed, in addition to returning the output, R is capable of returning warnings (when something is not as expected, but not sufficient to elicit an error with a complete stop) or a message (text output that gets displayed, often telling about progress). While these are useful when running code yourself, it can be annoying when generating a report and the 2nd page is a bunch of warning text being displayed. - -For example, when the R package `ggcyto` is loaded via the library call, it will automatically load several other packages, which typically results in these messages being outputted: - -![](images/21_WarningMessageTrue.png) - -
- ---- - -We can therefore set that code-chunk's warning/message arguments to FALSE, therefore silencing the message outputs that would otherwise clutter up our report. - -![](images/20_WarningMessageFalse.png) - -
- ---- - - -## Text Styles - -Quarto primarily uses Markdown for text styling. Consequently, markdown arguments can be used within the text to change how various text appears. - -![](images/22_StylisticElements.png) - -
- ---- - - -For a regular text, *This* single asterisk on each side of a word will italicize. - -![](images/23_Italics.png) - -
- ---- - -When the number of asterisk is doubled, **This** word is bolded. - -![](images/24_Bold.png) - -
- ---- - -When three asterisk are used, ***both*** are applied. - -![](images/25_ItalicBold.png) - -
- ---- - -For an underscore, the [word]{.underline} of interest is surrounded by square brackets "[]", with "{.underline}" adjacent. - - -## Hyperlinks - -You can link to a website by surrounding word of interest in [] and placing the url within () adjacent to it. - -![](images/26_Hyperlinks.png) - -
- ---- - - -## Images - -You can place images by adding the following, as long as the file.path to the image is correctly formatted. In my case, this is why I include images folders within my folders to simplify the copy and paste. - -![](images/27_Images.png) - -
- ---- - - -![](images/28_ImagesArgs.png) - -
- ---- - -# Wrap-up - -We have now briefly looked at various common customizations within a Quarto Markdown Document that can allow us to better document what we are doing, and control whether various code chunk outputs are displayed in the final rendered document. - -In the [next section](/course/00_Homeworks/), we will cover some course logistics by investigate using the Discussions Forums to get community feedback throughout the course, when to use the Issues page, as well as how to open a pull request to submit any completed optional Take-Home problems to get course instructor feedback. - - -# Additional Resources - -[Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) - -[YAML](https://quarto.org/docs/authoring/front-matter.html) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Introduction to Quarto" +author: "David Rach" +date: 01-21-2026 +format: html +toc: true +toc-depth: 4 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://www.youtube.com/live/VQNFWzKxgdk?si=Lbg1mbbnhYAqjSyZ) + + + +For screen-shot slides, click [here](/course/00_Quarto/slides.qmd) + +# Background + +In the [previous section](/course/00_Git/index.qmd), we briefly introduced Quarto Markdown Documents (.qmd) while working our way through version control concepts. Since we will be using .qmd files extensively throughout this course, this section will explore how we can build on these concepts to modify these files to create a variety of outputs (ranging from Word documents, pdfs, html webpages). We will also take a look at how to use code-chunk arguments to control what code is run or displayed within. + +# Getting Started + +We will start off by creating a a new .QMD document within our GitPractice repository. As we saw in the [previous section](/course/00_Git/index.qmd), the basic elements include: + +1) A [YAML]() header, that dictates formatting +2) The text body, where we can include documentation +3) Code-block chunks, in which we can write code that can be executed, as well as # comments + +![](images/00_BasicQMD.png) + +
+ +--- + +## Render/Preview + +The preview button, at the upper-left end of the Editor, is used to render/knit a quarto document. This triggers the process by which code-chunks are run, and then the outputs are cobbled together into the file format type designated by the YAML header. + + +![](images/01_Preview.png) + +
+ +--- + +### HTML + +In this case, the YAML header's format argument is set to html. After clicking preview, we can see the various rendering steps appear in the console below. Since no errors occured, the html document was formed succesfully and appears as a file in the left side-bar. Additional, a preview of the document appears in the View tab of the right side-bar, allowing for quick visual inspection. + +![](images/03_Preview.png) + +
+ +--- + +Alternatively, we can render a document via the terminal, by entering "quarto render ", followed by the name of the document. + +![](images/02_Preview.png) + +
+ +--- + +This results similar process as what we saw with the preview button + +![](images/04_Preview.png) + +
+ +--- + +We can also open the .html document via our File Explorer, which will open it within our web browser. + +![](images/05_HTML.png) + +
+ +--- + +Quarto documents can be rendered (previewed) in other formats besides html. These include pdf, Word documents (docx), and slides (revealjs). This is set by the format argument within the YAML header. + +### PDF + +By switching the format argument from html to pdf, we can render the document as a pdf + +![](images/06_PDF.png) + +
+ +--- + +We can see the pdf is now listed in the list of files, with a preview shown on the right side-bar. + +![](images/06_PDFOutput.png) + +
+ +--- + +### Docx + +We can also generate Word documents (.docx) as well. + +![](images/07_Docx.png) + +
+ +--- + +In this case, we can see that a Word document file was created, but nothing appears in the View tab. This is because the format is not yet supported for the View tab. We can however open and view the Word document via our File explorer. + +![](images/07_DocxRender.png) + +
+ +--- + +Which shows a Word Document style output. + +![](images/07_DocxOutput.png) + +
+ +--- + +## YAML + +We can additionally provide additional custom inputs to the YAML header. A couple examples include providing the document author and date. + +![](images/08_Yaml.png) + +
+ +--- + +Which we can see are updated after we preview/render. + +![](images/08_Yaml2.png) + +
+ +--- + + +## Table of Contents + +In the previous section, we saw that we could provide headings and subheadings to our .qmd file by placing a \# at the start of a line in the text portion of the document. A subheading was designated by a \#\#, with additional hierarchy being designated by appending an additional \#. + + +![](images/09_Headers.png) + +
+ +--- + +We can use the heading information to generate a table of contents for our document. To do this, we add a toc argument to the yaml header, and set it to TRUE. +After rendering, it appears on the upper-right side of the document. + +![](images/10_TOC.png) + +
+ +--- + +Notice, that the subheaders do not appear currently within the TOC. + +![](images/11_HeaderSubs.png) + +
+ +--- + +We can fix this by setting a toc-expand argument in the YAML to true. + +![](images/12_TOCexpanded.png) + +
+ +--- + + +## Code Chunk Arguments + +As we briefly touched on in the [last section](/course/00_Git/index.qmd), code-chunks can be modified by including arguments, which affect whether a particular code chunk gets evaluated. In that example, we included a "#| eval: FALSE" to the install commands since we did not want them to be re-run subsequently. We will take a closer look at the other arguments in this section. + +### Eval + +The code-chunk argument, "Eval", is used to determine when a code-chunk get's evaluated. When set to true (or by default if no eval argument is included), the code-chunks contents will be run/executed, and the output will appear. We can see this in the html output, as below the code block, we get back the address of my working directory. + +![](images/13_EvalTRUE.png) + +
+ +--- + +When we switch the Eval argument to FALSE, and then render the document, we can see that the code block remains, but we do not get any output for the code contained within. + +In every-day practice, we will "use eval: FALSE" arguments when we want to keep the code for later use, but want to manually run the code contained within ourselves. + +![](images/14_EvalFALSE.png) + +
+ +--- + +### Echo + +The code-block argument "echo" dictates whether the code within the code-block is displayed within the document. So in the case when "echo: true", we get both the code displayed, as well as the output that gets returned by the code. + +![](images/16_EchoTRUE.png) + +
+ +--- + +By contrast, when "echo: FALSE", we do not have the code displayed, but do get the output of that code being run. + +In daily-practice, "echo: FALSE" gets often used when generating plots that we want to include in the report, without the code that generated them being displayed. + +![](images/17_EchoFALSE.png) + +
+ +--- + +### Include + +The next code-chunk argument is include. Unlike echo, which focuses on whether the code is displayed, but still returns the output, include dictates behavior of both the code-block and it's output. Unlike eval however, it will still run the code, which allows it to be available for the next code-chunk that might need it. When we set "include: false", no trace of that code-chunk is present in the document. This is useful when making reports where we do not want to include the code used to generate a particular figure. + +![](images/15_IncludeFALSE.png) + +
+ +--- + +By contrast, when we set "include: true", the code block and it's output is once again included within the rendered document. + +![](images/15_IncludeTRUE.png) + +
+ +--- + +### Code-Fold + +One of my favorites is "code-fold". When we set it as "code-fold: show", it displays the code, but provides a drop-down arrow that can be closed to compress the code. + +![](images/18_CodeFoldShow.png) + +
+ +--- + +In contrast, if we want to make the code-available for those that are interested, but not directly visible, we can set as "code-fold: true" + +![](images/19_CodeFoldTRUE.png) + +
+ +--- + + +### Warnings + +Within R, when code is executed, in addition to returning the output, R is capable of returning warnings (when something is not as expected, but not sufficient to elicit an error with a complete stop) or a message (text output that gets displayed, often telling about progress). While these are useful when running code yourself, it can be annoying when generating a report and the 2nd page is a bunch of warning text being displayed. + +For example, when the R package `ggcyto` is loaded via the library call, it will automatically load several other packages, which typically results in these messages being outputted: + +![](images/21_WarningMessageTrue.png) + +
+ +--- + +We can therefore set that code-chunk's warning/message arguments to FALSE, therefore silencing the message outputs that would otherwise clutter up our report. + +![](images/20_WarningMessageFalse.png) + +
+ +--- + + +## Text Styles + +Quarto primarily uses Markdown for text styling. Consequently, markdown arguments can be used within the text to change how various text appears. + +![](images/22_StylisticElements.png) + +
+ +--- + + +For a regular text, *This* single asterisk on each side of a word will italicize. + +![](images/23_Italics.png) + +
+ +--- + +When the number of asterisk is doubled, **This** word is bolded. + +![](images/24_Bold.png) + +
+ +--- + +When three asterisk are used, ***both*** are applied. + +![](images/25_ItalicBold.png) + +
+ +--- + +For an underscore, the [word]{.underline} of interest is surrounded by square brackets "[]", with "{.underline}" adjacent. + + +## Hyperlinks + +You can link to a website by surrounding word of interest in [] and placing the url within () adjacent to it. + +![](images/26_Hyperlinks.png) + +
+ +--- + + +## Images + +You can place images by adding the following, as long as the file.path to the image is correctly formatted. In my case, this is why I include images folders within my folders to simplify the copy and paste. + +![](images/27_Images.png) + +
+ +--- + + +![](images/28_ImagesArgs.png) + +
+ +--- + +# Wrap-up + +We have now briefly looked at various common customizations within a Quarto Markdown Document that can allow us to better document what we are doing, and control whether various code chunk outputs are displayed in the final rendered document. + +In the [next section](/course/00_Homeworks/), we will cover some course logistics by investigate using the Discussions Forums to get community feedback throughout the course, when to use the Issues page, as well as how to open a pull request to submit any completed optional Take-Home problems to get course instructor feedback. + + +# Additional Resources + +[Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) + +[YAML](https://quarto.org/docs/authoring/front-matter.html) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_Quarto/slides.qmd b/course/00_Quarto/slides.qmd index daca079..0c3e888 100644 --- a/course/00_Quarto/slides.qmd +++ b/course/00_Quarto/slides.qmd @@ -1,519 +1,519 @@ ---- -title: "Introduction to Quarto" -author: "David Rach" -date: 02-01-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -# Background - - -::: {.fragment} -::: {.callout-tip title="."} -In the [previous section](/course/00_Git/index.qmd), we briefly introduced Quarto Markdown Documents (.qmd) while working our way through version control concepts. Since we will be using .qmd files extensively throughout this course, this section will explore how we can build on these concepts to modify these files to create a variety of outputs (ranging from Word documents, pdfs, html webpages). We will also take a look at how to use code-chunk arguments to control what code is run or displayed within. -::: -::: - -# Getting Started - -::: {.fragment} -::: {.callout-tip title="."} -We will start off by creating a a new .QMD document within our GitPractice repository. As we saw in the [previous section](/course/00_Git/index.qmd), the basic elements include: - -1) A [YAML]() header, that dictates formatting -2) The text body, where we can include documentation -3) Code-block chunks, in which we can write code that can be executed, as well as # comments - -::: -::: - ---- - -![](images/00_BasicQMD.png) - ---- - -## Render/Preview - -::: {.fragment} -::: {.callout-tip title="."} -The preview button, at the upper-left end of the Editor, is used to render/knit a quarto document. This triggers the process by which code-chunks are run, and then the outputs are cobbled together into the file format type designated by the YAML header. -::: -::: - ---- - -![](images/01_Preview.png) - ---- - -### HTML - -::: {.fragment} -::: {.callout-tip title="."} -In this case, the YAML header's format argument is set to html. After clicking preview, we can see the various rendering steps appear in the console below. Since no errors occured, the html document was formed succesfully and appears as a file in the left side-bar. Additional, a preview of the document appears in the View tab of the right side-bar, allowing for quick visual inspection. -::: -::: - ---- - - -![](images/03_Preview.png) - - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Alternatively, we can render a document via the terminal, by entering "quarto render ", followed by the name of the document. -::: -::: - ---- - -![](images/02_Preview.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -This results similar process as what we saw with the preview button -::: -::: - ---- - -![](images/04_Preview.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can also open the .html document via our File Explorer, which will open it within our web browser. -::: -::: - ---- - -![](images/05_HTML.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Quarto documents can be rendered (previewed) in other formats besides html. These include pdf, Word documents (docx), and slides (revealjs). This is set by the format argument within the YAML header. -::: -::: - -### PDF - -::: {.fragment} -::: {.callout-tip title="."} -By switching the format argument from html to pdf, we can render the document as a pdf -::: -::: - ---- - -![](images/06_PDF.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can see the pdf is now listed in the list of files, with a preview shown on the right side-bar. -::: -::: - ---- - -![](images/06_PDFOutput.png) - ---- - -### Docx - -::: {.fragment} -::: {.callout-tip title="."} -We can also generate Word documents (.docx) as well. -::: -::: - ---- - -![](images/07_Docx.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In this case, we can see that a Word document file was created, but nothing appears in the View tab. This is because the format is not yet supported for the View tab. We can however open and view the Word document via our File explorer. -::: -::: - ---- - -![](images/07_DocxRender.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Which shows a Word Document style output. -::: -::: - ---- - -![](images/07_DocxOutput.png) - ---- - -## YAML - -::: {.fragment} -::: {.callout-tip title="."} -We can additionally provide additional custom inputs to the YAML header. A couple examples include providing the document author and date. -::: -::: - ---- - -![](images/08_Yaml.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Which we can see are updated after we preview/render. -::: -::: - ---- - -![](images/08_Yaml2.png) - ---- - - -## Table of Contents - -::: {.fragment} -::: {.callout-tip title="."} -In the previous section, we saw that we could provide headings and subheadings to our .qmd file by placing a \# at the start of a line in the text portion of the document. A subheading was designated by a \#\#, with additional hierarchy being designated by appending an additional \#. -::: -::: - ---- - -![](images/09_Headers.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can use the heading information to generate a table of contents for our document. To do this, we add a toc argument to the yaml header, and set it to TRUE. -After rendering, it appears on the upper-right side of the document. -::: -::: - ---- - -![](images/10_TOC.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Notice, that the subheaders do not appear currently within the TOC. -::: -::: - ---- - -![](images/11_HeaderSubs.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can fix this by setting a toc-expand argument in the YAML to true. -::: -::: - ---- - -![](images/12_TOCexpanded.png) - ---- - - -## Code Chunk Arguments - -::: {.fragment} -::: {.callout-tip title="."} -As we briefly touched on in the [last section](/course/00_Git/index.qmd), code-chunks can be modified by including arguments, which affect whether a particular code chunk gets evaluated. In that example, we included a "#| eval: FALSE" to the install commands since we did not want them to be re-run subsequently. We will take a closer look at the other arguments in this section. -::: -::: - -### Eval - -::: {.fragment} -::: {.callout-tip title="."} -The code-chunk argument, "Eval", is used to determine when a code-chunk get's evaluated. When set to true (or by default if no eval argument is included), the code-chunks contents will be run/executed, and the output will appear. We can see this in the html output, as below the code block, we get back the address of my working directory. -::: -::: - ---- - -![](images/13_EvalTRUE.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When we switch the Eval argument to FALSE, and then render the document, we can see that the code block remains, but we do not get any output for the code contained within. - -In every-day practice, we will "use eval: FALSE" arguments when we want to keep the code for later use, but want to manually run the code contained within ourselves. -::: -::: - ---- - -![](images/14_EvalFALSE.png) - ---- - -### Echo - -::: {.fragment} -::: {.callout-tip title="."} -The code-block argument "echo" dictates whether the code within the code-block is displayed within the document. So in the case when "echo: true", we get both the code displayed, as well as the output that gets returned by the code. -::: -::: - ---- - -![](images/16_EchoTRUE.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -By contrast, when "echo: FALSE", we do not have the code displayed, but do get the output of that code being run. - -In daily-practice, "echo: FALSE" gets often used when generating plots that we want to include in the report, without the code that generated them being displayed. -::: -::: - ---- - -![](images/17_EchoFALSE.png) - ---- - -### Include - -::: {.fragment} -::: {.callout-tip title="."} -The next code-chunk argument is include. Unlike echo, which focuses on whether the code is displayed, but still returns the output, include dictates behavior of both the code-block and it's output. Unlike eval however, it will still run the code, which allows it to be available for the next code-chunk that might need it. When we set "include: false", no trace of that code-chunk is present in the document. This is useful when making reports where we do not want to include the code used to generate a particular figure. -::: -::: - ---- - -![](images/15_IncludeFALSE.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -By contrast, when we set "include: true", the code block and it's output is once again included within the rendered document. -::: -::: - ---- - -![](images/15_IncludeTRUE.png) - ---- - -### Code-Fold - -::: {.fragment} -::: {.callout-tip title="."} -One of my favorites is "code-fold". When we set it as "code-fold: show", it displays the code, but provides a drop-down arrow that can be closed to compress the code. -::: -::: - ---- - -![](images/18_CodeFoldShow.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In contrast, if we want to make the code-available for those that are interested, but not directly visible, we can set as "code-fold: true" -::: -::: - ---- - -![](images/19_CodeFoldTRUE.png) - ---- - -### Warnings - -::: {.fragment} -::: {.callout-tip title="."} -Within R, when code is executed, in addition to returning the output, R is capable of returning warnings (when something is not as expected, but not sufficient to elicit an error with a complete stop) or a message (text output that gets displayed, often telling about progress). While these are useful when running code yourself, it can be annoying when generating a report and the 2nd page is a bunch of warning text being displayed. - -For example, when the R package `ggcyto` is loaded via the library call, it will automatically load several other packages, which typically results in these messages being outputted: -::: -::: - ---- - -![](images/21_WarningMessageTrue.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can therefore set that code-chunk's warning/message arguments to FALSE, therefore silencing the message outputs that would otherwise clutter up our report. -::: -::: - ---- - -![](images/20_WarningMessageFalse.png) - ---- - - -## Text Styles - -::: {.fragment} -::: {.callout-tip title="."} -Quarto primarily uses Markdown for text styling. Consequently, markdown arguments can be used within the text to change how various text appears. -::: -::: - ---- - -![](images/22_StylisticElements.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For a regular text, *This* single asterisk on each side of a word will italicize. -::: -::: - ---- - -![](images/23_Italics.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When the number of asterisk is doubled, **This** word is bolded. -::: -::: - ---- - -![](images/24_Bold.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When three asterisk are used, ***both*** are applied. -::: -::: - ---- - -![](images/25_ItalicBold.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For an underscore, the [word]{.underline} of interest is surrounded by square brackets "[]", with "{.underline}" adjacent. -::: -::: - -## Hyperlinks - -::: {.fragment} -::: {.callout-tip title="."} -You can link to a website by surrounding word of interest in [] and placing the url within () adjacent to it. -::: -::: - ---- - -![](images/26_Hyperlinks.png) - ---- - - -## Images - -::: {.fragment} -::: {.callout-tip title="."} -You can place images by adding the following, as long as the file.path to the image is correctly formatted. In my case, this is why I include images folders within my folders to simplify the copy and paste. -::: -::: - ---- - -![](images/27_Images.png) - ---- - -![](images/28_ImagesArgs.png) - ---- - -# Wrap-up - -::: {.fragment} -::: {.callout-tip title="."} -We have now briefly looked at various common customizations within a Quarto Markdown Document that can allow us to better document what we are doing, and control whether various code chunk outputs are displayed in the final rendered document. - -In the [next section](/course/00_Homeworks/), we will cover some course logistics by investigate using the Discussions Forums to get community feedback throughout the course, when to use the Issues page, as well as how to open a pull request to submit any completed optional Take-Home problems to get course instructor feedback. -::: -::: - -# Additional Resources - -[Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) - -[YAML](https://quarto.org/docs/authoring/front-matter.html) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Introduction to Quarto" +author: "David Rach" +date: 02-01-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +# Background + + +::: {.fragment} +::: {.callout-tip title="."} +In the [previous section](/course/00_Git/index.qmd), we briefly introduced Quarto Markdown Documents (.qmd) while working our way through version control concepts. Since we will be using .qmd files extensively throughout this course, this section will explore how we can build on these concepts to modify these files to create a variety of outputs (ranging from Word documents, pdfs, html webpages). We will also take a look at how to use code-chunk arguments to control what code is run or displayed within. +::: +::: + +# Getting Started + +::: {.fragment} +::: {.callout-tip title="."} +We will start off by creating a a new .QMD document within our GitPractice repository. As we saw in the [previous section](/course/00_Git/index.qmd), the basic elements include: + +1) A [YAML]() header, that dictates formatting +2) The text body, where we can include documentation +3) Code-block chunks, in which we can write code that can be executed, as well as # comments + +::: +::: + +--- + +![](images/00_BasicQMD.png) + +--- + +## Render/Preview + +::: {.fragment} +::: {.callout-tip title="."} +The preview button, at the upper-left end of the Editor, is used to render/knit a quarto document. This triggers the process by which code-chunks are run, and then the outputs are cobbled together into the file format type designated by the YAML header. +::: +::: + +--- + +![](images/01_Preview.png) + +--- + +### HTML + +::: {.fragment} +::: {.callout-tip title="."} +In this case, the YAML header's format argument is set to html. After clicking preview, we can see the various rendering steps appear in the console below. Since no errors occured, the html document was formed succesfully and appears as a file in the left side-bar. Additional, a preview of the document appears in the View tab of the right side-bar, allowing for quick visual inspection. +::: +::: + +--- + + +![](images/03_Preview.png) + + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, we can render a document via the terminal, by entering "quarto render ", followed by the name of the document. +::: +::: + +--- + +![](images/02_Preview.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This results similar process as what we saw with the preview button +::: +::: + +--- + +![](images/04_Preview.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can also open the .html document via our File Explorer, which will open it within our web browser. +::: +::: + +--- + +![](images/05_HTML.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Quarto documents can be rendered (previewed) in other formats besides html. These include pdf, Word documents (docx), and slides (revealjs). This is set by the format argument within the YAML header. +::: +::: + +### PDF + +::: {.fragment} +::: {.callout-tip title="."} +By switching the format argument from html to pdf, we can render the document as a pdf +::: +::: + +--- + +![](images/06_PDF.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can see the pdf is now listed in the list of files, with a preview shown on the right side-bar. +::: +::: + +--- + +![](images/06_PDFOutput.png) + +--- + +### Docx + +::: {.fragment} +::: {.callout-tip title="."} +We can also generate Word documents (.docx) as well. +::: +::: + +--- + +![](images/07_Docx.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this case, we can see that a Word document file was created, but nothing appears in the View tab. This is because the format is not yet supported for the View tab. We can however open and view the Word document via our File explorer. +::: +::: + +--- + +![](images/07_DocxRender.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Which shows a Word Document style output. +::: +::: + +--- + +![](images/07_DocxOutput.png) + +--- + +## YAML + +::: {.fragment} +::: {.callout-tip title="."} +We can additionally provide additional custom inputs to the YAML header. A couple examples include providing the document author and date. +::: +::: + +--- + +![](images/08_Yaml.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Which we can see are updated after we preview/render. +::: +::: + +--- + +![](images/08_Yaml2.png) + +--- + + +## Table of Contents + +::: {.fragment} +::: {.callout-tip title="."} +In the previous section, we saw that we could provide headings and subheadings to our .qmd file by placing a \# at the start of a line in the text portion of the document. A subheading was designated by a \#\#, with additional hierarchy being designated by appending an additional \#. +::: +::: + +--- + +![](images/09_Headers.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can use the heading information to generate a table of contents for our document. To do this, we add a toc argument to the yaml header, and set it to TRUE. +After rendering, it appears on the upper-right side of the document. +::: +::: + +--- + +![](images/10_TOC.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Notice, that the subheaders do not appear currently within the TOC. +::: +::: + +--- + +![](images/11_HeaderSubs.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can fix this by setting a toc-expand argument in the YAML to true. +::: +::: + +--- + +![](images/12_TOCexpanded.png) + +--- + + +## Code Chunk Arguments + +::: {.fragment} +::: {.callout-tip title="."} +As we briefly touched on in the [last section](/course/00_Git/index.qmd), code-chunks can be modified by including arguments, which affect whether a particular code chunk gets evaluated. In that example, we included a "#| eval: FALSE" to the install commands since we did not want them to be re-run subsequently. We will take a closer look at the other arguments in this section. +::: +::: + +### Eval + +::: {.fragment} +::: {.callout-tip title="."} +The code-chunk argument, "Eval", is used to determine when a code-chunk get's evaluated. When set to true (or by default if no eval argument is included), the code-chunks contents will be run/executed, and the output will appear. We can see this in the html output, as below the code block, we get back the address of my working directory. +::: +::: + +--- + +![](images/13_EvalTRUE.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When we switch the Eval argument to FALSE, and then render the document, we can see that the code block remains, but we do not get any output for the code contained within. + +In every-day practice, we will "use eval: FALSE" arguments when we want to keep the code for later use, but want to manually run the code contained within ourselves. +::: +::: + +--- + +![](images/14_EvalFALSE.png) + +--- + +### Echo + +::: {.fragment} +::: {.callout-tip title="."} +The code-block argument "echo" dictates whether the code within the code-block is displayed within the document. So in the case when "echo: true", we get both the code displayed, as well as the output that gets returned by the code. +::: +::: + +--- + +![](images/16_EchoTRUE.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +By contrast, when "echo: FALSE", we do not have the code displayed, but do get the output of that code being run. + +In daily-practice, "echo: FALSE" gets often used when generating plots that we want to include in the report, without the code that generated them being displayed. +::: +::: + +--- + +![](images/17_EchoFALSE.png) + +--- + +### Include + +::: {.fragment} +::: {.callout-tip title="."} +The next code-chunk argument is include. Unlike echo, which focuses on whether the code is displayed, but still returns the output, include dictates behavior of both the code-block and it's output. Unlike eval however, it will still run the code, which allows it to be available for the next code-chunk that might need it. When we set "include: false", no trace of that code-chunk is present in the document. This is useful when making reports where we do not want to include the code used to generate a particular figure. +::: +::: + +--- + +![](images/15_IncludeFALSE.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +By contrast, when we set "include: true", the code block and it's output is once again included within the rendered document. +::: +::: + +--- + +![](images/15_IncludeTRUE.png) + +--- + +### Code-Fold + +::: {.fragment} +::: {.callout-tip title="."} +One of my favorites is "code-fold". When we set it as "code-fold: show", it displays the code, but provides a drop-down arrow that can be closed to compress the code. +::: +::: + +--- + +![](images/18_CodeFoldShow.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In contrast, if we want to make the code-available for those that are interested, but not directly visible, we can set as "code-fold: true" +::: +::: + +--- + +![](images/19_CodeFoldTRUE.png) + +--- + +### Warnings + +::: {.fragment} +::: {.callout-tip title="."} +Within R, when code is executed, in addition to returning the output, R is capable of returning warnings (when something is not as expected, but not sufficient to elicit an error with a complete stop) or a message (text output that gets displayed, often telling about progress). While these are useful when running code yourself, it can be annoying when generating a report and the 2nd page is a bunch of warning text being displayed. + +For example, when the R package `ggcyto` is loaded via the library call, it will automatically load several other packages, which typically results in these messages being outputted: +::: +::: + +--- + +![](images/21_WarningMessageTrue.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can therefore set that code-chunk's warning/message arguments to FALSE, therefore silencing the message outputs that would otherwise clutter up our report. +::: +::: + +--- + +![](images/20_WarningMessageFalse.png) + +--- + + +## Text Styles + +::: {.fragment} +::: {.callout-tip title="."} +Quarto primarily uses Markdown for text styling. Consequently, markdown arguments can be used within the text to change how various text appears. +::: +::: + +--- + +![](images/22_StylisticElements.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For a regular text, *This* single asterisk on each side of a word will italicize. +::: +::: + +--- + +![](images/23_Italics.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When the number of asterisk is doubled, **This** word is bolded. +::: +::: + +--- + +![](images/24_Bold.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When three asterisk are used, ***both*** are applied. +::: +::: + +--- + +![](images/25_ItalicBold.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For an underscore, the [word]{.underline} of interest is surrounded by square brackets "[]", with "{.underline}" adjacent. +::: +::: + +## Hyperlinks + +::: {.fragment} +::: {.callout-tip title="."} +You can link to a website by surrounding word of interest in [] and placing the url within () adjacent to it. +::: +::: + +--- + +![](images/26_Hyperlinks.png) + +--- + + +## Images + +::: {.fragment} +::: {.callout-tip title="."} +You can place images by adding the following, as long as the file.path to the image is correctly formatted. In my case, this is why I include images folders within my folders to simplify the copy and paste. +::: +::: + +--- + +![](images/27_Images.png) + +--- + +![](images/28_ImagesArgs.png) + +--- + +# Wrap-up + +::: {.fragment} +::: {.callout-tip title="."} +We have now briefly looked at various common customizations within a Quarto Markdown Document that can allow us to better document what we are doing, and control whether various code chunk outputs are displayed in the final rendered document. + +In the [next section](/course/00_Homeworks/), we will cover some course logistics by investigate using the Discussions Forums to get community feedback throughout the course, when to use the Issues page, as well as how to open a pull request to submit any completed optional Take-Home problems to get course instructor feedback. +::: +::: + +# Additional Resources + +[Quarto Markdown](https://quarto.org/docs/authoring/markdown-basics.html#overview) + +[YAML](https://quarto.org/docs/authoring/front-matter.html) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_WorkstationSetup/.DS_Store b/course/00_WorkstationSetup/.DS_Store deleted file mode 100644 index c77a9d1..0000000 Binary files a/course/00_WorkstationSetup/.DS_Store and /dev/null differ diff --git a/course/00_WorkstationSetup/Linux.qmd b/course/00_WorkstationSetup/Linux.qmd index 57da3a0..fba2538 100644 --- a/course/00_WorkstationSetup/Linux.qmd +++ b/course/00_WorkstationSetup/Linux.qmd @@ -1,413 +1,413 @@ ---- -title: "Installing Software on Linux" -author: "David Rach" -date: 01-21-2026 -format: html -toc: true -toc-depth: 4 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -For the YouTube livestream recording, see [here](https://www.youtube.com/live/xZtvnQ6OsWM?si=1Vo-ajnf33HHHePJ) - - - -For screen-shot slides, click [here](/course/00_WorkstationSetup/LinuxSlides.qmd) - -This is the software installation walkthrough for those whose computers are running Linux. First off, welcome! Based on our pre-course interest form, there was a suprising number of you daily-drivers out there! However, a CytometryInR interest form is unlikely to be representative of the general population, so please stash all Year of the Linux desktop banners until further notice. - -![](/course/00_WorkstationSetup/images/ComputerOS.png){width=100%} - -
- ---- - -# Background - -If you are daily-driving Linux, you are likely not a stranger to the process of getting software installed on your particular distribution. - -When it comes to installing [R website](https://www.r-project.org/), the R project supports packaging formats for both Debian (including Ubuntu, Linux Mint, etc) and RHEL (including Fedora) based-distributions. The supported branch for SUSE has not been active since 2012. This is similarly the case when installing [Positron](https://positron.posit.co/). Depending on your distribution, you might also need to install [Git](https://git-scm.com/) via your package manager. - -I daily-drive Debian stable (Trixie), so this walk-through documents the installation process for the Debian branch. I plan to circle back with a Fedora version, but if that doesn't occur by the publishing time, I refer you to the R for Linux [documentation](https://cran.r-project.org/bin/linux/fedora/#fedora) to help get you started. - -
- ---- - -# Getting Started - -## Debian-based Distros - -### Installing R - -To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. - -![](images/Linux/01_RLanding.png) - -
- ---- - -On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. - -![](images/Linux/02_Mirror.png) - -
- ---- - -Once this is done, select your Linux Distro (or one that shares your package managers format). - -![](images/Linux/03_Debian.png) - -
- ---- - -On the landing page, you will find a bunch of relevant installation information, which is worthwhile giving a read-through when you have time. - -![](images/Linux/04_Landing.png) - -
- ---- - -The process to successfully install R can be summarized as follows: - -Update apt/sources.list to include the CRAN repository (allowing access to R packages) - -![](images/Linux/08_AptSources.png) - -
- ---- - -Since we are running on Debian stable (Trixie), we would add the following line to sources.list - -![](images/Linux/07_TrixieRepo.png) - -
- ---- - -So in practice, open sources.list: - -![](images/Linux/09_EditAptSources.png) - -
- ---- - -Paste the line, and "Ctrl + O"; "Enter"; "Ctrl + X" to save the changes. - -![](images/Linux/10_UpdatedEditAptSources.png) - -
- ---- - -Next, we will need to retrieve the keyID used to sign. This can be fetched from Ubuntu via the terminal. - -![](images/Linux/06_SecureAptKey.png) - -
- ---- - -![](images/Linux/12_AptKey.png) - -
- ---- - -Then we need to export and write it - -![](images/Linux/12_AptKey2.png) - -
- ---- - -Which if successful, will display the public key. - -![](images/Linux/12_PublicKey.png) - -
- ---- - -With the above set up, we can proceed via our apt package manager to install both r-base and r-base-dev (which contains the equivalent of Rtools for Windows, or Xcode Command Line Tools for macOS). - -![](images/Linux/05_BaseR.png) - -
- ---- - -![](images/Linux/13_InstallBaseAndDev.png) - -
- ---- - -![](images/Linux/13_Install.png) - -
- ---- - -And if all goes well, R should now be installed. - -## Installing Git - -```{r} -# sudo apt install git -``` - -## Installing Positron - -Finally, you will need to install [Positron](https://positron.posit.co/). It will be the integrated development environment (IDE) we will be using for the course. - -First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. - -![](images/Windows/25_Positron.png) - -
- ---- - -You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). - -![](images/Linux/15_TermsService.png) - - -
- ---- - -With the license accepted, you will be able to select distribution and architecture. - -![](images/Linux/16_LinuxFlavor.png) - -
- ---- - -Once the Download completes, proceed to install the .deb package as you would nornally. GUI example via Discover below. - -![](images/Linux/17_DebPackageInstall.png) - -
- ---- - -Depending on your configurations, you may be asked to exert your sudo powers. - -![](images/Linux/18_Password.png) - -
- ---- - -Once this completes, you should now be able to launch the software for the first time. - -![](images/Linux/19_InstallSuccess.png) - -
- ---- - -# Connecting GitHub and Positron - -Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected. - -When opening Positron for the first time, you will encounter the following view: - -![](images/Linux/20_PositronStart.png) - -
- ---- - -We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right. - - -![](images/Linux/20_PositronStart.png) - -
- ---- - -Then select the most recent/up-to-date R version. - -![](images/Linux/21_R.png) - -
- ---- - -R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) - -![](images/Linux/22_RSuccess.png) - -
- ---- - -Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. - -Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. - - -![](images/Linux/23_GitHub.png) - -
- ---- - -Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. - -![](images/Linux/24_Code.png) - -
- ---- - -If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. - - -![](images/Linux/25_GitHubAccount.png) - -
- ---- - -You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. - -![](images/Linux/26_EnterNumber.png) - -
- ---- - -And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. - -![](images/Linux/27_Confirm.png) - -
- ---- - -And if all works out, you should see the following succes page - -![](images/Linux/28_ConfirmationPage.png) - -
- ---- - -Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. - -![](images/Linux/29_PositronSuccess.png) - -
- ---- - -# New Folder from Git - -With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. - -To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option - -![](images/MacOS/24.png) - -
- ---- - -Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" - -![](images/FolderFromGit1.png) - -
- ---- - -You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. - -![](images/Import2.png) - -
- ---- - -You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. - -![](images/MacOS/28.png) - -
- ---- - -And with that done, you should now see the forked Cytometry in R course contents appear within Positron. - -![](images/Import2Done.png) - -
- ---- - -We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" - -![](images/FolderFromGit2.png) - -
- ---- - -After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. - -![](images/Import2.png) - -
- ---- - -And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. - -![](images/Import2Done.png) - -
- ---- - -# Wrap-up - -In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. - -In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. - -
- ---- - -# Additional Resources - -[How to Download and Install Software on Linux](https://youtu.be/lC4d4EpMMxg?si=9TeFkwFzrRbzA-Ma) - -[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) - -[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) - -[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) - - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Installing Software on Linux" +author: "David Rach" +date: 01-21-2026 +format: html +toc: true +toc-depth: 4 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://www.youtube.com/live/xZtvnQ6OsWM?si=1Vo-ajnf33HHHePJ) + + + +For screen-shot slides, click [here](/course/00_WorkstationSetup/LinuxSlides.qmd) + +This is the software installation walkthrough for those whose computers are running Linux. First off, welcome! Based on our pre-course interest form, there was a suprising number of you daily-drivers out there! However, a CytometryInR interest form is unlikely to be representative of the general population, so please stash all Year of the Linux desktop banners until further notice. + +![](/course/00_WorkstationSetup/images/ComputerOS.png){width=100%} + +
+ +--- + +# Background + +If you are daily-driving Linux, you are likely not a stranger to the process of getting software installed on your particular distribution. + +When it comes to installing [R website](https://www.r-project.org/), the R project supports packaging formats for both Debian (including Ubuntu, Linux Mint, etc) and RHEL (including Fedora) based-distributions. The supported branch for SUSE has not been active since 2012. This is similarly the case when installing [Positron](https://positron.posit.co/). Depending on your distribution, you might also need to install [Git](https://git-scm.com/) via your package manager. + +I daily-drive Debian stable (Trixie), so this walk-through documents the installation process for the Debian branch. I plan to circle back with a Fedora version, but if that doesn't occur by the publishing time, I refer you to the R for Linux [documentation](https://cran.r-project.org/bin/linux/fedora/#fedora) to help get you started. + +
+ +--- + +# Getting Started + +## Debian-based Distros + +### Installing R + +To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. + +![](images/Linux/01_RLanding.png) + +
+ +--- + +On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. + +![](images/Linux/02_Mirror.png) + +
+ +--- + +Once this is done, select your Linux Distro (or one that shares your package managers format). + +![](images/Linux/03_Debian.png) + +
+ +--- + +On the landing page, you will find a bunch of relevant installation information, which is worthwhile giving a read-through when you have time. + +![](images/Linux/04_Landing.png) + +
+ +--- + +The process to successfully install R can be summarized as follows: + +Update apt/sources.list to include the CRAN repository (allowing access to R packages) + +![](images/Linux/08_AptSources.png) + +
+ +--- + +Since we are running on Debian stable (Trixie), we would add the following line to sources.list + +![](images/Linux/07_TrixieRepo.png) + +
+ +--- + +So in practice, open sources.list: + +![](images/Linux/09_EditAptSources.png) + +
+ +--- + +Paste the line, and "Ctrl + O"; "Enter"; "Ctrl + X" to save the changes. + +![](images/Linux/10_UpdatedEditAptSources.png) + +
+ +--- + +Next, we will need to retrieve the keyID used to sign. This can be fetched from Ubuntu via the terminal. + +![](images/Linux/06_SecureAptKey.png) + +
+ +--- + +![](images/Linux/12_AptKey.png) + +
+ +--- + +Then we need to export and write it + +![](images/Linux/12_AptKey2.png) + +
+ +--- + +Which if successful, will display the public key. + +![](images/Linux/12_PublicKey.png) + +
+ +--- + +With the above set up, we can proceed via our apt package manager to install both r-base and r-base-dev (which contains the equivalent of Rtools for Windows, or Xcode Command Line Tools for macOS). + +![](images/Linux/05_BaseR.png) + +
+ +--- + +![](images/Linux/13_InstallBaseAndDev.png) + +
+ +--- + +![](images/Linux/13_Install.png) + +
+ +--- + +And if all goes well, R should now be installed. + +## Installing Git + +```{r} +# sudo apt install git +``` + +## Installing Positron + +Finally, you will need to install [Positron](https://positron.posit.co/). It will be the integrated development environment (IDE) we will be using for the course. + +First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. + +![](images/Windows/25_Positron.png) + +
+ +--- + +You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). + +![](images/Linux/15_TermsService.png) + + +
+ +--- + +With the license accepted, you will be able to select distribution and architecture. + +![](images/Linux/16_LinuxFlavor.png) + +
+ +--- + +Once the Download completes, proceed to install the .deb package as you would nornally. GUI example via Discover below. + +![](images/Linux/17_DebPackageInstall.png) + +
+ +--- + +Depending on your configurations, you may be asked to exert your sudo powers. + +![](images/Linux/18_Password.png) + +
+ +--- + +Once this completes, you should now be able to launch the software for the first time. + +![](images/Linux/19_InstallSuccess.png) + +
+ +--- + +# Connecting GitHub and Positron + +Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected. + +When opening Positron for the first time, you will encounter the following view: + +![](images/Linux/20_PositronStart.png) + +
+ +--- + +We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right. + + +![](images/Linux/20_PositronStart.png) + +
+ +--- + +Then select the most recent/up-to-date R version. + +![](images/Linux/21_R.png) + +
+ +--- + +R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) + +![](images/Linux/22_RSuccess.png) + +
+ +--- + +Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. + +Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. + + +![](images/Linux/23_GitHub.png) + +
+ +--- + +Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. + +![](images/Linux/24_Code.png) + +
+ +--- + +If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. + + +![](images/Linux/25_GitHubAccount.png) + +
+ +--- + +You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. + +![](images/Linux/26_EnterNumber.png) + +
+ +--- + +And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. + +![](images/Linux/27_Confirm.png) + +
+ +--- + +And if all works out, you should see the following succes page + +![](images/Linux/28_ConfirmationPage.png) + +
+ +--- + +Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. + +![](images/Linux/29_PositronSuccess.png) + +
+ +--- + +# New Folder from Git + +With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. + +To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option + +![](images/MacOS/24.png) + +
+ +--- + +Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" + +![](images/FolderFromGit1.png) + +
+ +--- + +You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. + +![](images/Import2.png) + +
+ +--- + +You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. + +![](images/MacOS/28.png) + +
+ +--- + +And with that done, you should now see the forked Cytometry in R course contents appear within Positron. + +![](images/Import2Done.png) + +
+ +--- + +We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" + +![](images/FolderFromGit2.png) + +
+ +--- + +After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. + +![](images/Import2.png) + +
+ +--- + +And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. + +![](images/Import2Done.png) + +
+ +--- + +# Wrap-up + +In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. + +In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. + +
+ +--- + +# Additional Resources + +[How to Download and Install Software on Linux](https://youtu.be/lC4d4EpMMxg?si=9TeFkwFzrRbzA-Ma) + +[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) + +[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) + +[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) + + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_WorkstationSetup/LinuxSlides.qmd b/course/00_WorkstationSetup/LinuxSlides.qmd index 77d36af..560601a 100644 --- a/course/00_WorkstationSetup/LinuxSlides.qmd +++ b/course/00_WorkstationSetup/LinuxSlides.qmd @@ -1,568 +1,568 @@ ---- -title: "Installing Software on Linux" -author: "David Rach" -date: 02-01-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -For screen-shot slide format, click [here](/course/00_WorkstationSetup/LinuxSlides.qmd) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -::: {.fragment} -::: {.callout-tip title="."} - -This is the software installation walkthrough for those whose computers are running Linux. First off, welcome! Based on our pre-course interest form, there was a suprising number of you daily-drivers out there! However, a CytometryInR interest form is unlikely to be representative of the general population, so please stash all Year of the Linux desktop banners until further notice. -::: -::: - ---- - -![](/course/00_WorkstationSetup/images/ComputerOS.png) - ---- - -# Background - -::: {.fragment} -::: {.callout-tip title="."} -If you are daily-driving Linux, you are likely not a stranger to the process of getting software installed on your particular distribution. - -When it comes to installing [R website](https://www.r-project.org/), the R project supports packaging formats for both Debian (including Ubuntu, Linux Mint, etc) and RHEL (including Fedora) based-distributions. The supported branch for SUSE has not been active since 2012. This is similarly the case when installing [Positron](https://positron.posit.co/). Depending on your distribution, you might also need to install [Git](https://git-scm.com/) via your package manager. - -I daily-drive Debian stable (Trixie), so this walk-through documents the installation process for the Debian branch. I plan to circle back with a Fedora version, but if that doesn't occur by the publishing time, I refer you to the R for Linux [documentation](https://cran.r-project.org/bin/linux/fedora/#fedora) to help get you started. -::: -::: - ---- - -# Getting Started - -## Debian-based Distros - -### Installing R - -::: {.fragment} -::: {.callout-tip title="."} -To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. -::: -::: - ---- - -![](images/Linux/01_RLanding.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. -::: -::: - ---- - -![](images/Linux/02_Mirror.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once this is done, select your Linux Distro (or one that shares your package managers format). -::: -::: - ---- - -![](images/Linux/03_Debian.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -On the landing page, you will find a bunch of relevant installation information, which is worthwhile giving a read-through when you have time. -::: -::: - ---- - -![](images/Linux/04_Landing.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The process to successfully install R can be summarized as follows: - -Update apt/sources.list to include the CRAN repository (allowing access to R packages) -::: -::: - ---- - -![](images/Linux/08_AptSources.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Since we are running on Debian stable (Trixie), we would add the following line to sources.list -::: -::: - ---- - -![](images/Linux/07_TrixieRepo.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -So in practice, open sources.list: -::: -::: - ---- - -![](images/Linux/09_EditAptSources.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Paste the line, and "Ctrl + O"; "Enter"; "Ctrl + X" to save the changes. -::: -::: - ---- - -![](images/Linux/10_UpdatedEditAptSources.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next, we will need to retrieve the keyID used to sign. This can be fetched from Ubuntu via the terminal. -::: -::: - ---- - -![](images/Linux/06_SecureAptKey.png) - ---- - -![](images/Linux/12_AptKey.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Then we need to export and write it -::: -::: - ---- - -![](images/Linux/12_AptKey2.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Which if successful, will display the public key. -::: -::: - ---- - -![](images/Linux/12_PublicKey.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -With the above set up, we can proceed via our apt package manager to install both r-base and r-base-dev (which contains the equivalent of Rtools for Windows, or Xcode Command Line Tools for macOS). -::: -::: - ---- - -![](images/Linux/05_BaseR.png) - ---- - -![](images/Linux/13_InstallBaseAndDev.png) - ---- - -![](images/Linux/13_Install.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And if all goes well, R should now be installed. -::: -::: - -## Installing Git - -```{r} -# sudo apt install git -``` - -## Installing Positron - -::: {.fragment} -::: {.callout-tip title="."} -Finally, you will need to install [Positron](https://positron.posit.co/). It will be the integrated development environment (IDE) we will be using for the course. - -First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. -::: -::: - ---- - -![](images/Windows/25_Positron.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). -::: -::: - ---- - -![](images/Linux/15_TermsService.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -With the license accepted, you will be able to select distribution and architecture. -::: -::: - ---- - -![](images/Linux/16_LinuxFlavor.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once the Download completes, proceed to install the .deb package as you would nornally. GUI example via Discover below. -::: -::: - ---- - -![](images/Linux/17_DebPackageInstall.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Depending on your configurations, you may be asked to exert your sudo powers. -::: -::: - ---- - -![](images/Linux/18_Password.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once this completes, you should now be able to launch the software for the first time. -::: -::: - ---- - -![](images/Linux/19_InstallSuccess.png) - ---- - -# Connecting GitHub and Positron - -::: {.fragment} -::: {.callout-tip title="."} -Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected. - -When opening Positron for the first time, you will encounter the following view: -::: -::: - ---- - -![](images/Linux/20_PositronStart.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right. -::: -::: - ---- - -![](images/Linux/20_PositronStart.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Then select the most recent/up-to-date R version. -::: -::: - ---- - -![](images/Linux/21_R.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) -::: -::: - ---- - -![](images/Linux/22_RSuccess.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. - -Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. -::: -::: - ---- - -![](images/Linux/23_GitHub.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. -::: -::: - ---- - -![](images/Linux/24_Code.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. -::: -::: - ---- - -![](images/Linux/25_GitHubAccount.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. -::: -::: - ---- - -![](images/Linux/26_EnterNumber.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. -::: -::: - ---- - -![](images/Linux/27_Confirm.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And if all works out, you should see the following succes page -::: -::: - ---- - -![](images/Linux/28_ConfirmationPage.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. -::: -::: - ---- - -![](images/Linux/29_PositronSuccess.png) - ---- - -# New Folder from Git - -::: {.fragment} -::: {.callout-tip title="."} -With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. - -To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option -::: -::: - ---- - -![](images/MacOS/24.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" -::: -::: - ---- - -![](images/FolderFromGit1.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. -::: -::: - ---- - -![](images/Import2.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. -::: -::: - ---- - -![](images/MacOS/28.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And with that done, you should now see the forked Cytometry in R course contents appear within Positron. -::: -::: - ---- - -![](images/Import2Done.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" -::: -::: - ---- - -![](images/FolderFromGit2.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. -::: -::: - ---- - -![](images/Import2.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. -::: -::: - ---- - -![](images/Import2Done.png) - ---- - -# Wrap-up - -::: {.fragment} -::: {.callout-tip title="."} -In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. - -In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. -::: -::: - ---- - -# Additional Resources - -[How to Download and Install Software on Linux](https://youtu.be/lC4d4EpMMxg?si=9TeFkwFzrRbzA-Ma) - -[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) - -[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) - -[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) - - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Installing Software on Linux" +author: "David Rach" +date: 02-01-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +For screen-shot slide format, click [here](/course/00_WorkstationSetup/LinuxSlides.qmd) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +::: {.fragment} +::: {.callout-tip title="."} + +This is the software installation walkthrough for those whose computers are running Linux. First off, welcome! Based on our pre-course interest form, there was a suprising number of you daily-drivers out there! However, a CytometryInR interest form is unlikely to be representative of the general population, so please stash all Year of the Linux desktop banners until further notice. +::: +::: + +--- + +![](/course/00_WorkstationSetup/images/ComputerOS.png) + +--- + +# Background + +::: {.fragment} +::: {.callout-tip title="."} +If you are daily-driving Linux, you are likely not a stranger to the process of getting software installed on your particular distribution. + +When it comes to installing [R website](https://www.r-project.org/), the R project supports packaging formats for both Debian (including Ubuntu, Linux Mint, etc) and RHEL (including Fedora) based-distributions. The supported branch for SUSE has not been active since 2012. This is similarly the case when installing [Positron](https://positron.posit.co/). Depending on your distribution, you might also need to install [Git](https://git-scm.com/) via your package manager. + +I daily-drive Debian stable (Trixie), so this walk-through documents the installation process for the Debian branch. I plan to circle back with a Fedora version, but if that doesn't occur by the publishing time, I refer you to the R for Linux [documentation](https://cran.r-project.org/bin/linux/fedora/#fedora) to help get you started. +::: +::: + +--- + +# Getting Started + +## Debian-based Distros + +### Installing R + +::: {.fragment} +::: {.callout-tip title="."} +To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. +::: +::: + +--- + +![](images/Linux/01_RLanding.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. +::: +::: + +--- + +![](images/Linux/02_Mirror.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once this is done, select your Linux Distro (or one that shares your package managers format). +::: +::: + +--- + +![](images/Linux/03_Debian.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +On the landing page, you will find a bunch of relevant installation information, which is worthwhile giving a read-through when you have time. +::: +::: + +--- + +![](images/Linux/04_Landing.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The process to successfully install R can be summarized as follows: + +Update apt/sources.list to include the CRAN repository (allowing access to R packages) +::: +::: + +--- + +![](images/Linux/08_AptSources.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Since we are running on Debian stable (Trixie), we would add the following line to sources.list +::: +::: + +--- + +![](images/Linux/07_TrixieRepo.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +So in practice, open sources.list: +::: +::: + +--- + +![](images/Linux/09_EditAptSources.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Paste the line, and "Ctrl + O"; "Enter"; "Ctrl + X" to save the changes. +::: +::: + +--- + +![](images/Linux/10_UpdatedEditAptSources.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next, we will need to retrieve the keyID used to sign. This can be fetched from Ubuntu via the terminal. +::: +::: + +--- + +![](images/Linux/06_SecureAptKey.png) + +--- + +![](images/Linux/12_AptKey.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Then we need to export and write it +::: +::: + +--- + +![](images/Linux/12_AptKey2.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Which if successful, will display the public key. +::: +::: + +--- + +![](images/Linux/12_PublicKey.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +With the above set up, we can proceed via our apt package manager to install both r-base and r-base-dev (which contains the equivalent of Rtools for Windows, or Xcode Command Line Tools for macOS). +::: +::: + +--- + +![](images/Linux/05_BaseR.png) + +--- + +![](images/Linux/13_InstallBaseAndDev.png) + +--- + +![](images/Linux/13_Install.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And if all goes well, R should now be installed. +::: +::: + +## Installing Git + +```{r} +# sudo apt install git +``` + +## Installing Positron + +::: {.fragment} +::: {.callout-tip title="."} +Finally, you will need to install [Positron](https://positron.posit.co/). It will be the integrated development environment (IDE) we will be using for the course. + +First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. +::: +::: + +--- + +![](images/Windows/25_Positron.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). +::: +::: + +--- + +![](images/Linux/15_TermsService.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +With the license accepted, you will be able to select distribution and architecture. +::: +::: + +--- + +![](images/Linux/16_LinuxFlavor.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once the Download completes, proceed to install the .deb package as you would nornally. GUI example via Discover below. +::: +::: + +--- + +![](images/Linux/17_DebPackageInstall.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Depending on your configurations, you may be asked to exert your sudo powers. +::: +::: + +--- + +![](images/Linux/18_Password.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once this completes, you should now be able to launch the software for the first time. +::: +::: + +--- + +![](images/Linux/19_InstallSuccess.png) + +--- + +# Connecting GitHub and Positron + +::: {.fragment} +::: {.callout-tip title="."} +Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected. + +When opening Positron for the first time, you will encounter the following view: +::: +::: + +--- + +![](images/Linux/20_PositronStart.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right. +::: +::: + +--- + +![](images/Linux/20_PositronStart.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Then select the most recent/up-to-date R version. +::: +::: + +--- + +![](images/Linux/21_R.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) +::: +::: + +--- + +![](images/Linux/22_RSuccess.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. + +Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. +::: +::: + +--- + +![](images/Linux/23_GitHub.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. +::: +::: + +--- + +![](images/Linux/24_Code.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. +::: +::: + +--- + +![](images/Linux/25_GitHubAccount.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. +::: +::: + +--- + +![](images/Linux/26_EnterNumber.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. +::: +::: + +--- + +![](images/Linux/27_Confirm.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And if all works out, you should see the following succes page +::: +::: + +--- + +![](images/Linux/28_ConfirmationPage.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. +::: +::: + +--- + +![](images/Linux/29_PositronSuccess.png) + +--- + +# New Folder from Git + +::: {.fragment} +::: {.callout-tip title="."} +With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. + +To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option +::: +::: + +--- + +![](images/MacOS/24.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" +::: +::: + +--- + +![](images/FolderFromGit1.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. +::: +::: + +--- + +![](images/Import2.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. +::: +::: + +--- + +![](images/MacOS/28.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And with that done, you should now see the forked Cytometry in R course contents appear within Positron. +::: +::: + +--- + +![](images/Import2Done.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" +::: +::: + +--- + +![](images/FolderFromGit2.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. +::: +::: + +--- + +![](images/Import2.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. +::: +::: + +--- + +![](images/Import2Done.png) + +--- + +# Wrap-up + +::: {.fragment} +::: {.callout-tip title="."} +In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. + +In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. +::: +::: + +--- + +# Additional Resources + +[How to Download and Install Software on Linux](https://youtu.be/lC4d4EpMMxg?si=9TeFkwFzrRbzA-Ma) + +[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) + +[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) + +[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) + + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_WorkstationSetup/MacOS.qmd b/course/00_WorkstationSetup/MacOS.qmd index 18f9c06..e875265 100644 --- a/course/00_WorkstationSetup/MacOS.qmd +++ b/course/00_WorkstationSetup/MacOS.qmd @@ -1,413 +1,413 @@ ---- -title: "Installing Software on MacOS" -author: "David Rach" -date: 01-21-2026 -format: html -toc: true -toc-depth: 4 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -For the YouTube livestream recording, see [here](https://www.youtube.com/live/ik395dIsFbc?si=Z90yMpRdzI1XzRPd) - - - -For screen-shot slides, click [here](/course/00_WorkstationSetup/MacOSSlides.qmd) - -This is the software installation walkthrough for those whose computers are running MacOS. Based on our pre-course interest form, you make up a solid proportion of the course participants. - -![](/course/00_WorkstationSetup/images/ComputerOS.png){width=100%} - -# Background - -In this walkthrough, we will have you install the following pieces of software: - -[R website](https://www.r-project.org/) : The programming language we will be using throughout the course. - -[Positron](https://positron.posit.co/) : The integrated development environment (IDE) in which we will open, modify and run our code. - -[Git](https://git-scm.com/) : The version control software that will allow us to track changes to our files. You may or may not already it on your computer depending on whether Xcode Command Line Tools is installed. - -Please note, the installation steps detailed below were carried out on a Mac with the older older pre-2020 x86 Intel chips, if you are running a Mac with the newer ARM (M1 or greater) chips, the installation instructions will differ some of the options you selecct during the download. If you encounter major differences in installation, please take screenshots and open an [issue](https://github.com/UMGCCCFCSR/CytometryInR/issues) so that we can update the documentation for your architecture. - -
- ---- - -# Getting Started - -
- ---- - -## Installing R - -To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. - -![](images/MacOS/4_RLanding.png) - -
- ---- - -On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. - -![](images/MacOS/5_RMirror.png) - -
- ---- - -You will then select your Operating System, in this case, [macOS](https://cloud.r-project.org/bin/macosx/) - - -![](images/MacOS/6_ROS.png) - -
- ---- - -Next, you will need to select the appropiate [download](https://cloud.r-project.org/bin/macosx/) based on your computers architecture. On newer Macs (containing M1+ chips) this would the arm64 option on the center left of the screen. For the older Intel (pre-2020) Macs, you would select the x86_64 option. If you are unsure, check your [About This Mac](https://youtu.be/l3xW84TFeSA?si=i53tL5Ac_rEwEyjn) tab - -![](images/MacOS/7_RMacCPU.png) - -
- ---- - -After the download has completed, launch the installer - -![](images/MacOS/8_RInstall.png) - -
- ---- - -Proceed through the Read Me - -![](images/MacOS/9_RInstall.png) - -
- ---- - -You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course). - -![](images/MacOS/10_RInstallLicense.png) - -
- ---- - -![](images/MacOS/11_RInstallLicense.png) - -
- ---- - -Next, you will need to navigate through several pages, keeping the defaults. - -![](images/MacOS/12_RInstall.png) - -
- ---- - -And with any luck, you should see that the installation was successful. - -![](images/MacOS/13_RInstall.png) - -
- ---- - -## Xcode Command Line Tools - -Depending on your version of macOS, you may or may not already have [Git](https://git-scm.com/install/mac) installed on your computer. The reason is that it comes bundled within the Xcode Command Line Tools. - -If this is not your first foray into coding, you may have previously seen an installation pop-up along the lines of "XYZ requires command line developer tools. Would you like to install the tools now?" when installing an IDE (like Positron, Rstudio or Visual Studio Code). - -![](images/MacOS/00_Popup.png) - -
- ---- - -Since these command line developer tools contain both Git, and also the equivalent of Rtools for Windows, we will need to install them for this course. To get started, first open your terminal. - -![](images/MacOS/00_1OpenTerminal.png) - -
- ---- - -Next run the following code: - -```{r} -#| eval: FALSE -xcode-select --install -``` - -![](images/MacOS/00_2XcodeInstall.png) - -
- ---- - -You will then have the pop-up asking whether you want to install the command line tools (which contain Git). Select Install. - -![](images/MacOS/00_3CommandLineDeveloperTools.png) - -
- ---- - -You will then be asked to accept the license - -![](images/MacOS/00_4License.png) - -
- ---- - -Your installation will then proceed - -![](images/MacOS/00_5InstallProgress.png) - -
- ---- - -And if all goes well, the software will finish installing. - -![](images/MacOS/00_6Success.png) - - -
- ---- - -After you complete Positron installation (next section), if you check the version control tab on the action bar on the far left side of the screen, you should see the following if Git was installed correctly. - -![](images/MacOS/00_7Success.png) - -
- ---- - -Alternatively, if you see this, you will need to reattempt the installation. - -![](images/MacOS/00_8Unsuccess.png) - -
- ---- - -## Install Positron - -Finally, you will install [Positron](https://positron.posit.co/). It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course. - -First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. - -![](images/MacOS/1_Positron.png) - -
- ---- - -You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). - -With the license accepted, you will be able to select your operating system and the relevant installer depending on whether you are on an M1+ (ARM) or older Intel (x86) Mac. - -![](images/MacOS/2_PositronOS.png) - -
- - -Once the Download completes, proceed to install the package as you normally would for any other program. - -
- ---- - -# Connecting GitHub and Positron - -Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your [GitHub](https://github.com/) account and Positron are connected. - -When opening Positron for the first time, you will encounter the following view: - -![](images/MacOS/14_Positron.png) - -
- ---- - -We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right, and then select the most recent/up-to-date R version. - - -![](images/MacOS/15_PositronSession.png) - -
- ---- - -R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) - -![](images/MacOS/16_PositronActive.png) - -
- ---- - -Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. - -Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. - -![](images/MacOS/17_PositronGitHub.png) - -
- ---- - -Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. - -![](images/MacOS/18.png) - -
- ---- - -If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. - -![](images/Windows/41_GitHub.png) - -
- ---- - -You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. - -![](images/MacOS/20.png) - -
- ---- - -And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. - -![](images/MacOS/21_GitHubAccess.png) - -
- ---- - -And if all works out, you should see the following succes page - -![](images/MacOS/22.png) - -
- ---- - -Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. - -![](images/MacOS/23_PositronAccessActive.png) - -
- ---- - -# New Folder from Git - -With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. - -To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option - -![](images/MacOS/24.png) - -
- ---- - -Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" - -![](images/FolderFromGit1.png) - -
- ---- - -You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. - -![](images/Import2.png) - -
- ---- - -You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. - -![](images/MacOS/28.png) - -
- ---- - -And with that done, you should now see the forked Cytometry in R course contents appear within Positron. - -![](images/Import2Done.png) - -
- ---- - -We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" - -![](images/FolderFromGit2.png) - -
- ---- - -After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. - -![](images/Import2.png) - -
- ---- - -And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. - -![](images/Import2Done.png) - -
- ---- - - - -# Wrap-up - -In this walkthrough, we installed R, Positron, and ensured that Git/Command Line Tools were active. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. - -In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. - -# Additional Resources - -[How to Install Software on a Mac](https://youtu.be/OH6cSQikbdw?si=ywXBU_eD2kl9AnLU) - -[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) - -[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) - -[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Installing Software on MacOS" +author: "David Rach" +date: 01-21-2026 +format: html +toc: true +toc-depth: 4 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://www.youtube.com/live/ik395dIsFbc?si=Z90yMpRdzI1XzRPd) + + + +For screen-shot slides, click [here](/course/00_WorkstationSetup/MacOSSlides.qmd) + +This is the software installation walkthrough for those whose computers are running MacOS. Based on our pre-course interest form, you make up a solid proportion of the course participants. + +![](/course/00_WorkstationSetup/images/ComputerOS.png){width=100%} + +# Background + +In this walkthrough, we will have you install the following pieces of software: + +[R website](https://www.r-project.org/) : The programming language we will be using throughout the course. + +[Positron](https://positron.posit.co/) : The integrated development environment (IDE) in which we will open, modify and run our code. + +[Git](https://git-scm.com/) : The version control software that will allow us to track changes to our files. You may or may not already it on your computer depending on whether Xcode Command Line Tools is installed. + +Please note, the installation steps detailed below were carried out on a Mac with the older older pre-2020 x86 Intel chips, if you are running a Mac with the newer ARM (M1 or greater) chips, the installation instructions will differ some of the options you selecct during the download. If you encounter major differences in installation, please take screenshots and open an [issue](https://github.com/UMGCCCFCSR/CytometryInR/issues) so that we can update the documentation for your architecture. + +
+ +--- + +# Getting Started + +
+ +--- + +## Installing R + +To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. + +![](images/MacOS/4_RLanding.png) + +
+ +--- + +On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. + +![](images/MacOS/5_RMirror.png) + +
+ +--- + +You will then select your Operating System, in this case, [macOS](https://cloud.r-project.org/bin/macosx/) + + +![](images/MacOS/6_ROS.png) + +
+ +--- + +Next, you will need to select the appropiate [download](https://cloud.r-project.org/bin/macosx/) based on your computers architecture. On newer Macs (containing M1+ chips) this would the arm64 option on the center left of the screen. For the older Intel (pre-2020) Macs, you would select the x86_64 option. If you are unsure, check your [About This Mac](https://youtu.be/l3xW84TFeSA?si=i53tL5Ac_rEwEyjn) tab + +![](images/MacOS/7_RMacCPU.png) + +
+ +--- + +After the download has completed, launch the installer + +![](images/MacOS/8_RInstall.png) + +
+ +--- + +Proceed through the Read Me + +![](images/MacOS/9_RInstall.png) + +
+ +--- + +You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course). + +![](images/MacOS/10_RInstallLicense.png) + +
+ +--- + +![](images/MacOS/11_RInstallLicense.png) + +
+ +--- + +Next, you will need to navigate through several pages, keeping the defaults. + +![](images/MacOS/12_RInstall.png) + +
+ +--- + +And with any luck, you should see that the installation was successful. + +![](images/MacOS/13_RInstall.png) + +
+ +--- + +## Xcode Command Line Tools + +Depending on your version of macOS, you may or may not already have [Git](https://git-scm.com/install/mac) installed on your computer. The reason is that it comes bundled within the Xcode Command Line Tools. + +If this is not your first foray into coding, you may have previously seen an installation pop-up along the lines of "XYZ requires command line developer tools. Would you like to install the tools now?" when installing an IDE (like Positron, Rstudio or Visual Studio Code). + +![](images/MacOS/00_Popup.png) + +
+ +--- + +Since these command line developer tools contain both Git, and also the equivalent of Rtools for Windows, we will need to install them for this course. To get started, first open your terminal. + +![](images/MacOS/00_1OpenTerminal.png) + +
+ +--- + +Next run the following code: + +```{r} +#| eval: FALSE +xcode-select --install +``` + +![](images/MacOS/00_2XcodeInstall.png) + +
+ +--- + +You will then have the pop-up asking whether you want to install the command line tools (which contain Git). Select Install. + +![](images/MacOS/00_3CommandLineDeveloperTools.png) + +
+ +--- + +You will then be asked to accept the license + +![](images/MacOS/00_4License.png) + +
+ +--- + +Your installation will then proceed + +![](images/MacOS/00_5InstallProgress.png) + +
+ +--- + +And if all goes well, the software will finish installing. + +![](images/MacOS/00_6Success.png) + + +
+ +--- + +After you complete Positron installation (next section), if you check the version control tab on the action bar on the far left side of the screen, you should see the following if Git was installed correctly. + +![](images/MacOS/00_7Success.png) + +
+ +--- + +Alternatively, if you see this, you will need to reattempt the installation. + +![](images/MacOS/00_8Unsuccess.png) + +
+ +--- + +## Install Positron + +Finally, you will install [Positron](https://positron.posit.co/). It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course. + +First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. + +![](images/MacOS/1_Positron.png) + +
+ +--- + +You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). + +With the license accepted, you will be able to select your operating system and the relevant installer depending on whether you are on an M1+ (ARM) or older Intel (x86) Mac. + +![](images/MacOS/2_PositronOS.png) + +
+ + +Once the Download completes, proceed to install the package as you normally would for any other program. + +
+ +--- + +# Connecting GitHub and Positron + +Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your [GitHub](https://github.com/) account and Positron are connected. + +When opening Positron for the first time, you will encounter the following view: + +![](images/MacOS/14_Positron.png) + +
+ +--- + +We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right, and then select the most recent/up-to-date R version. + + +![](images/MacOS/15_PositronSession.png) + +
+ +--- + +R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) + +![](images/MacOS/16_PositronActive.png) + +
+ +--- + +Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. + +Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. + +![](images/MacOS/17_PositronGitHub.png) + +
+ +--- + +Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. + +![](images/MacOS/18.png) + +
+ +--- + +If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. + +![](images/Windows/41_GitHub.png) + +
+ +--- + +You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. + +![](images/MacOS/20.png) + +
+ +--- + +And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. + +![](images/MacOS/21_GitHubAccess.png) + +
+ +--- + +And if all works out, you should see the following succes page + +![](images/MacOS/22.png) + +
+ +--- + +Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. + +![](images/MacOS/23_PositronAccessActive.png) + +
+ +--- + +# New Folder from Git + +With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. + +To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option + +![](images/MacOS/24.png) + +
+ +--- + +Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" + +![](images/FolderFromGit1.png) + +
+ +--- + +You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. + +![](images/Import2.png) + +
+ +--- + +You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. + +![](images/MacOS/28.png) + +
+ +--- + +And with that done, you should now see the forked Cytometry in R course contents appear within Positron. + +![](images/Import2Done.png) + +
+ +--- + +We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" + +![](images/FolderFromGit2.png) + +
+ +--- + +After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. + +![](images/Import2.png) + +
+ +--- + +And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. + +![](images/Import2Done.png) + +
+ +--- + + + +# Wrap-up + +In this walkthrough, we installed R, Positron, and ensured that Git/Command Line Tools were active. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. + +In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. + +# Additional Resources + +[How to Install Software on a Mac](https://youtu.be/OH6cSQikbdw?si=ywXBU_eD2kl9AnLU) + +[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) + +[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) + +[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_WorkstationSetup/MacOSSlides.qmd b/course/00_WorkstationSetup/MacOSSlides.qmd index a154981..c181faa 100644 --- a/course/00_WorkstationSetup/MacOSSlides.qmd +++ b/course/00_WorkstationSetup/MacOSSlides.qmd @@ -1,619 +1,619 @@ ---- -title: "Installing Software on MacOS" -author: "David Rach" -date: 02-01-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -::: {.fragment} -::: {.callout-tip title="."} -This is the software installation walkthrough for those whose computers are running MacOS. Based on our pre-course interest form, you make up a solid proportion of the course participants. -::: -::: - ---- - -![](/course/00_WorkstationSetup/images/ComputerOS.png){width=100%} - ---- - -# Background - -::: {.fragment} -::: {.callout-tip title="."} -In this walkthrough, we will have you install the following pieces of software: - -[R website](https://www.r-project.org/) : The programming language we will be using throughout the course. - -[Positron](https://positron.posit.co/) : The integrated development environment (IDE) in which we will open, modify and run our code. - -[Git](https://git-scm.com/) : The version control software that will allow us to track changes to our files. You may or may not already it on your computer depending on whether Xcode Command Line Tools is installed. - -Please note, the installation steps detailed below were carried out on a Mac with the older older pre-2020 x86 Intel chips, if you are running a Mac with the newer ARM (M1 or greater) chips, the installation instructions will differ some of the options you selecct during the download. If you encounter major differences in installation, please take screenshots and open an [issue](https://github.com/UMGCCCFCSR/CytometryInR/issues) so that we can update the documentation for your architecture. -::: -::: - - ---- - -# Getting Started - - ---- - -## Installing R - -::: {.fragment} -::: {.callout-tip title="."} -To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. -::: -::: - ---- - -![](images/MacOS/4_RLanding.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. -::: -::: - ---- - -![](images/MacOS/5_RMirror.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then select your Operating System, in this case, [macOS](https://cloud.r-project.org/bin/macosx/) -::: -::: - ---- - -![](images/MacOS/6_ROS.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next, you will need to select the appropiate [download](https://cloud.r-project.org/bin/macosx/) based on your computers architecture. On newer Macs (containing M1+ chips) this would the arm64 option on the center left of the screen. For the older Intel (pre-2020) Macs, you would select the x86_64 option. If you are unsure, check your [About This Mac](https://youtu.be/l3xW84TFeSA?si=i53tL5Ac_rEwEyjn) tab -::: -::: - ---- - -![](images/MacOS/7_RMacCPU.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -After the download has completed, launch the installer -::: -::: - ---- - -![](images/MacOS/8_RInstall.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Proceed through the Read Me -::: -::: - ---- - -![](images/MacOS/9_RInstall.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course). -::: -::: - ---- - -![](images/MacOS/10_RInstallLicense.png) - - ---- ---- - -![](images/MacOS/11_RInstallLicense.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next, you will need to navigate through several pages, keeping the defaults. -::: -::: - ---- - -![](images/MacOS/12_RInstall.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And with any luck, you should see that the installation was successful. -::: -::: - ---- - -![](images/MacOS/13_RInstall.png) - - ---- - -## Xcode Command Line Tools - -::: {.fragment} -::: {.callout-tip title="."} -Depending on your version of macOS, you may or may not already have [Git](https://git-scm.com/install/mac) installed on your computer. The reason is that it comes bundled within the Xcode Command Line Tools. - -If this is not your first foray into coding, you may have previously seen an installation pop-up along the lines of "XYZ requires command line developer tools. Would you like to install the tools now?" when installing an IDE (like Positron, Rstudio or Visual Studio Code). -::: -::: - ---- - -![](images/MacOS/00_Popup.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Since these command line developer tools contain both Git, and also the equivalent of Rtools for Windows, we will need to install them for this course. To get started, first open your terminal. -::: -::: - ---- - -![](images/MacOS/00_1OpenTerminal.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next run the following code: -::: -::: - -```{r} -#| eval: FALSE -xcode-select --install -``` ---- - -![](images/MacOS/00_2XcodeInstall.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then have the pop-up asking whether you want to install the command line tools (which contain Git). Select Install. -::: -::: - ---- - -![](images/MacOS/00_3CommandLineDeveloperTools.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then be asked to accept the license -::: -::: - ---- - -![](images/MacOS/00_4License.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Your installation will then proceed -::: -::: - ---- - -![](images/MacOS/00_5InstallProgress.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And if all goes well, the software will finish installing. -::: -::: - ---- - -![](images/MacOS/00_6Success.png) - - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -After you complete Positron installation (next section), if you check the version control tab on the action bar on the far left side of the screen, you should see the following if Git was installed correctly. -::: -::: - ---- - -![](images/MacOS/00_7Success.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Alternatively, if you see this, you will need to reattempt the installation. -::: -::: - ---- - -![](images/MacOS/00_8Unsuccess.png) - - ---- - -## Install Positron - -::: {.fragment} -::: {.callout-tip title="."} -Finally, you will install [Positron](https://positron.posit.co/). It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course. - -First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. -::: -::: - ---- - -![](images/MacOS/1_Positron.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). - -With the license accepted, you will be able to select your operating system and the relevant installer depending on whether you are on an M1+ (ARM) or older Intel (x86) Mac. -::: -::: - ---- - -![](images/MacOS/2_PositronOS.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once the Download completes, proceed to install the package as you normally would for any other program. -::: -::: - - ---- - -# Connecting GitHub and Positron - -::: {.fragment} -::: {.callout-tip title="."} -Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your [GitHub](https://github.com/) account and Positron are connected. - -When opening Positron for the first time, you will encounter the following view: -::: -::: - ---- - -![](images/MacOS/14_Positron.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right, and then select the most recent/up-to-date R version. -::: -::: - ---- - -![](images/MacOS/15_PositronSession.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) -::: -::: - ---- - -![](images/MacOS/16_PositronActive.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. - -Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. -::: -::: - ---- - -![](images/MacOS/17_PositronGitHub.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. -::: -::: - ---- - -![](images/MacOS/18.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. -::: -::: - ---- - -![](images/Windows/41_GitHub.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. -::: -::: - ---- - -![](images/MacOS/20.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. -::: -::: - ---- - -![](images/MacOS/21_GitHubAccess.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And if all works out, you should see the following succes page -::: -::: - ---- - -![](images/MacOS/22.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. -::: -::: - ---- - -![](images/MacOS/23_PositronAccessActive.png) - - ---- - -# New Folder from Git - -::: {.fragment} -::: {.callout-tip title="."} -With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. - -To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option -::: -::: - ---- - -![](images/MacOS/24.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" -::: -::: - ---- - -![](images/FolderFromGit1.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. -::: -::: - ---- - -![](images/Import2.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. -::: -::: - ---- - -![](images/MacOS/28.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And with that done, you should now see the forked Cytometry in R course contents appear within Positron. -::: -::: - ---- - -![](images/Import2Done.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" -::: -::: - ---- - -![](images/FolderFromGit2.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. -::: -::: - ---- - -![](images/Import2.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. -::: -::: - ---- - -![](images/Import2Done.png) - - ---- - - - -# Wrap-up - -::: {.fragment} -::: {.callout-tip title="."} -In this walkthrough, we installed R, Positron, and ensured that Git/Command Line Tools were active. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. - -In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. -::: -::: - -# Additional Resources - -[How to Install Software on a Mac](https://youtu.be/OH6cSQikbdw?si=ywXBU_eD2kl9AnLU) - -[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) - -[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) - -[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Installing Software on MacOS" +author: "David Rach" +date: 02-01-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +::: {.fragment} +::: {.callout-tip title="."} +This is the software installation walkthrough for those whose computers are running MacOS. Based on our pre-course interest form, you make up a solid proportion of the course participants. +::: +::: + +--- + +![](/course/00_WorkstationSetup/images/ComputerOS.png){width=100%} + +--- + +# Background + +::: {.fragment} +::: {.callout-tip title="."} +In this walkthrough, we will have you install the following pieces of software: + +[R website](https://www.r-project.org/) : The programming language we will be using throughout the course. + +[Positron](https://positron.posit.co/) : The integrated development environment (IDE) in which we will open, modify and run our code. + +[Git](https://git-scm.com/) : The version control software that will allow us to track changes to our files. You may or may not already it on your computer depending on whether Xcode Command Line Tools is installed. + +Please note, the installation steps detailed below were carried out on a Mac with the older older pre-2020 x86 Intel chips, if you are running a Mac with the newer ARM (M1 or greater) chips, the installation instructions will differ some of the options you selecct during the download. If you encounter major differences in installation, please take screenshots and open an [issue](https://github.com/UMGCCCFCSR/CytometryInR/issues) so that we can update the documentation for your architecture. +::: +::: + + +--- + +# Getting Started + + +--- + +## Installing R + +::: {.fragment} +::: {.callout-tip title="."} +To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. +::: +::: + +--- + +![](images/MacOS/4_RLanding.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. +::: +::: + +--- + +![](images/MacOS/5_RMirror.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then select your Operating System, in this case, [macOS](https://cloud.r-project.org/bin/macosx/) +::: +::: + +--- + +![](images/MacOS/6_ROS.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next, you will need to select the appropiate [download](https://cloud.r-project.org/bin/macosx/) based on your computers architecture. On newer Macs (containing M1+ chips) this would the arm64 option on the center left of the screen. For the older Intel (pre-2020) Macs, you would select the x86_64 option. If you are unsure, check your [About This Mac](https://youtu.be/l3xW84TFeSA?si=i53tL5Ac_rEwEyjn) tab +::: +::: + +--- + +![](images/MacOS/7_RMacCPU.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +After the download has completed, launch the installer +::: +::: + +--- + +![](images/MacOS/8_RInstall.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Proceed through the Read Me +::: +::: + +--- + +![](images/MacOS/9_RInstall.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course). +::: +::: + +--- + +![](images/MacOS/10_RInstallLicense.png) + + +--- +--- + +![](images/MacOS/11_RInstallLicense.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next, you will need to navigate through several pages, keeping the defaults. +::: +::: + +--- + +![](images/MacOS/12_RInstall.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And with any luck, you should see that the installation was successful. +::: +::: + +--- + +![](images/MacOS/13_RInstall.png) + + +--- + +## Xcode Command Line Tools + +::: {.fragment} +::: {.callout-tip title="."} +Depending on your version of macOS, you may or may not already have [Git](https://git-scm.com/install/mac) installed on your computer. The reason is that it comes bundled within the Xcode Command Line Tools. + +If this is not your first foray into coding, you may have previously seen an installation pop-up along the lines of "XYZ requires command line developer tools. Would you like to install the tools now?" when installing an IDE (like Positron, Rstudio or Visual Studio Code). +::: +::: + +--- + +![](images/MacOS/00_Popup.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Since these command line developer tools contain both Git, and also the equivalent of Rtools for Windows, we will need to install them for this course. To get started, first open your terminal. +::: +::: + +--- + +![](images/MacOS/00_1OpenTerminal.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next run the following code: +::: +::: + +```{r} +#| eval: FALSE +xcode-select --install +``` +--- + +![](images/MacOS/00_2XcodeInstall.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then have the pop-up asking whether you want to install the command line tools (which contain Git). Select Install. +::: +::: + +--- + +![](images/MacOS/00_3CommandLineDeveloperTools.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then be asked to accept the license +::: +::: + +--- + +![](images/MacOS/00_4License.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Your installation will then proceed +::: +::: + +--- + +![](images/MacOS/00_5InstallProgress.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And if all goes well, the software will finish installing. +::: +::: + +--- + +![](images/MacOS/00_6Success.png) + + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +After you complete Positron installation (next section), if you check the version control tab on the action bar on the far left side of the screen, you should see the following if Git was installed correctly. +::: +::: + +--- + +![](images/MacOS/00_7Success.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, if you see this, you will need to reattempt the installation. +::: +::: + +--- + +![](images/MacOS/00_8Unsuccess.png) + + +--- + +## Install Positron + +::: {.fragment} +::: {.callout-tip title="."} +Finally, you will install [Positron](https://positron.posit.co/). It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course. + +First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. +::: +::: + +--- + +![](images/MacOS/1_Positron.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). + +With the license accepted, you will be able to select your operating system and the relevant installer depending on whether you are on an M1+ (ARM) or older Intel (x86) Mac. +::: +::: + +--- + +![](images/MacOS/2_PositronOS.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once the Download completes, proceed to install the package as you normally would for any other program. +::: +::: + + +--- + +# Connecting GitHub and Positron + +::: {.fragment} +::: {.callout-tip title="."} +Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your [GitHub](https://github.com/) account and Positron are connected. + +When opening Positron for the first time, you will encounter the following view: +::: +::: + +--- + +![](images/MacOS/14_Positron.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right, and then select the most recent/up-to-date R version. +::: +::: + +--- + +![](images/MacOS/15_PositronSession.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) +::: +::: + +--- + +![](images/MacOS/16_PositronActive.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. + +Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. +::: +::: + +--- + +![](images/MacOS/17_PositronGitHub.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. +::: +::: + +--- + +![](images/MacOS/18.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. +::: +::: + +--- + +![](images/Windows/41_GitHub.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. +::: +::: + +--- + +![](images/MacOS/20.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. +::: +::: + +--- + +![](images/MacOS/21_GitHubAccess.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And if all works out, you should see the following succes page +::: +::: + +--- + +![](images/MacOS/22.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. +::: +::: + +--- + +![](images/MacOS/23_PositronAccessActive.png) + + +--- + +# New Folder from Git + +::: {.fragment} +::: {.callout-tip title="."} +With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. + +To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option +::: +::: + +--- + +![](images/MacOS/24.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" +::: +::: + +--- + +![](images/FolderFromGit1.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. +::: +::: + +--- + +![](images/Import2.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. +::: +::: + +--- + +![](images/MacOS/28.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And with that done, you should now see the forked Cytometry in R course contents appear within Positron. +::: +::: + +--- + +![](images/Import2Done.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" +::: +::: + +--- + +![](images/FolderFromGit2.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. +::: +::: + +--- + +![](images/Import2.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. +::: +::: + +--- + +![](images/Import2Done.png) + + +--- + + + +# Wrap-up + +::: {.fragment} +::: {.callout-tip title="."} +In this walkthrough, we installed R, Positron, and ensured that Git/Command Line Tools were active. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. + +In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. +::: +::: + +# Additional Resources + +[How to Install Software on a Mac](https://youtu.be/OH6cSQikbdw?si=ywXBU_eD2kl9AnLU) + +[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) + +[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) + +[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_WorkstationSetup/Windows.qmd b/course/00_WorkstationSetup/Windows.qmd index 1133d72..2ce2f43 100644 --- a/course/00_WorkstationSetup/Windows.qmd +++ b/course/00_WorkstationSetup/Windows.qmd @@ -1,663 +1,663 @@ ---- -title: "Installing Software on Windows" -author: "David Rach" -date: 01-21-2026 -format: html -toc: true -toc-depth: 4 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -For the YouTube livestream recording, see [here](https://www.youtube.com/live/WP6JMzlj6B4?si=P1EE1NzLO8i5L0cE) - - - -For screen-shots slides, click [here](/course/00_WorkstationSetup/WindowsSlides.qmd) - - - -This is the software installation walkthrough for those whose computers are running Windows. Based on our pre-course interest form, you make up the majority of course participants. - -![](/course/00_WorkstationSetup/images/ComputerOS.png){width=100%} - -# Background - -
- ---- - -In this walkthrough, we will have you install the following pieces of software: - -[R website](https://www.r-project.org/) : The programming language we will be using throughout the course. - -[Positron](https://positron.posit.co/) : The integrated development environment (IDE) in which we will open, modify and run our code. - -[Git](https://git-scm.com/) : The version control software that will allow us to track changes to our files. - -Additionally, Windows users will need to install: - -[RTools](https://cran.r-project.org/bin/windows/Rtools/rtools45/rtools.html) : Used to build R packages from source code. - -# Getting Started - -
- ---- - -## Installing R - -To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. - -![](images/Windows/01_RLanding.png) - -
- ---- - -On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. - -![](images/Windows/02_Landing.png) - -
- ---- - -You will then select your Operating System, in this case, [Windows](https://cloud.r-project.org/bin/windows/). - -![](images/Windows/03_ForWindows.png) - -
- ---- - -And go ahead and select the [Install R for the first time](https://cloud.r-project.org/bin/windows/base/) link. - -![](images/Windows/04_ForFirstTime.png) - -
- ---- - - -Next, you will select the download the current version option at the top of the page. - - -![](images/Windows/04_CurrentVersion.png) - -
- ---- - -The popup window will then ask where you want to save the installer (.exe) file. We generally save this to either Downloads or Desktop to make finding it easier. - -![](images/Windows/05_SaveTheInstaller.png) - - -
- ---- - -After the download is complete, double click on the installer's .exe file. This will open a popup asking you to select your preferred language. - -![](images/Windows/07_DesiredLanguage.png) - -
- ---- - -You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course). - -![](images/Windows/08_GPL2.png) - -
- ---- - -On Windows, R will normally save it's software folder under Program Files. - -![](images/Windows/09_ProgramFiles.png) - -
- ---- - -Next, please accept the defaults. - -![](images/Windows/10_Defaults.png) - -
- ---- - - -![](images/Windows/11_Defaults.png) - -
- ---- - -![](images/Windows/12_Defaults.png) - -
- ---- - -![](images/Windows/13_Defaults.png) - -
- ---- - -With the defaults accepted, the installation will commence. Feel free to go have a coffee/tea/beverage-of-your choice break while you wait. - -![](images/Windows/14_Install.png) - -
- ---- - -And if all goes well, the installation will complete without any issues. - -![](images/Windows/15_Success.png) - -
- ---- - -## Installing RTools - -We will now work on installing Rtools. This software is needed when building R packages from source, which we will need throughout the course for R packages hosted on GitHub. - -To get started, we will return to the [R installation](https://cloud.r-project.org/) page we visited previously and instead click on the [Rtools](https://cloud.r-project.org/bin/windows/Rtools/) option. - - -![](images/Windows/16_Rtools.png) - -
- ---- - -Next, select the most recent version of Rtools to Download. - -![](images/Windows/17_RtoolsRecent.png) - -
- ---- - -You will then select for your architecture. For the vast majority of Windows users, your computer will likely be be using a x86 chip architecture, so you would select the Rtools45 installer option. - -If your computer however uses the ARM chip architecture, you would select the 64-bit ARM Rtools45 installer instead. If you are unsure, see the [following](https://youtu.be/Z_lcEqomG0k?si=U0fd7sHTZhCJroSm). - -![](images/Windows/18_64x86.png) - -
- ---- - -Next, you will select the location to save the Rtools installer to. We generally save this to either Downloads or Desktop to make finding it easier. - - - -![](images/Windows/17_Downloads.png) - -
- ---- - -Once downloaded, double click on the .exe to launch the Rtools installer. - - -![](images/Windows/19_RtoolsInstall.png) - -
- ---- - -Similar to what we did when installing R, go ahead and keep the defaults. - -![](images/Windows/20_RtoolsDefaults.png) - -
- ---- - -And click install to proceed with the installation. - -![](images/Windows/21_RtoolsDefaults.png) - -
- ---- - -And wait while the installation wraps up. - -![](images/Windows/22_Download.png) - -
- ---- - -If all goes well, you should see the following installation success page. - -![](images/Windows/24_Rtools.png) - -
- ---- - -## Installing Git - -[Git](https://git-scm.com/) is a version control software widely used among software developers and bioinformaticians. We will use it extensively throughout the course, both locally on our computers (to keep track of changes to our files), as well as in combination with [GitHub](https://github.com/)(to maintain online backups of our files). - -We will first navigate to the [website](https://git-scm.com/) and select the download from Windows option. - - -
- ---- - -![](images/Windows/01_Git.png){fig-align="center" width="600"} - -
- ---- - -We will then proceed and select [install 64-bit Git for Windows Setup]{.underline} option - -![](images/Windows/02_Git.png){fig-align="center" width="600"} - -
- ---- - -As was the case with our installation of R and Rtools, a pop-up will appear asking for a location to save the installer to. - -Once downloaded, double-click and proceed with the installation. - -You will be asked to accept the Git License (which is the free copyleft GPL2 license, which we will learn about later in the course). - -![](images/Windows/02_GitLicense.png) - -
- ---- - -Then you will be asked to select the folder to save to software to (usually your Programs folder) - -![](images/Windows/03_GitDestination.png) - -
- ---- - -At this point, the Git installer will ask a series of increasingly niche questions. It is best to just accept all the default options, to avoid wandering too far down a ["What is Vim?!?"](https://www.vim.org/) rabbit-hole. - -![](images/Windows/04_GitComponents.png) - -
- ---- - -![](images/Windows/05_GitStartMenu.png) - -
- ---- - -![](images/Windows/06_GitWhatsVim.png) - -
- ---- - -![](images/Windows/07_GitDecide.png) - -
- ---- - -![](images/Windows/08_GitCommandLine.png) - -
- ---- - -![](images/Windows/09_GitBundledSSH.png) - -
- ---- - -![](images/Windows/10_GitHTTPS.png) - -
- ---- - -![](images/Windows/11_GitUnix.png) - -
- ---- - -![](images/Windows/12_GitEmulator.png) - -
- ---- - -![](images/Windows/13_GitPull.png) - -
- ---- - -![](images/Windows/14_GitCredentialManager.png) - -
- ---- - -Having made it through all the niche customization screens, we finally reach the install button. - -![](images/Windows/15_GitFileCatch.png) - -
- ---- - -We then can wait for the install to complete. - -![](images/Windows/16_GitInstalling.png) - -
- ---- - -And success, we have now installed Git. - -![](images/Windows/17_GitInstalled.png) - -
- ---- - - -## Installing Positron - -Finally, you will install [Positron](https://positron.posit.co/). It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course. - -First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. - -![](images/Windows/25_Positron.png) - -
- ---- - -You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). - -With the license accepted, you will be able to select your operating system. In this case, we will select Windows, specifally the user level install. - -![](images/Windows/26_UserInstall.png) - -
- ---- - -Please note, if you are using a Windows computer with an ARM based chip (like is the case with Snapdragons), you will need to download the installed from the Positron's GitHub [Release Page](), as they are still testing some features. - -![](images/Windows/WindowsArm.png) - ---- - -You will then be prompted to select the location you want to save the installer to. We will generally save this to either Downloads or Desktop to make finding it easier. - -![](images/Windows/27_InstallerLocation.png) - -
- ---- - -Once the download is complete, double click on the installer, and again accept the license agreement. - -![](images/Windows/28_Elastic.png) - -
- ---- - -Generally, Positron will be store its software folder under Program Files. - -![](images/Windows/29_SaveLocation.png) - -
- ---- - -Next up, accept the default options for the following screens - -![](images/Windows/30_Defaults.png) - -
- ---- - -![](images/Windows/31_Defaults.png) - -
- ---- - -And finally, click Install. - -![](images/Windows/32_Defaults.png) - -
- ---- - -![](images/Windows/34_Install.png) -
- ---- - -If all goes well, you should then see the installation success page. - -![](images/Windows/35_Success.png) - -
- ---- - -# Connecting GitHub and Positron - -Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected. - -When opening Positron for the first time, you will encounter the following view: - -![](images/Windows/36_PositronLanding.png) - -
- ---- - -We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right, and then select the most recent/up-to-date R version. - -![](images/Windows/37_AllHiddenCondas.png) - -
- ---- - -R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) - -![](images/Windows/38_Loaded.png) - -
- ---- - -Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. - -Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. - -![](images/Windows/39_GitHubSetup.png) - -
- ---- - -Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. - -![](images/Windows/40_Code.png) - -
- ---- - -If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. - -![](images/Windows/41_GitHub.png) - -
- ---- - -You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. - -![](images/Windows/42_GitHubPassword.png) - -
- ---- - -And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. - -![](images/Windows/43_GitHubSetup.png) - -
- ---- - -Depending on your computer settings, you may be asked for your two-factor authorization passkey. If so, complete this step. - -![](images/Windows/44_Passkey.png) - -
- ---- - -And if all works out, you should see the following succes page - -![](images/Windows/45_PasskeySuccess.png) - -
- ---- - -Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. - -![](images/Windows/46_PositronSuccess.png) - -
- ---- - -# New Folder from Git - -With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. - -To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option - -![](images/MacOS/24.png) - -
- ---- - -Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" - -![](images/FolderFromGit1.png) - -
- ---- - -You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. - -![](images/Import2.png) - -
- ---- - -You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. - -![](images/MacOS/28.png) - -
- ---- - -And with that done, you should now see the forked Cytometry in R course contents appear within Positron. - -![](images/Import2Done.png) - -
- ---- - -We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" - -![](images/FolderFromGit2.png) - -
- ---- - -After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. - -![](images/Import2.png) - -
- ---- - -And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. - -![](images/Import2Done.png) - -
- ---- - -# Wrap-up - -In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. - -In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. - -
- ---- - -# Additional Resources - -[How to Download and Install Software on Windows 11](https://youtu.be/IEhnWKZB4p4?t=60) - -[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) - -[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) - -[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Installing Software on Windows" +author: "David Rach" +date: 01-21-2026 +format: html +toc: true +toc-depth: 4 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://www.youtube.com/live/WP6JMzlj6B4?si=P1EE1NzLO8i5L0cE) + + + +For screen-shots slides, click [here](/course/00_WorkstationSetup/WindowsSlides.qmd) + + + +This is the software installation walkthrough for those whose computers are running Windows. Based on our pre-course interest form, you make up the majority of course participants. + +![](/course/00_WorkstationSetup/images/ComputerOS.png){width=100%} + +# Background + +
+ +--- + +In this walkthrough, we will have you install the following pieces of software: + +[R website](https://www.r-project.org/) : The programming language we will be using throughout the course. + +[Positron](https://positron.posit.co/) : The integrated development environment (IDE) in which we will open, modify and run our code. + +[Git](https://git-scm.com/) : The version control software that will allow us to track changes to our files. + +Additionally, Windows users will need to install: + +[RTools](https://cran.r-project.org/bin/windows/Rtools/rtools45/rtools.html) : Used to build R packages from source code. + +# Getting Started + +
+ +--- + +## Installing R + +To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. + +![](images/Windows/01_RLanding.png) + +
+ +--- + +On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. + +![](images/Windows/02_Landing.png) + +
+ +--- + +You will then select your Operating System, in this case, [Windows](https://cloud.r-project.org/bin/windows/). + +![](images/Windows/03_ForWindows.png) + +
+ +--- + +And go ahead and select the [Install R for the first time](https://cloud.r-project.org/bin/windows/base/) link. + +![](images/Windows/04_ForFirstTime.png) + +
+ +--- + + +Next, you will select the download the current version option at the top of the page. + + +![](images/Windows/04_CurrentVersion.png) + +
+ +--- + +The popup window will then ask where you want to save the installer (.exe) file. We generally save this to either Downloads or Desktop to make finding it easier. + +![](images/Windows/05_SaveTheInstaller.png) + + +
+ +--- + +After the download is complete, double click on the installer's .exe file. This will open a popup asking you to select your preferred language. + +![](images/Windows/07_DesiredLanguage.png) + +
+ +--- + +You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course). + +![](images/Windows/08_GPL2.png) + +
+ +--- + +On Windows, R will normally save it's software folder under Program Files. + +![](images/Windows/09_ProgramFiles.png) + +
+ +--- + +Next, please accept the defaults. + +![](images/Windows/10_Defaults.png) + +
+ +--- + + +![](images/Windows/11_Defaults.png) + +
+ +--- + +![](images/Windows/12_Defaults.png) + +
+ +--- + +![](images/Windows/13_Defaults.png) + +
+ +--- + +With the defaults accepted, the installation will commence. Feel free to go have a coffee/tea/beverage-of-your choice break while you wait. + +![](images/Windows/14_Install.png) + +
+ +--- + +And if all goes well, the installation will complete without any issues. + +![](images/Windows/15_Success.png) + +
+ +--- + +## Installing RTools + +We will now work on installing Rtools. This software is needed when building R packages from source, which we will need throughout the course for R packages hosted on GitHub. + +To get started, we will return to the [R installation](https://cloud.r-project.org/) page we visited previously and instead click on the [Rtools](https://cloud.r-project.org/bin/windows/Rtools/) option. + + +![](images/Windows/16_Rtools.png) + +
+ +--- + +Next, select the most recent version of Rtools to Download. + +![](images/Windows/17_RtoolsRecent.png) + +
+ +--- + +You will then select for your architecture. For the vast majority of Windows users, your computer will likely be be using a x86 chip architecture, so you would select the Rtools45 installer option. + +If your computer however uses the ARM chip architecture, you would select the 64-bit ARM Rtools45 installer instead. If you are unsure, see the [following](https://youtu.be/Z_lcEqomG0k?si=U0fd7sHTZhCJroSm). + +![](images/Windows/18_64x86.png) + +
+ +--- + +Next, you will select the location to save the Rtools installer to. We generally save this to either Downloads or Desktop to make finding it easier. + + + +![](images/Windows/17_Downloads.png) + +
+ +--- + +Once downloaded, double click on the .exe to launch the Rtools installer. + + +![](images/Windows/19_RtoolsInstall.png) + +
+ +--- + +Similar to what we did when installing R, go ahead and keep the defaults. + +![](images/Windows/20_RtoolsDefaults.png) + +
+ +--- + +And click install to proceed with the installation. + +![](images/Windows/21_RtoolsDefaults.png) + +
+ +--- + +And wait while the installation wraps up. + +![](images/Windows/22_Download.png) + +
+ +--- + +If all goes well, you should see the following installation success page. + +![](images/Windows/24_Rtools.png) + +
+ +--- + +## Installing Git + +[Git](https://git-scm.com/) is a version control software widely used among software developers and bioinformaticians. We will use it extensively throughout the course, both locally on our computers (to keep track of changes to our files), as well as in combination with [GitHub](https://github.com/)(to maintain online backups of our files). + +We will first navigate to the [website](https://git-scm.com/) and select the download from Windows option. + + +
+ +--- + +![](images/Windows/01_Git.png){fig-align="center" width="600"} + +
+ +--- + +We will then proceed and select [install 64-bit Git for Windows Setup]{.underline} option + +![](images/Windows/02_Git.png){fig-align="center" width="600"} + +
+ +--- + +As was the case with our installation of R and Rtools, a pop-up will appear asking for a location to save the installer to. + +Once downloaded, double-click and proceed with the installation. + +You will be asked to accept the Git License (which is the free copyleft GPL2 license, which we will learn about later in the course). + +![](images/Windows/02_GitLicense.png) + +
+ +--- + +Then you will be asked to select the folder to save to software to (usually your Programs folder) + +![](images/Windows/03_GitDestination.png) + +
+ +--- + +At this point, the Git installer will ask a series of increasingly niche questions. It is best to just accept all the default options, to avoid wandering too far down a ["What is Vim?!?"](https://www.vim.org/) rabbit-hole. + +![](images/Windows/04_GitComponents.png) + +
+ +--- + +![](images/Windows/05_GitStartMenu.png) + +
+ +--- + +![](images/Windows/06_GitWhatsVim.png) + +
+ +--- + +![](images/Windows/07_GitDecide.png) + +
+ +--- + +![](images/Windows/08_GitCommandLine.png) + +
+ +--- + +![](images/Windows/09_GitBundledSSH.png) + +
+ +--- + +![](images/Windows/10_GitHTTPS.png) + +
+ +--- + +![](images/Windows/11_GitUnix.png) + +
+ +--- + +![](images/Windows/12_GitEmulator.png) + +
+ +--- + +![](images/Windows/13_GitPull.png) + +
+ +--- + +![](images/Windows/14_GitCredentialManager.png) + +
+ +--- + +Having made it through all the niche customization screens, we finally reach the install button. + +![](images/Windows/15_GitFileCatch.png) + +
+ +--- + +We then can wait for the install to complete. + +![](images/Windows/16_GitInstalling.png) + +
+ +--- + +And success, we have now installed Git. + +![](images/Windows/17_GitInstalled.png) + +
+ +--- + + +## Installing Positron + +Finally, you will install [Positron](https://positron.posit.co/). It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course. + +First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. + +![](images/Windows/25_Positron.png) + +
+ +--- + +You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). + +With the license accepted, you will be able to select your operating system. In this case, we will select Windows, specifally the user level install. + +![](images/Windows/26_UserInstall.png) + +
+ +--- + +Please note, if you are using a Windows computer with an ARM based chip (like is the case with Snapdragons), you will need to download the installed from the Positron's GitHub [Release Page](), as they are still testing some features. + +![](images/Windows/WindowsArm.png) + +--- + +You will then be prompted to select the location you want to save the installer to. We will generally save this to either Downloads or Desktop to make finding it easier. + +![](images/Windows/27_InstallerLocation.png) + +
+ +--- + +Once the download is complete, double click on the installer, and again accept the license agreement. + +![](images/Windows/28_Elastic.png) + +
+ +--- + +Generally, Positron will be store its software folder under Program Files. + +![](images/Windows/29_SaveLocation.png) + +
+ +--- + +Next up, accept the default options for the following screens + +![](images/Windows/30_Defaults.png) + +
+ +--- + +![](images/Windows/31_Defaults.png) + +
+ +--- + +And finally, click Install. + +![](images/Windows/32_Defaults.png) + +
+ +--- + +![](images/Windows/34_Install.png) +
+ +--- + +If all goes well, you should then see the installation success page. + +![](images/Windows/35_Success.png) + +
+ +--- + +# Connecting GitHub and Positron + +Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected. + +When opening Positron for the first time, you will encounter the following view: + +![](images/Windows/36_PositronLanding.png) + +
+ +--- + +We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right, and then select the most recent/up-to-date R version. + +![](images/Windows/37_AllHiddenCondas.png) + +
+ +--- + +R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) + +![](images/Windows/38_Loaded.png) + +
+ +--- + +Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. + +Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. + +![](images/Windows/39_GitHubSetup.png) + +
+ +--- + +Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. + +![](images/Windows/40_Code.png) + +
+ +--- + +If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. + +![](images/Windows/41_GitHub.png) + +
+ +--- + +You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. + +![](images/Windows/42_GitHubPassword.png) + +
+ +--- + +And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. + +![](images/Windows/43_GitHubSetup.png) + +
+ +--- + +Depending on your computer settings, you may be asked for your two-factor authorization passkey. If so, complete this step. + +![](images/Windows/44_Passkey.png) + +
+ +--- + +And if all works out, you should see the following succes page + +![](images/Windows/45_PasskeySuccess.png) + +
+ +--- + +Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. + +![](images/Windows/46_PositronSuccess.png) + +
+ +--- + +# New Folder from Git + +With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. + +To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option + +![](images/MacOS/24.png) + +
+ +--- + +Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" + +![](images/FolderFromGit1.png) + +
+ +--- + +You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. + +![](images/Import2.png) + +
+ +--- + +You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. + +![](images/MacOS/28.png) + +
+ +--- + +And with that done, you should now see the forked Cytometry in R course contents appear within Positron. + +![](images/Import2Done.png) + +
+ +--- + +We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" + +![](images/FolderFromGit2.png) + +
+ +--- + +After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. + +![](images/Import2.png) + +
+ +--- + +And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. + +![](images/Import2Done.png) + +
+ +--- + +# Wrap-up + +In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. + +In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. + +
+ +--- + +# Additional Resources + +[How to Download and Install Software on Windows 11](https://youtu.be/IEhnWKZB4p4?t=60) + +[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) + +[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) + +[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_WorkstationSetup/WindowsSlides.qmd b/course/00_WorkstationSetup/WindowsSlides.qmd index ec70008..c1bca79 100644 --- a/course/00_WorkstationSetup/WindowsSlides.qmd +++ b/course/00_WorkstationSetup/WindowsSlides.qmd @@ -1,920 +1,920 @@ ---- -title: "Installing Software on Windows" -author: "David Rach" -date: 02-01-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -::: {.fragment} -::: {.callout-tip title="."} -This is the software installation walkthrough for those whose computers are running Windows. Based on our pre-course interest form, you make up the majority of course participants. -::: -::: - ---- - -![](/course/00_WorkstationSetup/images/ComputerOS.png){width=100%} - ---- - -# Background - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In this walkthrough, we will have you install the following pieces of software: - -[R website](https://www.r-project.org/) : The programming language we will be using throughout the course. - -[Positron](https://positron.posit.co/) : The integrated development environment (IDE) in which we will open, modify and run our code. - -[Git](https://git-scm.com/) : The version control software that will allow us to track changes to our files. - -Additionally, Windows users will need to install: - -[RTools](https://cran.r-project.org/bin/windows/Rtools/rtools45/rtools.html) : Used to build R packages from source code. -::: -::: - -# Getting Started - - ---- - -## Installing R - -::: {.fragment} -::: {.callout-tip title="."} -To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. -::: -::: - ---- - -![](images/Windows/01_RLanding.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. -::: -::: - ---- - -![](images/Windows/02_Landing.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then select your Operating System, in this case, [Windows](https://cloud.r-project.org/bin/windows/). -::: -::: - ---- - -![](images/Windows/03_ForWindows.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And go ahead and select the [Install R for the first time](https://cloud.r-project.org/bin/windows/base/) link. -::: -::: - ---- - -![](images/Windows/04_ForFirstTime.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next, you will select the download the current version option at the top of the page. -::: -::: - ---- - -![](images/Windows/04_CurrentVersion.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The popup window will then ask where you want to save the installer (.exe) file. We generally save this to either Downloads or Desktop to make finding it easier. -::: -::: - ---- - -![](images/Windows/05_SaveTheInstaller.png) - - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -After the download is complete, double click on the installer's .exe file. This will open a popup asking you to select your preferred language. -::: -::: - ---- - -![](images/Windows/07_DesiredLanguage.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course). -::: -::: - ---- - -![](images/Windows/08_GPL2.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -On Windows, R will normally save it's software folder under Program Files. -::: -::: - ---- - -![](images/Windows/09_ProgramFiles.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next, please accept the defaults. -::: -::: - ---- - -![](images/Windows/10_Defaults.png) - - ---- - - -![](images/Windows/11_Defaults.png) - ---- - -![](images/Windows/12_Defaults.png) - ---- - -![](images/Windows/13_Defaults.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -With the defaults accepted, the installation will commence. Feel free to go have a coffee/tea/beverage-of-your choice break while you wait. -::: -::: - ---- - -![](images/Windows/14_Install.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And if all goes well, the installation will complete without any issues. -::: -::: - ---- - -![](images/Windows/15_Success.png) - - ---- - -## Installing RTools - -::: {.fragment} -::: {.callout-tip title="."} -We will now work on installing Rtools. This software is needed when building R packages from source, which we will need throughout the course for R packages hosted on GitHub. - -To get started, we will return to the [R installation](https://cloud.r-project.org/) page we visited previously and instead click on the [Rtools](https://cloud.r-project.org/bin/windows/Rtools/) option. -::: -::: - ---- - -![](images/Windows/16_Rtools.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next, select the most recent version of Rtools to Download. -::: -::: - ---- - -![](images/Windows/17_RtoolsRecent.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then select for your architecture. For the vast majority of Windows users, your computer will likely be be using a x86 chip architecture, so you would select the Rtools45 installer option. - -If your computer however uses the ARM chip architecture, you would select the 64-bit ARM Rtools45 installer instead. If you are unsure, see the [following](https://youtu.be/Z_lcEqomG0k?si=U0fd7sHTZhCJroSm). -::: -::: - ---- - -![](images/Windows/18_64x86.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next, you will select the location to save the Rtools installer to. We generally save this to either Downloads or Desktop to make finding it easier. -::: -::: - ---- - -![](images/Windows/17_Downloads.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once downloaded, double click on the .exe to launch the Rtools installer. -::: -::: - ---- - -![](images/Windows/19_RtoolsInstall.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Similar to what we did when installing R, go ahead and keep the defaults. -::: -::: - ---- - -![](images/Windows/20_RtoolsDefaults.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And click install to proceed with the installation. -::: -::: - ---- - -![](images/Windows/21_RtoolsDefaults.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And wait while the installation wraps up. -::: -::: - ---- - -![](images/Windows/22_Download.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If all goes well, you should see the following installation success page. -::: -::: - ---- - -![](images/Windows/24_Rtools.png) - - ---- - -## Installing Git - -::: {.fragment} -::: {.callout-tip title="."} -[Git](https://git-scm.com/) is a version control software widely used among software developers and bioinformaticians. We will use it extensively throughout the course, both locally on our computers (to keep track of changes to our files), as well as in combination with [GitHub](https://github.com/)(to maintain online backups of our files). - -We will first navigate to the [website](https://git-scm.com/) and select the download from Windows option. -::: -::: - ---- - -![](images/Windows/01_Git.png){fig-align="center" width="600"} - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will then proceed and select [install 64-bit Git for Windows Setup]{.underline} option -::: -::: - ---- - -![](images/Windows/02_Git.png){fig-align="center" width="600"} - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -As was the case with our installation of R and Rtools, a pop-up will appear asking for a location to save the installer to. - -Once downloaded, double-click and proceed with the installation. - -You will be asked to accept the Git License (which is the free copyleft GPL2 license, which we will learn about later in the course). -::: -::: - ---- - -![](images/Windows/02_GitLicense.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Then you will be asked to select the folder to save to software to (usually your Programs folder) -::: -::: - ---- - -![](images/Windows/03_GitDestination.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -At this point, the Git installer will ask a series of increasingly niche questions. It is best to just accept all the default options, to avoid wandering too far down a ["What is Vim?!?"](https://www.vim.org/) rabbit-hole. -::: -::: - ---- - -![](images/Windows/04_GitComponents.png) - - ---- - -![](images/Windows/05_GitStartMenu.png) - ---- - -![](images/Windows/06_GitWhatsVim.png) - - ---- - -![](images/Windows/07_GitDecide.png) - ---- - -![](images/Windows/08_GitCommandLine.png) - - ---- - -![](images/Windows/09_GitBundledSSH.png) - ---- - -![](images/Windows/10_GitHTTPS.png) - ---- - -![](images/Windows/11_GitUnix.png) - ---- - -![](images/Windows/12_GitEmulator.png) - ---- - -![](images/Windows/13_GitPull.png) - ---- - -![](images/Windows/14_GitCredentialManager.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Having made it through all the niche customization screens, we finally reach the install button. -::: -::: - ---- - -![](images/Windows/15_GitFileCatch.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We then can wait for the install to complete. -::: -::: - ---- - -![](images/Windows/16_GitInstalling.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And success, we have now installed Git. -::: -::: - ---- - -![](images/Windows/17_GitInstalled.png) - - ---- - - -## Installing Positron - -::: {.fragment} -::: {.callout-tip title="."} -Finally, you will install [Positron](https://positron.posit.co/). It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course. - -First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. -::: -::: - ---- - -![](images/Windows/25_Positron.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). - -With the license accepted, you will be able to select your operating system. In this case, we will select Windows, specifally the user level install. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -![](images/Windows/26_UserInstall.png) -::: -::: - ---- - -Please note, if you are using a Windows computer with an ARM based chip (like is the case with Snapdragons), you will need to download the installed from the Positron's GitHub [Release Page](), as they are still testing some features. - ---- - -![](images/Windows/WindowsArm.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then be prompted to select the location you want to save the installer to. We will generally save this to either Downloads or Desktop to make finding it easier. -::: -::: - ---- - -![](images/Windows/27_InstallerLocation.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once the download is complete, double click on the installer, and again accept the license agreement. -::: -::: - ---- - -![](images/Windows/28_Elastic.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Generally, Positron will be store its software folder under Program Files. -::: -::: - ---- - -![](images/Windows/29_SaveLocation.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next up, accept the default options for the following screens -::: -::: - ---- - -![](images/Windows/30_Defaults.png) - ---- - -![](images/Windows/31_Defaults.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And finally, click Install. -::: -::: - ---- - -![](images/Windows/32_Defaults.png) - ---- - -![](images/Windows/34_Install.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If all goes well, you should then see the installation success page. -::: -::: - ---- - -![](images/Windows/35_Success.png) - - ---- - -# Connecting GitHub and Positron - -::: {.fragment} -::: {.callout-tip title="."} -Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected. - -When opening Positron for the first time, you will encounter the following view: -::: -::: - ---- - -![](images/Windows/36_PositronLanding.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right, and then select the most recent/up-to-date R version. -::: -::: - ---- - -![](images/Windows/37_AllHiddenCondas.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) -::: -::: - ---- - -![](images/Windows/38_Loaded.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. - -Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. -::: -::: - ---- - -![](images/Windows/39_GitHubSetup.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. -::: -::: - ---- - -![](images/Windows/40_Code.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. -::: -::: - ---- - -![](images/Windows/41_GitHub.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. -::: -::: - ---- - -![](images/Windows/42_GitHubPassword.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. -::: -::: - ---- - -![](images/Windows/43_GitHubSetup.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Depending on your computer settings, you may be asked for your two-factor authorization passkey. If so, complete this step. -::: -::: - ---- - -![](images/Windows/44_Passkey.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And if all works out, you should see the following succes page -::: -::: - ---- - -![](images/Windows/45_PasskeySuccess.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. -::: -::: - ---- - -![](images/Windows/46_PositronSuccess.png) - - ---- - -# New Folder from Git - -::: {.fragment} -::: {.callout-tip title="."} -With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. - -To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option -::: -::: - ---- - -![](images/MacOS/24.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" -::: -::: - ---- - -![](images/FolderFromGit1.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. -::: -::: - ---- - -![](images/Import2.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. -::: -::: - ---- - -![](images/MacOS/28.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And with that done, you should now see the forked Cytometry in R course contents appear within Positron. -::: -::: - ---- - -![](images/Import2Done.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" -::: -::: - ---- - -![](images/FolderFromGit2.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. -::: -::: - ---- - -![](images/Import2.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. -::: -::: - ---- - -![](images/Import2Done.png) - - ---- - -# Wrap-up - -::: {.fragment} -::: {.callout-tip title="."} -In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. - -In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. -::: -::: - - ---- - -# Additional Resources - -[How to Download and Install Software on Windows 11](https://youtu.be/IEhnWKZB4p4?t=60) - -[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) - -[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) - -[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Installing Software on Windows" +author: "David Rach" +date: 02-01-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +::: {.fragment} +::: {.callout-tip title="."} +This is the software installation walkthrough for those whose computers are running Windows. Based on our pre-course interest form, you make up the majority of course participants. +::: +::: + +--- + +![](/course/00_WorkstationSetup/images/ComputerOS.png){width=100%} + +--- + +# Background + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this walkthrough, we will have you install the following pieces of software: + +[R website](https://www.r-project.org/) : The programming language we will be using throughout the course. + +[Positron](https://positron.posit.co/) : The integrated development environment (IDE) in which we will open, modify and run our code. + +[Git](https://git-scm.com/) : The version control software that will allow us to track changes to our files. + +Additionally, Windows users will need to install: + +[RTools](https://cran.r-project.org/bin/windows/Rtools/rtools45/rtools.html) : Used to build R packages from source code. +::: +::: + +# Getting Started + + +--- + +## Installing R + +::: {.fragment} +::: {.callout-tip title="."} +To get started, first navigate to the [R website](https://www.r-project.org/). Once there, click on [Download R](https://cran.r-project.org/mirrors.html) option towards the top of the page. +::: +::: + +--- + +![](images/Windows/01_RLanding.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the [Cloud](https://cloud.r-project.org/) option which should redirect you. +::: +::: + +--- + +![](images/Windows/02_Landing.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then select your Operating System, in this case, [Windows](https://cloud.r-project.org/bin/windows/). +::: +::: + +--- + +![](images/Windows/03_ForWindows.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And go ahead and select the [Install R for the first time](https://cloud.r-project.org/bin/windows/base/) link. +::: +::: + +--- + +![](images/Windows/04_ForFirstTime.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next, you will select the download the current version option at the top of the page. +::: +::: + +--- + +![](images/Windows/04_CurrentVersion.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The popup window will then ask where you want to save the installer (.exe) file. We generally save this to either Downloads or Desktop to make finding it easier. +::: +::: + +--- + +![](images/Windows/05_SaveTheInstaller.png) + + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +After the download is complete, double click on the installer's .exe file. This will open a popup asking you to select your preferred language. +::: +::: + +--- + +![](images/Windows/07_DesiredLanguage.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course). +::: +::: + +--- + +![](images/Windows/08_GPL2.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +On Windows, R will normally save it's software folder under Program Files. +::: +::: + +--- + +![](images/Windows/09_ProgramFiles.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next, please accept the defaults. +::: +::: + +--- + +![](images/Windows/10_Defaults.png) + + +--- + + +![](images/Windows/11_Defaults.png) + +--- + +![](images/Windows/12_Defaults.png) + +--- + +![](images/Windows/13_Defaults.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +With the defaults accepted, the installation will commence. Feel free to go have a coffee/tea/beverage-of-your choice break while you wait. +::: +::: + +--- + +![](images/Windows/14_Install.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And if all goes well, the installation will complete without any issues. +::: +::: + +--- + +![](images/Windows/15_Success.png) + + +--- + +## Installing RTools + +::: {.fragment} +::: {.callout-tip title="."} +We will now work on installing Rtools. This software is needed when building R packages from source, which we will need throughout the course for R packages hosted on GitHub. + +To get started, we will return to the [R installation](https://cloud.r-project.org/) page we visited previously and instead click on the [Rtools](https://cloud.r-project.org/bin/windows/Rtools/) option. +::: +::: + +--- + +![](images/Windows/16_Rtools.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next, select the most recent version of Rtools to Download. +::: +::: + +--- + +![](images/Windows/17_RtoolsRecent.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then select for your architecture. For the vast majority of Windows users, your computer will likely be be using a x86 chip architecture, so you would select the Rtools45 installer option. + +If your computer however uses the ARM chip architecture, you would select the 64-bit ARM Rtools45 installer instead. If you are unsure, see the [following](https://youtu.be/Z_lcEqomG0k?si=U0fd7sHTZhCJroSm). +::: +::: + +--- + +![](images/Windows/18_64x86.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next, you will select the location to save the Rtools installer to. We generally save this to either Downloads or Desktop to make finding it easier. +::: +::: + +--- + +![](images/Windows/17_Downloads.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once downloaded, double click on the .exe to launch the Rtools installer. +::: +::: + +--- + +![](images/Windows/19_RtoolsInstall.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Similar to what we did when installing R, go ahead and keep the defaults. +::: +::: + +--- + +![](images/Windows/20_RtoolsDefaults.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And click install to proceed with the installation. +::: +::: + +--- + +![](images/Windows/21_RtoolsDefaults.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And wait while the installation wraps up. +::: +::: + +--- + +![](images/Windows/22_Download.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If all goes well, you should see the following installation success page. +::: +::: + +--- + +![](images/Windows/24_Rtools.png) + + +--- + +## Installing Git + +::: {.fragment} +::: {.callout-tip title="."} +[Git](https://git-scm.com/) is a version control software widely used among software developers and bioinformaticians. We will use it extensively throughout the course, both locally on our computers (to keep track of changes to our files), as well as in combination with [GitHub](https://github.com/)(to maintain online backups of our files). + +We will first navigate to the [website](https://git-scm.com/) and select the download from Windows option. +::: +::: + +--- + +![](images/Windows/01_Git.png){fig-align="center" width="600"} + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will then proceed and select [install 64-bit Git for Windows Setup]{.underline} option +::: +::: + +--- + +![](images/Windows/02_Git.png){fig-align="center" width="600"} + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As was the case with our installation of R and Rtools, a pop-up will appear asking for a location to save the installer to. + +Once downloaded, double-click and proceed with the installation. + +You will be asked to accept the Git License (which is the free copyleft GPL2 license, which we will learn about later in the course). +::: +::: + +--- + +![](images/Windows/02_GitLicense.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Then you will be asked to select the folder to save to software to (usually your Programs folder) +::: +::: + +--- + +![](images/Windows/03_GitDestination.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +At this point, the Git installer will ask a series of increasingly niche questions. It is best to just accept all the default options, to avoid wandering too far down a ["What is Vim?!?"](https://www.vim.org/) rabbit-hole. +::: +::: + +--- + +![](images/Windows/04_GitComponents.png) + + +--- + +![](images/Windows/05_GitStartMenu.png) + +--- + +![](images/Windows/06_GitWhatsVim.png) + + +--- + +![](images/Windows/07_GitDecide.png) + +--- + +![](images/Windows/08_GitCommandLine.png) + + +--- + +![](images/Windows/09_GitBundledSSH.png) + +--- + +![](images/Windows/10_GitHTTPS.png) + +--- + +![](images/Windows/11_GitUnix.png) + +--- + +![](images/Windows/12_GitEmulator.png) + +--- + +![](images/Windows/13_GitPull.png) + +--- + +![](images/Windows/14_GitCredentialManager.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Having made it through all the niche customization screens, we finally reach the install button. +::: +::: + +--- + +![](images/Windows/15_GitFileCatch.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We then can wait for the install to complete. +::: +::: + +--- + +![](images/Windows/16_GitInstalling.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And success, we have now installed Git. +::: +::: + +--- + +![](images/Windows/17_GitInstalled.png) + + +--- + + +## Installing Positron + +::: {.fragment} +::: {.callout-tip title="."} +Finally, you will install [Positron](https://positron.posit.co/). It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course. + +First, navigate to their [homepage](https://positron.posit.co/), and select the blue Download option button on the upper-right. +::: +::: + +--- + +![](images/Windows/25_Positron.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course). + +With the license accepted, you will be able to select your operating system. In this case, we will select Windows, specifally the user level install. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +![](images/Windows/26_UserInstall.png) +::: +::: + +--- + +Please note, if you are using a Windows computer with an ARM based chip (like is the case with Snapdragons), you will need to download the installed from the Positron's GitHub [Release Page](), as they are still testing some features. + +--- + +![](images/Windows/WindowsArm.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then be prompted to select the location you want to save the installer to. We will generally save this to either Downloads or Desktop to make finding it easier. +::: +::: + +--- + +![](images/Windows/27_InstallerLocation.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once the download is complete, double click on the installer, and again accept the license agreement. +::: +::: + +--- + +![](images/Windows/28_Elastic.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Generally, Positron will be store its software folder under Program Files. +::: +::: + +--- + +![](images/Windows/29_SaveLocation.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next up, accept the default options for the following screens +::: +::: + +--- + +![](images/Windows/30_Defaults.png) + +--- + +![](images/Windows/31_Defaults.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And finally, click Install. +::: +::: + +--- + +![](images/Windows/32_Defaults.png) + +--- + +![](images/Windows/34_Install.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If all goes well, you should then see the installation success page. +::: +::: + +--- + +![](images/Windows/35_Success.png) + + +--- + +# Connecting GitHub and Positron + +::: {.fragment} +::: {.callout-tip title="."} +Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected. + +When opening Positron for the first time, you will encounter the following view: +::: +::: + +--- + +![](images/Windows/36_PositronLanding.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will go over the various aspects of using Positron in the next [section](/course/00_Positron/index.qmd). For now select the "Start Session" button on the upper right, and then select the most recent/up-to-date R version. +::: +::: + +--- + +![](images/Windows/37_AllHiddenCondas.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +R will proceed to activate, and you will see a message appear in the bottom center window (ie. console) +::: +::: + +--- + +![](images/Windows/38_Loaded.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your [GitHub](https://github.com/) account from your preferred web browser. + +Once this is done, return to Positron, and click on the profile Icon and select "Sign with GitHub" option. +::: +::: + +--- + +![](images/Windows/39_GitHubSetup.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the "Copy & Continue to GitHub" button. +::: +::: + +--- + +![](images/Windows/40_Code.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account. +::: +::: + +--- + +![](images/Windows/41_GitHub.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue. +::: +::: + +--- + +![](images/Windows/42_GitHubPassword.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And select "Authorize posit-dev" to authorize Positron to interact with your GitHub Account. +::: +::: + +--- + +![](images/Windows/43_GitHubSetup.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Depending on your computer settings, you may be asked for your two-factor authorization passkey. If so, complete this step. +::: +::: + +--- + +![](images/Windows/44_Passkey.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And if all works out, you should see the following succes page +::: +::: + +--- + +![](images/Windows/45_PasskeySuccess.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed. +::: +::: + +--- + +![](images/Windows/46_PositronSuccess.png) + + +--- + +# New Folder from Git + +::: {.fragment} +::: {.callout-tip title="."} +With [GitHub](https://github.com/) and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer. + +To this, first navigate to the Folder icon on the upper-right, and select the "New Folder from Git" option +::: +::: + +--- + +![](images/MacOS/24.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in "https://github.com/UMGCCCFCSR/CytometryInR" +::: +::: + +--- + +![](images/FolderFromGit1.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder. +::: +::: + +--- + +![](images/Import2.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven't had time to properly vet. +::: +::: + +--- + +![](images/MacOS/28.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And with that done, you should now see the forked Cytometry in R course contents appear within Positron. +::: +::: + +--- + +![](images/Import2Done.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will now repeat the process to bring in youir GitHub profile's ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: "https://github.com/UMGCCCFCSR/UMGCCCFCSR" +::: +::: + +--- + +![](images/FolderFromGit2.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK. +::: +::: + +--- + +![](images/Import2.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer. +::: +::: + +--- + +![](images/Import2Done.png) + + +--- + +# Wrap-up + +::: {.fragment} +::: {.callout-tip title="."} +In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course. + +In the [next section](/course/00_Positron/), we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send [changes](/course/00_Git/) from your local repositories back to GitHub. +::: +::: + + +--- + +# Additional Resources + +[How to Download and Install Software on Windows 11](https://youtu.be/IEhnWKZB4p4?t=60) + +[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) + +[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) + +[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/00_WorkstationSetup/images/.DS_Store b/course/00_WorkstationSetup/images/.DS_Store deleted file mode 100644 index 14ba08b..0000000 Binary files a/course/00_WorkstationSetup/images/.DS_Store and /dev/null differ diff --git a/course/00_WorkstationSetup/images/MacOS/.DS_Store b/course/00_WorkstationSetup/images/MacOS/.DS_Store deleted file mode 100644 index 3278aca..0000000 Binary files a/course/00_WorkstationSetup/images/MacOS/.DS_Store and /dev/null differ diff --git a/course/00_WorkstationSetup/index.qmd b/course/00_WorkstationSetup/index.qmd index 523b9f2..5f2be3e 100644 --- a/course/00_WorkstationSetup/index.qmd +++ b/course/00_WorkstationSetup/index.qmd @@ -1,86 +1,86 @@ ---- -title: "Workstation Setup" -author: "David Rach" -date: 01-17-2026 -format: html -toc: true -toc-depth: 4 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -In the previous [section](/course/00_GitHub/index.qmd), we first set up your [GitHub](https://github.com/) account. Then we modified your GitHub profile and added a README section. Finally, we forked the [CytometryInR](https://github.com/UMGCCCFCSR/CytometryInR/) repository so that you can easily retrieve the new course materials each week. - -It is now time to install the required software on your computer, which will get your work-station set up with everything needed for this course. Depending on your computers operating system, the installation requirements may differ a bit. In general, you will need to install the following software: - -[R website](https://www.r-project.org/) : The programming language we will be using throughout the course. - -[Positron](https://positron.posit.co/) : The integrated development environment (IDE) in which we will open, modify and run our code. - -[Git](https://git-scm.com/) : The version control software that will allow us to track changes to our files. - -Additionally, Windows users will need to install: - -[RTools](https://cran.r-project.org/bin/windows/Rtools/rtools45/rtools.html) : Used to build R packages from source code. - -You can find the operating system specific installation walkthroughs below. Once you have completed your specific walkthrough, return to this page and proceed to the [next section](/course/00_Positron/). - -***Please note:*** For those using university or company administered computers, please be aware that you may not have the necessary permissions to install these directly, and may need to reach out to your IT department to help get the software installed and running correctly. - -If you are using your own computer, congratulations, you are your system administrator, and should already have the necessary permissions. - -# Install Software for - -## Windows - -![](https://winaero.com/blog/wp-content/uploads/2021/06/Windows-11-Win-X-Menu-icon.png){width=25%} - -Installation walkthrough for [Windows](Windows.qmd) - -
- ---- - -## MacOS - -![](https://substackcdn.com/image/fetch/$s_!G1lk!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F8ed3d547-94ff-48e1-9f20-8c14a7030a02_2000x2000.jpeg){width=25%} - -Installation walkthrough for [MacOS](MacOS.qmd) - -
- ---- - -## Linux (Debian) - -![](https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTAx6camOf_G96Zcs2Zj34Yjmy0ysPd-p0oJQ&s){width=25%} - -Installation walkthrough for [Linux](Linux.qmd) - -
- ---- - -# Additional Resources - -[How to Download and Install Software on Windows 11](https://youtu.be/IEhnWKZB4p4?t=60) - -[How to Install Software on a Mac](https://youtu.be/OH6cSQikbdw?si=ywXBU_eD2kl9AnLU) - -[How to Download and Install Software on Linux](https://youtu.be/lC4d4EpMMxg?si=9TeFkwFzrRbzA-Ma) - -[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) - -[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) - -[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) - - - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "Workstation Setup" +author: "David Rach" +date: 01-17-2026 +format: html +toc: true +toc-depth: 4 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +In the previous [section](/course/00_GitHub/index.qmd), we first set up your [GitHub](https://github.com/) account. Then we modified your GitHub profile and added a README section. Finally, we forked the [CytometryInR](https://github.com/UMGCCCFCSR/CytometryInR/) repository so that you can easily retrieve the new course materials each week. + +It is now time to install the required software on your computer, which will get your work-station set up with everything needed for this course. Depending on your computers operating system, the installation requirements may differ a bit. In general, you will need to install the following software: + +[R website](https://www.r-project.org/) : The programming language we will be using throughout the course. + +[Positron](https://positron.posit.co/) : The integrated development environment (IDE) in which we will open, modify and run our code. + +[Git](https://git-scm.com/) : The version control software that will allow us to track changes to our files. + +Additionally, Windows users will need to install: + +[RTools](https://cran.r-project.org/bin/windows/Rtools/rtools45/rtools.html) : Used to build R packages from source code. + +You can find the operating system specific installation walkthroughs below. Once you have completed your specific walkthrough, return to this page and proceed to the [next section](/course/00_Positron/). + +***Please note:*** For those using university or company administered computers, please be aware that you may not have the necessary permissions to install these directly, and may need to reach out to your IT department to help get the software installed and running correctly. + +If you are using your own computer, congratulations, you are your system administrator, and should already have the necessary permissions. + +# Install Software for + +## Windows + +![](https://winaero.com/blog/wp-content/uploads/2021/06/Windows-11-Win-X-Menu-icon.png){width=25%} + +Installation walkthrough for [Windows](Windows.qmd) + +
+ +--- + +## MacOS + +![](https://substackcdn.com/image/fetch/$s_!G1lk!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F8ed3d547-94ff-48e1-9f20-8c14a7030a02_2000x2000.jpeg){width=25%} + +Installation walkthrough for [MacOS](MacOS.qmd) + +
+ +--- + +## Linux (Debian) + +![](https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTAx6camOf_G96Zcs2Zj34Yjmy0ysPd-p0oJQ&s){width=25%} + +Installation walkthrough for [Linux](Linux.qmd) + +
+ +--- + +# Additional Resources + +[How to Download and Install Software on Windows 11](https://youtu.be/IEhnWKZB4p4?t=60) + +[How to Install Software on a Mac](https://youtu.be/OH6cSQikbdw?si=ywXBU_eD2kl9AnLU) + +[How to Download and Install Software on Linux](https://youtu.be/lC4d4EpMMxg?si=9TeFkwFzrRbzA-Ma) + +[Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)](https://youtu.be/D6CunpqF04E?si=jeU6-XiSRj-ygDf_) + +[A brief tour of Positron](https://posit.co/blog/a-quick-tour-of-positron/) + +[A brief introduction to Git for beginners](https://youtu.be/r8jQ9hVA2qs?si=jNastI7kNiGHHG9O) + + + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/01_InstallingRPackages/homeworks/README.md b/course/01_InstallingRPackages/homeworks/README.md index 2818b5e..fe53443 100644 --- a/course/01_InstallingRPackages/homeworks/README.md +++ b/course/01_InstallingRPackages/homeworks/README.md @@ -1,5 +1,5 @@ -# Turning In Optional Take-Home Problems - -This folder is for the use of submitting your completed Take-Home Problems for evaluation by course instructors. Please see [Getting Help](/course/00_Homeworks/index.qmd) walkthrough for more detailed instructions. - +# Turning In Optional Take-Home Problems + +This folder is for the use of submitting your completed Take-Home Problems for evaluation by course instructors. Please see [Getting Help](/course/00_Homeworks/index.qmd) walkthrough for more detailed instructions. + Within your branch, inside this "homeworks" folder, create a new folder (name it with your GitHub username). Then copy all files you will be submitting within your folder. Then commit the change to git, and push to GitHub. See [Getting Help](/course/00_Homeworks/index.qmd)for details on submitting the pull request to the UMGCCCFCSR/CytometryInR homework branch. \ No newline at end of file diff --git a/course/01_InstallingRPackages/homeworks/claude-chew/Week1_Homework.qmd b/course/01_InstallingRPackages/homeworks/claude-chew/Week1_Homework.qmd new file mode 100644 index 0000000..d748c0a --- /dev/null +++ b/course/01_InstallingRPackages/homeworks/claude-chew/Week1_Homework.qmd @@ -0,0 +1,83 @@ +--- +title: "Week1 Homework" +format: html +--- + +# Problem 1: PeacoQC functions: + +# These are all arguments, not functions +ff +channels +determine_good_cells +plot +save_fcs +output_directory +name_directory +report +events_per_bin +min_cells +max_bins +step +MAD +IT_limit +consecutive_bins +remove_zeros +suffix_fcs +force_IT +peak_removal +min_nr_bins_peakdetection +time_channel_parameter + +# PeacoQC also has a Heatmap function - PeacoQCHeatmap() that contains: +# These are all aguments, not functions +report_location +show_values +show_row_names +latest_tests +title + +And you can add extra parameters to the heatmap function. + +You can also plot the deleted cells from running PeacoQC using PlotPeacoQC() + +Preprocessing functions to PeacoQC are: + +PeacoQC +PeacoQCHeatmap +PlotPeacoQC +RemoveDoublets() +RemoveMargins() + + +# Problem 2: 1. How many cytometry packages are currently in Bioconductor and the 2. author/maintainer with the most contributed cytometry R packages. 3. Couple of packages to explore later in the course + +1. There are 69 cytometry packages currently in Bioconductor +2. Mike Jiang +3. cytoMEM, FlowSOM + +# Problem 3: Using pak to install “broom”, “cytoMEM”, “DillonHammill/CytoExploreR”. + +First thing I had to do was install pak itself from CRAN using install.packages("pak") +Then, using pak to install these packages meant that I had to call the pkg_install function from pak using the pak::pkg_install() command. It generated a different string of installation commands for each package installed. + +I ran into a problem attempting to install CytoExploreR. I had to specifically call for a version 1.0.0 of the package "superheat" from GitHub, that was a dependency of CytoExploreR. Once I had that installed, CytoExploreR successfully installed using pak. + +Code used for this is below. + +```{r} +install.packages("pak") +library(pak) +pak::pkg_install("broom") +pak::pkg_install("cytoMEM") + + + +# Install superheat 1.0.0 from GitHub +pak::pkg_install("rlbarter/superheat") +pak::pkg_install("DillonHammill/CytoExploreR") +``` + + +![Installing Broom](installing_broom.png) +![Installing cytoMEM](installing_cytoMEM.png) +![Installing CytoExploreR](installing_CytoExploreR.png) \ No newline at end of file diff --git a/course/01_InstallingRPackages/homeworks/claude-chew/installing_CytoExploreR.png b/course/01_InstallingRPackages/homeworks/claude-chew/installing_CytoExploreR.png new file mode 100644 index 0000000..06f22cc Binary files /dev/null and b/course/01_InstallingRPackages/homeworks/claude-chew/installing_CytoExploreR.png differ diff --git a/course/01_InstallingRPackages/homeworks/claude-chew/installing_broom.png b/course/01_InstallingRPackages/homeworks/claude-chew/installing_broom.png new file mode 100644 index 0000000..e5fd813 Binary files /dev/null and b/course/01_InstallingRPackages/homeworks/claude-chew/installing_broom.png differ diff --git a/course/01_InstallingRPackages/homeworks/claude-chew/installing_cytoMEM.png b/course/01_InstallingRPackages/homeworks/claude-chew/installing_cytoMEM.png new file mode 100644 index 0000000..2729f9e Binary files /dev/null and b/course/01_InstallingRPackages/homeworks/claude-chew/installing_cytoMEM.png differ diff --git a/course/01_InstallingRPackages/homeworks/claude-chew/installing_superheat.png b/course/01_InstallingRPackages/homeworks/claude-chew/installing_superheat.png new file mode 100644 index 0000000..0f04aaf Binary files /dev/null and b/course/01_InstallingRPackages/homeworks/claude-chew/installing_superheat.png differ diff --git a/course/01_InstallingRPackages/index.qmd b/course/01_InstallingRPackages/index.qmd index 0cb7f8a..6c9f198 100644 --- a/course/01_InstallingRPackages/index.qmd +++ b/course/01_InstallingRPackages/index.qmd @@ -1,1337 +1,1337 @@ ---- -title: "01 - Installing R Packages" -author: "David Rach" -date: 02-01-2026 -format: html -toc: true -toc-depth: 5 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -For the YouTube livestream recording, see [here](https://youtube.com/live/ZNFNokzsBaM) - - - -For screen-shot slides, click [here](/course/01_InstallingRPackages/slides.qmd) - -```{r} -#| include: FALSE -library(BiocStyle) -``` - -Welcome to the first week of [Cytometry in R](/Schedule.qmd)! This week we will be diving into how R packages work, and the how to go about installing them. - -Before getting started, please make sure you have completed the creating a [GitHub](/course/00_GitHub/) and [Workstation Setup](/course/00_WorkstationSetup/) walk-throughs, since we will begin where they left off once the required software was successfully installed. - -:::{.callout-important} -Please make sure to [sync](/course/00_Homeworks/index.qmd#sync-your-fork) your forked version of the CytometryInR repository, and [pull](/course/00_Git/index.qmd#pull) any changes to your local computer's CytometryInR project folder so that you have the most recent version of the code and data available. -::: - -
- ---- - -# Background - -During [Workstation Setup](/course/00_WorkstationSetup/), you installed the R software to your local computer. R as a [programming language](https://en.wikipedia.org/wiki/R_(programming_language)) that started up in the 1990s. While its original focus was on statistics, it is now widely used in various fields thanks to contributions of many open-source developers over the years. - -This expanded reach is in part due to the ability to create [**R packages**](https://en.wikipedia.org/wiki/R_package), that encapsulate additional [**functions**](https://adv-r.hadley.nz/functions.html#function-fundamentals), that can do new things beyond what the original software (ie. **base R**) was capable of doing. - -
- ---- - -Currently, there are [thousands](https://cran.r-project.org/web/packages/available_packages_by_name.html) of R packages available. Furthermore, there is a vibrant [community](https://www.reddit.com/r/rstats/) of individuals that help maintain and document how to use these packages, which has helped sustain and grow the R ecosystem over the last couple [decades](https://youtu.be/gjpNEVcG1nU?si=rcEBSc7AnAsgsAy2). - -Regardless if you are working with [flow cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry), or in [ecology](https://drmattg.github.io/REcol-verse/), or in [econometrics](https://www.econometrics-with-r.org/1-introduction.html), or [political science](https://github.com/fivethirtyeight/data), a lot of the analysis and visualizations that you see in publications often involve R. - -
- ---- - -:::{.callout-tip} -R packages can also just be made for fun! Among my favorite examples of this, there is an R package that lets you add the snake game to your [recalculating screen](https://github.com/AdamSpannbauer/snakeLoadR), as well as R packages that provide the color-palette schemes needed to make your plots with [Studio Ghibli](https://github.com/ewenme/ghibli), [Wes Anderson](https://github.com/karthik/wesanderson), or [Bluey](https://github.com/ekholme/blueycolors) colors. -::: - -
- ---- - -These R packages start off as [source code](https://r-pkgs.org/structure.html#sec-package-states) (which is what we will be learning to write during this course). When you install a R package to your computer, this human-readable source code gets converted into a binary format with which your computer can interact directly. - -
- ---- - -Expanding on this concept, a new R package can be made up of new code (primarily in the form of tools (ie. **functions**) that do a particular useful things) that is entirely self-contained, or reuse functions present in existing R packages to help make something new. When an R package relies on a function from another R package, it needs the other R package to be installed in order for everything to work properly. This is known as a package **dependency**. - -
- ---- - -To make distributing the thousands of R packages and their associated package dependencies easier, R packages are collected (ie. hosted) within **repositories**, which function as an intermediate distributor. - -The three main locations for R packages from are **[CRAN](https://cran.r-project.org/)** (containing 23069 packages), **[Bioconductor](https://www.bioconductor.org/)** (containing 2361 packages), and individual R packages hosted by their developers via **[GitHub](https://github.com/trending/r)**. - -
- ---- - -The process of installing R packages will vary a bit depending on which repository the respective R package is in. For beginners, this often prooves to be a pain-point, as they will attempt to install an R package using one set of installation commands, only to get an error (because the R package is not in that repository). - -
- ---- - -In this session, we will work on installing the various R packages we will need through the course. While doing so, we will explore how to figure out which repository the individual package is in; what installation commands to use to download it; and how to look up the help documentation. We will also touch on how the functions within an R package are made available for our computer to use (via the `library()` call), and how to troubleshoot the more commonly encountered installation errors. - -
- ---- - -# Getting Started - -## Set Up - -Alright, with the background out of the way, let's get started! - -:::{.callout-important} -Please make sure to [sync](/course/00_Homeworks/index.qmd#sync-your-fork) your forked version of the CytometryInR repository, and [pull](/course/00_Git/index.qmd#pull) any changes to your local computer's CytometryInR project folder so that you have the most recent version of the code and data available. -::: - -:::{.callout-warning} -Please remember to always copy over the new material from your local CytometryInR folder to a separate Project Folder that you created and named (ex. "Week_01" or "MyLearningFolder", etc.). This will ensure any edits you make to the files do not affect your ability to bring in next week's materials to the CytometryInR folder -::: - -
- ---- - -After pulling the new data and code locally, open CytometryInR, open the course folder, and open the 01_InstallingRPackages folder. From here, copy the **index.qmd** file to your own working Project Folder (ex. Week_01) where you can work on it without causing any conflicts. Then return to Positron and open up your working project folder (ex. Week_01). - -![](images/01_Interpreter.png) - -
- ---- - -Next up, within [Positron](/course/00_Positron/index.qmd#interpreter), let's make sure to select R as the coding language being used for this session. - -![](images/01_Interpreter.png) - -
- ---- - -Now that R is running within Positron, the console (lower portion of the screenn) is now able to run (ie. execute) any R code that is sent to it. - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - -## Checking for Loaded Packages - -For the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active. - -
- ---- - -### Accessing Help Documentation - -Within your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following `sessionInfo()` function: - -```{r} -#| eval: FALSE -sessionInfo() -``` - -
- ---- - -If you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over. - -![](images/02_HelpHover.png) - -
- ---- - -In this case, we can see the help documentation corresponding for `sessionInfo()`. Beyond hovering over the function, this can also be accessed by adding a ? directly in front of the function, and then running that line of code. - -```{r} -#| eval: FALSE -?sessionInfo() -``` - -![](images/03_QuestionMark.png) - -
- ---- - -When executed, the function's help file documentation will open up within the Help tab in the secondary side bar on the right-side of the screen. Glancing at the top of the page we can see the name of the package that contains the `sessionInfo()` function (`{utils}`). Scrolling down the help page past all the documentation, we can see a link to the index page. - -![](images/04_Index.png) - -
- ---- - -After clicking, the Help tab switches from viewing the documentation for the `sessionInfo()` function, to showing all the functions within the `utils` package. Most R packages contain help documentation, so this process can be adapted to find out additional information about what a function does, and what arguments are needed to produce customized outputs. - -![](images/05_UtilsFunctions.png) - - -
- ---- - -### sessionInfo() - -Within your .qmd file, let's go ahead and run the following code-block: - -```{r} -sessionInfo() -``` - -
- ---- - -The outputs that get returned by `sessionInfo()` will vary a bit depending on your computer's [operating system](/course/00_WorkstationSetup/), and the version of R you have installed. - -For today, let's focus on the last two elements of the output: - -![](images/06_sessionInfo.png) - -
- ---- - -The [R software](https://www.r-project.org/) itself is made up of several **base R packages**, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages. - -As we install additional R packages and load them using the `library()` function throughout this session, sporadically re-run `sessionInfo()` to see how this list of R packages changes. - -
- ---- - -## Installing from CRAN - -We will start by installing R packages that are part of the [CRAN](https://cran.r-project.org/) repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository. - -These include the [tidyverse](https://tidyverse.org/) packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today. - -
- ---- - -### dplyr - -Our first R package we will install during this session is the [dplyr](https://dplyr.tidyverse.org/) package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function `install.packages()`. - -```{r} -#| eval: FALSE -?install.packages() -``` - -![](images/07_InstallPackages.png) - -
- ---- - -For the `install.packages()` function, we place within the () the name of the R package from CRAN that we wish to install. - -```{r} -#| eval: FALSE -install.packages("dplyr") -``` - -
- ---- - -:::{.callout-tip} -A usual struggle point for beginners is that install.packages() requires " " to be placed around the package name. Forgetting them results in the error that we see below. -::: - -```{r} -#| error: TRUE - -install.packages(dplyr) -``` - -
- ---- - -```{r} -#| eval: FALSE -install.packages("dplyr") -``` - - -Go ahead and click on "Run Cell" next to your code-block, to install the `dplyr` R package. - -
- ---- - -When a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system). - -![](images/08_InstallScript.png) - -
- ---- - -Within this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN. - -If the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder. - -![](images/09_InstallScript2.png) - -
- ---- - -The final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the "Done" line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder). - -
- ---- - -### Attaching packages via library() - -If an R package has been installed successfully, we are now able to load it (ie. make it's functions available) to our local environment using the `library()` function. - -```{r} -#| eval: FALSE -?library() -``` - -
- ---- - -Unlike `install.packages()`, where we needed "" around the package name, the `library()` function does not require "" around the package name. Let's go ahead and load in `dplyr`, making its respective functions to our local environment. - -```{r} -library(dplyr) -``` - -
- ---- - -From the output, we can see that `dplyr` has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages. - -With `dplyr` now loaded via the `library()` call, let's check `sessionInfo()` to see what has changed. - -```{r} -sessionInfo() -``` - -
- ---- - -Similar to what was seen for the base R packages, `dplyr` is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the `dplyr` packages `select()` function and it's respective help page. - -```{r} -#| eval: FALSE -?select -``` - -![](images/10_Attached.png) - -
- ---- - -Since its parent package has been attached to our local environment (via the `library()` call), we can see `dplyr` functions appear as suggestions as we begin to type. - -By contrast, is we check for the `ggplot()` function from the ggplot2 package (which we haven't yet installed or attached via `library()`), no suggestions will pop up. - -```{r} -?ggplot -``` - -
- ---- - -Beyond individual functions, some R packages also have help landing pages, that can be similarly accessed by adding a ? in front of the package name: - -![](images/11_PackageLanding.png) - -
- ---- - -### Unattaching - -So far, we have installed an R package, and then attached it (via `library()`). How would we reverse these steps? - -Well, to unload it from the local environment, there are a couple options. You could of course simply shut down Positron. The local environment only exist in context of when you open and close the session, which closing the program will do. All previously loaded R packages will be unattached, which is why when you start a new session you will need to load in all packages you plan on using via `library()`. - -Alternatively, although less used, you could `detach()` it via your console: - -```{r} -detach("package:dplyr", unload=TRUE) -``` - -```{r} -sessionInfo() -``` - -
- ---- - -Looking at the `sessionInfo()` output, dplyr is no longer attached to the local environment. Consequently, if we try to once again look for the documentation, no information will be retrieved. - -```{r} -?dplyr -``` - -
- ---- - -There is a workaround however, if we want to access functions from an unloaded R package. We can specify the R package's name, followed by two :, and then the function name. The :: conveys the context to your computer that the package is present, but may not be attached. - -```{r} -#| eval: FALSE -?dplyr::select() -``` - -This particular use case can be useful if we want to run a particular function, but not load in all a packages functions (which may have identical function names to other R packages we are using and cause some conflicts). - -
- ---- - -### Removing Packages - -Just as we can install an R package, we can also uninstall an R package (although doing so is rare, most often when encountering package dependency conflict). To do so, we would use the `remove.packages()` function. - -```{r} -#| eval: FALSE -?remove.packages() -``` - -```{r} -#| eval: FALSE -remove.packages("dplyr") -``` - -This results in the package being removed entirely from our computer. We would then need to reinstall it if needed in the future. - -
- ---- - -### Common Issues - -As previously mentioned, [CRAN](https://cran.r-project.org/) is the main repository for R packages. But what if we tried to install an R package that is only found on [Bioconductor](https://www.bioconductor.org/) or via [GitHub](https://github.com/trending/r) using the `install.packages()` function? - -To see what occurs, let's try installing the `PeacoQC` [package](https://www.bioconductor.org/packages/release/bioc/html/PeacoQC.html) (which is found on Bioconductor). - -```{r} -install.packages("PeacoQC") -``` - -
- ---- - -As you can see, the initial warning message suggest that `PeacoQC` is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn't figure out what was going on. - -This is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN. - -
- ---- - -## Installing from Bioconductor - -**[Bioconductor](https://www.bioconductor.org/)** is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this [link](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) you can find it's current flow and mass cytometry R packages. - -Bioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different [standards](https://contributions.bioconductor.org/) for acceptance than [CRAN](https://r-pkgs.org/release.html). They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems. - -
- ---- - -To install an R package that is located on [Bioconductor](https://www.bioconductor.org/), we first need to install the `BiocManager` package from CRAN. This package will allow us to install Bioconductor packages from their respective repository. - -```{r} -#| eval: FALSE -install.packages("BiocManager") -``` - -
- ---- - -Once BiocManager is installed, we can attach it to our local environment using the `library()` function - -```{r} -library(BiocManager) -``` - -
- ---- - -When loaded, you will see an output showing the current Bioconductor and R versions. - -We can then use BiocManager's `install()` function to go back and install `PeacoQC()`. - -:::{.callout-tip} -As always, don't forget the "" when running an `install()` command. -::: - -```{r} -#| eval: FALSE -?install() -``` - -```{r} -#| eval: FALSE - -install("PeacoQC") -``` - -
- ---- - -We see a similar opening sequence of installation steps as what we saw when installing the `dplyr` package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation. - -:::{.callout-note} -Behind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process -::: - -![](images/12_PeacoQCDependencies.png) - -
- ---- - -Within the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with `dplyr`, with a "Done (packagename)" being printed upon successful installation. - -![](images/13_rjson.png) - -
- ---- - -This process continues for each dependency being installed. - -![](images/13b_Other.png) - -
- ---- - -And finally, once all the dependencies are installed, `PeacoQC` starts to install. - -![](images/13c_PeacoQC.png) - -
- ---- - -Occasionally, during installation, you will see a pop-up windown like this one in the console. This let's you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n]. - -![](images/14_UpdateAll.png) - -
- ---- - -Alternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter. - -![](images/16_GitHubInstall.png) - -
- ---- - -Generally, it's okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn't cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option. - -![](images/14_UpdateAll.png) - -
- ---- - -With PeacoQC has been installed, we can load it via the `library()` call - -:::{.callout-tip} -Remeber, `library()` doesn't require " " -::: - -```{r} -library(PeacoQC) -``` - -
- ---- - -And we can check to see if it has been attached to the local environment - -```{r} -sessionInfo() -``` - -
- ---- - -As you may have noticed, the section of ***loaded via namespace (but not attached)*** packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment. - -![](images/15_AdditionalDependencies.png) - -
- ---- - -To see what packages are installed (but not yet loaded), we can use the `installed.packages()` function to return a list of R packages for your computer. - -```{r} -#| eval: FALSE - -installed.packages() -``` - -
- ---- - -## Install from GitHub - -In addition to the [CRAN](https://cran.r-project.org/) and [Bioconductor](https://www.bioconductor.org/) repositories, individual R packages can also be found on [GitHub](https://github.com/trending/r) hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to [CRAN](https://r-pkgs.org/release.html) or [Bioconductor]((https://contributions.bioconductor.org/))) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all. - -
- ---- - -While many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to [deprecation](https://devguide.ropensci.org/maintenance_evolution.html) since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it's useful to check the [commits](https://github.com/carlosproca/autospill/commits/master/) and [issues](https://github.com/carlosproca/autospill/issues) pages to see when the last contribution occurred. We will take a closer look at how to do so [later on](/Schedule.qmd#the-art-of-github-diving). - -
- ---- - -To install packages from GitHub, you will need the `remotes` package, which can be found on CRAN. - -:::{.callout-tip title="Spot Check #1"} -To install a package from CRAN, what function would you use? -Click on the code-fold arrow below to reveal the answer. -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -install.packages("remotes") -``` - -
- ---- - -With the `remotes` package now installed, we can attach it to our local environment. - -:::{.callout-tip title="Spot Check #2"} -What function would be used to do so? -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -library(remotes) -``` - -
- ---- - -And finally, we can use the `install_github()` function to download R packages from the invidual developers GitHub account. - -:::{.callout-tip title="Spot Check #3"} -How would you look up the help documentation for this function? -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Either by hovering over it within Positron or via - -?install_github() -``` - -
- ---- - -We will be installing a small R package [flowSpectrum](https://github.com/hally166/flowSpectrum) for this example. It's one of the packages created by [Christopher Hall](https://github.com/hally166), whose small series of [Flow Cytometry Data Analysis in R](https://youtu.be/2INqQNMNaV0?si=dZ_rJ1S26KnNbUmU) tutorials were immensely useful when I was first getting started learning R. `flowSpectrum` can be used to generate spectrum-style plots for spectral flow cytometry data. - -![](images/PE_Spectrum.png) - -
- ---- - -To install an R package from GitHub, we first need the GitHub username (so [hally166](https://github.com/hally166) in this case), which is followed by a "/", and then the name of the package repository (so [flowSpectrum](https://github.com/hally166/flowSpectrum) in this case). Our code should consequently be: - -```{r} -#| eval: FALSE - -install_github("hally166/flowSpectrum") -``` - -
- ---- - -When installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding. - -This process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating [R packages](/Schedule.qmd#building-your-first-r-package). - -![](images/17_InstallSource.png) - -
- ---- - -## Troubleshooting Install Errors - -We have now installed three R packages, `dplyr`, `PeacoQC`, and `flowSpectrum`. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies. - -When encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below. - -![](images/18_ErrorExample.png) - -
- ---- - -If you encounter an installation error this week, please take screenshots of the error message and post them to this [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future. - -
- ---- - -## Installing Specific-Package Versions - -While we may be tempted to think of R packages as static, they change quite often, as their develipers add new features, fix bugs, etc. To help keep track of these changes (essential for [reproducibility](https://www.nature.com/articles/d42473-019-00004-y) and replicability), R packages have version numbers. - -When we run `sessionInfo()`, we can see an example of this, with the version number appearing after the package name. - -```{r} -sessionInfo() -``` - -
- ---- - -Alternatively, we can retrieve the same information for the individual packages via the `packageVersion()` function - -```{r} -packageVersion("PeacoQC") -``` - -
- ---- - -As well as from the `citation()` function. - -```{r} -citation("PeacoQC") -``` - -
- ---- - -How does a version number work? Lets say we have the following version number: **1.20.0** - -The first number of the version (**1.** in this case) denotes major changes, primarily those where after the version change the package may not be compatible with the code used in the prior version. As a consequence, this number changes rarely. - -The second number (**.20.** in this case) is the minor version. Minor changes typically consist of new features that are added, that don't affect the overall package function. These will change more frequently, especially for Bioconductor packages with fixed [release cycles](https://www.bioconductor.org/developers/release-schedule/). - -The final number (**.0** in this case) is often used to denote small changes occuring within a minor release period, often bug-fixes or fixing typos within the documentation. - -
- ---- - -We may in the future need to install specific package versions (but wont be doing so today). As expected, which repository contains the R package influences how we would go about doing this. - -For CRAN packages, we can use the `remotes` packages `install_version()` function. This allows us to provide the version number, and designate the repository location (the CRAN url in this case). - -```{r} -#| eval: FALSE -remotes::install_version("ggplot2", version = "3.5.2", repos = "https://cloud.r-project.org") -``` - -For GitHub-based R packages, the package versioning schema is not as strict as that of CRAN or Bioconductor. Typically, changes in R packagaes are put out by their developers as [releases](https://github.com/DavidRach/Luciernaga/releases). When trying to install a particular release, we can add an additional argument to the `install_github()` function, specifying the release version's tag number. For example: - -```{r} -#| eval: FALSE -remotes::install_github("DavidRach/Luciernaga", ref = "v0.99.7") -``` - -Alternatively, if the developer doesn't implement releases, you can provide the hash number of a particular commit. - -```{r} -#| eval: FALSE - -remotes::install_github("DavidRach/Luciernaga", ref = "8d1d694") -``` - -## Documentation and Websites - -We have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package. - -For CRAN-based packages, we can start off by searching for the package name. So, in the case of `dplyr`: - -![](images/19_DplyrGoogle.png) - -
- ---- - -Two main suggestions pop up. One is the package's [CRAN](https://cran.r-project.org/web/packages/dplyr/index.html) page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible. - -![](images/20_DplyrCRAN.png) - -
- ---- - -Because of this, many CRAN-based R packages (especially those part of the tidyverse) use [pkgdown](https://pkgdown.r-lib.org/)-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr's pkgdown-style [website](https://dplyr.tidyverse.org/) - -![](images/21_DplyrPkgdown.png) - -
- ---- - -We can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab. - -![](images/22_PkgdownArticles.png) - -
- ---- - -GitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository's ReadMe. - -![](images/23_GitHub.png) - -
- ---- - -For Bioconductor-based packages, on the package's page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with [PeacoQC](https://www.bioconductor.org/packages/release/bioc/vignettes/PeacoQC/inst/doc/PeacoQC_Vignette.pdf): - -![](images/24_PeacoQCBioc.png) - -
- ---- - -Additionally, package vignettes can also be reached via the packages help index page. These will usually appear under ***User guides, package vignettes, and other documentation***. - -![](images/25_Vignettes.png) - -
- ---- - - -# Your Turn - -Alright, we have now gone through the process of installing an R package from [CRAN](/course/01_InstallingRPackages/index.qmd#installing-from-cran), [Bioconductor](/course/01_InstallingRPackages/index.qmd#installing-from-bioconductor), and [GitHub](/course/01_InstallingRPackages/index.qmd#install-from-github). We will now install 20 other R packages we will need throughout the rest of the course. - -:::{.callout-note} -To make this interactive, [**I will task you**]{.underscore} to apply the previous concepts to figure out whether the packages need to be installed via CRAN, Bioconductor or GitHub. -::: - -:::{.callout-important} -Feel free to view the [website](https://umgcccfcsr.github.io/CytometryInR/course/) version to avoid accidental spoilers from the copied over index.qmd file. Alternatively, you can attempt to switch from the Source view to Visual Mode by right clicking with your mouse and selecting that option. -::: - -:::{.callout-tip} -Start by searching each packages name. See if you can spot first either a CRAN or a Bioconductor website. Then enter the respective installation command (`install.packages()`, `install()`, `install_github()`) for the appropiate repository, add the package name, and run the code to see if the installation proceeds. - -For cases where you are truly stuck, expand the code-fold below each package name to see the answer. -::: - -:::{.callout-note} -Some of these packages may be dependencies of each other and may wind up installed before you get to them. If that is the case, no need to reinstall, count it as a win, and proceed to the next R package. -::: - -Remember,if you encountered any installation errors in the process, please take screenshots and post them on the the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10) to help with improved documentation. - -
- ---- - -:::{.callout-tip title="1/20"} -R package: purrr -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://purrr.tidyverse.org/ - -install.packages("purrr") -``` - -
- ---- - -:::{.callout-tip title="2/20"} -R package: flowCore -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/flowCore.html - -install("flowCore") -``` - -
- ---- - -:::{.callout-tip title="3/20"} -R package: flowWorkspace -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/flowWorkspace.html - -install("flowWorkspace") -``` - -
- ---- - -:::{.callout-tip title="4/20"} -R package: stringr -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://stringr.tidyverse.org/ - -install.packages("stringr") -``` - -
- ---- - -:::{.callout-tip title="5/20"} -R package: ggplot2 -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://ggplot2.tidyverse.org/ - -install.packages("ggplot2") -``` - -
- ---- - - -:::{.callout-tip title="6/20"} -R package: ggcyto -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/ggcyto.html - -install("ggcyto") -``` - -
- ---- - -:::{.callout-tip title="7/20"} -R package: tidyr -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://tidyr.tidyverse.org/ - -install.packages("tidyr") -``` - -
- ---- - -:::{.callout-tip title="8/20"} -R package: openCyto -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/openCyto.html - -install("openCyto") -``` - -
- ---- - -:::{.callout-tip title="9/20"} -R package: FlowSOM -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/FlowSOM.html - -install("FlowSOM") -``` - -
- ---- - -:::{.callout-tip title="10/20"} -R package: xml2 -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://xml2.r-lib.org/ - -install.packages("xml2") -``` - -
- ---- - - -:::{.callout-tip title="11/20"} -R package: saeyslab/CytoNorm -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: GitHub -# Website: https://github.com/saeyslab/CytoNorm - -install_github("saeyslab/CytoNorm") -``` - -
- ---- - -:::{.callout-tip title="12/20"} -R package: lubridate -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://lubridate.tidyverse.org/ - -install.packages("lubridate") -``` - -
- ---- - -:::{.callout-tip title="13/20"} -R package: httr2 -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://httr2.r-lib.org/ - -install.packages("httr2") -``` - -
- ---- - -:::{.callout-tip title="14/20"} -R package: flowGate -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/flowGate.html - -install("flowGate") -``` - -
- ---- - -:::{.callout-tip title="15/20"} -R package: devtools -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://devtools.r-lib.org/ - -install.packages("devtools") -``` - -
- ---- - -:::{.callout-tip title="16/20"} -R package: plotly -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://plotly.com/r/getting-started/ - -install.packages("plotly") -``` - -
- ---- - -:::{.callout-tip title="17/20"} -R package: biosurf/cyCombine -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: GitHub -# Website: https://github.com/biosurf/cyCombine - -install_github("biosurf/cyCombine") -``` - -
- ---- - -:::{.callout-tip title="18/20"} -R package: CytoML -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/CytoML.html - -install("CytoML") -``` - -
- ---- - -:::{.callout-tip title="19/20"} -R package: Rtsne -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://github.com/jkrijthe/Rtsne - -install.packages("Rtsne") -``` - -
- ---- - -:::{.callout-tip title="20/20"} -R package: uwot -::: - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website:https://jlmelville.github.io/uwot/ - -install.packages("uwot") -``` - -
- ---- - -**Congratulations!** You have (hopefully) survived the package installation onslaught that is Week #1 of the course. - -![](images/Entertained.jpg) - -Remember to submit any encountered installation error screenshots to the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). - -
- ---- - -# Wrap-Up - -In this session, we walked through what are R packages, where to find them, how to install them, and a bit about troubleshooting any installation errors you may encounter during the process. - -You then proceeded to install most of the R packages that you would need throughout the [Cytometry in R course](/Schedule.qmd). These included tidyverse packages from the [CRAN](https://cran.r-project.org/) repository used for working with data structures and plots, as well as more cytometry focused R packages from [Bioconductor](https://www.bioconductor.org/) repository. - -If you have any questions, or want to discuss this week's topics in more depth with the other course participants, please head over to the [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page and open a new topic. - -Next week, we will start learning about [file paths](/Schedule.qmd#file-paths), by which we will be able to tell our computer where to find your fcs files, how to retrieve the file names, subset those that may be of particular interest, and copy them over to a new folder. In the processs, we will learn a little more about how variables, objects, and list work within R. - -Until then, Best Wishes! - -- David - -
- -![](/course/01_InstallingRPackages/images/ExitImage.png) - ---- - -# Additional Resources - -[Tidy Tales](https://tidytales.ca/series/2023-01-24_reproducible-data-science/posts/r-packages.html) An useful beginner-friendly blogpost covering additional aspects from a different perspective. - -[Introduction to Bioconductor](https://youtu.be/dg6NvmMVQ3I?si=WfsqpO3Z-M2oG8zh) A talk by Martin Morgan with more information about the Bioconductor project. - -[R Packages](https://r-pkgs.org/) A book by Hadley Wickham and Jennifer Bryan, covering all the different internals of R packages. - -
- ---- - - -# Take-home Problems - -Below you will find the optional take-home problems for Week #1. Learning how to code well requires continous practice, and that involves cycles of trying something, failing, and troubleshooting to get it working. The goal of these problems is to help you explore the topic in greater depth than the currated boundaries of this one lecture. - -You are more than welcome to open a [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) to engage with others in the course to discuss these questions. Once you are done tinkering, and want to get final instructor feedback on your work, place your files within a folder, and follow the instructions to submit it as a [Pull Request](/course/00_Homeworks/index.qmd#submitting-take-home-problems) to the Cytometry In R repositories homework branch. - -:::{.callout-tip title="Problem 1"} -We installed PeacoQC during this session, but we didn't have time to explore what functions are present within the package. Using what you have learned about accessing documentation, figure out and list what functions it contains -::: - -:::{.callout-tip title="Problem 2"} -Take a closer look at the list of Bioconductor [cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) packages. Report back on how many there are currently in Bioconductor, the author/maintainer with the most contributed cytometry R packages, and a couple packages that you would be interested in exploring more in-depth later in the course. -::: - -:::{.callout-tip title="Problem 3"} -There is another way to install R packages, using the newer [pak](https://pak.r-lib.org/) package. Positron uses this when installing suggested dependencies. - -After learning more about it via the documentation and it's pkgdown website, I would like you to attempt to install the following three R packages using this newer method: "broom", "cytoMEM", "DillonHammill/CytoExploreR". - -Take screenshots, and in a new [quarto markdown document](/course/00_Quarto/index.qmd), describe how the installation process differed from what you saw for `install.packages()`, `install()` and `install_github()`. -::: - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - +--- +title: "01 - Installing R Packages" +author: "David Rach" +date: 02-01-2026 +format: html +toc: true +toc-depth: 5 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://youtube.com/live/ZNFNokzsBaM) + + + +For screen-shot slides, click [here](/course/01_InstallingRPackages/slides.qmd) + +```{r} +#| include: FALSE +library(BiocStyle) +``` + +Welcome to the first week of [Cytometry in R](/Schedule.qmd)! This week we will be diving into how R packages work, and the how to go about installing them. + +Before getting started, please make sure you have completed the creating a [GitHub](/course/00_GitHub/) and [Workstation Setup](/course/00_WorkstationSetup/) walk-throughs, since we will begin where they left off once the required software was successfully installed. + +:::{.callout-important} +Please make sure to [sync](/course/00_Homeworks/index.qmd#sync-your-fork) your forked version of the CytometryInR repository, and [pull](/course/00_Git/index.qmd#pull) any changes to your local computer's CytometryInR project folder so that you have the most recent version of the code and data available. +::: + +
+ +--- + +# Background + +During [Workstation Setup](/course/00_WorkstationSetup/), you installed the R software to your local computer. R as a [programming language](https://en.wikipedia.org/wiki/R_(programming_language)) that started up in the 1990s. While its original focus was on statistics, it is now widely used in various fields thanks to contributions of many open-source developers over the years. + +This expanded reach is in part due to the ability to create [**R packages**](https://en.wikipedia.org/wiki/R_package), that encapsulate additional [**functions**](https://adv-r.hadley.nz/functions.html#function-fundamentals), that can do new things beyond what the original software (ie. **base R**) was capable of doing. + +
+ +--- + +Currently, there are [thousands](https://cran.r-project.org/web/packages/available_packages_by_name.html) of R packages available. Furthermore, there is a vibrant [community](https://www.reddit.com/r/rstats/) of individuals that help maintain and document how to use these packages, which has helped sustain and grow the R ecosystem over the last couple [decades](https://youtu.be/gjpNEVcG1nU?si=rcEBSc7AnAsgsAy2). + +Regardless if you are working with [flow cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry), or in [ecology](https://drmattg.github.io/REcol-verse/), or in [econometrics](https://www.econometrics-with-r.org/1-introduction.html), or [political science](https://github.com/fivethirtyeight/data), a lot of the analysis and visualizations that you see in publications often involve R. + +
+ +--- + +:::{.callout-tip} +R packages can also just be made for fun! Among my favorite examples of this, there is an R package that lets you add the snake game to your [recalculating screen](https://github.com/AdamSpannbauer/snakeLoadR), as well as R packages that provide the color-palette schemes needed to make your plots with [Studio Ghibli](https://github.com/ewenme/ghibli), [Wes Anderson](https://github.com/karthik/wesanderson), or [Bluey](https://github.com/ekholme/blueycolors) colors. +::: + +
+ +--- + +These R packages start off as [source code](https://r-pkgs.org/structure.html#sec-package-states) (which is what we will be learning to write during this course). When you install a R package to your computer, this human-readable source code gets converted into a binary format with which your computer can interact directly. + +
+ +--- + +Expanding on this concept, a new R package can be made up of new code (primarily in the form of tools (ie. **functions**) that do a particular useful things) that is entirely self-contained, or reuse functions present in existing R packages to help make something new. When an R package relies on a function from another R package, it needs the other R package to be installed in order for everything to work properly. This is known as a package **dependency**. + +
+ +--- + +To make distributing the thousands of R packages and their associated package dependencies easier, R packages are collected (ie. hosted) within **repositories**, which function as an intermediate distributor. + +The three main locations for R packages from are **[CRAN](https://cran.r-project.org/)** (containing 23069 packages), **[Bioconductor](https://www.bioconductor.org/)** (containing 2361 packages), and individual R packages hosted by their developers via **[GitHub](https://github.com/trending/r)**. + +
+ +--- + +The process of installing R packages will vary a bit depending on which repository the respective R package is in. For beginners, this often prooves to be a pain-point, as they will attempt to install an R package using one set of installation commands, only to get an error (because the R package is not in that repository). + +
+ +--- + +In this session, we will work on installing the various R packages we will need through the course. While doing so, we will explore how to figure out which repository the individual package is in; what installation commands to use to download it; and how to look up the help documentation. We will also touch on how the functions within an R package are made available for our computer to use (via the `library()` call), and how to troubleshoot the more commonly encountered installation errors. + +
+ +--- + +# Getting Started + +## Set Up + +Alright, with the background out of the way, let's get started! + +:::{.callout-important} +Please make sure to [sync](/course/00_Homeworks/index.qmd#sync-your-fork) your forked version of the CytometryInR repository, and [pull](/course/00_Git/index.qmd#pull) any changes to your local computer's CytometryInR project folder so that you have the most recent version of the code and data available. +::: + +:::{.callout-warning} +Please remember to always copy over the new material from your local CytometryInR folder to a separate Project Folder that you created and named (ex. "Week_01" or "MyLearningFolder", etc.). This will ensure any edits you make to the files do not affect your ability to bring in next week's materials to the CytometryInR folder +::: + +
+ +--- + +After pulling the new data and code locally, open CytometryInR, open the course folder, and open the 01_InstallingRPackages folder. From here, copy the **index.qmd** file to your own working Project Folder (ex. Week_01) where you can work on it without causing any conflicts. Then return to Positron and open up your working project folder (ex. Week_01). + +![](images/01_Interpreter.png) + +
+ +--- + +Next up, within [Positron](/course/00_Positron/index.qmd#interpreter), let's make sure to select R as the coding language being used for this session. + +![](images/01_Interpreter.png) + +
+ +--- + +Now that R is running within Positron, the console (lower portion of the screenn) is now able to run (ie. execute) any R code that is sent to it. + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + +## Checking for Loaded Packages + +For the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active. + +
+ +--- + +### Accessing Help Documentation + +Within your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following `sessionInfo()` function: + +```{r} +#| eval: FALSE +sessionInfo() +``` + +
+ +--- + +If you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over. + +![](images/02_HelpHover.png) + +
+ +--- + +In this case, we can see the help documentation corresponding for `sessionInfo()`. Beyond hovering over the function, this can also be accessed by adding a ? directly in front of the function, and then running that line of code. + +```{r} +#| eval: FALSE +?sessionInfo() +``` + +![](images/03_QuestionMark.png) + +
+ +--- + +When executed, the function's help file documentation will open up within the Help tab in the secondary side bar on the right-side of the screen. Glancing at the top of the page we can see the name of the package that contains the `sessionInfo()` function (`{utils}`). Scrolling down the help page past all the documentation, we can see a link to the index page. + +![](images/04_Index.png) + +
+ +--- + +After clicking, the Help tab switches from viewing the documentation for the `sessionInfo()` function, to showing all the functions within the `utils` package. Most R packages contain help documentation, so this process can be adapted to find out additional information about what a function does, and what arguments are needed to produce customized outputs. + +![](images/05_UtilsFunctions.png) + + +
+ +--- + +### sessionInfo() + +Within your .qmd file, let's go ahead and run the following code-block: + +```{r} +sessionInfo() +``` + +
+ +--- + +The outputs that get returned by `sessionInfo()` will vary a bit depending on your computer's [operating system](/course/00_WorkstationSetup/), and the version of R you have installed. + +For today, let's focus on the last two elements of the output: + +![](images/06_sessionInfo.png) + +
+ +--- + +The [R software](https://www.r-project.org/) itself is made up of several **base R packages**, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages. + +As we install additional R packages and load them using the `library()` function throughout this session, sporadically re-run `sessionInfo()` to see how this list of R packages changes. + +
+ +--- + +## Installing from CRAN + +We will start by installing R packages that are part of the [CRAN](https://cran.r-project.org/) repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository. + +These include the [tidyverse](https://tidyverse.org/) packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today. + +
+ +--- + +### dplyr + +Our first R package we will install during this session is the [dplyr](https://dplyr.tidyverse.org/) package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function `install.packages()`. + +```{r} +#| eval: FALSE +?install.packages() +``` + +![](images/07_InstallPackages.png) + +
+ +--- + +For the `install.packages()` function, we place within the () the name of the R package from CRAN that we wish to install. + +```{r} +#| eval: FALSE +install.packages("dplyr") +``` + +
+ +--- + +:::{.callout-tip} +A usual struggle point for beginners is that install.packages() requires " " to be placed around the package name. Forgetting them results in the error that we see below. +::: + +```{r} +#| error: TRUE + +install.packages(dplyr) +``` + +
+ +--- + +```{r} +#| eval: FALSE +install.packages("dplyr") +``` + + +Go ahead and click on "Run Cell" next to your code-block, to install the `dplyr` R package. + +
+ +--- + +When a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system). + +![](images/08_InstallScript.png) + +
+ +--- + +Within this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN. + +If the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder. + +![](images/09_InstallScript2.png) + +
+ +--- + +The final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the "Done" line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder). + +
+ +--- + +### Attaching packages via library() + +If an R package has been installed successfully, we are now able to load it (ie. make it's functions available) to our local environment using the `library()` function. + +```{r} +#| eval: FALSE +?library() +``` + +
+ +--- + +Unlike `install.packages()`, where we needed "" around the package name, the `library()` function does not require "" around the package name. Let's go ahead and load in `dplyr`, making its respective functions to our local environment. + +```{r} +library(dplyr) +``` + +
+ +--- + +From the output, we can see that `dplyr` has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages. + +With `dplyr` now loaded via the `library()` call, let's check `sessionInfo()` to see what has changed. + +```{r} +sessionInfo() +``` + +
+ +--- + +Similar to what was seen for the base R packages, `dplyr` is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the `dplyr` packages `select()` function and it's respective help page. + +```{r} +#| eval: FALSE +?select +``` + +![](images/10_Attached.png) + +
+ +--- + +Since its parent package has been attached to our local environment (via the `library()` call), we can see `dplyr` functions appear as suggestions as we begin to type. + +By contrast, is we check for the `ggplot()` function from the ggplot2 package (which we haven't yet installed or attached via `library()`), no suggestions will pop up. + +```{r} +?ggplot +``` + +
+ +--- + +Beyond individual functions, some R packages also have help landing pages, that can be similarly accessed by adding a ? in front of the package name: + +![](images/11_PackageLanding.png) + +
+ +--- + +### Unattaching + +So far, we have installed an R package, and then attached it (via `library()`). How would we reverse these steps? + +Well, to unload it from the local environment, there are a couple options. You could of course simply shut down Positron. The local environment only exist in context of when you open and close the session, which closing the program will do. All previously loaded R packages will be unattached, which is why when you start a new session you will need to load in all packages you plan on using via `library()`. + +Alternatively, although less used, you could `detach()` it via your console: + +```{r} +detach("package:dplyr", unload=TRUE) +``` + +```{r} +sessionInfo() +``` + +
+ +--- + +Looking at the `sessionInfo()` output, dplyr is no longer attached to the local environment. Consequently, if we try to once again look for the documentation, no information will be retrieved. + +```{r} +?dplyr +``` + +
+ +--- + +There is a workaround however, if we want to access functions from an unloaded R package. We can specify the R package's name, followed by two :, and then the function name. The :: conveys the context to your computer that the package is present, but may not be attached. + +```{r} +#| eval: FALSE +?dplyr::select() +``` + +This particular use case can be useful if we want to run a particular function, but not load in all a packages functions (which may have identical function names to other R packages we are using and cause some conflicts). + +
+ +--- + +### Removing Packages + +Just as we can install an R package, we can also uninstall an R package (although doing so is rare, most often when encountering package dependency conflict). To do so, we would use the `remove.packages()` function. + +```{r} +#| eval: FALSE +?remove.packages() +``` + +```{r} +#| eval: FALSE +remove.packages("dplyr") +``` + +This results in the package being removed entirely from our computer. We would then need to reinstall it if needed in the future. + +
+ +--- + +### Common Issues + +As previously mentioned, [CRAN](https://cran.r-project.org/) is the main repository for R packages. But what if we tried to install an R package that is only found on [Bioconductor](https://www.bioconductor.org/) or via [GitHub](https://github.com/trending/r) using the `install.packages()` function? + +To see what occurs, let's try installing the `PeacoQC` [package](https://www.bioconductor.org/packages/release/bioc/html/PeacoQC.html) (which is found on Bioconductor). + +```{r} +install.packages("PeacoQC") +``` + +
+ +--- + +As you can see, the initial warning message suggest that `PeacoQC` is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn't figure out what was going on. + +This is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN. + +
+ +--- + +## Installing from Bioconductor + +**[Bioconductor](https://www.bioconductor.org/)** is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this [link](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) you can find it's current flow and mass cytometry R packages. + +Bioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different [standards](https://contributions.bioconductor.org/) for acceptance than [CRAN](https://r-pkgs.org/release.html). They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems. + +
+ +--- + +To install an R package that is located on [Bioconductor](https://www.bioconductor.org/), we first need to install the `BiocManager` package from CRAN. This package will allow us to install Bioconductor packages from their respective repository. + +```{r} +#| eval: FALSE +install.packages("BiocManager") +``` + +
+ +--- + +Once BiocManager is installed, we can attach it to our local environment using the `library()` function + +```{r} +library(BiocManager) +``` + +
+ +--- + +When loaded, you will see an output showing the current Bioconductor and R versions. + +We can then use BiocManager's `install()` function to go back and install `PeacoQC()`. + +:::{.callout-tip} +As always, don't forget the "" when running an `install()` command. +::: + +```{r} +#| eval: FALSE +?install() +``` + +```{r} +#| eval: FALSE + +install("PeacoQC") +``` + +
+ +--- + +We see a similar opening sequence of installation steps as what we saw when installing the `dplyr` package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation. + +:::{.callout-note} +Behind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process +::: + +![](images/12_PeacoQCDependencies.png) + +
+ +--- + +Within the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with `dplyr`, with a "Done (packagename)" being printed upon successful installation. + +![](images/13_rjson.png) + +
+ +--- + +This process continues for each dependency being installed. + +![](images/13b_Other.png) + +
+ +--- + +And finally, once all the dependencies are installed, `PeacoQC` starts to install. + +![](images/13c_PeacoQC.png) + +
+ +--- + +Occasionally, during installation, you will see a pop-up windown like this one in the console. This let's you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n]. + +![](images/14_UpdateAll.png) + +
+ +--- + +Alternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter. + +![](images/16_GitHubInstall.png) + +
+ +--- + +Generally, it's okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn't cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option. + +![](images/14_UpdateAll.png) + +
+ +--- + +With PeacoQC has been installed, we can load it via the `library()` call + +:::{.callout-tip} +Remeber, `library()` doesn't require " " +::: + +```{r} +library(PeacoQC) +``` + +
+ +--- + +And we can check to see if it has been attached to the local environment + +```{r} +sessionInfo() +``` + +
+ +--- + +As you may have noticed, the section of ***loaded via namespace (but not attached)*** packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment. + +![](images/15_AdditionalDependencies.png) + +
+ +--- + +To see what packages are installed (but not yet loaded), we can use the `installed.packages()` function to return a list of R packages for your computer. + +```{r} +#| eval: FALSE + +installed.packages() +``` + +
+ +--- + +## Install from GitHub + +In addition to the [CRAN](https://cran.r-project.org/) and [Bioconductor](https://www.bioconductor.org/) repositories, individual R packages can also be found on [GitHub](https://github.com/trending/r) hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to [CRAN](https://r-pkgs.org/release.html) or [Bioconductor]((https://contributions.bioconductor.org/))) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all. + +
+ +--- + +While many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to [deprecation](https://devguide.ropensci.org/maintenance_evolution.html) since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it's useful to check the [commits](https://github.com/carlosproca/autospill/commits/master/) and [issues](https://github.com/carlosproca/autospill/issues) pages to see when the last contribution occurred. We will take a closer look at how to do so [later on](/Schedule.qmd#the-art-of-github-diving). + +
+ +--- + +To install packages from GitHub, you will need the `remotes` package, which can be found on CRAN. + +:::{.callout-tip title="Spot Check #1"} +To install a package from CRAN, what function would you use? +Click on the code-fold arrow below to reveal the answer. +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +install.packages("remotes") +``` + +
+ +--- + +With the `remotes` package now installed, we can attach it to our local environment. + +:::{.callout-tip title="Spot Check #2"} +What function would be used to do so? +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +library(remotes) +``` + +
+ +--- + +And finally, we can use the `install_github()` function to download R packages from the invidual developers GitHub account. + +:::{.callout-tip title="Spot Check #3"} +How would you look up the help documentation for this function? +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Either by hovering over it within Positron or via + +?install_github() +``` + +
+ +--- + +We will be installing a small R package [flowSpectrum](https://github.com/hally166/flowSpectrum) for this example. It's one of the packages created by [Christopher Hall](https://github.com/hally166), whose small series of [Flow Cytometry Data Analysis in R](https://youtu.be/2INqQNMNaV0?si=dZ_rJ1S26KnNbUmU) tutorials were immensely useful when I was first getting started learning R. `flowSpectrum` can be used to generate spectrum-style plots for spectral flow cytometry data. + +![](images/PE_Spectrum.png) + +
+ +--- + +To install an R package from GitHub, we first need the GitHub username (so [hally166](https://github.com/hally166) in this case), which is followed by a "/", and then the name of the package repository (so [flowSpectrum](https://github.com/hally166/flowSpectrum) in this case). Our code should consequently be: + +```{r} +#| eval: FALSE + +install_github("hally166/flowSpectrum") +``` + +
+ +--- + +When installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding. + +This process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating [R packages](/Schedule.qmd#building-your-first-r-package). + +![](images/17_InstallSource.png) + +
+ +--- + +## Troubleshooting Install Errors + +We have now installed three R packages, `dplyr`, `PeacoQC`, and `flowSpectrum`. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies. + +When encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below. + +![](images/18_ErrorExample.png) + +
+ +--- + +If you encounter an installation error this week, please take screenshots of the error message and post them to this [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future. + +
+ +--- + +## Installing Specific-Package Versions + +While we may be tempted to think of R packages as static, they change quite often, as their develipers add new features, fix bugs, etc. To help keep track of these changes (essential for [reproducibility](https://www.nature.com/articles/d42473-019-00004-y) and replicability), R packages have version numbers. + +When we run `sessionInfo()`, we can see an example of this, with the version number appearing after the package name. + +```{r} +sessionInfo() +``` + +
+ +--- + +Alternatively, we can retrieve the same information for the individual packages via the `packageVersion()` function + +```{r} +packageVersion("PeacoQC") +``` + +
+ +--- + +As well as from the `citation()` function. + +```{r} +citation("PeacoQC") +``` + +
+ +--- + +How does a version number work? Lets say we have the following version number: **1.20.0** + +The first number of the version (**1.** in this case) denotes major changes, primarily those where after the version change the package may not be compatible with the code used in the prior version. As a consequence, this number changes rarely. + +The second number (**.20.** in this case) is the minor version. Minor changes typically consist of new features that are added, that don't affect the overall package function. These will change more frequently, especially for Bioconductor packages with fixed [release cycles](https://www.bioconductor.org/developers/release-schedule/). + +The final number (**.0** in this case) is often used to denote small changes occuring within a minor release period, often bug-fixes or fixing typos within the documentation. + +
+ +--- + +We may in the future need to install specific package versions (but wont be doing so today). As expected, which repository contains the R package influences how we would go about doing this. + +For CRAN packages, we can use the `remotes` packages `install_version()` function. This allows us to provide the version number, and designate the repository location (the CRAN url in this case). + +```{r} +#| eval: FALSE +remotes::install_version("ggplot2", version = "3.5.2", repos = "https://cloud.r-project.org") +``` + +For GitHub-based R packages, the package versioning schema is not as strict as that of CRAN or Bioconductor. Typically, changes in R packagaes are put out by their developers as [releases](https://github.com/DavidRach/Luciernaga/releases). When trying to install a particular release, we can add an additional argument to the `install_github()` function, specifying the release version's tag number. For example: + +```{r} +#| eval: FALSE +remotes::install_github("DavidRach/Luciernaga", ref = "v0.99.7") +``` + +Alternatively, if the developer doesn't implement releases, you can provide the hash number of a particular commit. + +```{r} +#| eval: FALSE + +remotes::install_github("DavidRach/Luciernaga", ref = "8d1d694") +``` + +## Documentation and Websites + +We have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package. + +For CRAN-based packages, we can start off by searching for the package name. So, in the case of `dplyr`: + +![](images/19_DplyrGoogle.png) + +
+ +--- + +Two main suggestions pop up. One is the package's [CRAN](https://cran.r-project.org/web/packages/dplyr/index.html) page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible. + +![](images/20_DplyrCRAN.png) + +
+ +--- + +Because of this, many CRAN-based R packages (especially those part of the tidyverse) use [pkgdown](https://pkgdown.r-lib.org/)-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr's pkgdown-style [website](https://dplyr.tidyverse.org/) + +![](images/21_DplyrPkgdown.png) + +
+ +--- + +We can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab. + +![](images/22_PkgdownArticles.png) + +
+ +--- + +GitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository's ReadMe. + +![](images/23_GitHub.png) + +
+ +--- + +For Bioconductor-based packages, on the package's page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with [PeacoQC](https://www.bioconductor.org/packages/release/bioc/vignettes/PeacoQC/inst/doc/PeacoQC_Vignette.pdf): + +![](images/24_PeacoQCBioc.png) + +
+ +--- + +Additionally, package vignettes can also be reached via the packages help index page. These will usually appear under ***User guides, package vignettes, and other documentation***. + +![](images/25_Vignettes.png) + +
+ +--- + + +# Your Turn + +Alright, we have now gone through the process of installing an R package from [CRAN](/course/01_InstallingRPackages/index.qmd#installing-from-cran), [Bioconductor](/course/01_InstallingRPackages/index.qmd#installing-from-bioconductor), and [GitHub](/course/01_InstallingRPackages/index.qmd#install-from-github). We will now install 20 other R packages we will need throughout the rest of the course. + +:::{.callout-note} +To make this interactive, [**I will task you**]{.underscore} to apply the previous concepts to figure out whether the packages need to be installed via CRAN, Bioconductor or GitHub. +::: + +:::{.callout-important} +Feel free to view the [website](https://umgcccfcsr.github.io/CytometryInR/course/) version to avoid accidental spoilers from the copied over index.qmd file. Alternatively, you can attempt to switch from the Source view to Visual Mode by right clicking with your mouse and selecting that option. +::: + +:::{.callout-tip} +Start by searching each packages name. See if you can spot first either a CRAN or a Bioconductor website. Then enter the respective installation command (`install.packages()`, `install()`, `install_github()`) for the appropiate repository, add the package name, and run the code to see if the installation proceeds. + +For cases where you are truly stuck, expand the code-fold below each package name to see the answer. +::: + +:::{.callout-note} +Some of these packages may be dependencies of each other and may wind up installed before you get to them. If that is the case, no need to reinstall, count it as a win, and proceed to the next R package. +::: + +Remember,if you encountered any installation errors in the process, please take screenshots and post them on the the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10) to help with improved documentation. + +
+ +--- + +:::{.callout-tip title="1/20"} +R package: purrr +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://purrr.tidyverse.org/ + +install.packages("purrr") +``` + +
+ +--- + +:::{.callout-tip title="2/20"} +R package: flowCore +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/flowCore.html + +install("flowCore") +``` + +
+ +--- + +:::{.callout-tip title="3/20"} +R package: flowWorkspace +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/flowWorkspace.html + +install("flowWorkspace") +``` + +
+ +--- + +:::{.callout-tip title="4/20"} +R package: stringr +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://stringr.tidyverse.org/ + +install.packages("stringr") +``` + +
+ +--- + +:::{.callout-tip title="5/20"} +R package: ggplot2 +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://ggplot2.tidyverse.org/ + +install.packages("ggplot2") +``` + +
+ +--- + + +:::{.callout-tip title="6/20"} +R package: ggcyto +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/ggcyto.html + +install("ggcyto") +``` + +
+ +--- + +:::{.callout-tip title="7/20"} +R package: tidyr +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://tidyr.tidyverse.org/ + +install.packages("tidyr") +``` + +
+ +--- + +:::{.callout-tip title="8/20"} +R package: openCyto +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/openCyto.html + +install("openCyto") +``` + +
+ +--- + +:::{.callout-tip title="9/20"} +R package: FlowSOM +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/FlowSOM.html + +install("FlowSOM") +``` + +
+ +--- + +:::{.callout-tip title="10/20"} +R package: xml2 +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://xml2.r-lib.org/ + +install.packages("xml2") +``` + +
+ +--- + + +:::{.callout-tip title="11/20"} +R package: saeyslab/CytoNorm +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: GitHub +# Website: https://github.com/saeyslab/CytoNorm + +install_github("saeyslab/CytoNorm") +``` + +
+ +--- + +:::{.callout-tip title="12/20"} +R package: lubridate +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://lubridate.tidyverse.org/ + +install.packages("lubridate") +``` + +
+ +--- + +:::{.callout-tip title="13/20"} +R package: httr2 +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://httr2.r-lib.org/ + +install.packages("httr2") +``` + +
+ +--- + +:::{.callout-tip title="14/20"} +R package: flowGate +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/flowGate.html + +install("flowGate") +``` + +
+ +--- + +:::{.callout-tip title="15/20"} +R package: devtools +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://devtools.r-lib.org/ + +install.packages("devtools") +``` + +
+ +--- + +:::{.callout-tip title="16/20"} +R package: plotly +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://plotly.com/r/getting-started/ + +install.packages("plotly") +``` + +
+ +--- + +:::{.callout-tip title="17/20"} +R package: biosurf/cyCombine +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: GitHub +# Website: https://github.com/biosurf/cyCombine + +install_github("biosurf/cyCombine") +``` + +
+ +--- + +:::{.callout-tip title="18/20"} +R package: CytoML +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/CytoML.html + +install("CytoML") +``` + +
+ +--- + +:::{.callout-tip title="19/20"} +R package: Rtsne +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://github.com/jkrijthe/Rtsne + +install.packages("Rtsne") +``` + +
+ +--- + +:::{.callout-tip title="20/20"} +R package: uwot +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website:https://jlmelville.github.io/uwot/ + +install.packages("uwot") +``` + +
+ +--- + +**Congratulations!** You have (hopefully) survived the package installation onslaught that is Week #1 of the course. + +![](images/Entertained.jpg) + +Remember to submit any encountered installation error screenshots to the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). + +
+ +--- + +# Wrap-Up + +In this session, we walked through what are R packages, where to find them, how to install them, and a bit about troubleshooting any installation errors you may encounter during the process. + +You then proceeded to install most of the R packages that you would need throughout the [Cytometry in R course](/Schedule.qmd). These included tidyverse packages from the [CRAN](https://cran.r-project.org/) repository used for working with data structures and plots, as well as more cytometry focused R packages from [Bioconductor](https://www.bioconductor.org/) repository. + +If you have any questions, or want to discuss this week's topics in more depth with the other course participants, please head over to the [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page and open a new topic. + +Next week, we will start learning about [file paths](/Schedule.qmd#file-paths), by which we will be able to tell our computer where to find your fcs files, how to retrieve the file names, subset those that may be of particular interest, and copy them over to a new folder. In the processs, we will learn a little more about how variables, objects, and list work within R. + +Until then, Best Wishes! + +- David + +
+ +![](/course/01_InstallingRPackages/images/ExitImage.png) + +--- + +# Additional Resources + +[Tidy Tales](https://tidytales.ca/series/2023-01-24_reproducible-data-science/posts/r-packages.html) An useful beginner-friendly blogpost covering additional aspects from a different perspective. + +[Introduction to Bioconductor](https://youtu.be/dg6NvmMVQ3I?si=WfsqpO3Z-M2oG8zh) A talk by Martin Morgan with more information about the Bioconductor project. + +[R Packages](https://r-pkgs.org/) A book by Hadley Wickham and Jennifer Bryan, covering all the different internals of R packages. + +
+ +--- + + +# Take-home Problems + +Below you will find the optional take-home problems for Week #1. Learning how to code well requires continous practice, and that involves cycles of trying something, failing, and troubleshooting to get it working. The goal of these problems is to help you explore the topic in greater depth than the currated boundaries of this one lecture. + +You are more than welcome to open a [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) to engage with others in the course to discuss these questions. Once you are done tinkering, and want to get final instructor feedback on your work, place your files within a folder, and follow the instructions to submit it as a [Pull Request](/course/00_Homeworks/index.qmd#submitting-take-home-problems) to the Cytometry In R repositories homework branch. + +:::{.callout-tip title="Problem 1"} +We installed PeacoQC during this session, but we didn't have time to explore what functions are present within the package. Using what you have learned about accessing documentation, figure out and list what functions it contains +::: + +:::{.callout-tip title="Problem 2"} +Take a closer look at the list of Bioconductor [cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) packages. Report back on how many there are currently in Bioconductor, the author/maintainer with the most contributed cytometry R packages, and a couple packages that you would be interested in exploring more in-depth later in the course. +::: + +:::{.callout-tip title="Problem 3"} +There is another way to install R packages, using the newer [pak](https://pak.r-lib.org/) package. Positron uses this when installing suggested dependencies. + +After learning more about it via the documentation and it's pkgdown website, I would like you to attempt to install the following three R packages using this newer method: "broom", "cytoMEM", "DillonHammill/CytoExploreR". + +Take screenshots, and in a new [quarto markdown document](/course/00_Quarto/index.qmd), describe how the installation process differed from what you saw for `install.packages()`, `install()` and `install_github()`. +::: + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + diff --git a/course/01_InstallingRPackages/slides.qmd b/course/01_InstallingRPackages/slides.qmd index ea8166e..da42fab 100644 --- a/course/01_InstallingRPackages/slides.qmd +++ b/course/01_InstallingRPackages/slides.qmd @@ -1,2080 +1,2080 @@ ---- -title: "01 - Installing R Packages" -author: "David Rach" -date: 02-01-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {.callout-tip title="."} - -Welcome to the first week of [Cytometry in R](/Schedule.qmd)! This week we will be diving into how R packages work, and the how to go about installing them. - -::: - ---- - -::: {.fragment} -::: {.callout-important} - -Before getting started, please make sure you have completed the creating a [GitHub](/course/00_GitHub/) and [Workstation Setup](/course/00_WorkstationSetup/) walk-throughs, since we will begin where they left off once the required software was successfully installed. - -::: -::: - -::: {.fragment} -::: {.callout-important} - -Please make sure to [sync](/course/00_Homeworks/index.qmd#sync-your-fork) your forked version of the CytometryInR repository, and [pull](/course/00_Git/index.qmd#pull) any changes to your local computer's CytometryInR project folder so that you have the most recent version of the code and data available. - -::: -::: - ---- - -# Background - -::: {.fragment} -::: {.callout-tip title="."} - -During [Workstation Setup](/course/00_WorkstationSetup/), you installed the R software to your local computer. R as a [programming language](https://en.wikipedia.org/wiki/R_(programming_language)) that started up in the 1990s. While its original focus was on statistics, it is now widely used in various fields thanks to contributions of many open-source developers over the years. - -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} - -This expanded reach is in part due to the ability to create [**R packages**](https://en.wikipedia.org/wiki/R_package), that encapsulate additional [**functions**](https://adv-r.hadley.nz/functions.html#function-fundamentals), that can do new things beyond what the original software (ie. **base R**) was capable of doing. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Currently, there are [thousands](https://cran.r-project.org/web/packages/available_packages_by_name.html) of R packages available. Furthermore, there is a vibrant [community](https://www.reddit.com/r/rstats/) of individuals that help maintain and document how to use these packages, which has helped sustain and grow the R ecosystem over the last couple [decades](https://youtu.be/gjpNEVcG1nU?si=rcEBSc7AnAsgsAy2). - -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} - -Regardless if you are working with [flow cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry), or in [ecology](https://drmattg.github.io/REcol-verse/), or in [econometrics](https://www.econometrics-with-r.org/1-introduction.html), or [political science](https://github.com/fivethirtyeight/data), a lot of the analysis and visualizations that you see in publications often involve R. - -::: -::: - ---- - -:::{.callout-tip} - -R packages can also just be made for fun! Among my favorite examples of this, there is an R package that lets you add the snake game to your [recalculating screen](https://github.com/AdamSpannbauer/snakeLoadR), as well as R packages that provide the color-palette schemes needed to make your plots with [Studio Ghibli](https://github.com/ewenme/ghibli), [Wes Anderson](https://github.com/karthik/wesanderson), or [Bluey](https://github.com/ekholme/blueycolors) colors. - -::: - -::: {.fragment} - -![](images/Ghibli.png){fig-width=100} -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -These R packages start off as [source code](https://r-pkgs.org/structure.html#sec-package-states) (which is what we will be learning to write during this course). When you install a R package to your computer, this human-readable source code gets converted into a binary format with which your computer can interact directly. - -::: -::: - - -::: {.fragment} -::: {.callout-tip title="."} - -Expanding on this concept, a new R package can be made up of new code (primarily in the form of tools (ie. **functions**) that do a particular useful things) that is entirely self-contained, or reuse functions present in existing R packages to help make something new. When an R package relies on a function from another R package, it needs the other R package to be installed in order for everything to work properly. This is known as a package **dependency**. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To make distributing the thousands of R packages and their associated package dependencies easier, R packages are collected (ie. hosted) within **repositories**, which function as an intermediate distributor. - -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} - -The three main locations for R packages from are **[CRAN](https://cran.r-project.org/)** (containing 23069 packages), **[Bioconductor](https://www.bioconductor.org/)** (containing 2361 packages), and individual R packages hosted by their developers via **[GitHub](https://github.com/trending/r)**. - -::: -::: - ---- - - - -::: {.fragment} -::: {.callout-tip title="."} - -The process of installing R packages will vary a bit depending on which repository the respective R package is in. For beginners, this often prooves to be a pain-point, as they will attempt to install an R package using one set of installation commands, only to get an error (because the R package is not in that repository). - -::: -::: - - -::: {.fragment} -::: {.callout-tip title="."} - -In this session, we will work on installing the various R packages we will need through the course. While doing so, we will explore how to figure out which repository the individual package is in; what installation commands to use to download it; and how to look up the help documentation. We will also touch on how the functions within an R package are made available for our computer to use (via the `library()` call), and how to troubleshoot the more commonly encountered installation errors. - -::: -::: - ---- - -# Getting Started - -## Set Up - -Alright, with the background out of the way, let's get started! - -::: {.fragment} -:::{.callout-important} - -Please make sure to [sync](/course/00_Homeworks/index.qmd#sync-your-fork) your forked version of the CytometryInR repository, and [pull](/course/00_Git/index.qmd#pull) any changes to your local computer's CytometryInR project folder so that you have the most recent version of the code and data available. - -::: -::: - -::: {.fragment} -:::{.callout-warning} - -Please remember to always copy over the new material from your local CytometryInR folder to a separate Project Folder that you created and named (ex. "Week_01" or "MyLearningFolder", etc.). This will ensure any edits you make to the files do not affect your ability to bring in next week's materials to the CytometryInR folder - -::: -::: - ---- - -::: {.fragment} -:::{.callout-warning} - -After pulling the new data and code locally, open CytometryInR, open the course folder, and open the 01_InstallingRPackages folder. From here, copy the **index.qmd** file to your own working Project Folder (ex. Week_01) where you can work on it without causing any conflicts. Then return to Positron and open up your working project folder (ex. Week_01). - -::: -::: - ---- - -![](images/01_Interpreter.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Next up, within [Positron](/course/00_Positron/index.qmd#interpreter), let's make sure to select R as the coding language being used for this session. - -::: -::: - ---- - -![](images/01_Interpreter.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Now that R is running within Positron, the console (lower portion of the screenn) is now able to run (ie. execute) any R code that is sent to it. - -::: -::: - ---- - -![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) - -## Checking for Loaded Packages - -::: {.fragment} -::: {.callout-tip title="."} - -For the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active. - -::: -::: - ---- - -### Accessing Help Documentation - -::: {.fragment} -::: {.callout-tip title="."} - -Within your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following `sessionInfo()` function - -::: -::: - - -::: {.fragment} - -```{r} -#| eval: FALSE -sessionInfo() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -If you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over. - -::: -::: - ---- - -![](images/02_HelpHover.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -In this case, we can see the help documentation corresponding for `sessionInfo()`. Beyond hovering over the function, this can also be accessed by adding a ? directly in front of the function, and then running that line of code. - -::: -::: - - -::: {.fragment} - -```{r} -#| eval: FALSE -?sessionInfo() -``` - -::: - ---- - -![](images/03_QuestionMark.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -When executed, the function's help file documentation will open up within the Help tab in the secondary side bar on the right-side of the screen. Glancing at the top of the page we can see the name of the package that contains the `sessionInfo()` function (`{utils}`). Scrolling down the help page past all the documentation, we can see a link to the index page. - -::: -::: - ---- - -![](images/04_Index.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -After clicking, the Help tab switches from viewing the documentation for the `sessionInfo()` function, to showing all the functions within the `utils` package. Most R packages contain help documentation, so this process can be adapted to find out additional information about what a function does, and what arguments are needed to produce customized outputs. - -::: -::: - ---- - -![](images/05_UtilsFunctions.png) - ---- - -### sessionInfo() - -::: {.fragment} -::: {.callout-tip title="."} - -Within your .qmd file, let's go ahead and run the following code-block: - -::: -::: - - -::: {.fragment} - -```{r} -#| echo: TRUE -sessionInfo() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -The outputs that get returned by `sessionInfo()` will vary a bit depending on your computer's [operating system](/course/00_WorkstationSetup/), and the version of R you have installed. - -For today, let's focus on the last two elements of the output: - -::: -::: - ---- - -![](images/06_sessionInfo.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -The [R software](https://www.r-project.org/) itself is made up of several **base R packages**, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages. - -As we install additional R packages and load them using the `library()` function throughout this session, sporadically re-run `sessionInfo()` to see how this list of R packages changes. - -::: -::: - ---- - -## Installing from CRAN - -::: {.fragment} -::: {.callout-tip title="."} - -We will start by installing R packages that are part of the [CRAN](https://cran.r-project.org/) repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository. - -These include the [tidyverse](https://tidyverse.org/) packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today. - -::: -::: - ---- - -### dplyr - -::: {.fragment} -::: {.callout-tip title="."} - -Our first R package we will install during this session is the [dplyr](https://dplyr.tidyverse.org/) package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function `install.packages()`. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -?install.packages() -``` - -::: - ---- - -![](images/07_InstallPackages.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -For the `install.packages()` function, we place within the () the name of the R package from CRAN that we wish to install. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -install.packages("dplyr") -``` - -::: - ---- - -:::{.callout-tip} - -A usual struggle point for beginners is that install.packages() requires " " to be placed around the package name. Forgetting them results in the error that we see below. - -::: - - -::: {.fragment} - -```{r} -#| error: TRUE - -install.packages(dplyr) -``` - -::: - ---- - -::: {.fragment} - -```{r} -#| eval: FALSE -install.packages("dplyr") -``` - -::: - -::: {.fragment} -::: {.callout-tip title="."} - -Go ahead and click on "Run Cell" next to your code-block, to install the `dplyr` R package. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -When a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system). - -::: -::: - ---- - -![](images/08_InstallScript.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Within this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN. - -If the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder. - -::: -::: - ---- - -![](images/09_InstallScript2.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -The final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the "Done" line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder). - -::: -::: - ---- - -### Attaching packages via library() - -::: {.fragment} -::: {.callout-tip title="."} - -If an R package has been installed successfully, we are now able to load it (ie. make it's functions available) to our local environment using the `library()` function. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -?library() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Unlike `install.packages()`, where we needed "" around the package name, the `library()` function does not require "" around the package name. Let's go ahead and load in `dplyr`, making its respective functions to our local environment. - -::: -::: - -::: {.fragment} - -```{r} -library(dplyr) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -From the output, we can see that `dplyr` has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages. - -With `dplyr` now loaded via the `library()` call, let's check `sessionInfo()` to see what has changed. - -::: -::: - -::: {.fragment} - -```{r} -sessionInfo() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Similar to what was seen for the base R packages, `dplyr` is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the `dplyr` packages `select()` function and it's respective help page. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -?select -``` - -::: - ---- - -![](images/10_Attached.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Since its parent package has been attached to our local environment (via the `library()` call), we can see `dplyr` functions appear as suggestions as we begin to type. - -By contrast, is we check for the `ggplot()` function from the ggplot2 package (which we haven't yet installed or attached via `library()`), no suggestions will pop up. - -::: -::: - ---- - -::: {.fragment} - -```{r} -?ggplot -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Beyond individual functions, some R packages also have help landing pages, that can be similarly accessed by adding a ? in front of the package name: - -::: -::: - ---- - -![](images/11_PackageLanding.png) - ---- - -### Unattaching - -::: {.fragment} -::: {.callout-tip title="."} - -So far, we have installed an R package, and then attached it (via `library()`). How would we reverse these steps? - -Well, to unload it from the local environment, there are a couple options. You could of course simply shut down Positron. The local environment only exist in context of when you open and close the session, which closing the program will do. All previously loaded R packages will be unattached, which is why when you start a new session you will need to load in all packages you plan on using via `library()`. - -Alternatively, although less used, you could `detach()` it via your console: - -::: -::: - -::: {.fragment} - -```{r} -detach("package:dplyr", unload=TRUE) -``` - -::: - -::: {.fragment} - -```{r} -sessionInfo() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Looking at the `sessionInfo()` output, dplyr is no longer attached to the local environment. Consequently, if we try to once again look for the documentation, no information will be retrieved. - -::: -::: - -::: {.fragment} - -```{r} -?dplyr -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -There is a workaround however, if we want to access functions from an unloaded R package. We can specify the R package's name, followed by two :, and then the function name. The :: conveys the context to your computer that the package is present, but may not be attached. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -?dplyr::select() -``` - -::: - -::: {.fragment} -::: {.callout-tip title="."} - -This particular use case can be useful if we want to run a particular function, but not load in all a packages functions (which may have identical function names to other R packages we are using and cause some conflicts). - -::: -::: - ---- - -### Removing Packages - -::: {.fragment} -::: {.callout-tip title="."} - -Just as we can install an R package, we can also uninstall an R package (although doing so is rare, most often when encountering package dependency conflict). To do so, we would use the `remove.packages()` function. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -?remove.packages() -``` - -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -remove.packages("dplyr") -``` - -::: - -::: {.fragment} -::: {.callout-tip title="."} - -This results in the package being removed entirely from our computer. We would then need to reinstall it if needed in the future. - -::: -::: - ---- - -### Common Issues - -::: {.fragment} -::: {.callout-tip title="."} - -As previously mentioned, [CRAN](https://cran.r-project.org/) is the main repository for R packages. But what if we tried to install an R package that is only found on [Bioconductor](https://www.bioconductor.org/) or via [GitHub](https://github.com/trending/r) using the `install.packages()` function? - -To see what occurs, let's try installing the `PeacoQC` [package](https://www.bioconductor.org/packages/release/bioc/html/PeacoQC.html) (which is found on Bioconductor). - -::: -::: - -::: {.fragment} - -```{r} -install.packages("PeacoQC") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -As you can see, the initial warning message suggest that `PeacoQC` is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn't figure out what was going on. - -This is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN. - -::: -::: - ---- - -## Installing from Bioconductor - -::: {.fragment} -::: {.callout-tip title="."} - -**[Bioconductor](https://www.bioconductor.org/)** is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this [link](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) you can find it's current flow and mass cytometry R packages. - -Bioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different [standards](https://contributions.bioconductor.org/) for acceptance than [CRAN](https://r-pkgs.org/release.html). They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To install an R package that is located on [Bioconductor](https://www.bioconductor.org/), we first need to install the `BiocManager` package from CRAN. This package will allow us to install Bioconductor packages from their respective repository. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -install.packages("BiocManager") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Once BiocManager is installed, we can attach it to our local environment using the `library()` function - -::: -::: - -::: {.fragment} - -```{r} -library(BiocManager) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -When loaded, you will see an output showing the current Bioconductor and R versions. - -We can then use BiocManager's `install()` function to go back and install `PeacoQC()`. - -::: -::: - -:::{.callout-tip} - -As always, don't forget the "" when running an `install()` command. - -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -?install() -``` - -::: - -::: {.fragment} - -```{r} -install("PeacoQC") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -We see a similar opening sequence of installation steps as what we saw when installing the `dplyr` package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation. - -::: -::: - -::: {.fragment} -:::{.callout-note} - -Behind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process - -::: -::: - ---- - -![](images/12_PeacoQCDependencies.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Within the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with `dplyr`, with a "Done (packagename)" being printed upon successful installation. - -::: -::: - ---- - -![](images/13_rjson.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -This process continues for each dependency being installed. - -::: -::: - ---- - -![](images/13b_Other.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -And finally, once all the dependencies are installed, `PeacoQC` starts to install. - -::: -::: - ---- - -![](images/13c_PeacoQC.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Occasionally, during installation, you will see a pop-up windown like this one in the console. This let's you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n]. - -::: -::: - ---- - -![](images/14_UpdateAll.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Alternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter. - -::: -::: - ---- - -![](images/16_GitHubInstall.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Generally, it's okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn't cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option. - -::: -::: - ---- - -![](images/14_UpdateAll.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -With PeacoQC has been installed, we can load it via the `library()` call - -::: -::: - -:::{.callout-tip} - -Remeber, `library()` doesn't require " " - -::: - -::: {.fragment} - -```{r} -library(PeacoQC) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -And we can check to see if it has been attached to the local environment - -::: -::: - -::: {.fragment} - -```{r} -sessionInfo() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -As you may have noticed, the section of ***loaded via namespace (but not attached)*** packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment. - -::: -::: - ---- - -![](images/15_AdditionalDependencies.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To see what packages are installed (but not yet loaded), we can use the `installed.packages()` function to return a list of R packages for your computer. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE - -installed.packages() -``` - -::: - ---- - -## Install from GitHub - -::: {.fragment} -::: {.callout-tip title="."} - -In addition to the [CRAN](https://cran.r-project.org/) and [Bioconductor](https://www.bioconductor.org/) repositories, individual R packages can also be found on [GitHub](https://github.com/trending/r) hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to [CRAN](https://r-pkgs.org/release.html) or [Bioconductor]((https://contributions.bioconductor.org/))) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -While many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to [deprecation](https://devguide.ropensci.org/maintenance_evolution.html) since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it's useful to check the [commits](https://github.com/carlosproca/autospill/commits/master/) and [issues](https://github.com/carlosproca/autospill/issues) pages to see when the last contribution occurred. We will take a closer look at how to do so [later on](/Schedule.qmd#the-art-of-github-diving). - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To install packages from GitHub, you will need the `remotes` package, which can be found on CRAN. - -::: -::: - -::: {.fragment} -:::{.callout-tip title="Spot Check #1"} - -To install a package from CRAN, what function would you use? -Click on the code-fold arrow below to reveal the answer. - -::: -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -install.packages("remotes") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -With the `remotes` package now installed, we can attach it to our local environment. - -::: -::: - -::: {.fragment} -:::{.callout-tip title="Spot Check #2"} - -What function would be used to do so? - -::: -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -library(remotes) -``` - -::: - - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -And finally, we can use the `install_github()` function to download R packages from the invidual developers GitHub account. - -::: -::: - -::: {.fragment} -:::{.callout-tip title="Spot Check #3"} - -How would you look up the help documentation for this function? - -::: -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Either by hovering over it within Positron or via - -?install_github() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -We will be installing a small R package [flowSpectrum](https://github.com/hally166/flowSpectrum) for this example. It's one of the packages created by [Christopher Hall](https://github.com/hally166), whose small series of [Flow Cytometry Data Analysis in R](https://youtu.be/2INqQNMNaV0?si=dZ_rJ1S26KnNbUmU) tutorials were immensely useful when I was first getting started learning R. `flowSpectrum` can be used to generate spectrum-style plots for spectral flow cytometry data. - -::: -::: - ---- - -![](images/PE_Spectrum.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To install an R package from GitHub, we first need the GitHub username (so [hally166](https://github.com/hally166) in this case), which is followed by a "/", and then the name of the package repository (so [flowSpectrum](https://github.com/hally166/flowSpectrum) in this case). Our code should consequently be - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE - -install_github("hally166/flowSpectrum") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -When installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding. - -This process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating [R packages](/Schedule.qmd#building-your-first-r-package). - -::: -::: - ---- - -![](images/17_InstallSource.png) - ---- - -## Troubleshooting Install Errors - -::: {.fragment} -::: {.callout-tip title="."} - -We have now installed three R packages, `dplyr`, `PeacoQC`, and `flowSpectrum`. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies. - -When encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below. - -::: -::: - ---- - -![](images/18_ErrorExample.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -If you encounter an installation error this week, please take screenshots of the error message and post them to this [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future. - -::: -::: - ---- - -## Installing Specific-Package Versions - -::: {.fragment} - -::: {.callout-tip title="."} -While we may be tempted to think of R packages as static, they change quite often, as their develipers add new features, fix bugs, etc. To help keep track of these changes (essential for [reproducibility](https://www.nature.com/articles/d42473-019-00004-y) and replicability), R packages have version numbers. - -When we run `sessionInfo()`, we can see an example of this, with the version number appearing after the package name. - -::: -::: - - -::: {.fragment} - -```{r} -sessionInfo() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Alternatively, we can retrieve the same information for the individual packages via the `packageVersion()` function - -::: -::: - -::: {.fragment} - -```{r} -packageVersion("PeacoQC") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -As well as from the `citation()` function. - -::: -::: - -::: {.fragment} - -```{r} -citation("PeacoQC") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -How does a version number work? Lets say we have the following version number: **1.20.0** - -The first number of the version (**1.** in this case) denotes major changes, primarily those where after the version change the package may not be compatible with the code used in the prior version. As a consequence, this number changes rarely. - -The second number (**.20.** in this case) is the minor version. Minor changes typically consist of new features that are added, that don't affect the overall package function. These will change more frequently, especially for Bioconductor packages with fixed [release cycles](https://www.bioconductor.org/developers/release-schedule/). - -The final number (**.0** in this case) is often used to denote small changes occuring within a minor release period, often bug-fixes or fixing typos within the documentation. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -We may in the future need to install specific package versions (but wont be doing so today). As expected, which repository contains the R package influences how we would go about doing this. - -For CRAN packages, we can use the `remotes` packages `install_version()` function. This allows us to provide the version number, and designate the repository location (the CRAN url in this case). - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -remotes::install_version("ggplot2", version = "3.5.2", repos = "https://cloud.r-project.org") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -For GitHub-based R packages, the package versioning schema is not as strict as that of CRAN or Bioconductor. Typically, changes in R packagaes are put out by their developers as [releases](https://github.com/DavidRach/Luciernaga/releases). When trying to install a particular release, we can add an additional argument to the `install_github()` function, specifying the release version's tag number. For example: - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -remotes::install_github("DavidRach/Luciernaga", ref = "v0.99.7") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Alternatively, if the developer doesn't implement releases, you can provide the hash number of a particular commit. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE - -remotes::install_github("DavidRach/Luciernaga", ref = "8d1d694") -``` - -::: - - -## Documentation and Websites - -::: {.fragment} -::: {.callout-tip title="."} - -We have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package. - -For CRAN-based packages, we can start off by searching for the package name. So, in the case of `dplyr` - -::: -::: - ---- - -![](images/19_DplyrGoogle.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Two main suggestions pop up. One is the package's [CRAN](https://cran.r-project.org/web/packages/dplyr/index.html) page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible. - -::: -::: - ---- - -![](images/20_DplyrCRAN.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Because of this, many CRAN-based R packages (especially those part of the tidyverse) use [pkgdown](https://pkgdown.r-lib.org/)-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr's pkgdown-style [website](https://dplyr.tidyverse.org/) - -::: -::: - ---- - -![](images/21_DplyrPkgdown.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -We can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab. - -::: -::: - ---- - -![](images/22_PkgdownArticles.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -GitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository's ReadMe. - -::: -::: - ---- - -![](images/23_GitHub.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -For Bioconductor-based packages, on the package's page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with [PeacoQC](https://www.bioconductor.org/packages/release/bioc/vignettes/PeacoQC/inst/doc/PeacoQC_Vignette.pdf): - -::: -::: - ---- - -![](images/24_PeacoQCBioc.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Additionally, package vignettes can also be reached via the packages help index page. These will usually appear under ***User guides, package vignettes, and other documentation***. - -::: -::: - ---- - -![](images/25_Vignettes.png) - ---- - - -# Your Turn - -::: {.fragment} -::: {.callout-tip title="."} - -Alright, we have now gone through the process of installing an R package from [CRAN](/course/01_InstallingRPackages/index.qmd#installing-from-cran), [Bioconductor](/course/01_InstallingRPackages/index.qmd#installing-from-bioconductor), and [GitHub](/course/01_InstallingRPackages/index.qmd#install-from-github). We will now install 20 other R packages we will need throughout the rest of the course. - -::: -::: - -:::{.callout-note} - -To make this interactive, [**I will task you**]{.underscore} to apply the previous concepts to figure out whether the packages need to be installed via CRAN, Bioconductor or GitHub. - -::: - -:::{.callout-important} - -Feel free to view the [website](https://umgcccfcsr.github.io/CytometryInR/course/) version to avoid accidental spoilers from the copied over index.qmd file. Alternatively, you can attempt to switch from the Source view to Visual Mode by right clicking with your mouse and selecting that option. - -::: - -:::{.callout-tip} - -Start by searching each packages name. See if you can spot first either a CRAN or a Bioconductor website. Then enter the respective installation command (`install.packages()`, `install()`, `install_github()`) for the appropiate repository, add the package name, and run the code to see if the installation proceeds. - -For cases where you are truly stuck, expand the code-fold below each package name to see the answer. - -::: - -:::{.callout-note} - -Some of these packages may be dependencies of each other and may wind up installed before you get to them. If that is the case, no need to reinstall, count it as a win, and proceed to the next R package. - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Remember,if you encountered any installation errors in the process, please take screenshots and post them on the the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10) to help with improved documentation. - -::: -::: - ---- - -:::{.callout-tip title="1/20"} - -R package: purrr - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://purrr.tidyverse.org/ - -install.packages("purrr") -``` - -::: - ---- - -:::{.callout-tip title="2/20"} - -R package: flowCore - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/flowCore.html - -install("flowCore") -``` - -::: - ---- - -:::{.callout-tip title="3/20"} - -R package: flowWorkspace - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/flowWorkspace.html - -install("flowWorkspace") -``` - -::: - ---- - -:::{.callout-tip title="4/20"} - -R package: stringr - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://stringr.tidyverse.org/ - -install.packages("stringr") -``` - -::: - ---- - -:::{.callout-tip title="5/20"} - -R package: ggplot2 - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://ggplot2.tidyverse.org/ - -install.packages("ggplot2") -``` - -::: - ---- - - -:::{.callout-tip title="6/20"} - -R package: ggcyto - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/ggcyto.html - -install("ggcyto") -``` - -::: - ---- - -:::{.callout-tip title="7/20"} - -R package: tidyr - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://tidyr.tidyverse.org/ - -install.packages("tidyr") -``` - -::: - ---- - -:::{.callout-tip title="8/20"} - -R package: openCyto - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/openCyto.html - -install("openCyto") -``` - -::: - ---- - -:::{.callout-tip title="9/20"} - -R package: FlowSOM - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/FlowSOM.html - -install("FlowSOM") -``` - -::: - ---- - -:::{.callout-tip title="10/20"} - -R package: xml2 - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://xml2.r-lib.org/ - -install.packages("xml2") -``` - -::: - ---- - - -:::{.callout-tip title="11/20"} - -R package: saeyslab/CytoNorm - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: GitHub -# Website: https://github.com/saeyslab/CytoNorm - -install_github("saeyslab/CytoNorm") -``` - -::: - ---- - -:::{.callout-tip title="12/20"} - -R package: lubridate - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://lubridate.tidyverse.org/ - -install.packages("lubridate") -``` - -::: - ---- - -:::{.callout-tip title="13/20"} - -R package: httr2 - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://httr2.r-lib.org/ - -install.packages("httr2") -``` - -::: - ---- - -:::{.callout-tip title="14/20"} - -R package: flowGate - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/flowGate.html - -install("flowGate") -``` - -::: - ---- - -:::{.callout-tip title="15/20"} - -R package: devtools - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://devtools.r-lib.org/ - -install.packages("devtools") -``` - -::: - ---- - -:::{.callout-tip title="16/20"} - -R package: plotly - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://plotly.com/r/getting-started/ - -install.packages("plotly") -``` - -::: - ---- - -:::{.callout-tip title="17/20"} - -R package: biosurf/cyCombine - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: GitHub -# Website: https://github.com/biosurf/cyCombine - -install_github("biosurf/cyCombine") -``` - -::: - ---- - -:::{.callout-tip title="18/20"} - -R package: CytoML - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/CytoML.html - -install("CytoML") -``` - -::: - ---- - -:::{.callout-tip title="19/20"} - -R package: Rtsne - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://github.com/jkrijthe/Rtsne - -install.packages("Rtsne") -``` - -::: - ---- - -:::{.callout-tip title="20/20"} - -R package: uwot - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website:https://jlmelville.github.io/uwot/ - -install.packages("uwot") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -**Congratulations!** You have (hopefully) survived the package installation onslaught that is Week #1 of the course. - -::: -::: - ---- - -![](images/Entertained.jpg) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Remember to submit any encountered installation error screenshots to the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). - -::: -::: - ---- - -# Wrap-Up - -::: {.fragment} -::: {.callout-tip title="."} - -In this session, we walked through what are R packages, where to find them, how to install them, and a bit about troubleshooting any installation errors you may encounter during the process. - -You then proceeded to install most of the R packages that you would need throughout the [Cytometry in R course](/Schedule.qmd). These included tidyverse packages from the [CRAN] repository used for working with data structures and plots, as well as more cytometry focused R packages from [Bioconductor] repository. - -If you have any questions, or want to discuss this week's topics in more depth with the other course participants, please head over to the [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page and open a new topic. - -Next week, we will start learning about [file paths](/Schedule.qmd#file-paths), by which we will be able to tell our computer where to find your fcs files, how to retrieve the file names, subset those that may be of particular interest, and copy them over to a new folder. In the processs, we will learn a little more about how variables, objects, and list work within R. - -Until then, Best Wishes! - -- David - -::: -::: - ---- - -![](/course/01_InstallingRPackages/images/ExitImage.png) - ---- - -# Additional Resources - -::: {.fragment} -::: {.callout-tip title="."} - -[Tidy Tales](https://tidytales.ca/series/2023-01-24_reproducible-data-science/posts/r-packages.html) An usefu beginner-friendly blogpost covering additional aspects from a different perspective. - -[Introduction to Bioconductor](https://youtu.be/dg6NvmMVQ3I?si=WfsqpO3Z-M2oG8zh) A talk by Martin Morgan with more information about the Bioconductor project. - -[R Packages](https://r-pkgs.org/) A book by Hadley Wickham and Jennifer Bryan, covering all the different internals of R packages. - -::: -::: - ---- - - -# Take-home Problems - -::: {.fragment} -::: {.callout-tip title="."} - -Below you will find the optional take-home problems for Week #1. Learning how to code well requires continous practice, and that involves cycles of trying something, failing, and troubleshooting to get it working. The goal of these problems is to help you explore the topic in greater depth than the currated boundaries of this one lecture. - -You are more than welcome to open a [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) to engage with others in the course to discuss these questions. Once you are done tinkering, and want to get final instructor feedback on your work, place your files within a folder, and follow the instructions to submit it as a [Pull Request](/course/00_Homeworks/index.qmd#submitting-take-home-problems) to the Cytometry In R repositories homework branch. - -::: -::: - ---- - -:::{.callout-tip title="Problem 1"} - -We installed PeacoQC during this session, but we didn't have time to explore what functions are present within the package. Using what you have learned about accessing documentation, figure out and list what functions it contains - -::: - ---- - -:::{.callout-tip title="Problem 2"} - -Take a closer look at the list of Bioconductor [cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) packages. Report back on how many there are currently in Bioconductor, the author/maintainer with the most contributed cytometry R packages, and a couple packages that you would be interested in exploring more in-depth later in the course. - -::: - ---- - -:::{.callout-tip title="Problem 3"} - -There is another way to install R packages, using the newer [pak](https://pak.r-lib.org/) package. Positron uses this when installing suggested dependencies. - -After learning more about it via the documentation and it's pkgdown website, I would like you to attempt to install the following three R packages using this newer method: "broom", "cytoMEM", "DillonHammill/CytoExploreR". - -Take screenshots, and in a new [quarto markdown document](/course/00_Quarto/index.qmd), describe how the installation process differed from what you saw for `install.packages()`, `install()` and `install_github()`. - -::: - ---- - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - +--- +title: "01 - Installing R Packages" +author: "David Rach" +date: 02-01-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {.callout-tip title="."} + +Welcome to the first week of [Cytometry in R](/Schedule.qmd)! This week we will be diving into how R packages work, and the how to go about installing them. + +::: + +--- + +::: {.fragment} +::: {.callout-important} + +Before getting started, please make sure you have completed the creating a [GitHub](/course/00_GitHub/) and [Workstation Setup](/course/00_WorkstationSetup/) walk-throughs, since we will begin where they left off once the required software was successfully installed. + +::: +::: + +::: {.fragment} +::: {.callout-important} + +Please make sure to [sync](/course/00_Homeworks/index.qmd#sync-your-fork) your forked version of the CytometryInR repository, and [pull](/course/00_Git/index.qmd#pull) any changes to your local computer's CytometryInR project folder so that you have the most recent version of the code and data available. + +::: +::: + +--- + +# Background + +::: {.fragment} +::: {.callout-tip title="."} + +During [Workstation Setup](/course/00_WorkstationSetup/), you installed the R software to your local computer. R as a [programming language](https://en.wikipedia.org/wiki/R_(programming_language)) that started up in the 1990s. While its original focus was on statistics, it is now widely used in various fields thanks to contributions of many open-source developers over the years. + +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} + +This expanded reach is in part due to the ability to create [**R packages**](https://en.wikipedia.org/wiki/R_package), that encapsulate additional [**functions**](https://adv-r.hadley.nz/functions.html#function-fundamentals), that can do new things beyond what the original software (ie. **base R**) was capable of doing. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Currently, there are [thousands](https://cran.r-project.org/web/packages/available_packages_by_name.html) of R packages available. Furthermore, there is a vibrant [community](https://www.reddit.com/r/rstats/) of individuals that help maintain and document how to use these packages, which has helped sustain and grow the R ecosystem over the last couple [decades](https://youtu.be/gjpNEVcG1nU?si=rcEBSc7AnAsgsAy2). + +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} + +Regardless if you are working with [flow cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry), or in [ecology](https://drmattg.github.io/REcol-verse/), or in [econometrics](https://www.econometrics-with-r.org/1-introduction.html), or [political science](https://github.com/fivethirtyeight/data), a lot of the analysis and visualizations that you see in publications often involve R. + +::: +::: + +--- + +:::{.callout-tip} + +R packages can also just be made for fun! Among my favorite examples of this, there is an R package that lets you add the snake game to your [recalculating screen](https://github.com/AdamSpannbauer/snakeLoadR), as well as R packages that provide the color-palette schemes needed to make your plots with [Studio Ghibli](https://github.com/ewenme/ghibli), [Wes Anderson](https://github.com/karthik/wesanderson), or [Bluey](https://github.com/ekholme/blueycolors) colors. + +::: + +::: {.fragment} + +![](images/Ghibli.png){fig-width=100} +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +These R packages start off as [source code](https://r-pkgs.org/structure.html#sec-package-states) (which is what we will be learning to write during this course). When you install a R package to your computer, this human-readable source code gets converted into a binary format with which your computer can interact directly. + +::: +::: + + +::: {.fragment} +::: {.callout-tip title="."} + +Expanding on this concept, a new R package can be made up of new code (primarily in the form of tools (ie. **functions**) that do a particular useful things) that is entirely self-contained, or reuse functions present in existing R packages to help make something new. When an R package relies on a function from another R package, it needs the other R package to be installed in order for everything to work properly. This is known as a package **dependency**. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To make distributing the thousands of R packages and their associated package dependencies easier, R packages are collected (ie. hosted) within **repositories**, which function as an intermediate distributor. + +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} + +The three main locations for R packages from are **[CRAN](https://cran.r-project.org/)** (containing 23069 packages), **[Bioconductor](https://www.bioconductor.org/)** (containing 2361 packages), and individual R packages hosted by their developers via **[GitHub](https://github.com/trending/r)**. + +::: +::: + +--- + + + +::: {.fragment} +::: {.callout-tip title="."} + +The process of installing R packages will vary a bit depending on which repository the respective R package is in. For beginners, this often prooves to be a pain-point, as they will attempt to install an R package using one set of installation commands, only to get an error (because the R package is not in that repository). + +::: +::: + + +::: {.fragment} +::: {.callout-tip title="."} + +In this session, we will work on installing the various R packages we will need through the course. While doing so, we will explore how to figure out which repository the individual package is in; what installation commands to use to download it; and how to look up the help documentation. We will also touch on how the functions within an R package are made available for our computer to use (via the `library()` call), and how to troubleshoot the more commonly encountered installation errors. + +::: +::: + +--- + +# Getting Started + +## Set Up + +Alright, with the background out of the way, let's get started! + +::: {.fragment} +:::{.callout-important} + +Please make sure to [sync](/course/00_Homeworks/index.qmd#sync-your-fork) your forked version of the CytometryInR repository, and [pull](/course/00_Git/index.qmd#pull) any changes to your local computer's CytometryInR project folder so that you have the most recent version of the code and data available. + +::: +::: + +::: {.fragment} +:::{.callout-warning} + +Please remember to always copy over the new material from your local CytometryInR folder to a separate Project Folder that you created and named (ex. "Week_01" or "MyLearningFolder", etc.). This will ensure any edits you make to the files do not affect your ability to bring in next week's materials to the CytometryInR folder + +::: +::: + +--- + +::: {.fragment} +:::{.callout-warning} + +After pulling the new data and code locally, open CytometryInR, open the course folder, and open the 01_InstallingRPackages folder. From here, copy the **index.qmd** file to your own working Project Folder (ex. Week_01) where you can work on it without causing any conflicts. Then return to Positron and open up your working project folder (ex. Week_01). + +::: +::: + +--- + +![](images/01_Interpreter.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Next up, within [Positron](/course/00_Positron/index.qmd#interpreter), let's make sure to select R as the coding language being used for this session. + +::: +::: + +--- + +![](images/01_Interpreter.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Now that R is running within Positron, the console (lower portion of the screenn) is now able to run (ie. execute) any R code that is sent to it. + +::: +::: + +--- + +![](https://positron.posit.co/images/user-interface-for-rstudio-migration.jpeg) + +## Checking for Loaded Packages + +::: {.fragment} +::: {.callout-tip title="."} + +For the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active. + +::: +::: + +--- + +### Accessing Help Documentation + +::: {.fragment} +::: {.callout-tip title="."} + +Within your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following `sessionInfo()` function + +::: +::: + + +::: {.fragment} + +```{r} +#| eval: FALSE +sessionInfo() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +If you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over. + +::: +::: + +--- + +![](images/02_HelpHover.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +In this case, we can see the help documentation corresponding for `sessionInfo()`. Beyond hovering over the function, this can also be accessed by adding a ? directly in front of the function, and then running that line of code. + +::: +::: + + +::: {.fragment} + +```{r} +#| eval: FALSE +?sessionInfo() +``` + +::: + +--- + +![](images/03_QuestionMark.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +When executed, the function's help file documentation will open up within the Help tab in the secondary side bar on the right-side of the screen. Glancing at the top of the page we can see the name of the package that contains the `sessionInfo()` function (`{utils}`). Scrolling down the help page past all the documentation, we can see a link to the index page. + +::: +::: + +--- + +![](images/04_Index.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +After clicking, the Help tab switches from viewing the documentation for the `sessionInfo()` function, to showing all the functions within the `utils` package. Most R packages contain help documentation, so this process can be adapted to find out additional information about what a function does, and what arguments are needed to produce customized outputs. + +::: +::: + +--- + +![](images/05_UtilsFunctions.png) + +--- + +### sessionInfo() + +::: {.fragment} +::: {.callout-tip title="."} + +Within your .qmd file, let's go ahead and run the following code-block: + +::: +::: + + +::: {.fragment} + +```{r} +#| echo: TRUE +sessionInfo() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +The outputs that get returned by `sessionInfo()` will vary a bit depending on your computer's [operating system](/course/00_WorkstationSetup/), and the version of R you have installed. + +For today, let's focus on the last two elements of the output: + +::: +::: + +--- + +![](images/06_sessionInfo.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +The [R software](https://www.r-project.org/) itself is made up of several **base R packages**, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages. + +As we install additional R packages and load them using the `library()` function throughout this session, sporadically re-run `sessionInfo()` to see how this list of R packages changes. + +::: +::: + +--- + +## Installing from CRAN + +::: {.fragment} +::: {.callout-tip title="."} + +We will start by installing R packages that are part of the [CRAN](https://cran.r-project.org/) repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository. + +These include the [tidyverse](https://tidyverse.org/) packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today. + +::: +::: + +--- + +### dplyr + +::: {.fragment} +::: {.callout-tip title="."} + +Our first R package we will install during this session is the [dplyr](https://dplyr.tidyverse.org/) package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function `install.packages()`. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +?install.packages() +``` + +::: + +--- + +![](images/07_InstallPackages.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +For the `install.packages()` function, we place within the () the name of the R package from CRAN that we wish to install. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +install.packages("dplyr") +``` + +::: + +--- + +:::{.callout-tip} + +A usual struggle point for beginners is that install.packages() requires " " to be placed around the package name. Forgetting them results in the error that we see below. + +::: + + +::: {.fragment} + +```{r} +#| error: TRUE + +install.packages(dplyr) +``` + +::: + +--- + +::: {.fragment} + +```{r} +#| eval: FALSE +install.packages("dplyr") +``` + +::: + +::: {.fragment} +::: {.callout-tip title="."} + +Go ahead and click on "Run Cell" next to your code-block, to install the `dplyr` R package. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +When a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system). + +::: +::: + +--- + +![](images/08_InstallScript.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Within this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN. + +If the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder. + +::: +::: + +--- + +![](images/09_InstallScript2.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +The final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the "Done" line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder). + +::: +::: + +--- + +### Attaching packages via library() + +::: {.fragment} +::: {.callout-tip title="."} + +If an R package has been installed successfully, we are now able to load it (ie. make it's functions available) to our local environment using the `library()` function. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +?library() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Unlike `install.packages()`, where we needed "" around the package name, the `library()` function does not require "" around the package name. Let's go ahead and load in `dplyr`, making its respective functions to our local environment. + +::: +::: + +::: {.fragment} + +```{r} +library(dplyr) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +From the output, we can see that `dplyr` has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages. + +With `dplyr` now loaded via the `library()` call, let's check `sessionInfo()` to see what has changed. + +::: +::: + +::: {.fragment} + +```{r} +sessionInfo() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Similar to what was seen for the base R packages, `dplyr` is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the `dplyr` packages `select()` function and it's respective help page. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +?select +``` + +::: + +--- + +![](images/10_Attached.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Since its parent package has been attached to our local environment (via the `library()` call), we can see `dplyr` functions appear as suggestions as we begin to type. + +By contrast, is we check for the `ggplot()` function from the ggplot2 package (which we haven't yet installed or attached via `library()`), no suggestions will pop up. + +::: +::: + +--- + +::: {.fragment} + +```{r} +?ggplot +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Beyond individual functions, some R packages also have help landing pages, that can be similarly accessed by adding a ? in front of the package name: + +::: +::: + +--- + +![](images/11_PackageLanding.png) + +--- + +### Unattaching + +::: {.fragment} +::: {.callout-tip title="."} + +So far, we have installed an R package, and then attached it (via `library()`). How would we reverse these steps? + +Well, to unload it from the local environment, there are a couple options. You could of course simply shut down Positron. The local environment only exist in context of when you open and close the session, which closing the program will do. All previously loaded R packages will be unattached, which is why when you start a new session you will need to load in all packages you plan on using via `library()`. + +Alternatively, although less used, you could `detach()` it via your console: + +::: +::: + +::: {.fragment} + +```{r} +detach("package:dplyr", unload=TRUE) +``` + +::: + +::: {.fragment} + +```{r} +sessionInfo() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Looking at the `sessionInfo()` output, dplyr is no longer attached to the local environment. Consequently, if we try to once again look for the documentation, no information will be retrieved. + +::: +::: + +::: {.fragment} + +```{r} +?dplyr +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +There is a workaround however, if we want to access functions from an unloaded R package. We can specify the R package's name, followed by two :, and then the function name. The :: conveys the context to your computer that the package is present, but may not be attached. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +?dplyr::select() +``` + +::: + +::: {.fragment} +::: {.callout-tip title="."} + +This particular use case can be useful if we want to run a particular function, but not load in all a packages functions (which may have identical function names to other R packages we are using and cause some conflicts). + +::: +::: + +--- + +### Removing Packages + +::: {.fragment} +::: {.callout-tip title="."} + +Just as we can install an R package, we can also uninstall an R package (although doing so is rare, most often when encountering package dependency conflict). To do so, we would use the `remove.packages()` function. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +?remove.packages() +``` + +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +remove.packages("dplyr") +``` + +::: + +::: {.fragment} +::: {.callout-tip title="."} + +This results in the package being removed entirely from our computer. We would then need to reinstall it if needed in the future. + +::: +::: + +--- + +### Common Issues + +::: {.fragment} +::: {.callout-tip title="."} + +As previously mentioned, [CRAN](https://cran.r-project.org/) is the main repository for R packages. But what if we tried to install an R package that is only found on [Bioconductor](https://www.bioconductor.org/) or via [GitHub](https://github.com/trending/r) using the `install.packages()` function? + +To see what occurs, let's try installing the `PeacoQC` [package](https://www.bioconductor.org/packages/release/bioc/html/PeacoQC.html) (which is found on Bioconductor). + +::: +::: + +::: {.fragment} + +```{r} +install.packages("PeacoQC") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +As you can see, the initial warning message suggest that `PeacoQC` is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn't figure out what was going on. + +This is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN. + +::: +::: + +--- + +## Installing from Bioconductor + +::: {.fragment} +::: {.callout-tip title="."} + +**[Bioconductor](https://www.bioconductor.org/)** is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this [link](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) you can find it's current flow and mass cytometry R packages. + +Bioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different [standards](https://contributions.bioconductor.org/) for acceptance than [CRAN](https://r-pkgs.org/release.html). They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To install an R package that is located on [Bioconductor](https://www.bioconductor.org/), we first need to install the `BiocManager` package from CRAN. This package will allow us to install Bioconductor packages from their respective repository. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +install.packages("BiocManager") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Once BiocManager is installed, we can attach it to our local environment using the `library()` function + +::: +::: + +::: {.fragment} + +```{r} +library(BiocManager) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +When loaded, you will see an output showing the current Bioconductor and R versions. + +We can then use BiocManager's `install()` function to go back and install `PeacoQC()`. + +::: +::: + +:::{.callout-tip} + +As always, don't forget the "" when running an `install()` command. + +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +?install() +``` + +::: + +::: {.fragment} + +```{r} +install("PeacoQC") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +We see a similar opening sequence of installation steps as what we saw when installing the `dplyr` package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation. + +::: +::: + +::: {.fragment} +:::{.callout-note} + +Behind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process + +::: +::: + +--- + +![](images/12_PeacoQCDependencies.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Within the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with `dplyr`, with a "Done (packagename)" being printed upon successful installation. + +::: +::: + +--- + +![](images/13_rjson.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +This process continues for each dependency being installed. + +::: +::: + +--- + +![](images/13b_Other.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +And finally, once all the dependencies are installed, `PeacoQC` starts to install. + +::: +::: + +--- + +![](images/13c_PeacoQC.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Occasionally, during installation, you will see a pop-up windown like this one in the console. This let's you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n]. + +::: +::: + +--- + +![](images/14_UpdateAll.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Alternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter. + +::: +::: + +--- + +![](images/16_GitHubInstall.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Generally, it's okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn't cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option. + +::: +::: + +--- + +![](images/14_UpdateAll.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +With PeacoQC has been installed, we can load it via the `library()` call + +::: +::: + +:::{.callout-tip} + +Remeber, `library()` doesn't require " " + +::: + +::: {.fragment} + +```{r} +library(PeacoQC) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +And we can check to see if it has been attached to the local environment + +::: +::: + +::: {.fragment} + +```{r} +sessionInfo() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +As you may have noticed, the section of ***loaded via namespace (but not attached)*** packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment. + +::: +::: + +--- + +![](images/15_AdditionalDependencies.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To see what packages are installed (but not yet loaded), we can use the `installed.packages()` function to return a list of R packages for your computer. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE + +installed.packages() +``` + +::: + +--- + +## Install from GitHub + +::: {.fragment} +::: {.callout-tip title="."} + +In addition to the [CRAN](https://cran.r-project.org/) and [Bioconductor](https://www.bioconductor.org/) repositories, individual R packages can also be found on [GitHub](https://github.com/trending/r) hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to [CRAN](https://r-pkgs.org/release.html) or [Bioconductor]((https://contributions.bioconductor.org/))) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +While many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to [deprecation](https://devguide.ropensci.org/maintenance_evolution.html) since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it's useful to check the [commits](https://github.com/carlosproca/autospill/commits/master/) and [issues](https://github.com/carlosproca/autospill/issues) pages to see when the last contribution occurred. We will take a closer look at how to do so [later on](/Schedule.qmd#the-art-of-github-diving). + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To install packages from GitHub, you will need the `remotes` package, which can be found on CRAN. + +::: +::: + +::: {.fragment} +:::{.callout-tip title="Spot Check #1"} + +To install a package from CRAN, what function would you use? +Click on the code-fold arrow below to reveal the answer. + +::: +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +install.packages("remotes") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +With the `remotes` package now installed, we can attach it to our local environment. + +::: +::: + +::: {.fragment} +:::{.callout-tip title="Spot Check #2"} + +What function would be used to do so? + +::: +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +library(remotes) +``` + +::: + + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +And finally, we can use the `install_github()` function to download R packages from the invidual developers GitHub account. + +::: +::: + +::: {.fragment} +:::{.callout-tip title="Spot Check #3"} + +How would you look up the help documentation for this function? + +::: +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Either by hovering over it within Positron or via + +?install_github() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +We will be installing a small R package [flowSpectrum](https://github.com/hally166/flowSpectrum) for this example. It's one of the packages created by [Christopher Hall](https://github.com/hally166), whose small series of [Flow Cytometry Data Analysis in R](https://youtu.be/2INqQNMNaV0?si=dZ_rJ1S26KnNbUmU) tutorials were immensely useful when I was first getting started learning R. `flowSpectrum` can be used to generate spectrum-style plots for spectral flow cytometry data. + +::: +::: + +--- + +![](images/PE_Spectrum.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To install an R package from GitHub, we first need the GitHub username (so [hally166](https://github.com/hally166) in this case), which is followed by a "/", and then the name of the package repository (so [flowSpectrum](https://github.com/hally166/flowSpectrum) in this case). Our code should consequently be + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE + +install_github("hally166/flowSpectrum") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +When installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding. + +This process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating [R packages](/Schedule.qmd#building-your-first-r-package). + +::: +::: + +--- + +![](images/17_InstallSource.png) + +--- + +## Troubleshooting Install Errors + +::: {.fragment} +::: {.callout-tip title="."} + +We have now installed three R packages, `dplyr`, `PeacoQC`, and `flowSpectrum`. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies. + +When encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below. + +::: +::: + +--- + +![](images/18_ErrorExample.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +If you encounter an installation error this week, please take screenshots of the error message and post them to this [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future. + +::: +::: + +--- + +## Installing Specific-Package Versions + +::: {.fragment} + +::: {.callout-tip title="."} +While we may be tempted to think of R packages as static, they change quite often, as their develipers add new features, fix bugs, etc. To help keep track of these changes (essential for [reproducibility](https://www.nature.com/articles/d42473-019-00004-y) and replicability), R packages have version numbers. + +When we run `sessionInfo()`, we can see an example of this, with the version number appearing after the package name. + +::: +::: + + +::: {.fragment} + +```{r} +sessionInfo() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Alternatively, we can retrieve the same information for the individual packages via the `packageVersion()` function + +::: +::: + +::: {.fragment} + +```{r} +packageVersion("PeacoQC") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +As well as from the `citation()` function. + +::: +::: + +::: {.fragment} + +```{r} +citation("PeacoQC") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +How does a version number work? Lets say we have the following version number: **1.20.0** + +The first number of the version (**1.** in this case) denotes major changes, primarily those where after the version change the package may not be compatible with the code used in the prior version. As a consequence, this number changes rarely. + +The second number (**.20.** in this case) is the minor version. Minor changes typically consist of new features that are added, that don't affect the overall package function. These will change more frequently, especially for Bioconductor packages with fixed [release cycles](https://www.bioconductor.org/developers/release-schedule/). + +The final number (**.0** in this case) is often used to denote small changes occuring within a minor release period, often bug-fixes or fixing typos within the documentation. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +We may in the future need to install specific package versions (but wont be doing so today). As expected, which repository contains the R package influences how we would go about doing this. + +For CRAN packages, we can use the `remotes` packages `install_version()` function. This allows us to provide the version number, and designate the repository location (the CRAN url in this case). + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +remotes::install_version("ggplot2", version = "3.5.2", repos = "https://cloud.r-project.org") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +For GitHub-based R packages, the package versioning schema is not as strict as that of CRAN or Bioconductor. Typically, changes in R packagaes are put out by their developers as [releases](https://github.com/DavidRach/Luciernaga/releases). When trying to install a particular release, we can add an additional argument to the `install_github()` function, specifying the release version's tag number. For example: + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +remotes::install_github("DavidRach/Luciernaga", ref = "v0.99.7") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Alternatively, if the developer doesn't implement releases, you can provide the hash number of a particular commit. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE + +remotes::install_github("DavidRach/Luciernaga", ref = "8d1d694") +``` + +::: + + +## Documentation and Websites + +::: {.fragment} +::: {.callout-tip title="."} + +We have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package. + +For CRAN-based packages, we can start off by searching for the package name. So, in the case of `dplyr` + +::: +::: + +--- + +![](images/19_DplyrGoogle.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Two main suggestions pop up. One is the package's [CRAN](https://cran.r-project.org/web/packages/dplyr/index.html) page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible. + +::: +::: + +--- + +![](images/20_DplyrCRAN.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Because of this, many CRAN-based R packages (especially those part of the tidyverse) use [pkgdown](https://pkgdown.r-lib.org/)-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr's pkgdown-style [website](https://dplyr.tidyverse.org/) + +::: +::: + +--- + +![](images/21_DplyrPkgdown.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +We can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab. + +::: +::: + +--- + +![](images/22_PkgdownArticles.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +GitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository's ReadMe. + +::: +::: + +--- + +![](images/23_GitHub.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +For Bioconductor-based packages, on the package's page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with [PeacoQC](https://www.bioconductor.org/packages/release/bioc/vignettes/PeacoQC/inst/doc/PeacoQC_Vignette.pdf): + +::: +::: + +--- + +![](images/24_PeacoQCBioc.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Additionally, package vignettes can also be reached via the packages help index page. These will usually appear under ***User guides, package vignettes, and other documentation***. + +::: +::: + +--- + +![](images/25_Vignettes.png) + +--- + + +# Your Turn + +::: {.fragment} +::: {.callout-tip title="."} + +Alright, we have now gone through the process of installing an R package from [CRAN](/course/01_InstallingRPackages/index.qmd#installing-from-cran), [Bioconductor](/course/01_InstallingRPackages/index.qmd#installing-from-bioconductor), and [GitHub](/course/01_InstallingRPackages/index.qmd#install-from-github). We will now install 20 other R packages we will need throughout the rest of the course. + +::: +::: + +:::{.callout-note} + +To make this interactive, [**I will task you**]{.underscore} to apply the previous concepts to figure out whether the packages need to be installed via CRAN, Bioconductor or GitHub. + +::: + +:::{.callout-important} + +Feel free to view the [website](https://umgcccfcsr.github.io/CytometryInR/course/) version to avoid accidental spoilers from the copied over index.qmd file. Alternatively, you can attempt to switch from the Source view to Visual Mode by right clicking with your mouse and selecting that option. + +::: + +:::{.callout-tip} + +Start by searching each packages name. See if you can spot first either a CRAN or a Bioconductor website. Then enter the respective installation command (`install.packages()`, `install()`, `install_github()`) for the appropiate repository, add the package name, and run the code to see if the installation proceeds. + +For cases where you are truly stuck, expand the code-fold below each package name to see the answer. + +::: + +:::{.callout-note} + +Some of these packages may be dependencies of each other and may wind up installed before you get to them. If that is the case, no need to reinstall, count it as a win, and proceed to the next R package. + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Remember,if you encountered any installation errors in the process, please take screenshots and post them on the the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10) to help with improved documentation. + +::: +::: + +--- + +:::{.callout-tip title="1/20"} + +R package: purrr + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://purrr.tidyverse.org/ + +install.packages("purrr") +``` + +::: + +--- + +:::{.callout-tip title="2/20"} + +R package: flowCore + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/flowCore.html + +install("flowCore") +``` + +::: + +--- + +:::{.callout-tip title="3/20"} + +R package: flowWorkspace + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/flowWorkspace.html + +install("flowWorkspace") +``` + +::: + +--- + +:::{.callout-tip title="4/20"} + +R package: stringr + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://stringr.tidyverse.org/ + +install.packages("stringr") +``` + +::: + +--- + +:::{.callout-tip title="5/20"} + +R package: ggplot2 + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://ggplot2.tidyverse.org/ + +install.packages("ggplot2") +``` + +::: + +--- + + +:::{.callout-tip title="6/20"} + +R package: ggcyto + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/ggcyto.html + +install("ggcyto") +``` + +::: + +--- + +:::{.callout-tip title="7/20"} + +R package: tidyr + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://tidyr.tidyverse.org/ + +install.packages("tidyr") +``` + +::: + +--- + +:::{.callout-tip title="8/20"} + +R package: openCyto + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/openCyto.html + +install("openCyto") +``` + +::: + +--- + +:::{.callout-tip title="9/20"} + +R package: FlowSOM + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/FlowSOM.html + +install("FlowSOM") +``` + +::: + +--- + +:::{.callout-tip title="10/20"} + +R package: xml2 + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://xml2.r-lib.org/ + +install.packages("xml2") +``` + +::: + +--- + + +:::{.callout-tip title="11/20"} + +R package: saeyslab/CytoNorm + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: GitHub +# Website: https://github.com/saeyslab/CytoNorm + +install_github("saeyslab/CytoNorm") +``` + +::: + +--- + +:::{.callout-tip title="12/20"} + +R package: lubridate + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://lubridate.tidyverse.org/ + +install.packages("lubridate") +``` + +::: + +--- + +:::{.callout-tip title="13/20"} + +R package: httr2 + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://httr2.r-lib.org/ + +install.packages("httr2") +``` + +::: + +--- + +:::{.callout-tip title="14/20"} + +R package: flowGate + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/flowGate.html + +install("flowGate") +``` + +::: + +--- + +:::{.callout-tip title="15/20"} + +R package: devtools + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://devtools.r-lib.org/ + +install.packages("devtools") +``` + +::: + +--- + +:::{.callout-tip title="16/20"} + +R package: plotly + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://plotly.com/r/getting-started/ + +install.packages("plotly") +``` + +::: + +--- + +:::{.callout-tip title="17/20"} + +R package: biosurf/cyCombine + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: GitHub +# Website: https://github.com/biosurf/cyCombine + +install_github("biosurf/cyCombine") +``` + +::: + +--- + +:::{.callout-tip title="18/20"} + +R package: CytoML + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/CytoML.html + +install("CytoML") +``` + +::: + +--- + +:::{.callout-tip title="19/20"} + +R package: Rtsne + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://github.com/jkrijthe/Rtsne + +install.packages("Rtsne") +``` + +::: + +--- + +:::{.callout-tip title="20/20"} + +R package: uwot + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website:https://jlmelville.github.io/uwot/ + +install.packages("uwot") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +**Congratulations!** You have (hopefully) survived the package installation onslaught that is Week #1 of the course. + +::: +::: + +--- + +![](images/Entertained.jpg) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Remember to submit any encountered installation error screenshots to the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). + +::: +::: + +--- + +# Wrap-Up + +::: {.fragment} +::: {.callout-tip title="."} + +In this session, we walked through what are R packages, where to find them, how to install them, and a bit about troubleshooting any installation errors you may encounter during the process. + +You then proceeded to install most of the R packages that you would need throughout the [Cytometry in R course](/Schedule.qmd). These included tidyverse packages from the [CRAN] repository used for working with data structures and plots, as well as more cytometry focused R packages from [Bioconductor] repository. + +If you have any questions, or want to discuss this week's topics in more depth with the other course participants, please head over to the [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page and open a new topic. + +Next week, we will start learning about [file paths](/Schedule.qmd#file-paths), by which we will be able to tell our computer where to find your fcs files, how to retrieve the file names, subset those that may be of particular interest, and copy them over to a new folder. In the processs, we will learn a little more about how variables, objects, and list work within R. + +Until then, Best Wishes! + +- David + +::: +::: + +--- + +![](/course/01_InstallingRPackages/images/ExitImage.png) + +--- + +# Additional Resources + +::: {.fragment} +::: {.callout-tip title="."} + +[Tidy Tales](https://tidytales.ca/series/2023-01-24_reproducible-data-science/posts/r-packages.html) An usefu beginner-friendly blogpost covering additional aspects from a different perspective. + +[Introduction to Bioconductor](https://youtu.be/dg6NvmMVQ3I?si=WfsqpO3Z-M2oG8zh) A talk by Martin Morgan with more information about the Bioconductor project. + +[R Packages](https://r-pkgs.org/) A book by Hadley Wickham and Jennifer Bryan, covering all the different internals of R packages. + +::: +::: + +--- + + +# Take-home Problems + +::: {.fragment} +::: {.callout-tip title="."} + +Below you will find the optional take-home problems for Week #1. Learning how to code well requires continous practice, and that involves cycles of trying something, failing, and troubleshooting to get it working. The goal of these problems is to help you explore the topic in greater depth than the currated boundaries of this one lecture. + +You are more than welcome to open a [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) to engage with others in the course to discuss these questions. Once you are done tinkering, and want to get final instructor feedback on your work, place your files within a folder, and follow the instructions to submit it as a [Pull Request](/course/00_Homeworks/index.qmd#submitting-take-home-problems) to the Cytometry In R repositories homework branch. + +::: +::: + +--- + +:::{.callout-tip title="Problem 1"} + +We installed PeacoQC during this session, but we didn't have time to explore what functions are present within the package. Using what you have learned about accessing documentation, figure out and list what functions it contains + +::: + +--- + +:::{.callout-tip title="Problem 2"} + +Take a closer look at the list of Bioconductor [cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) packages. Report back on how many there are currently in Bioconductor, the author/maintainer with the most contributed cytometry R packages, and a couple packages that you would be interested in exploring more in-depth later in the course. + +::: + +--- + +:::{.callout-tip title="Problem 3"} + +There is another way to install R packages, using the newer [pak](https://pak.r-lib.org/) package. Positron uses this when installing suggested dependencies. + +After learning more about it via the documentation and it's pkgdown website, I would like you to attempt to install the following three R packages using this newer method: "broom", "cytoMEM", "DillonHammill/CytoExploreR". + +Take screenshots, and in a new [quarto markdown document](/course/00_Quarto/index.qmd), describe how the installation process differed from what you saw for `install.packages()`, `install()` and `install_github()`. + +::: + +--- + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + diff --git a/course/01_InstallingRPackages/slides_inperson.qmd b/course/01_InstallingRPackages/slides_inperson.qmd index 078e802..3cc1f08 100644 --- a/course/01_InstallingRPackages/slides_inperson.qmd +++ b/course/01_InstallingRPackages/slides_inperson.qmd @@ -1,1661 +1,1661 @@ ---- -title: "01 - Installing R Packages" -author: "David Rach" -date: 02-01-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {.callout-tip title="."} - -Welcome to the first week of [Cytometry in R](/Schedule.qmd)! This week we will be diving into how R packages work, and the how to go about installing them. - -::: - -# Background - -::: {.fragment} -::: {.callout-tip title="."} - -During [Workstation Setup](/course/00_WorkstationSetup/), you installed the R software to your local computer. R as a [programming language](https://en.wikipedia.org/wiki/R_(programming_language)) that started up in the 1990s. While its original focus was on statistics, it is now widely used in various fields thanks to contributions of many open-source developers over the years. - -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} - -This expanded reach is in part due to the ability to create [**R packages**](https://en.wikipedia.org/wiki/R_package), that encapsulate additional [**functions**](https://adv-r.hadley.nz/functions.html#function-fundamentals), that can do new things beyond what the original software (ie. **base R**) was capable of doing. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Currently, there are [thousands](https://cran.r-project.org/web/packages/available_packages_by_name.html) of R packages available. Furthermore, there is a vibrant [community](https://www.reddit.com/r/rstats/) of individuals that help maintain and document how to use these packages, which has helped sustain and grow the R ecosystem over the last couple [decades](https://youtu.be/gjpNEVcG1nU?si=rcEBSc7AnAsgsAy2). - -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} - -Regardless if you are working with [flow cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry), or in [ecology](https://drmattg.github.io/REcol-verse/), or in [econometrics](https://www.econometrics-with-r.org/1-introduction.html), or [political science](https://github.com/fivethirtyeight/data), a lot of the analysis and visualizations that you see in publications often involve R. - -::: -::: - ---- - - -::: {.fragment} -::: {.callout-tip title="."} - -Expanding on this concept, a new R package can be made up of new code (primarily in the form of tools (ie. **functions**) that do a particular useful things) that is entirely self-contained, or reuse functions present in existing R packages to help make something new. When an R package relies on a function from another R package, it needs the other R package to be installed in order for everything to work properly. This is known as a package **dependency**. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -The three main locations for R packages from are **[CRAN](https://cran.r-project.org/)** (containing 23069 packages), **[Bioconductor](https://www.bioconductor.org/)** (containing 2361 packages), and individual R packages hosted by their developers via **[GitHub](https://github.com/trending/r)**. - -::: -::: - ---- - - - -::: {.fragment} -::: {.callout-tip title="."} - -The process of installing R packages will vary a bit depending on which repository the respective R package is in. For beginners, this often prooves to be a pain-point, as they will attempt to install an R package using one set of installation commands, only to get an error (because the R package is not in that repository). - -::: -::: - ---- - -# Getting Started - -## Checking for Loaded Packages - -::: {.fragment} -::: {.callout-tip title="."} - -For the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active. - -::: -::: - ---- - -### Accessing Help Documentation - -::: {.fragment} -::: {.callout-tip title="."} - -Within your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following `sessionInfo()` function - -::: -::: - - -::: {.fragment} - -```{r} -#| eval: FALSE -sessionInfo() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -If you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over. - -::: -::: - ---- - -![](images/02_HelpHover.png) - ---- - -::: {.fragment} - -```{r} -#| eval: FALSE -?sessionInfo() -``` - -::: - ---- - -![](images/03_QuestionMark.png) - ---- - -### sessionInfo() - -::: {.fragment} -::: {.callout-tip title="."} - -Within your .qmd file, let's go ahead and run the following code-block: - -::: -::: - - -::: {.fragment} - -```{r} -#| echo: TRUE -sessionInfo() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -The outputs that get returned by `sessionInfo()` will vary a bit depending on your computer's [operating system](/course/00_WorkstationSetup/), and the version of R you have installed. - -For today, let's focus on the last two elements of the output: - -::: -::: - ---- - -![](images/06_sessionInfo.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -The [R software](https://www.r-project.org/) itself is made up of several **base R packages**, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages. - -As we install additional R packages and load them using the `library()` function throughout this session, sporadically re-run `sessionInfo()` to see how this list of R packages changes. - -::: -::: - ---- - -## Installing from CRAN - -::: {.fragment} -::: {.callout-tip title="."} - -We will start by installing R packages that are part of the [CRAN](https://cran.r-project.org/) repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository. - -These include the [tidyverse](https://tidyverse.org/) packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today. - -::: -::: - ---- - -### dplyr - -::: {.fragment} -::: {.callout-tip title="."} - -Our first R package we will install during this session is the [dplyr](https://dplyr.tidyverse.org/) package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function `install.packages()`. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -?install.packages() -``` - -::: - ---- - -![](images/07_InstallPackages.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -For the `install.packages()` function, we place within the () the name of the R package from CRAN that we wish to install. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -install.packages("dplyr") -``` - -::: - ---- - -:::{.callout-tip} - -A usual struggle point for beginners is that install.packages() requires " " to be placed around the package name. Forgetting them results in the error that we see below. - -::: - - -::: {.fragment} - -```{r} -#| error: TRUE - -install.packages(dplyr) -``` - -::: - ---- - -::: {.fragment} - -```{r} -#| eval: FALSE -install.packages("dplyr") -``` - -::: - -::: {.fragment} -::: {.callout-tip title="."} - -Go ahead and click on "Run Cell" next to your code-block, to install the `dplyr` R package. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -When a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system). - -::: -::: - ---- - -![](images/08_InstallScript.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Within this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN. - -If the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder. - -::: -::: - ---- - -![](images/09_InstallScript2.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -The final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the "Done" line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder). - -::: -::: - ---- - -### Attaching packages via library() - -::: {.fragment} -::: {.callout-tip title="."} - -If an R package has been installed successfully, we are now able to load it (ie. make it's functions available) to our local environment using the `library()` function. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -?library() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Unlike `install.packages()`, where we needed "" around the package name, the `library()` function does not require "" around the package name. Let's go ahead and load in `dplyr`, making its respective functions to our local environment. - -::: -::: - -::: {.fragment} - -```{r} -library(dplyr) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -From the output, we can see that `dplyr` has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages. - -With `dplyr` now loaded via the `library()` call, let's check `sessionInfo()` to see what has changed. - -::: -::: - -::: {.fragment} - -```{r} -sessionInfo() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Similar to what was seen for the base R packages, `dplyr` is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the `dplyr` packages `select()` function and it's respective help page. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -?select -``` - -::: - ---- - -![](images/10_Attached.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Since its parent package has been attached to our local environment (via the `library()` call), we can see `dplyr` functions appear as suggestions as we begin to type. - -By contrast, is we check for the `ggplot()` function from the ggplot2 package (which we haven't yet installed or attached via `library()`), no suggestions will pop up. - -::: -::: - ---- - -::: {.fragment} - -```{r} -?ggplot -``` - -::: - ---- - -### Common Issues - -::: {.fragment} -::: {.callout-tip title="."} - -As previously mentioned, [CRAN](https://cran.r-project.org/) is the main repository for R packages. But what if we tried to install an R package that is only found on [Bioconductor](https://www.bioconductor.org/) or via [GitHub](https://github.com/trending/r) using the `install.packages()` function? - -To see what occurs, let's try installing the `PeacoQC` [package](https://www.bioconductor.org/packages/release/bioc/html/PeacoQC.html) (which is found on Bioconductor). - -::: -::: - -::: {.fragment} - -```{r} -install.packages("PeacoQC") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -As you can see, the initial warning message suggest that `PeacoQC` is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn't figure out what was going on. - -This is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN. - -::: -::: - ---- - -## Installing from Bioconductor - -::: {.fragment} -::: {.callout-tip title="."} - -**[Bioconductor](https://www.bioconductor.org/)** is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this [link](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) you can find it's current flow and mass cytometry R packages. - -Bioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different [standards](https://contributions.bioconductor.org/) for acceptance than [CRAN](https://r-pkgs.org/release.html). They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To install an R package that is located on [Bioconductor](https://www.bioconductor.org/), we first need to install the `BiocManager` package from CRAN. This package will allow us to install Bioconductor packages from their respective repository. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -install.packages("BiocManager") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Once BiocManager is installed, we can attach it to our local environment using the `library()` function - -::: -::: - -::: {.fragment} - -```{r} -library(BiocManager) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -When loaded, you will see an output showing the current Bioconductor and R versions. - -We can then use BiocManager's `install()` function to go back and install `PeacoQC()`. - -::: -::: - -:::{.callout-tip} - -As always, don't forget the "" when running an `install()` command. - -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -?install() -``` - -::: - -::: {.fragment} - -```{r} -install("PeacoQC") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -We see a similar opening sequence of installation steps as what we saw when installing the `dplyr` package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation. - -::: -::: - -::: {.fragment} -:::{.callout-note} - -Behind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process - -::: -::: - ---- - -![](images/12_PeacoQCDependencies.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Within the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with `dplyr`, with a "Done (packagename)" being printed upon successful installation. - -::: -::: - ---- - -![](images/13_rjson.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -This process continues for each dependency being installed. - -::: -::: - ---- - -![](images/13b_Other.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -And finally, once all the dependencies are installed, `PeacoQC` starts to install. - -::: -::: - ---- - -![](images/13c_PeacoQC.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Occasionally, during installation, you will see a pop-up windown like this one in the console. This let's you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n]. - -::: -::: - ---- - -![](images/14_UpdateAll.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Alternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter. - -::: -::: - ---- - -![](images/16_GitHubInstall.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Generally, it's okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn't cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option. - -::: -::: - ---- - -![](images/14_UpdateAll.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -With PeacoQC has been installed, we can load it via the `library()` call - -::: -::: - -:::{.callout-tip} - -Remeber, `library()` doesn't require " " - -::: - -::: {.fragment} - -```{r} -library(PeacoQC) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -And we can check to see if it has been attached to the local environment - -::: -::: - -::: {.fragment} - -```{r} -sessionInfo() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -As you may have noticed, the section of ***loaded via namespace (but not attached)*** packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment. - -::: -::: - ---- - -![](images/15_AdditionalDependencies.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To see what packages are installed (but not yet loaded), we can use the `installed.packages()` function to return a list of R packages for your computer. - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE - -installed.packages() -``` - -::: - ---- - -## Install from GitHub - -::: {.fragment} -::: {.callout-tip title="."} - -In addition to the [CRAN](https://cran.r-project.org/) and [Bioconductor](https://www.bioconductor.org/) repositories, individual R packages can also be found on [GitHub](https://github.com/trending/r) hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to [CRAN](https://r-pkgs.org/release.html) or [Bioconductor]((https://contributions.bioconductor.org/))) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all. - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -While many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to [deprecation](https://devguide.ropensci.org/maintenance_evolution.html) since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it's useful to check the [commits](https://github.com/carlosproca/autospill/commits/master/) and [issues](https://github.com/carlosproca/autospill/issues) pages to see when the last contribution occurred. We will take a closer look at how to do so [later on](/Schedule.qmd#the-art-of-github-diving). - -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To install packages from GitHub, you will need the `remotes` package, which can be found on CRAN. - -::: -::: - -::: {.fragment} -:::{.callout-tip title="Spot Check #1"} - -To install a package from CRAN, what function would you use? -Click on the code-fold arrow below to reveal the answer. - -::: -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -install.packages("remotes") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -With the `remotes` package now installed, we can attach it to our local environment. - -::: -::: - -::: {.fragment} -:::{.callout-tip title="Spot Check #2"} - -What function would be used to do so? - -::: -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -library(remotes) -``` - -::: - - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -And finally, we can use the `install_github()` function to download R packages from the invidual developers GitHub account. - -::: -::: - -::: {.fragment} -:::{.callout-tip title="Spot Check #3"} - -How would you look up the help documentation for this function? - -::: -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Either by hovering over it within Positron or via - -?install_github() -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -We will be installing a small R package [flowSpectrum](https://github.com/hally166/flowSpectrum) for this example. It's one of the packages created by [Christopher Hall](https://github.com/hally166), whose small series of [Flow Cytometry Data Analysis in R](https://youtu.be/2INqQNMNaV0?si=dZ_rJ1S26KnNbUmU) tutorials were immensely useful when I was first getting started learning R. `flowSpectrum` can be used to generate spectrum-style plots for spectral flow cytometry data. - -::: -::: - ---- - -![](images/PE_Spectrum.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -To install an R package from GitHub, we first need the GitHub username (so [hally166](https://github.com/hally166) in this case), which is followed by a "/", and then the name of the package repository (so [flowSpectrum](https://github.com/hally166/flowSpectrum) in this case). Our code should consequently be - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE - -install_github("hally166/flowSpectrum") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -When installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding. - -This process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating [R packages](/Schedule.qmd#building-your-first-r-package). - -::: -::: - ---- - -![](images/17_InstallSource.png) - ---- - -## Troubleshooting Install Errors - -::: {.fragment} -::: {.callout-tip title="."} - -We have now installed three R packages, `dplyr`, `PeacoQC`, and `flowSpectrum`. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies. - -When encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below. - -::: -::: - ---- - -![](images/18_ErrorExample.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -If you encounter an installation error this week, please take screenshots of the error message and post them to this [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future. - -::: -::: - ---- - - -## Documentation and Websites - -::: {.fragment} -::: {.callout-tip title="."} - -We have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package. - -For CRAN-based packages, we can start off by searching for the package name. So, in the case of `dplyr` - -::: -::: - ---- - -![](images/19_DplyrGoogle.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Two main suggestions pop up. One is the package's [CRAN](https://cran.r-project.org/web/packages/dplyr/index.html) page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible. - -::: -::: - ---- - -![](images/20_DplyrCRAN.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Because of this, many CRAN-based R packages (especially those part of the tidyverse) use [pkgdown](https://pkgdown.r-lib.org/)-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr's pkgdown-style [website](https://dplyr.tidyverse.org/) - -::: -::: - ---- - -![](images/21_DplyrPkgdown.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -We can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab. - -::: -::: - ---- - -![](images/22_PkgdownArticles.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -GitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository's ReadMe. - -::: -::: - ---- - -![](images/23_GitHub.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -For Bioconductor-based packages, on the package's page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with [PeacoQC](https://www.bioconductor.org/packages/release/bioc/vignettes/PeacoQC/inst/doc/PeacoQC_Vignette.pdf): - -::: -::: - ---- - -![](images/24_PeacoQCBioc.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Additionally, package vignettes can also be reached via the packages help index page. These will usually appear under ***User guides, package vignettes, and other documentation***. - -::: -::: - ---- - -![](images/25_Vignettes.png) - ---- - - -# Your Turn - -::: {.fragment} -::: {.callout-tip title="."} - -Alright, we have now gone through the process of installing an R package from [CRAN](/course/01_InstallingRPackages/index.qmd#installing-from-cran), [Bioconductor](/course/01_InstallingRPackages/index.qmd#installing-from-bioconductor), and [GitHub](/course/01_InstallingRPackages/index.qmd#install-from-github). We will now install 20 other R packages we will need throughout the rest of the course. - -::: -::: - -:::{.callout-note} - -To make this interactive, [**I will task you**]{.underscore} to apply the previous concepts to figure out whether the packages need to be installed via CRAN, Bioconductor or GitHub. - -::: - -:::{.callout-important} - -Feel free to view the [website](https://umgcccfcsr.github.io/CytometryInR/course/) version to avoid accidental spoilers from the copied over index.qmd file. Alternatively, you can attempt to switch from the Source view to Visual Mode by right clicking with your mouse and selecting that option. - -::: - -:::{.callout-tip} - -Start by searching each packages name. See if you can spot first either a CRAN or a Bioconductor website. Then enter the respective installation command (`install.packages()`, `install()`, `install_github()`) for the appropiate repository, add the package name, and run the code to see if the installation proceeds. - -For cases where you are truly stuck, expand the code-fold below each package name to see the answer. - -::: - -:::{.callout-note} - -Some of these packages may be dependencies of each other and may wind up installed before you get to them. If that is the case, no need to reinstall, count it as a win, and proceed to the next R package. - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Remember,if you encountered any installation errors in the process, please take screenshots and post them on the the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10) to help with improved documentation. - -::: -::: - ---- - -:::{.callout-tip title="1/20"} - -R package: purrr - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://purrr.tidyverse.org/ - -install.packages("purrr") -``` - -::: - ---- - -:::{.callout-tip title="2/20"} - -R package: flowCore - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/flowCore.html - -install("flowCore") -``` - -::: - ---- - -:::{.callout-tip title="3/20"} - -R package: flowWorkspace - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/flowWorkspace.html - -install("flowWorkspace") -``` - -::: - ---- - -:::{.callout-tip title="4/20"} - -R package: stringr - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://stringr.tidyverse.org/ - -install.packages("stringr") -``` - -::: - ---- - -:::{.callout-tip title="5/20"} - -R package: ggplot2 - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://ggplot2.tidyverse.org/ - -install.packages("ggplot2") -``` - -::: - ---- - - -:::{.callout-tip title="6/20"} - -R package: ggcyto - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/ggcyto.html - -install.packages("ggcyto") -``` - -::: - ---- - -:::{.callout-tip title="7/20"} - -R package: tidyr - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://tidyr.tidyverse.org/ - -install.packages("tidyr") -``` - -::: - ---- - -:::{.callout-tip title="8/20"} - -R package: openCyto - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/openCyto.html - -install.packages("openCyto") -``` - -::: - ---- - -:::{.callout-tip title="9/20"} - -R package: FlowSOM - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/FlowSOM.html - -install.packages("FlowSOM") -``` - -::: - ---- - -:::{.callout-tip title="10/20"} - -R package: xml2 - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: CRAN -# Website: https://xml2.r-lib.org/ - -install.packages("xml2") -``` - -::: - ---- - - -:::{.callout-tip title="11/20"} - -R package: saeyslab/CytoNorm - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - - -# Location: GitHub -# Website: https://github.com/saeyslab/CytoNorm - -install_github("saeyslab/CytoNorm") -``` - -::: - ---- - -:::{.callout-tip title="12/20"} - -R package: lubridate - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://lubridate.tidyverse.org/ - -install.packages("lubridate") -``` - -::: - ---- - -:::{.callout-tip title="13/20"} - -R package: httr2 - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://httr2.r-lib.org/ - -install.packages("httr2") -``` - -::: - ---- - -:::{.callout-tip title="14/20"} - -R package: flowGate - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/flowGate.html - -install("flowGate") -``` - -::: - ---- - -:::{.callout-tip title="15/20"} - -R package: devtools - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://devtools.r-lib.org/ - -install.packages("devtools") -``` - -::: - ---- - -:::{.callout-tip title="16/20"} - -R package: plotly - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://plotly.com/r/getting-started/ - -install.packages("plotly") -``` - -::: - ---- - -:::{.callout-tip title="17/20"} - -R package: biosurf/cyCombine - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: GitHub -# Website: https://github.com/biosurf/cyCombine - -install_github("biosurf/cyCombine") -``` - -::: - ---- - -:::{.callout-tip title="18/20"} - -R package: CytoML - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: Bioconductor -# Website: https://www.bioconductor.org/packages/release/bioc/html/CytoML.html - -install("CytoML") -``` - -::: - ---- - -:::{.callout-tip title="19/20"} - -R package: Rtsne - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website: https://github.com/jkrijthe/Rtsne - -install.packages("Rtsne") -``` - -::: - ---- - -:::{.callout-tip title="20/20"} - -R package: uwot - -::: - -::: {.fragment} - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Location: CRAN -# Website:https://jlmelville.github.io/uwot/ - -install.packages("uwot") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -**Congratulations!** You have (hopefully) survived the package installation onslaught that is Week #1 of the course. - -::: -::: - ---- - -![](images/Entertained.jpg) - ---- - -::: {.fragment} -::: {.callout-tip title="."} - -Remember to submit any encountered installation error screenshots to the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). - -::: -::: - ---- - -# Wrap-Up - -::: {.fragment} -::: {.callout-tip title="."} - -In this session, we walked through what are R packages, where to find them, how to install them, and a bit about troubleshooting any installation errors you may encounter during the process. - -You then proceeded to install most of the R packages that you would need throughout the [Cytometry in R course](/Schedule.qmd). These included tidyverse packages from the [CRAN] repository used for working with data structures and plots, as well as more cytometry focused R packages from [Bioconductor] repository. - -If you have any questions, or want to discuss this week's topics in more depth with the other course participants, please head over to the [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page and open a new topic. - -Next week, we will start learning about [file paths](/Schedule.qmd#file-paths), by which we will be able to tell our computer where to find your fcs files, how to retrieve the file names, subset those that may be of particular interest, and copy them over to a new folder. In the processs, we will learn a little more about how variables, objects, and list work within R. - -Until then, Best Wishes! - -- David - -::: -::: - ---- - -![](/course/01_InstallingRPackages/images/ExitImage.png) - ---- - -# Additional Resources - -::: {.fragment} -::: {.callout-tip title="."} - -[Tidy Tales](https://tidytales.ca/series/2023-01-24_reproducible-data-science/posts/r-packages.html) An usefu beginner-friendly blogpost covering additional aspects from a different perspective. - -[Introduction to Bioconductor](https://youtu.be/dg6NvmMVQ3I?si=WfsqpO3Z-M2oG8zh) A talk by Martin Morgan with more information about the Bioconductor project. - -[R Packages](https://r-pkgs.org/) A book by Hadley Wickham and Jennifer Bryan, covering all the different internals of R packages. - -::: -::: - ---- - - -# Take-home Problems - -::: {.fragment} -::: {.callout-tip title="."} - -Below you will find the optional take-home problems for Week #1. Learning how to code well requires continous practice, and that involves cycles of trying something, failing, and troubleshooting to get it working. The goal of these problems is to help you explore the topic in greater depth than the currated boundaries of this one lecture. - -You are more than welcome to open a [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) to engage with others in the course to discuss these questions. Once you are done tinkering, and want to get final instructor feedback on your work, place your files within a folder, and follow the instructions to submit it as a [Pull Request](/course/00_Homeworks/index.qmd#submitting-take-home-problems) to the Cytometry In R repositories homework branch. - -::: -::: - ---- - -:::{.callout-tip title="Problem 1"} - -We installed PeacoQC during this session, but we didn't have time to explore what functions are present within the package. Using what you have learned about accessing documentation, figure out and list what functions it contains - -::: - ---- - -:::{.callout-tip title="Problem 2"} - -Take a closer look at the list of Bioconductor [cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) packages. Report back on how many there are currently in Bioconductor, the author/maintainer with the most contributed cytometry R packages, and a couple packages that you would be interested in exploring more in-depth later in the course. - -::: - ---- - -:::{.callout-tip title="Problem 3"} - -There is another way to install R packages, using the newer [pak](https://pak.r-lib.org/) package. Positron uses this when installing suggested dependencies. - -After learning more about it via the documentation and it's pkgdown website, I would like you to attempt to install the following three R packages using this newer method: "broom", "cytoMEM", "DillonHammill/CytoExploreR". - -Take screenshots, and in a new [quarto markdown document](/course/00_Quarto/index.qmd), describe how the installation process differed from what you saw for `install.packages()`, `install()` and `install_github()`. - -::: - ---- - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - +--- +title: "01 - Installing R Packages" +author: "David Rach" +date: 02-01-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {.callout-tip title="."} + +Welcome to the first week of [Cytometry in R](/Schedule.qmd)! This week we will be diving into how R packages work, and the how to go about installing them. + +::: + +# Background + +::: {.fragment} +::: {.callout-tip title="."} + +During [Workstation Setup](/course/00_WorkstationSetup/), you installed the R software to your local computer. R as a [programming language](https://en.wikipedia.org/wiki/R_(programming_language)) that started up in the 1990s. While its original focus was on statistics, it is now widely used in various fields thanks to contributions of many open-source developers over the years. + +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} + +This expanded reach is in part due to the ability to create [**R packages**](https://en.wikipedia.org/wiki/R_package), that encapsulate additional [**functions**](https://adv-r.hadley.nz/functions.html#function-fundamentals), that can do new things beyond what the original software (ie. **base R**) was capable of doing. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Currently, there are [thousands](https://cran.r-project.org/web/packages/available_packages_by_name.html) of R packages available. Furthermore, there is a vibrant [community](https://www.reddit.com/r/rstats/) of individuals that help maintain and document how to use these packages, which has helped sustain and grow the R ecosystem over the last couple [decades](https://youtu.be/gjpNEVcG1nU?si=rcEBSc7AnAsgsAy2). + +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} + +Regardless if you are working with [flow cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry), or in [ecology](https://drmattg.github.io/REcol-verse/), or in [econometrics](https://www.econometrics-with-r.org/1-introduction.html), or [political science](https://github.com/fivethirtyeight/data), a lot of the analysis and visualizations that you see in publications often involve R. + +::: +::: + +--- + + +::: {.fragment} +::: {.callout-tip title="."} + +Expanding on this concept, a new R package can be made up of new code (primarily in the form of tools (ie. **functions**) that do a particular useful things) that is entirely self-contained, or reuse functions present in existing R packages to help make something new. When an R package relies on a function from another R package, it needs the other R package to be installed in order for everything to work properly. This is known as a package **dependency**. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +The three main locations for R packages from are **[CRAN](https://cran.r-project.org/)** (containing 23069 packages), **[Bioconductor](https://www.bioconductor.org/)** (containing 2361 packages), and individual R packages hosted by their developers via **[GitHub](https://github.com/trending/r)**. + +::: +::: + +--- + + + +::: {.fragment} +::: {.callout-tip title="."} + +The process of installing R packages will vary a bit depending on which repository the respective R package is in. For beginners, this often prooves to be a pain-point, as they will attempt to install an R package using one set of installation commands, only to get an error (because the R package is not in that repository). + +::: +::: + +--- + +# Getting Started + +## Checking for Loaded Packages + +::: {.fragment} +::: {.callout-tip title="."} + +For the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active. + +::: +::: + +--- + +### Accessing Help Documentation + +::: {.fragment} +::: {.callout-tip title="."} + +Within your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following `sessionInfo()` function + +::: +::: + + +::: {.fragment} + +```{r} +#| eval: FALSE +sessionInfo() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +If you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over. + +::: +::: + +--- + +![](images/02_HelpHover.png) + +--- + +::: {.fragment} + +```{r} +#| eval: FALSE +?sessionInfo() +``` + +::: + +--- + +![](images/03_QuestionMark.png) + +--- + +### sessionInfo() + +::: {.fragment} +::: {.callout-tip title="."} + +Within your .qmd file, let's go ahead and run the following code-block: + +::: +::: + + +::: {.fragment} + +```{r} +#| echo: TRUE +sessionInfo() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +The outputs that get returned by `sessionInfo()` will vary a bit depending on your computer's [operating system](/course/00_WorkstationSetup/), and the version of R you have installed. + +For today, let's focus on the last two elements of the output: + +::: +::: + +--- + +![](images/06_sessionInfo.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +The [R software](https://www.r-project.org/) itself is made up of several **base R packages**, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages. + +As we install additional R packages and load them using the `library()` function throughout this session, sporadically re-run `sessionInfo()` to see how this list of R packages changes. + +::: +::: + +--- + +## Installing from CRAN + +::: {.fragment} +::: {.callout-tip title="."} + +We will start by installing R packages that are part of the [CRAN](https://cran.r-project.org/) repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository. + +These include the [tidyverse](https://tidyverse.org/) packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today. + +::: +::: + +--- + +### dplyr + +::: {.fragment} +::: {.callout-tip title="."} + +Our first R package we will install during this session is the [dplyr](https://dplyr.tidyverse.org/) package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function `install.packages()`. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +?install.packages() +``` + +::: + +--- + +![](images/07_InstallPackages.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +For the `install.packages()` function, we place within the () the name of the R package from CRAN that we wish to install. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +install.packages("dplyr") +``` + +::: + +--- + +:::{.callout-tip} + +A usual struggle point for beginners is that install.packages() requires " " to be placed around the package name. Forgetting them results in the error that we see below. + +::: + + +::: {.fragment} + +```{r} +#| error: TRUE + +install.packages(dplyr) +``` + +::: + +--- + +::: {.fragment} + +```{r} +#| eval: FALSE +install.packages("dplyr") +``` + +::: + +::: {.fragment} +::: {.callout-tip title="."} + +Go ahead and click on "Run Cell" next to your code-block, to install the `dplyr` R package. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +When a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system). + +::: +::: + +--- + +![](images/08_InstallScript.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Within this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN. + +If the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder. + +::: +::: + +--- + +![](images/09_InstallScript2.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +The final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the "Done" line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder). + +::: +::: + +--- + +### Attaching packages via library() + +::: {.fragment} +::: {.callout-tip title="."} + +If an R package has been installed successfully, we are now able to load it (ie. make it's functions available) to our local environment using the `library()` function. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +?library() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Unlike `install.packages()`, where we needed "" around the package name, the `library()` function does not require "" around the package name. Let's go ahead and load in `dplyr`, making its respective functions to our local environment. + +::: +::: + +::: {.fragment} + +```{r} +library(dplyr) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +From the output, we can see that `dplyr` has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages. + +With `dplyr` now loaded via the `library()` call, let's check `sessionInfo()` to see what has changed. + +::: +::: + +::: {.fragment} + +```{r} +sessionInfo() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Similar to what was seen for the base R packages, `dplyr` is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the `dplyr` packages `select()` function and it's respective help page. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +?select +``` + +::: + +--- + +![](images/10_Attached.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Since its parent package has been attached to our local environment (via the `library()` call), we can see `dplyr` functions appear as suggestions as we begin to type. + +By contrast, is we check for the `ggplot()` function from the ggplot2 package (which we haven't yet installed or attached via `library()`), no suggestions will pop up. + +::: +::: + +--- + +::: {.fragment} + +```{r} +?ggplot +``` + +::: + +--- + +### Common Issues + +::: {.fragment} +::: {.callout-tip title="."} + +As previously mentioned, [CRAN](https://cran.r-project.org/) is the main repository for R packages. But what if we tried to install an R package that is only found on [Bioconductor](https://www.bioconductor.org/) or via [GitHub](https://github.com/trending/r) using the `install.packages()` function? + +To see what occurs, let's try installing the `PeacoQC` [package](https://www.bioconductor.org/packages/release/bioc/html/PeacoQC.html) (which is found on Bioconductor). + +::: +::: + +::: {.fragment} + +```{r} +install.packages("PeacoQC") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +As you can see, the initial warning message suggest that `PeacoQC` is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn't figure out what was going on. + +This is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN. + +::: +::: + +--- + +## Installing from Bioconductor + +::: {.fragment} +::: {.callout-tip title="."} + +**[Bioconductor](https://www.bioconductor.org/)** is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this [link](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) you can find it's current flow and mass cytometry R packages. + +Bioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different [standards](https://contributions.bioconductor.org/) for acceptance than [CRAN](https://r-pkgs.org/release.html). They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To install an R package that is located on [Bioconductor](https://www.bioconductor.org/), we first need to install the `BiocManager` package from CRAN. This package will allow us to install Bioconductor packages from their respective repository. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +install.packages("BiocManager") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Once BiocManager is installed, we can attach it to our local environment using the `library()` function + +::: +::: + +::: {.fragment} + +```{r} +library(BiocManager) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +When loaded, you will see an output showing the current Bioconductor and R versions. + +We can then use BiocManager's `install()` function to go back and install `PeacoQC()`. + +::: +::: + +:::{.callout-tip} + +As always, don't forget the "" when running an `install()` command. + +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +?install() +``` + +::: + +::: {.fragment} + +```{r} +install("PeacoQC") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +We see a similar opening sequence of installation steps as what we saw when installing the `dplyr` package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation. + +::: +::: + +::: {.fragment} +:::{.callout-note} + +Behind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process + +::: +::: + +--- + +![](images/12_PeacoQCDependencies.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Within the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with `dplyr`, with a "Done (packagename)" being printed upon successful installation. + +::: +::: + +--- + +![](images/13_rjson.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +This process continues for each dependency being installed. + +::: +::: + +--- + +![](images/13b_Other.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +And finally, once all the dependencies are installed, `PeacoQC` starts to install. + +::: +::: + +--- + +![](images/13c_PeacoQC.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Occasionally, during installation, you will see a pop-up windown like this one in the console. This let's you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n]. + +::: +::: + +--- + +![](images/14_UpdateAll.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Alternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter. + +::: +::: + +--- + +![](images/16_GitHubInstall.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Generally, it's okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn't cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option. + +::: +::: + +--- + +![](images/14_UpdateAll.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +With PeacoQC has been installed, we can load it via the `library()` call + +::: +::: + +:::{.callout-tip} + +Remeber, `library()` doesn't require " " + +::: + +::: {.fragment} + +```{r} +library(PeacoQC) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +And we can check to see if it has been attached to the local environment + +::: +::: + +::: {.fragment} + +```{r} +sessionInfo() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +As you may have noticed, the section of ***loaded via namespace (but not attached)*** packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment. + +::: +::: + +--- + +![](images/15_AdditionalDependencies.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To see what packages are installed (but not yet loaded), we can use the `installed.packages()` function to return a list of R packages for your computer. + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE + +installed.packages() +``` + +::: + +--- + +## Install from GitHub + +::: {.fragment} +::: {.callout-tip title="."} + +In addition to the [CRAN](https://cran.r-project.org/) and [Bioconductor](https://www.bioconductor.org/) repositories, individual R packages can also be found on [GitHub](https://github.com/trending/r) hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to [CRAN](https://r-pkgs.org/release.html) or [Bioconductor]((https://contributions.bioconductor.org/))) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all. + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +While many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to [deprecation](https://devguide.ropensci.org/maintenance_evolution.html) since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it's useful to check the [commits](https://github.com/carlosproca/autospill/commits/master/) and [issues](https://github.com/carlosproca/autospill/issues) pages to see when the last contribution occurred. We will take a closer look at how to do so [later on](/Schedule.qmd#the-art-of-github-diving). + +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To install packages from GitHub, you will need the `remotes` package, which can be found on CRAN. + +::: +::: + +::: {.fragment} +:::{.callout-tip title="Spot Check #1"} + +To install a package from CRAN, what function would you use? +Click on the code-fold arrow below to reveal the answer. + +::: +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +install.packages("remotes") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +With the `remotes` package now installed, we can attach it to our local environment. + +::: +::: + +::: {.fragment} +:::{.callout-tip title="Spot Check #2"} + +What function would be used to do so? + +::: +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +library(remotes) +``` + +::: + + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +And finally, we can use the `install_github()` function to download R packages from the invidual developers GitHub account. + +::: +::: + +::: {.fragment} +:::{.callout-tip title="Spot Check #3"} + +How would you look up the help documentation for this function? + +::: +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Either by hovering over it within Positron or via + +?install_github() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +We will be installing a small R package [flowSpectrum](https://github.com/hally166/flowSpectrum) for this example. It's one of the packages created by [Christopher Hall](https://github.com/hally166), whose small series of [Flow Cytometry Data Analysis in R](https://youtu.be/2INqQNMNaV0?si=dZ_rJ1S26KnNbUmU) tutorials were immensely useful when I was first getting started learning R. `flowSpectrum` can be used to generate spectrum-style plots for spectral flow cytometry data. + +::: +::: + +--- + +![](images/PE_Spectrum.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +To install an R package from GitHub, we first need the GitHub username (so [hally166](https://github.com/hally166) in this case), which is followed by a "/", and then the name of the package repository (so [flowSpectrum](https://github.com/hally166/flowSpectrum) in this case). Our code should consequently be + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE + +install_github("hally166/flowSpectrum") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +When installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding. + +This process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating [R packages](/Schedule.qmd#building-your-first-r-package). + +::: +::: + +--- + +![](images/17_InstallSource.png) + +--- + +## Troubleshooting Install Errors + +::: {.fragment} +::: {.callout-tip title="."} + +We have now installed three R packages, `dplyr`, `PeacoQC`, and `flowSpectrum`. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies. + +When encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below. + +::: +::: + +--- + +![](images/18_ErrorExample.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +If you encounter an installation error this week, please take screenshots of the error message and post them to this [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future. + +::: +::: + +--- + + +## Documentation and Websites + +::: {.fragment} +::: {.callout-tip title="."} + +We have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package. + +For CRAN-based packages, we can start off by searching for the package name. So, in the case of `dplyr` + +::: +::: + +--- + +![](images/19_DplyrGoogle.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Two main suggestions pop up. One is the package's [CRAN](https://cran.r-project.org/web/packages/dplyr/index.html) page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible. + +::: +::: + +--- + +![](images/20_DplyrCRAN.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Because of this, many CRAN-based R packages (especially those part of the tidyverse) use [pkgdown](https://pkgdown.r-lib.org/)-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr's pkgdown-style [website](https://dplyr.tidyverse.org/) + +::: +::: + +--- + +![](images/21_DplyrPkgdown.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +We can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab. + +::: +::: + +--- + +![](images/22_PkgdownArticles.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +GitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository's ReadMe. + +::: +::: + +--- + +![](images/23_GitHub.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +For Bioconductor-based packages, on the package's page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with [PeacoQC](https://www.bioconductor.org/packages/release/bioc/vignettes/PeacoQC/inst/doc/PeacoQC_Vignette.pdf): + +::: +::: + +--- + +![](images/24_PeacoQCBioc.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Additionally, package vignettes can also be reached via the packages help index page. These will usually appear under ***User guides, package vignettes, and other documentation***. + +::: +::: + +--- + +![](images/25_Vignettes.png) + +--- + + +# Your Turn + +::: {.fragment} +::: {.callout-tip title="."} + +Alright, we have now gone through the process of installing an R package from [CRAN](/course/01_InstallingRPackages/index.qmd#installing-from-cran), [Bioconductor](/course/01_InstallingRPackages/index.qmd#installing-from-bioconductor), and [GitHub](/course/01_InstallingRPackages/index.qmd#install-from-github). We will now install 20 other R packages we will need throughout the rest of the course. + +::: +::: + +:::{.callout-note} + +To make this interactive, [**I will task you**]{.underscore} to apply the previous concepts to figure out whether the packages need to be installed via CRAN, Bioconductor or GitHub. + +::: + +:::{.callout-important} + +Feel free to view the [website](https://umgcccfcsr.github.io/CytometryInR/course/) version to avoid accidental spoilers from the copied over index.qmd file. Alternatively, you can attempt to switch from the Source view to Visual Mode by right clicking with your mouse and selecting that option. + +::: + +:::{.callout-tip} + +Start by searching each packages name. See if you can spot first either a CRAN or a Bioconductor website. Then enter the respective installation command (`install.packages()`, `install()`, `install_github()`) for the appropiate repository, add the package name, and run the code to see if the installation proceeds. + +For cases where you are truly stuck, expand the code-fold below each package name to see the answer. + +::: + +:::{.callout-note} + +Some of these packages may be dependencies of each other and may wind up installed before you get to them. If that is the case, no need to reinstall, count it as a win, and proceed to the next R package. + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Remember,if you encountered any installation errors in the process, please take screenshots and post them on the the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10) to help with improved documentation. + +::: +::: + +--- + +:::{.callout-tip title="1/20"} + +R package: purrr + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://purrr.tidyverse.org/ + +install.packages("purrr") +``` + +::: + +--- + +:::{.callout-tip title="2/20"} + +R package: flowCore + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/flowCore.html + +install("flowCore") +``` + +::: + +--- + +:::{.callout-tip title="3/20"} + +R package: flowWorkspace + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/flowWorkspace.html + +install("flowWorkspace") +``` + +::: + +--- + +:::{.callout-tip title="4/20"} + +R package: stringr + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://stringr.tidyverse.org/ + +install.packages("stringr") +``` + +::: + +--- + +:::{.callout-tip title="5/20"} + +R package: ggplot2 + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://ggplot2.tidyverse.org/ + +install.packages("ggplot2") +``` + +::: + +--- + + +:::{.callout-tip title="6/20"} + +R package: ggcyto + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/ggcyto.html + +install.packages("ggcyto") +``` + +::: + +--- + +:::{.callout-tip title="7/20"} + +R package: tidyr + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://tidyr.tidyverse.org/ + +install.packages("tidyr") +``` + +::: + +--- + +:::{.callout-tip title="8/20"} + +R package: openCyto + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/openCyto.html + +install.packages("openCyto") +``` + +::: + +--- + +:::{.callout-tip title="9/20"} + +R package: FlowSOM + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/FlowSOM.html + +install.packages("FlowSOM") +``` + +::: + +--- + +:::{.callout-tip title="10/20"} + +R package: xml2 + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: CRAN +# Website: https://xml2.r-lib.org/ + +install.packages("xml2") +``` + +::: + +--- + + +:::{.callout-tip title="11/20"} + +R package: saeyslab/CytoNorm + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + + +# Location: GitHub +# Website: https://github.com/saeyslab/CytoNorm + +install_github("saeyslab/CytoNorm") +``` + +::: + +--- + +:::{.callout-tip title="12/20"} + +R package: lubridate + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://lubridate.tidyverse.org/ + +install.packages("lubridate") +``` + +::: + +--- + +:::{.callout-tip title="13/20"} + +R package: httr2 + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://httr2.r-lib.org/ + +install.packages("httr2") +``` + +::: + +--- + +:::{.callout-tip title="14/20"} + +R package: flowGate + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/flowGate.html + +install("flowGate") +``` + +::: + +--- + +:::{.callout-tip title="15/20"} + +R package: devtools + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://devtools.r-lib.org/ + +install.packages("devtools") +``` + +::: + +--- + +:::{.callout-tip title="16/20"} + +R package: plotly + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://plotly.com/r/getting-started/ + +install.packages("plotly") +``` + +::: + +--- + +:::{.callout-tip title="17/20"} + +R package: biosurf/cyCombine + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: GitHub +# Website: https://github.com/biosurf/cyCombine + +install_github("biosurf/cyCombine") +``` + +::: + +--- + +:::{.callout-tip title="18/20"} + +R package: CytoML + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: Bioconductor +# Website: https://www.bioconductor.org/packages/release/bioc/html/CytoML.html + +install("CytoML") +``` + +::: + +--- + +:::{.callout-tip title="19/20"} + +R package: Rtsne + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website: https://github.com/jkrijthe/Rtsne + +install.packages("Rtsne") +``` + +::: + +--- + +:::{.callout-tip title="20/20"} + +R package: uwot + +::: + +::: {.fragment} + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Location: CRAN +# Website:https://jlmelville.github.io/uwot/ + +install.packages("uwot") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +**Congratulations!** You have (hopefully) survived the package installation onslaught that is Week #1 of the course. + +::: +::: + +--- + +![](images/Entertained.jpg) + +--- + +::: {.fragment} +::: {.callout-tip title="."} + +Remember to submit any encountered installation error screenshots to the [Discussion page](https://github.com/UMGCCCFCSR/CytometryInR/discussions/10). + +::: +::: + +--- + +# Wrap-Up + +::: {.fragment} +::: {.callout-tip title="."} + +In this session, we walked through what are R packages, where to find them, how to install them, and a bit about troubleshooting any installation errors you may encounter during the process. + +You then proceeded to install most of the R packages that you would need throughout the [Cytometry in R course](/Schedule.qmd). These included tidyverse packages from the [CRAN] repository used for working with data structures and plots, as well as more cytometry focused R packages from [Bioconductor] repository. + +If you have any questions, or want to discuss this week's topics in more depth with the other course participants, please head over to the [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page and open a new topic. + +Next week, we will start learning about [file paths](/Schedule.qmd#file-paths), by which we will be able to tell our computer where to find your fcs files, how to retrieve the file names, subset those that may be of particular interest, and copy them over to a new folder. In the processs, we will learn a little more about how variables, objects, and list work within R. + +Until then, Best Wishes! + +- David + +::: +::: + +--- + +![](/course/01_InstallingRPackages/images/ExitImage.png) + +--- + +# Additional Resources + +::: {.fragment} +::: {.callout-tip title="."} + +[Tidy Tales](https://tidytales.ca/series/2023-01-24_reproducible-data-science/posts/r-packages.html) An usefu beginner-friendly blogpost covering additional aspects from a different perspective. + +[Introduction to Bioconductor](https://youtu.be/dg6NvmMVQ3I?si=WfsqpO3Z-M2oG8zh) A talk by Martin Morgan with more information about the Bioconductor project. + +[R Packages](https://r-pkgs.org/) A book by Hadley Wickham and Jennifer Bryan, covering all the different internals of R packages. + +::: +::: + +--- + + +# Take-home Problems + +::: {.fragment} +::: {.callout-tip title="."} + +Below you will find the optional take-home problems for Week #1. Learning how to code well requires continous practice, and that involves cycles of trying something, failing, and troubleshooting to get it working. The goal of these problems is to help you explore the topic in greater depth than the currated boundaries of this one lecture. + +You are more than welcome to open a [Discussion](https://github.com/UMGCCCFCSR/CytometryInR/discussions) to engage with others in the course to discuss these questions. Once you are done tinkering, and want to get final instructor feedback on your work, place your files within a folder, and follow the instructions to submit it as a [Pull Request](/course/00_Homeworks/index.qmd#submitting-take-home-problems) to the Cytometry In R repositories homework branch. + +::: +::: + +--- + +:::{.callout-tip title="Problem 1"} + +We installed PeacoQC during this session, but we didn't have time to explore what functions are present within the package. Using what you have learned about accessing documentation, figure out and list what functions it contains + +::: + +--- + +:::{.callout-tip title="Problem 2"} + +Take a closer look at the list of Bioconductor [cytometry](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) packages. Report back on how many there are currently in Bioconductor, the author/maintainer with the most contributed cytometry R packages, and a couple packages that you would be interested in exploring more in-depth later in the course. + +::: + +--- + +:::{.callout-tip title="Problem 3"} + +There is another way to install R packages, using the newer [pak](https://pak.r-lib.org/) package. Positron uses this when installing suggested dependencies. + +After learning more about it via the documentation and it's pkgdown website, I would like you to attempt to install the following three R packages using this newer method: "broom", "cytoMEM", "DillonHammill/CytoExploreR". + +Take screenshots, and in a new [quarto markdown document](/course/00_Quarto/index.qmd), describe how the installation process differed from what you saw for `install.packages()`, `install()` and `install_github()`. + +::: + +--- + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + diff --git a/course/02_FilePaths/Downsampler.qmd b/course/02_FilePaths/Downsampler.qmd index d879635..c6647df 100644 --- a/course/02_FilePaths/Downsampler.qmd +++ b/course/02_FilePaths/Downsampler.qmd @@ -1,81 +1,81 @@ ---- -title: "Downsampling" -author: "David Rach" - -format: html ---- - -# Background - -Due to trying to keep the overall file size down, I am downsampling to 100 events. For anyone interested in how I did this, this Quarto Markdown Document contains the code needed to repeat the process. - -# Getting Started - -Attach the required packages via the `library()` function - -```{r} -#| eval: FALSE -library(purrr) # CRAN -library(flowWorkspace) # Bioconductor -library(Luciernaga) #DavidRach/Luciernaga -``` - -## Specify file.path and identify files - -Due to the counts being conducter on two separate instruments, the number of columns differs, so they will need to be loaded into separate GatingSet objects. - -```{r} -#| eval: FALSE -StorageLocation <- file.path("course", "02_FilePaths", "data") -Existing <- list.files(StorageLocation, pattern=".fcs", full.names=TRUE) -List1 <- Existing[1:2] # 3L Aurora -List2 <- Existing[3:8] # 4L Aurora -``` - -## Load .fcs files into a GatingSet - -Load in files to their respective GatingSet objects - -```{r} -#| eval: FALSE -cs1 <- load_cytoset_from_fcs(List1, truncate_max_range = FALSE, transformation = FALSE) -gs1 <- GatingSet(cs1) - -cs2 <- load_cytoset_from_fcs(List2, truncate_max_range = FALSE, transformation = FALSE) -gs2 <- GatingSet(cs2) -``` - -# Downsample each sample and pass back to the folder - -From here, each file in the Gating set is passed to `Utility_Downsample()`, subsampling for 100 events. In this case, subsets argument is set to "root", so all events. If we had implemented gates, we could have selected a particular population from which to downsample. - -```{r} -#| eval: FALSE -walk(.x=gs1, .f=Luciernaga::Utility_Downsample, - sample.name=c("$PROJ", "GROUPNAME", "TUBENAME"), - export=TRUE, outpath=StorageLocation, - subsample=100, subsets="root", inverse.transform=FALSE) - -walk(.x=gs2, .f=Luciernaga::Utility_Downsample, - sample.name=c("$PROJ", "GROUPNAME", "TUBENAME"), - export=TRUE, outpath=StorageLocation, - subsample=100, subsets="root", inverse.transform=FALSE) -``` - -# Conclusion - -In the end, we went from having files that were the following size - -![](images/OG_Size.png) - -To ones that were like this: - -![](images/Downsampled.png) - -We will look more at how the Utility_Downsample is constructed during [Week #10](/Schedule.qmd#downsampling-and-concatenation) - -```{r} -#| eval: FALSE -sessionInfo() -``` - +--- +title: "Downsampling" +author: "David Rach" + +format: html +--- + +# Background + +Due to trying to keep the overall file size down, I am downsampling to 100 events. For anyone interested in how I did this, this Quarto Markdown Document contains the code needed to repeat the process. + +# Getting Started + +Attach the required packages via the `library()` function + +```{r} +#| eval: FALSE +library(purrr) # CRAN +library(flowWorkspace) # Bioconductor +library(Luciernaga) #DavidRach/Luciernaga +``` + +## Specify file.path and identify files + +Due to the counts being conducter on two separate instruments, the number of columns differs, so they will need to be loaded into separate GatingSet objects. + +```{r} +#| eval: FALSE +StorageLocation <- file.path("course", "02_FilePaths", "data") +Existing <- list.files(StorageLocation, pattern=".fcs", full.names=TRUE) +List1 <- Existing[1:2] # 3L Aurora +List2 <- Existing[3:8] # 4L Aurora +``` + +## Load .fcs files into a GatingSet + +Load in files to their respective GatingSet objects + +```{r} +#| eval: FALSE +cs1 <- load_cytoset_from_fcs(List1, truncate_max_range = FALSE, transformation = FALSE) +gs1 <- GatingSet(cs1) + +cs2 <- load_cytoset_from_fcs(List2, truncate_max_range = FALSE, transformation = FALSE) +gs2 <- GatingSet(cs2) +``` + +# Downsample each sample and pass back to the folder + +From here, each file in the Gating set is passed to `Utility_Downsample()`, subsampling for 100 events. In this case, subsets argument is set to "root", so all events. If we had implemented gates, we could have selected a particular population from which to downsample. + +```{r} +#| eval: FALSE +walk(.x=gs1, .f=Luciernaga::Utility_Downsample, + sample.name=c("$PROJ", "GROUPNAME", "TUBENAME"), + export=TRUE, outpath=StorageLocation, + subsample=100, subsets="root", inverse.transform=FALSE) + +walk(.x=gs2, .f=Luciernaga::Utility_Downsample, + sample.name=c("$PROJ", "GROUPNAME", "TUBENAME"), + export=TRUE, outpath=StorageLocation, + subsample=100, subsets="root", inverse.transform=FALSE) +``` + +# Conclusion + +In the end, we went from having files that were the following size + +![](images/OG_Size.png) + +To ones that were like this: + +![](images/Downsampled.png) + +We will look more at how the Utility_Downsample is constructed during [Week #10](/Schedule.qmd#downsampling-and-concatenation) + +```{r} +#| eval: FALSE +sessionInfo() +``` + diff --git a/course/02_FilePaths/homeworks/README.md b/course/02_FilePaths/homeworks/README.md index 2818b5e..fe53443 100644 --- a/course/02_FilePaths/homeworks/README.md +++ b/course/02_FilePaths/homeworks/README.md @@ -1,5 +1,5 @@ -# Turning In Optional Take-Home Problems - -This folder is for the use of submitting your completed Take-Home Problems for evaluation by course instructors. Please see [Getting Help](/course/00_Homeworks/index.qmd) walkthrough for more detailed instructions. - +# Turning In Optional Take-Home Problems + +This folder is for the use of submitting your completed Take-Home Problems for evaluation by course instructors. Please see [Getting Help](/course/00_Homeworks/index.qmd) walkthrough for more detailed instructions. + Within your branch, inside this "homeworks" folder, create a new folder (name it with your GitHub username). Then copy all files you will be submitting within your folder. Then commit the change to git, and push to GitHub. See [Getting Help](/course/00_Homeworks/index.qmd)for details on submitting the pull request to the UMGCCCFCSR/CytometryInR homework branch. \ No newline at end of file diff --git a/course/02_FilePaths/homeworks/claude-chew/LICENSE b/course/02_FilePaths/homeworks/claude-chew/LICENSE new file mode 100644 index 0000000..ada1a81 --- /dev/null +++ b/course/02_FilePaths/homeworks/claude-chew/LICENSE @@ -0,0 +1,661 @@ + GNU AFFERO GENERAL PUBLIC LICENSE + Version 3, 19 November 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU Affero General Public License is a free, copyleft license for +software and other kinds of works, specifically designed to ensure +cooperation with the community in the case of network server software. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If your software can interact with users remotely through a computer +network, you should also make sure that it provides a way for users to +get its source. For example, if your program is a web application, its +interface could display a "Source" link that leads users to an archive +of the code. There are many ways you could offer source, and different +solutions will be better for different programs; see section 13 for the +specific requirements. + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU AGPL, see +. diff --git a/course/02_FilePaths/homeworks/claude-chew/Problem1.png b/course/02_FilePaths/homeworks/claude-chew/Problem1.png new file mode 100644 index 0000000..e69de29 diff --git a/course/02_FilePaths/homeworks/claude-chew/README.md b/course/02_FilePaths/homeworks/claude-chew/README.md new file mode 100644 index 0000000..20d6f8e --- /dev/null +++ b/course/02_FilePaths/homeworks/claude-chew/README.md @@ -0,0 +1,2 @@ +# Week2 +Workflow and Version Control Example diff --git a/course/02_FilePaths/homeworks/claude-chew/Week2Homework.html b/course/02_FilePaths/homeworks/claude-chew/Week2Homework.html new file mode 100644 index 0000000..5f9c584 --- /dev/null +++ b/course/02_FilePaths/homeworks/claude-chew/Week2Homework.html @@ -0,0 +1,610 @@ + + + + + + + + + +week2homework + + + + + + + + + + + + + + + + + + + + + +
+ +
+ + + + +
+

Problem 1

+

Plug in an external hard-drive or USB into your computer. Manually, create a folder within called “TargetFolder”. Try to programmatically specify the file path to identify the folders and files present on your external drive. Then, try to copy your .fcs files from their current folder on your desktop to the TargetFolder on your drive using R. Remember, just copy, no deletion, you need to walk before you can run :D

+
+
FCSTargetFolder <- "F:/TargetFolder"
+FCS <- list.files("C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data", pattern=".fcs$", full.names=TRUE, recursive = FALSE)
+library(stringr)
+str_detect(FCS, "fcs")
+
+
[1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
+
+
FCS[str_detect(FCS,"fcs")]
+
+
[1] "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data/CellCounts3L_AB_02_INF052_00.fcs"     
+[2] "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data/CellCounts3L_AB_02_ND050_02.fcs"      
+[3] "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data/CellCounts4L_AB_03_INF134_00.fcs"     
+[4] "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data/CellCounts4L_AB_03_NY068_03.fcs"      
+[5] "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data/CellCounts4L_AB_04_INF124-7_00_01.fcs"
+[6] "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data/CellCounts4L_AB_04_ND006_04.fcs"      
+[7] "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data/CellCounts4L_AB_05_INF019-0_00_01.fcs"
+[8] "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data/CellCounts4L_AB_05_ND050_05.fcs"
+
+
FCSFiles <- FCS[str_detect(FCS, "fcs")]
+file.copy(from=FCSFiles, to="F:/TargetFolder/")
+
+
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
+
+
+
+
+

+
Problem1 screenshot
+
+
+
+
+

Problem 2

+

In this session, we used list.files() with the “full.names argument” set to TRUE, as well as the basename() function to identify specific files. But what if you wanted a particular directory. Run list.files() with “full.names argument” and “recursive” argument set to TRUE, and then search online to find an R function that would retrieve the “” individual directory folders.

+

Clarification from email: Hi @claude-chew and @jttoivon, sorry for the unclear question! What I would be looking for would a function that would be able to isolate lets say either data or Cytometry in R from the following file path:

+

C:/Users/JohnDoe/Documents/CytometryInR/course/02_FilePaths/datra/target3

+
+
list.files(path="data", full.names=TRUE, recursive=TRUE)
+
+
 [1] "data/CellCounts3L_AB_02_INF052_00.fcs"             
+ [2] "data/CellCounts3L_AB_02_ND050_02.fcs"              
+ [3] "data/CellCounts4L_AB_03_INF134_00.fcs"             
+ [4] "data/CellCounts4L_AB_03_NY068_03.fcs"              
+ [5] "data/CellCounts4L_AB_04_INF124-7_00_01.fcs"        
+ [6] "data/CellCounts4L_AB_04_ND006_04.fcs"              
+ [7] "data/CellCounts4L_AB_05_INF019-0_00_01.fcs"        
+ [8] "data/CellCounts4L_AB_05_ND050_05.fcs"              
+ [9] "data/target/CellCounts3L_AB_02_INF052_00.fcs"      
+[10] "data/target/CellCounts3L_AB_02_ND050_02.fcs"       
+[11] "data/target2/CellCounts3L_AB_02_INF052_00.fcs"     
+[12] "data/target2/CellCounts3L_AB_02_ND050_02.fcs"      
+[13] "data/target3/CellCounts3L_AB_02_INF052_00.fcs"     
+[14] "data/target3/CellCounts4L_AB_03_INF134_00.fcs"     
+[15] "data/target3/CellCounts4L_AB_04_INF124-7_00_01.fcs"
+[16] "data/target3/CellCounts4L_AB_05_INF019-0_00_01.fcs"
+
+
path <- "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data/target3"
+path1 <- "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/"
+basename(path)
+
+
[1] "target3"
+
+
dirname(path)
+
+
[1] "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data"
+
+
basename(path1)
+
+
[1] "Week2"
+
+
dirname(path1)
+
+
[1] "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents"
+
+
+
+
+

+
Problem2 screenshot
+
+
+
+
+

Problem 3

+

R packages often come with internal datasets, that are typically used for use in the help documentation examples. These can be accessed through the use of the system.file() function. See an example below.

+

system.file(“extdata”, package = “FlowSOM”)

+

Using what we have learned about file.path navigation, search your way down the file.directory of the FlowSOM and flowWorkspace packages, and identify any .fcs files that are present for use in the documentation.

+
+
system.file("extdata", package = "FlowSOM")
+
+
[1] "C:/Users/claud/AppData/Local/R/win-library/4.5/FlowSOM/extdata"
+
+
system.file("extdata", package = "flowWorkspace")
+
+
[1] "C:/Users/claud/AppData/Local/R/win-library/4.5/flowWorkspace/extdata"
+
+
list.files(path="C:/Users/claud/AppData/Local/R/win-library/4.5/FlowSOM/extdata", pattern=".fcs", full.names=TRUE, recursive=FALSE)
+
+
[1] "C:/Users/claud/AppData/Local/R/win-library/4.5/FlowSOM/extdata/68983.fcs"
+
+
list.files(path="C:/Users/claud/AppData/Local/R/win-library/4.5/flowWorkspace/extdata", pattern=".fcs", full.names=TRUE, recursive=FALSE)
+
+
character(0)
+
+
+
+
+

+
Problem3 screenshot
+
+
+
+ +
+ + +
+ + + + + \ No newline at end of file diff --git a/course/02_FilePaths/homeworks/claude-chew/Week2Homework.qmd b/course/02_FilePaths/homeworks/claude-chew/Week2Homework.qmd new file mode 100644 index 0000000..a38316e --- /dev/null +++ b/course/02_FilePaths/homeworks/claude-chew/Week2Homework.qmd @@ -0,0 +1,56 @@ + + +# Problem 1 +Plug in an external hard-drive or USB into your computer. Manually, create a folder within called “TargetFolder”. Try to programmatically specify the file path to identify the folders and files present on your external drive. Then, try to copy your .fcs files from their current folder on your desktop to the TargetFolder on your drive using R. Remember, just copy, no deletion, you need to walk before you can run :D + +```{r} +FCSTargetFolder <- "F:/TargetFolder" +FCS <- list.files("C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data", pattern=".fcs$", full.names=TRUE, recursive = FALSE) +library(stringr) +str_detect(FCS, "fcs") +FCS[str_detect(FCS,"fcs")] +FCSFiles <- FCS[str_detect(FCS, "fcs")] +file.copy(from=FCSFiles, to="F:/TargetFolder/") +``` + +![Problem1 screenshot](images/Problem1.png) + +# Problem 2 +In this session, we used list.files() with the “full.names argument” set to TRUE, as well as the basename() function to identify specific files. But what if you wanted a particular directory. Run list.files() with “full.names argument” and “recursive” argument set to TRUE, and then search online to find an R function that would retrieve the “” individual directory folders. + +Clarification from email: +Hi @claude-chew and @jttoivon, sorry for the unclear question! What I would be looking for would a function that would be able to isolate lets say either data or Cytometry in R from the following file path: + +C:/Users/JohnDoe/Documents/CytometryInR/course/02_FilePaths/datra/target3 + +```{r} +list.files(path="data", full.names=TRUE, recursive=TRUE) + +path <- "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/data/target3" +path1 <- "C:/Users/claud/OneDrive - Baylor College of Medicine/Documents/Week2/" +basename(path) +dirname(path) +basename(path1) +dirname(path1) + +``` + +![Problem2 screenshot](images/Problem2.png) + +# Problem 3 +R packages often come with internal datasets, that are typically used for use in the help documentation examples. These can be accessed through the use of the system.file() function. See an example below. + +system.file("extdata", package = "FlowSOM") + +Using what we have learned about file.path navigation, search your way down the file.directory of the FlowSOM and flowWorkspace packages, and identify any .fcs files that are present for use in the documentation. + + +```{r} +system.file("extdata", package = "FlowSOM") +system.file("extdata", package = "flowWorkspace") + +list.files(path="C:/Users/claud/AppData/Local/R/win-library/4.5/FlowSOM/extdata", pattern=".fcs", full.names=TRUE, recursive=FALSE) +list.files(path="C:/Users/claud/AppData/Local/R/win-library/4.5/flowWorkspace/extdata", pattern=".fcs", full.names=TRUE, recursive=FALSE) +``` + +![Problem3 screenshot](images/Problem3.png) \ No newline at end of file diff --git a/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/bootstrap/bootstrap-9e3ffae467580fdb927a41352e75a2e0.min.css 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1rem;--bs-nav-link-padding-y: 0.5rem;--bs-nav-link-font-weight: ;--bs-nav-link-color: #0d6efd;--bs-nav-link-hover-color: rgb(10.4, 88, 202.4);--bs-nav-link-disabled-color: rgba(33, 37, 41, 0.75);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding-left:0;margin-bottom:0;list-style:none}.nav-link{display:block;padding:var(--bs-nav-link-padding-y) var(--bs-nav-link-padding-x);font-size:var(--bs-nav-link-font-size);font-weight:var(--bs-nav-link-font-weight);color:var(--bs-nav-link-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background:none;border:0;transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out}@media(prefers-reduced-motion: reduce){.nav-link{transition:none}}.nav-link:hover,.nav-link:focus{color:var(--bs-nav-link-hover-color)}.nav-link:focus-visible{outline:0;box-shadow:0 0 0 .25rem 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0);--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgb%28253.26, 253.63, 253.98%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}[data-bs-theme=dark] .navbar-toggler-icon{--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgb%28253.26, 253.63, 253.98%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}.card{--bs-card-spacer-y: 1rem;--bs-card-spacer-x: 1rem;--bs-card-title-spacer-y: 0.5rem;--bs-card-title-color: ;--bs-card-subtitle-color: ;--bs-card-border-width: 1px;--bs-card-border-color: rgba(0, 0, 0, 0.175);--bs-card-border-radius: 0.375rem;--bs-card-box-shadow: ;--bs-card-inner-border-radius: calc(0.375rem - 1px);--bs-card-cap-padding-y: 0.5rem;--bs-card-cap-padding-x: 1rem;--bs-card-cap-bg: 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var(--bs-card-spacer-x);color:var(--bs-card-color)}.card-title{margin-bottom:var(--bs-card-title-spacer-y);color:var(--bs-card-title-color)}.card-subtitle{margin-top:calc(-0.5*var(--bs-card-title-spacer-y));margin-bottom:0;color:var(--bs-card-subtitle-color)}.card-text:last-child{margin-bottom:0}.card-link+.card-link{margin-left:var(--bs-card-spacer-x)}.card-header{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);margin-bottom:0;color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-bottom:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-header:first-child{border-radius:var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius) 0 0}.card-footer{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-top:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-footer:last-child{border-radius:0 0 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.nav-link.active{background-color:var(--bs-card-bg);border-bottom-color:var(--bs-card-bg)}.card-header-pills{margin-right:calc(-0.5*var(--bs-card-cap-padding-x));margin-left:calc(-0.5*var(--bs-card-cap-padding-x))}.card-img-overlay{position:absolute;top:0;right:0;bottom:0;left:0;padding:var(--bs-card-img-overlay-padding);border-radius:var(--bs-card-inner-border-radius)}.card-img,.card-img-top,.card-img-bottom{width:100%}.card-img,.card-img-top{border-top-left-radius:var(--bs-card-inner-border-radius);border-top-right-radius:var(--bs-card-inner-border-radius)}.card-img,.card-img-bottom{border-bottom-right-radius:var(--bs-card-inner-border-radius);border-bottom-left-radius:var(--bs-card-inner-border-radius)}.card-group>.card{margin-bottom:var(--bs-card-group-margin)}@media(min-width: 576px){.card-group{display:flex;display:-webkit-flex;flex-flow:row wrap;-webkit-flex-flow:row wrap}.card-group>.card{flex:1 0 0%;-webkit-flex:1 0 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ease;--bs-accordion-border-color: rgb(221.7, 222.3, 222.9);--bs-accordion-border-width: 1px;--bs-accordion-border-radius: 0.375rem;--bs-accordion-inner-border-radius: calc(0.375rem - 1px);--bs-accordion-btn-padding-x: 1.25rem;--bs-accordion-btn-padding-y: 1rem;--bs-accordion-btn-color: #212529;--bs-accordion-btn-bg: #ffffff;--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23212529'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-icon-width: 1.25rem;--bs-accordion-btn-icon-transform: rotate(-180deg);--bs-accordion-btn-icon-transition: transform 0.2s ease-in-out;--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%285.2, 44, 101.2%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-focus-border-color: rgb(134, 182.5, 254);--bs-accordion-btn-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: rgb(5.2, 44, 101.2);--bs-accordion-active-bg: rgb(206.6, 226, 254.6)}.accordion-button{position:relative;display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;border-radius:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media(prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1*var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media(prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:first-of-type{border-top-left-radius:var(--bs-accordion-border-radius);border-top-right-radius:var(--bs-accordion-border-radius)}.accordion-item:first-of-type .accordion-button{border-top-left-radius:var(--bs-accordion-inner-border-radius);border-top-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:not(:first-of-type){border-top:0}.accordion-item:last-of-type{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-item:last-of-type .accordion-button.collapsed{border-bottom-right-radius:var(--bs-accordion-inner-border-radius);border-bottom-left-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0;border-radius:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme=dark] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%28109.8, 168, 253.8%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%28109.8, 168, 253.8%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: 0;--bs-breadcrumb-padding-y: 0;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color: rgba(33, 37, 41, 0.75);--bs-breadcrumb-item-padding-x: 0.5rem;--bs-breadcrumb-item-active-color: rgba(33, 37, 41, 0.75);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg);border-radius:var(--bs-breadcrumb-border-radius)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, ">") /* rtl: var(--bs-breadcrumb-divider, ">") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: 0.75rem;--bs-pagination-padding-y: 0.375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: #0d6efd;--bs-pagination-bg: #ffffff;--bs-pagination-border-width: 1px;--bs-pagination-border-color: rgb(221.7, 222.3, 222.9);--bs-pagination-border-radius: 0.375rem;--bs-pagination-hover-color: rgb(10.4, 88, 202.4);--bs-pagination-hover-bg: #f8f9fa;--bs-pagination-hover-border-color: rgb(221.7, 222.3, 222.9);--bs-pagination-focus-color: rgb(10.4, 88, 202.4);--bs-pagination-focus-bg: #e9ecef;--bs-pagination-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-pagination-active-color: #ffffff;--bs-pagination-active-bg: #0d6efd;--bs-pagination-active-border-color: #0d6efd;--bs-pagination-disabled-color: rgba(33, 37, 41, 0.75);--bs-pagination-disabled-bg: #e9ecef;--bs-pagination-disabled-border-color: rgb(221.7, 222.3, 222.9);display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out}@media(prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(1px*-1)}.page-item:first-child .page-link{border-top-left-radius:var(--bs-pagination-border-radius);border-bottom-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-top-right-radius:var(--bs-pagination-border-radius);border-bottom-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: 0.75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: 0.5rem}.pagination-sm{--bs-pagination-padding-x: 0.5rem;--bs-pagination-padding-y: 0.25rem;--bs-pagination-font-size:0.875rem;--bs-pagination-border-radius: 0.25rem}.badge{--bs-badge-padding-x: 0.65em;--bs-badge-padding-y: 0.35em;--bs-badge-font-size:0.75em;--bs-badge-font-weight: 700;--bs-badge-color: #ffffff;--bs-badge-border-radius: 0.375rem;display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:var(--bs-badge-border-radius)}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: 1px solid var(--bs-alert-border-color);--bs-alert-border-radius: 0.375rem;--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height: 1rem;--bs-progress-font-size:0.75rem;--bs-progress-bg: #e9ecef;--bs-progress-border-radius: 0.375rem;--bs-progress-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.075);--bs-progress-bar-color: #ffffff;--bs-progress-bar-bg: #0d6efd;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media(prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media(prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: #212529;--bs-list-group-bg: #ffffff;--bs-list-group-border-color: rgb(221.7, 222.3, 222.9);--bs-list-group-border-width: 1px;--bs-list-group-border-radius: 0.375rem;--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: 0.5rem;--bs-list-group-action-color: rgba(33, 37, 41, 0.75);--bs-list-group-action-hover-color: #000;--bs-list-group-action-hover-bg: #f8f9fa;--bs-list-group-action-active-color: #212529;--bs-list-group-action-active-bg: #e9ecef;--bs-list-group-disabled-color: rgba(33, 37, 41, 0.75);--bs-list-group-disabled-bg: #ffffff;--bs-list-group-active-color: #ffffff;--bs-list-group-active-bg: #0d6efd;--bs-list-group-active-border-color: #0d6efd;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;border-radius:var(--bs-list-group-border-radius)}.list-group-numbered{list-style-type:none;counter-reset:section}.list-group-numbered>.list-group-item::before{content:counters(section, ".") ". ";counter-increment:section}.list-group-item-action{width:100%;color:var(--bs-list-group-action-color);text-align:inherit}.list-group-item-action:hover,.list-group-item-action:focus{z-index:1;color:var(--bs-list-group-action-hover-color);text-decoration:none;background-color:var(--bs-list-group-action-hover-bg)}.list-group-item-action:active{color:var(--bs-list-group-action-active-color);background-color:var(--bs-list-group-action-active-bg)}.list-group-item{position:relative;display:block;padding:var(--bs-list-group-item-padding-y) var(--bs-list-group-item-padding-x);color:var(--bs-list-group-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-list-group-bg);border:var(--bs-list-group-border-width) solid 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576px){.list-group-horizontal-sm{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-sm>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-sm>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-sm>.list-group-item.active{margin-top:0}.list-group-horizontal-sm>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-sm>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 768px){.list-group-horizontal-md{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-md>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-md>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-md>.list-group-item.active{margin-top:0}.list-group-horizontal-md>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-md>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 992px){.list-group-horizontal-lg{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-lg>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-lg>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1200px){.list-group-horizontal-xl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1400px){.list-group-horizontal-xxl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xxl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xxl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xxl>.list-group-item.active{margin-top:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}.list-group-flush{border-radius:0}.list-group-flush>.list-group-item{border-width:0 0 var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-default{--bs-list-group-color: var(--bs-default-text-emphasis);--bs-list-group-bg: var(--bs-default-bg-subtle);--bs-list-group-border-color: var(--bs-default-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-default-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-default-border-subtle);--bs-list-group-active-color: var(--bs-default-bg-subtle);--bs-list-group-active-bg: var(--bs-default-text-emphasis);--bs-list-group-active-border-color: var(--bs-default-text-emphasis)}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' 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0.375rem;--bs-toast-box-shadow: 0 0.5rem 1rem rgba(0, 0, 0, 0.15);--bs-toast-header-color: rgba(33, 37, 41, 0.75);--bs-toast-header-bg: rgba(255, 255, 255, 0.85);--bs-toast-header-border-color: rgba(0, 0, 0, 0.175);width:var(--bs-toast-max-width);max-width:100%;font-size:var(--bs-toast-font-size);color:var(--bs-toast-color);pointer-events:auto;background-color:var(--bs-toast-bg);background-clip:padding-box;border:var(--bs-toast-border-width) solid var(--bs-toast-border-color);box-shadow:var(--bs-toast-box-shadow);border-radius:var(--bs-toast-border-radius)}.toast.showing{opacity:0}.toast:not(.show){display:none}.toast-container{--bs-toast-zindex: 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;--quarto-scss-export-dropdown-dark-link-color: #dee2e6;--quarto-scss-export-dropdown-dark-link-hover-color: #ffffff;--quarto-scss-export-dropdown-dark-link-hover-bg: rgba(255, 255, 255, 0.15);--quarto-scss-export-dropdown-dark-link-active-color: #ffffff;--quarto-scss-export-dropdown-dark-link-active-bg: #0d6efd;--quarto-scss-export-dropdown-dark-link-disabled-color: #adb5bd;--quarto-scss-export-dropdown-dark-header-color: #adb5bd;--quarto-scss-export-pagination-color: #0d6efd;--quarto-scss-export-pagination-bg: #ffffff;--quarto-scss-export-pagination-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-pagination-focus-color: rgb(10.4, 88, 202.4);--quarto-scss-export-pagination-focus-bg: #e9ecef;--quarto-scss-export-pagination-hover-color: rgb(10.4, 88, 202.4);--quarto-scss-export-pagination-hover-bg: #f8f9fa;--quarto-scss-export-pagination-hover-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-pagination-active-color: #ffffff;--quarto-scss-export-pagination-active-bg: #0d6efd;--quarto-scss-export-pagination-active-border-color: #0d6efd;--quarto-scss-export-pagination-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-pagination-disabled-bg: #e9ecef;--quarto-scss-export-pagination-disabled-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-card-title-color: ;--quarto-scss-export-card-subtitle-color: ;--quarto-scss-export-card-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-card-box-shadow: ;--quarto-scss-export-card-cap-bg: rgba(33, 37, 41, 0.03);--quarto-scss-export-card-cap-color: ;--quarto-scss-export-card-height: ;--quarto-scss-export-card-color: ;--quarto-scss-export-card-bg: #ffffff;--quarto-scss-export-accordion-color: #212529;--quarto-scss-export-accordion-bg: #ffffff;--quarto-scss-export-accordion-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-accordion-button-color: #212529;--quarto-scss-export-accordion-button-bg: #ffffff;--quarto-scss-export-accordion-button-active-bg: rgb(206.6, 226, 254.6);--quarto-scss-export-accordion-button-active-color: rgb(5.2, 44, 101.2);--quarto-scss-export-accordion-button-focus-border-color: rgb(134, 182.5, 254);--quarto-scss-export-accordion-icon-color: #212529;--quarto-scss-export-accordion-icon-active-color: rgb(5.2, 44, 101.2);--quarto-scss-export-tooltip-color: #ffffff;--quarto-scss-export-tooltip-bg: #000;--quarto-scss-export-tooltip-margin: ;--quarto-scss-export-tooltip-arrow-color: ;--quarto-scss-export-form-feedback-tooltip-line-height: ;--quarto-scss-export-popover-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-popover-header-bg: #e9ecef;--quarto-scss-export-popover-body-color: #212529;--quarto-scss-export-popover-arrow-color: #ffffff;--quarto-scss-export-popover-arrow-outer-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-toast-color: ;--quarto-scss-export-toast-background-color: rgba(255, 255, 255, 0.85);--quarto-scss-export-toast-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-toast-header-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-toast-header-background-color: rgba(255, 255, 255, 0.85);--quarto-scss-export-toast-header-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-badge-color: #ffffff;--quarto-scss-export-modal-content-color: ;--quarto-scss-export-modal-content-bg: #ffffff;--quarto-scss-export-modal-content-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-modal-backdrop-bg: #000;--quarto-scss-export-modal-header-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-modal-footer-bg: ;--quarto-scss-export-modal-footer-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-progress-bg: #e9ecef;--quarto-scss-export-progress-bar-color: #ffffff;--quarto-scss-export-progress-bar-bg: #0d6efd;--quarto-scss-export-list-group-color: #212529;--quarto-scss-export-list-group-bg: #ffffff;--quarto-scss-export-list-group-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-list-group-hover-bg: #f8f9fa;--quarto-scss-export-list-group-active-bg: #0d6efd;--quarto-scss-export-list-group-active-color: #ffffff;--quarto-scss-export-list-group-active-border-color: #0d6efd;--quarto-scss-export-list-group-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-list-group-disabled-bg: #ffffff;--quarto-scss-export-list-group-action-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-list-group-action-hover-color: #000;--quarto-scss-export-list-group-action-active-color: #212529;--quarto-scss-export-list-group-action-active-bg: #e9ecef;--quarto-scss-export-thumbnail-bg: #ffffff;--quarto-scss-export-thumbnail-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-figure-caption-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-font-size: ;--quarto-scss-export-breadcrumb-bg: ;--quarto-scss-export-breadcrumb-divider-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-active-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-border-radius: ;--quarto-scss-export-carousel-control-color: #ffffff;--quarto-scss-export-carousel-indicator-active-bg: #ffffff;--quarto-scss-export-carousel-caption-color: #ffffff;--quarto-scss-export-carousel-dark-indicator-active-bg: #000;--quarto-scss-export-carousel-dark-caption-color: #000;--quarto-scss-export-btn-close-color: #000;--quarto-scss-export-offcanvas-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-offcanvas-bg-color: #ffffff;--quarto-scss-export-offcanvas-color: #212529;--quarto-scss-export-offcanvas-backdrop-bg: #000;--quarto-scss-export-code-color-dark: white;--quarto-scss-export-kbd-color: #ffffff;--quarto-scss-export-kbd-bg: #212529;--quarto-scss-export-nested-kbd-font-weight: ;--quarto-scss-export-pre-bg: #f8f9fa;--quarto-scss-export-pre-color: #000;--quarto-scss-export-bslib-page-sidebar-title-bg: #517699;--quarto-scss-export-bslib-page-sidebar-title-color: #ffffff;--quarto-scss-export-bslib-sidebar-bg: rgba(var(--bs-emphasis-color-rgb, 0, 0, 0), 0.05);--quarto-scss-export-bslib-sidebar-toggle-bg: rgba(var(--bs-emphasis-color-rgb, 0, 0, 0), 0.1);--quarto-scss-export-mermaid-bg-color: #ffffff;--quarto-scss-export-mermaid-edge-color: #6c757d;--quarto-scss-export-mermaid-node-fg-color: #212529;--quarto-scss-export-mermaid-fg-color: #212529;--quarto-scss-export-mermaid-fg-color--lighter: rgb(55.7432432432, 62.5, 69.2567567568);--quarto-scss-export-mermaid-fg-color--lightest: rgb(78.4864864865, 88, 97.5135135135);--quarto-scss-export-mermaid-label-bg-color: #ffffff;--quarto-scss-export-mermaid-label-fg-color: #0d6efd;--quarto-scss-export-mermaid-node-bg-color: rgba(13, 110, 253, 0.1);--quarto-scss-export-code-block-border-left-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-callout-color-note: #0d6efd;--quarto-scss-export-callout-color-tip: #198754;--quarto-scss-export-callout-color-important: #dc3545;--quarto-scss-export-callout-color-caution: 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J,Z="x"===y?zt:Vt,tt="x"===y?Rt:qt,et=A[w],it="y"===w?"height":"width",nt=et+g[Z],st=et-g[tt],ot=-1!==[zt,Vt].indexOf(_),rt=null!=(J=null==x?void 0:x[w])?J:0,at=ot?nt:et-E[it]-T[it]-rt+O.altAxis,lt=ot?et+E[it]+T[it]-rt-O.altAxis:st,ct=f&&ot?function(t,e,i){var n=Ne(t,e,i);return n>i?i:n}(at,et,lt):Ne(f?at:nt,et,f?lt:st);A[w]=ct,k[w]=ct-et}e.modifiersData[n]=k}},requiresIfExists:["offset"]};function di(t,e,i){void 0===i&&(i=!1);var n,s,o=me(e),r=me(e)&&function(t){var e=t.getBoundingClientRect(),i=we(e.width)/t.offsetWidth||1,n=we(e.height)/t.offsetHeight||1;return 1!==i||1!==n}(e),a=Le(e),l=Te(t,r,i),c={scrollLeft:0,scrollTop:0},h={x:0,y:0};return(o||!o&&!i)&&(("body"!==ue(e)||Ue(a))&&(c=(n=e)!==fe(n)&&me(n)?{scrollLeft:(s=n).scrollLeft,scrollTop:s.scrollTop}:Xe(n)),me(e)?((h=Te(e,!0)).x+=e.clientLeft,h.y+=e.clientTop):a&&(h.x=Ye(a))),{x:l.left+c.scrollLeft-h.x,y:l.top+c.scrollTop-h.y,width:l.width,height:l.height}}function ui(t){var e=new Map,i=new Set,n=[];function s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var fi={placement:"bottom",modifiers:[],strategy:"absolute"};function pi(){for(var t=arguments.length,e=new Array(t),i=0;iNumber.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(F.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...g(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=z.find(".dropdown-menu 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e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ei,Ti].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ii)?this:z.prev(this,Ii)[0]||z.next(this,Ii)[0]||z.findOne(Ii,t.delegateTarget.parentNode),o=qi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}N.on(document,Si,Ii,qi.dataApiKeydownHandler),N.on(document,Si,Pi,qi.dataApiKeydownHandler),N.on(document,Li,qi.clearMenus),N.on(document,Di,qi.clearMenus),N.on(document,Li,Ii,(function(t){t.preventDefault(),qi.getOrCreateInstance(this).toggle()})),m(qi);const Vi="backdrop",Ki="show",Qi=`mousedown.bs.${Vi}`,Xi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Yi={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Ui extends H{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Yi}static get NAME(){return Vi}show(t){if(!this._config.isVisible)return void g(t);this._append();const e=this._getElement();this._config.isAnimated&&d(e),e.classList.add(Ki),this._emulateAnimation((()=>{g(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),g(t)}))):g(t)}dispose(){this._isAppended&&(N.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=r(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),N.on(t,Qi,(()=>{g(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){_(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends H{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),N.off(document,Gi),N.on(document,Ji,(t=>this._handleFocusin(t))),N.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,N.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=z.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===tn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?tn:"forward")}}const on=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",rn=".sticky-top",an="padding-right",ln="margin-right";class cn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,an,(e=>e+t)),this._setElementAttributes(on,an,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,an),this._resetElementAttributes(on,an),this._resetElementAttributes(rn,ln)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&F.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=F.getDataAttribute(t,e);null!==i?(F.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(o(t))e(t);else for(const i of z.find(t,this._element))e(i)}}const hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",An="show",En="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends W{constructor(t,e){super(t,e),this._dialog=z.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||N.trigger(this._element,pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(wn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(N.trigger(this._element,dn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){N.off(window,hn),N.off(this._dialog,hn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Ui({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=z.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),d(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,N.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){N.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),N.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),N.on(this._element,bn,(t=>{N.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),N.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(N.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(En)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(En),this._queueCallback((()=>{this._element.classList.remove(En),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=p()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=p()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=On.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}N.on(document,yn,'[data-bs-toggle="modal"]',(function(t){const e=z.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),N.one(e,pn,(t=>{t.defaultPrevented||N.one(e,fn,(()=>{a(this)&&this.focus()}))}));const i=z.findOne(".modal.show");i&&On.getInstance(i).hide(),On.getOrCreateInstance(e).toggle(this)})),R(On),m(On);const xn=".bs.offcanvas",kn=".data-api",Ln=`load${xn}${kn}`,Sn="show",Dn="showing",$n="hiding",In=".offcanvas.show",Nn=`show${xn}`,Pn=`shown${xn}`,Mn=`hide${xn}`,jn=`hidePrevented${xn}`,Fn=`hidden${xn}`,Hn=`resize${xn}`,Wn=`click${xn}${kn}`,Bn=`keydown.dismiss${xn}`,zn={backdrop:!0,keyboard:!0,scroll:!1},Rn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class qn extends W{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||N.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),N.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(N.trigger(this._element,Mn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),N.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():N.trigger(this._element,jn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){N.on(this._element,Bn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():N.trigger(this._element,jn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}N.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=z.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),l(this))return;N.one(e,Fn,(()=>{a(this)&&this.focus()}));const i=z.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),N.on(window,Ln,(()=>{for(const t of z.find(In))qn.getOrCreateInstance(t).show()})),N.on(window,Hn,(()=>{for(const t of z.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),R(qn),m(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Yn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"
"},Un={allowList:"object",content:"object",extraClass:"(string|function)",html:"boolean",sanitize:"boolean",sanitizeFn:"(null|function)",template:"string"},Gn={entry:"(string|element|function|null)",selector:"(string|element)"};class Jn extends H{constructor(t){super(),this._config=this._getConfig(t)}static get Default(){return Yn}static get DefaultType(){return Un}static get NAME(){return"TemplateFactory"}getContent(){return Object.values(this._config.content).map((t=>this._resolvePossibleFunction(t))).filter(Boolean)}hasContent(){return this.getContent().length>0}changeContent(t){return this._checkContent(t),this._config.content={...this._config.content,...t},this}toHtml(){const t=document.createElement("div");t.innerHTML=this._maybeSanitize(this._config.template);for(const[e,i]of Object.entries(this._config.content))this._setContent(t,i,e);const e=t.children[0],i=this._resolvePossibleFunction(this._config.extraClass);return i&&e.classList.add(...i.split(" ")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=z.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?o(e)?this._putElementInTemplate(r(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return g(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const Zn=new Set(["sanitize","allowList","sanitizeFn"]),ts="fade",es="show",is=".modal",ns="hide.bs.modal",ss="hover",os="focus",rs={AUTO:"auto",TOP:"top",RIGHT:p()?"left":"right",BOTTOM:"bottom",LEFT:p()?"right":"left"},as={allowList:Vn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'',title:"",trigger:"hover 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this.options = options; + } + + report() { + throw new Error("report() is an abstract method"); + } +} + +class QuartoAxeJsonReporter extends QuartoAxeReporter { + constructor(axeResult, options) { + super(axeResult, options); + } + + report() { + console.log(JSON.stringify(this.axeResult, null, 2)); + } +} + +class QuartoAxeConsoleReporter extends QuartoAxeReporter { + constructor(axeResult, options) { + super(axeResult, options); + } + + report() { + for (const violation of this.axeResult.violations) { + console.log(violation.description); + for (const node of violation.nodes) { + for (const target of node.target) { + console.log(target); + console.log(document.querySelector(target)); + } + } + } + } +} + +class QuartoAxeDocumentReporter extends QuartoAxeReporter { + constructor(axeResult, options) { + super(axeResult, options); + } + + createViolationElement(violation) { + const violationElement = document.createElement("div"); + + const descriptionElement = document.createElement("div"); + descriptionElement.className = "quarto-axe-violation-description"; + descriptionElement.innerText = `${violation.impact.replace(/^[a-z]/, match => match.toLocaleUpperCase())}: ${violation.description}`; + violationElement.appendChild(descriptionElement); + + const helpElement = document.createElement("div"); + helpElement.className = "quarto-axe-violation-help"; + helpElement.innerText = violation.help; + violationElement.appendChild(helpElement); + + const nodesElement = document.createElement("div"); + nodesElement.className = "quarto-axe-violation-nodes"; + violationElement.appendChild(nodesElement); + const nodeElement = document.createElement("div"); + nodeElement.className = "quarto-axe-violation-selector"; + for (const node of violation.nodes) { + for (const target of node.target) { + const targetElement = document.createElement("span"); + targetElement.className = "quarto-axe-violation-target"; + targetElement.innerText = target; + nodeElement.appendChild(targetElement); + nodeElement.addEventListener("mouseenter", () => { + const element = document.querySelector(target); + if (element) { + element.scrollIntoView({ behavior: "smooth", block: "center" }); + element.classList.add("quarto-axe-hover-highlight"); + setTimeout(() => { + element.style.border = ""; + }, 2000); + } + }); + nodeElement.addEventListener("mouseleave", () => { + const element = document.querySelector(target); + if (element) { + element.classList.remove("quarto-axe-hover-highlight"); + } + }); + nodeElement.addEventListener("click", () => { + console.log(document.querySelector(target)); + }); + nodeElement.appendChild(targetElement); + } + nodesElement.appendChild(nodeElement); + } + return violationElement; + } + + report() { + const violations = this.axeResult.violations; + const reportElement = document.createElement("div"); + reportElement.className = "quarto-axe-report"; + if (violations.length === 0) { + const noViolationsElement = document.createElement("div"); + noViolationsElement.className = "quarto-axe-no-violations"; + noViolationsElement.innerText = "No axe-core violations found."; + reportElement.appendChild(noViolationsElement); + } + violations.forEach((violation) => { + reportElement.appendChild(this.createViolationElement(violation)); + }); + document.querySelector("main").appendChild(reportElement); + } +} + +const reporters = { + json: QuartoAxeJsonReporter, + console: QuartoAxeConsoleReporter, + document: QuartoAxeDocumentReporter, +}; + +class QuartoAxeChecker { + constructor(opts) { + this.options = opts; + } + async init() { + const axe = (await import("https://cdn.skypack.dev/pin/axe-core@v4.10.3-aVOFXWsJaCpVrtv89pCa/mode=imports,min/optimized/axe-core.js")).default; + const result = await axe.run({ + exclude: [ + // https://github.com/microsoft/tabster/issues/288 + // MS has claimed they won't fix this, so we need to add an exclusion to + // all tabster elements + "[data-tabster-dummy]" + ], + preload: { assets: ['cssom'], timeout: 50000 } + }); + const reporter = this.options === true ? new QuartoAxeConsoleReporter(result) : new reporters[this.options.output](result, this.options); + reporter.report(); + } +} + +export async function init() { + const opts = document.querySelector("#quarto-axe-checker-options"); + if (opts) { + const jsonOptions = JSON.parse(atob(opts.textContent)); + const checker = new QuartoAxeChecker(jsonOptions); + await checker.init(); + } +} \ No newline at end of file diff --git a/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/quarto-html/popper.min.js b/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/quarto-html/popper.min.js new file mode 100644 index 0000000..e3726d7 --- /dev/null +++ b/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/quarto-html/popper.min.js @@ -0,0 +1,6 @@ +/** + * @popperjs/core v2.11.7 - MIT License + */ + +!function(e,t){"object"==typeof exports&&"undefined"!=typeof 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b/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/quarto-html/quarto-syntax-highlighting-ed96de9b727972fe78a7b5d16c58bf87.css new file mode 100644 index 0000000..7bb4f73 --- /dev/null +++ b/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/quarto-html/quarto-syntax-highlighting-ed96de9b727972fe78a7b5d16c58bf87.css @@ -0,0 +1,236 @@ +/* quarto syntax highlight colors */ +:root { + --quarto-hl-ot-color: #003B4F; + --quarto-hl-at-color: #657422; + --quarto-hl-ss-color: #20794D; + --quarto-hl-an-color: #5E5E5E; + --quarto-hl-fu-color: #4758AB; + --quarto-hl-st-color: #20794D; + --quarto-hl-cf-color: #003B4F; + --quarto-hl-op-color: #5E5E5E; + --quarto-hl-er-color: #AD0000; + --quarto-hl-bn-color: #AD0000; + --quarto-hl-al-color: #AD0000; + --quarto-hl-va-color: #111111; + --quarto-hl-bu-color: inherit; + --quarto-hl-ex-color: inherit; + --quarto-hl-pp-color: #AD0000; + --quarto-hl-in-color: #5E5E5E; + --quarto-hl-vs-color: #20794D; + --quarto-hl-wa-color: #5E5E5E; + --quarto-hl-do-color: #5E5E5E; + --quarto-hl-im-color: #00769E; + --quarto-hl-ch-color: #20794D; + --quarto-hl-dt-color: #AD0000; + --quarto-hl-fl-color: #AD0000; + --quarto-hl-co-color: #5E5E5E; + --quarto-hl-cv-color: #5E5E5E; + --quarto-hl-cn-color: #8f5902; + --quarto-hl-sc-color: #5E5E5E; + --quarto-hl-dv-color: #AD0000; + --quarto-hl-kw-color: #003B4F; +} + +/* other quarto variables */ +:root { + --quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace; +} + +/* syntax highlight based on Pandoc's rules */ +pre > code.sourceCode > span { + color: #003B4F; +} + +code.sourceCode > span { + color: #003B4F; +} + +div.sourceCode, +div.sourceCode pre.sourceCode { + color: #003B4F; +} + +/* Normal */ +code span { + color: #003B4F; +} + +/* Alert */ +code span.al { + color: #AD0000; + font-style: inherit; +} + +/* Annotation */ +code span.an { + color: #5E5E5E; + font-style: inherit; +} + +/* Attribute */ +code span.at { + color: #657422; + font-style: inherit; +} + +/* BaseN */ +code span.bn { + color: #AD0000; + font-style: inherit; +} + +/* BuiltIn */ +code span.bu { + font-style: inherit; +} + +/* ControlFlow */ +code span.cf { + color: #003B4F; + font-weight: bold; + font-style: inherit; +} + +/* Char */ +code span.ch { + color: #20794D; + font-style: inherit; +} + +/* Constant */ +code span.cn { + color: #8f5902; + font-style: inherit; +} + +/* Comment */ +code span.co { + color: #5E5E5E; + font-style: inherit; +} + +/* CommentVar */ +code span.cv { + color: #5E5E5E; + font-style: italic; +} + +/* Documentation */ +code span.do { + color: #5E5E5E; + font-style: italic; +} + +/* DataType */ +code span.dt { + color: #AD0000; + font-style: inherit; +} + +/* DecVal */ +code span.dv { + color: #AD0000; + font-style: inherit; +} + +/* Error */ +code span.er { + color: #AD0000; + font-style: inherit; +} + +/* Extension */ +code span.ex { + font-style: inherit; +} + +/* Float */ +code span.fl { + color: #AD0000; + font-style: inherit; +} + +/* Function */ +code span.fu { + color: #4758AB; + font-style: inherit; +} + +/* Import */ +code span.im { + color: #00769E; + font-style: inherit; +} + +/* Information */ +code span.in { + color: #5E5E5E; + font-style: inherit; +} + +/* Keyword */ +code span.kw { + color: #003B4F; + font-weight: bold; + font-style: inherit; +} + +/* Operator */ +code span.op { + color: #5E5E5E; + font-style: inherit; +} + +/* Other */ +code span.ot { + color: #003B4F; + font-style: inherit; +} + +/* Preprocessor */ +code span.pp { + color: #AD0000; + font-style: inherit; +} + +/* SpecialChar */ +code span.sc { + color: #5E5E5E; + font-style: inherit; +} + +/* SpecialString */ +code span.ss { + color: #20794D; + font-style: inherit; +} + +/* String */ +code span.st { + color: #20794D; + font-style: inherit; +} + +/* Variable */ +code span.va { + color: #111111; + font-style: inherit; +} + +/* VerbatimString */ +code span.vs { + color: #20794D; + font-style: inherit; +} + +/* Warning */ +code span.wa { + color: #5E5E5E; + font-style: italic; +} + +.prevent-inlining { + content: " { + // Find any conflicting margin elements and add margins to the + // top to prevent overlap + const marginChildren = window.document.querySelectorAll( + ".column-margin.column-container > *, .margin-caption, .aside" + ); + + let lastBottom = 0; + for (const marginChild of marginChildren) { + if (marginChild.offsetParent !== null) { + // clear the top margin so we recompute it + marginChild.style.marginTop = null; + const top = marginChild.getBoundingClientRect().top + window.scrollY; + if (top < lastBottom) { + const marginChildStyle = window.getComputedStyle(marginChild); + const marginBottom = parseFloat(marginChildStyle["marginBottom"]); + const margin = lastBottom - top + marginBottom; + marginChild.style.marginTop = `${margin}px`; + } + const styles = window.getComputedStyle(marginChild); + const marginTop = parseFloat(styles["marginTop"]); + lastBottom = top + marginChild.getBoundingClientRect().height + marginTop; + } + } +}; + +window.document.addEventListener("DOMContentLoaded", function (_event) { + // Recompute the position of margin elements anytime the body size changes + if (window.ResizeObserver) { + const resizeObserver = new window.ResizeObserver( + throttle(() => { + layoutMarginEls(); + if ( + window.document.body.getBoundingClientRect().width < 990 && + isReaderMode() + ) { + quartoToggleReader(); + } + }, 50) + ); + resizeObserver.observe(window.document.body); + } + + const tocEl = window.document.querySelector('nav.toc-active[role="doc-toc"]'); + const sidebarEl = window.document.getElementById("quarto-sidebar"); + const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left"); + const marginSidebarEl = window.document.getElementById( + "quarto-margin-sidebar" + ); + // function to determine whether the element has a previous sibling that is active + const prevSiblingIsActiveLink = (el) => { + const sibling = el.previousElementSibling; + if (sibling && sibling.tagName === "A") { + return sibling.classList.contains("active"); + } else { + return false; + } + }; + + // dispatch for htmlwidgets + // they use slideenter event to trigger resize + function fireSlideEnter() { + const event = window.document.createEvent("Event"); + event.initEvent("slideenter", true, true); + window.document.dispatchEvent(event); + } + + const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]'); + tabs.forEach((tab) => { + tab.addEventListener("shown.bs.tab", fireSlideEnter); + }); + + // dispatch for shiny + // they use BS shown and hidden events to trigger rendering + function distpatchShinyEvents(previous, current) { + if (window.jQuery) { + if (previous) { + window.jQuery(previous).trigger("hidden"); + } + if (current) { + window.jQuery(current).trigger("shown"); + } + } + } + + // tabby.js listener: Trigger event for htmlwidget and shiny + document.addEventListener( + "tabby", + function (event) { + fireSlideEnter(); + distpatchShinyEvents(event.detail.previousTab, event.detail.tab); + }, + false + ); + + // Track scrolling and mark TOC links as active + // get table of contents and sidebar (bail if we don't have at least one) + const tocLinks = tocEl + ? [...tocEl.querySelectorAll("a[data-scroll-target]")] + : []; + const makeActive = (link) => tocLinks[link].classList.add("active"); + const removeActive = (link) => tocLinks[link].classList.remove("active"); + const removeAllActive = () => + [...Array(tocLinks.length).keys()].forEach((link) => removeActive(link)); + + // activate the anchor for a section associated with this TOC entry + tocLinks.forEach((link) => { + link.addEventListener("click", () => { + if (link.href.indexOf("#") !== -1) { + const anchor = link.href.split("#")[1]; + const heading = window.document.querySelector( + `[data-anchor-id="${anchor}"]` + ); + if (heading) { + // Add the class + heading.classList.add("reveal-anchorjs-link"); + + // function to show the anchor + const handleMouseout = () => { + heading.classList.remove("reveal-anchorjs-link"); + heading.removeEventListener("mouseout", handleMouseout); + }; + + // add a function to clear the anchor when the user mouses out of it + heading.addEventListener("mouseout", handleMouseout); + } + } + }); + }); + + const sections = tocLinks.map((link) => { + const target = link.getAttribute("data-scroll-target"); + if (target.startsWith("#")) { + return window.document.getElementById(decodeURI(`${target.slice(1)}`)); + } else { + return window.document.querySelector(decodeURI(`${target}`)); + } + }); + + const sectionMargin = 200; + let currentActive = 0; + // track whether we've initialized state the first time + let init = false; + + const updateActiveLink = () => { + // The index from bottom to top (e.g. reversed list) + let sectionIndex = -1; + if ( + window.innerHeight + window.pageYOffset >= + window.document.body.offsetHeight + ) { + // This is the no-scroll case where last section should be the active one + sectionIndex = 0; + } else { + // This finds the last section visible on screen that should be made active + sectionIndex = [...sections].reverse().findIndex((section) => { + if (section) { + return window.pageYOffset >= section.offsetTop - sectionMargin; + } else { + return false; + } + }); + } + if (sectionIndex > -1) { + const current = sections.length - sectionIndex - 1; + if (current !== currentActive) { + removeAllActive(); + currentActive = current; + makeActive(current); + if (init) { + window.dispatchEvent(sectionChanged); + } + init = true; + } + } + }; + + const inHiddenRegion = (top, bottom, hiddenRegions) => { + for (const region of hiddenRegions) { + if (top <= region.bottom && bottom >= region.top) { + return true; + } + } + return false; + }; + + const categorySelector = "header.quarto-title-block .quarto-category"; + const activateCategories = (href) => { + // Find any categories + // Surround them with a link pointing back to: + // #category=Authoring + try { + const categoryEls = window.document.querySelectorAll(categorySelector); + for (const categoryEl of categoryEls) { + const categoryText = categoryEl.textContent; + if (categoryText) { + const link = `${href}#category=${encodeURIComponent(categoryText)}`; + const linkEl = window.document.createElement("a"); + linkEl.setAttribute("href", link); + for (const child of categoryEl.childNodes) { + linkEl.append(child); + } + categoryEl.appendChild(linkEl); + } + } + } catch { + // Ignore errors + } + }; + function hasTitleCategories() { + return window.document.querySelector(categorySelector) !== null; + } + + function offsetRelativeUrl(url) { + const offset = getMeta("quarto:offset"); + return offset ? offset + url : url; + } + + function offsetAbsoluteUrl(url) { + const offset = getMeta("quarto:offset"); + const baseUrl = new URL(offset, window.location); + + const projRelativeUrl = url.replace(baseUrl, ""); + if (projRelativeUrl.startsWith("/")) { + return projRelativeUrl; + } else { + return "/" + projRelativeUrl; + } + } + + // read a meta tag value + function getMeta(metaName) { + const metas = window.document.getElementsByTagName("meta"); + for (let i = 0; i < metas.length; i++) { + if (metas[i].getAttribute("name") === metaName) { + return metas[i].getAttribute("content"); + } + } + return ""; + } + + async function findAndActivateCategories() { + // Categories search with listing only use path without query + const currentPagePath = offsetAbsoluteUrl( + window.location.origin + window.location.pathname + ); + const response = await fetch(offsetRelativeUrl("listings.json")); + if (response.status == 200) { + return response.json().then(function (listingPaths) { + const listingHrefs = []; + for (const listingPath of listingPaths) { + const pathWithoutLeadingSlash = listingPath.listing.substring(1); + for (const item of listingPath.items) { + const encodedItem = encodeURI(item); + if ( + encodedItem === currentPagePath || + encodedItem === currentPagePath + "index.html" + ) { + // Resolve this path against the offset to be sure + // we already are using the correct path to the listing + // (this adjusts the listing urls to be rooted against + // whatever root the page is actually running against) + const relative = offsetRelativeUrl(pathWithoutLeadingSlash); + const baseUrl = window.location; + const resolvedPath = new URL(relative, baseUrl); + listingHrefs.push(resolvedPath.pathname); + break; + } + } + } + + // Look up the tree for a nearby linting and use that if we find one + const nearestListing = findNearestParentListing( + offsetAbsoluteUrl(window.location.pathname), + listingHrefs + ); + if (nearestListing) { + activateCategories(nearestListing); + } else { + // See if the referrer is a listing page for this item + const referredRelativePath = offsetAbsoluteUrl(document.referrer); + const referrerListing = listingHrefs.find((listingHref) => { + const isListingReferrer = + listingHref === referredRelativePath || + listingHref === referredRelativePath + "index.html"; + return isListingReferrer; + }); + + if (referrerListing) { + // Try to use the referrer if possible + activateCategories(referrerListing); + } else if (listingHrefs.length > 0) { + // Otherwise, just fall back to the first listing + activateCategories(listingHrefs[0]); + } + } + }); + } + } + if (hasTitleCategories()) { + findAndActivateCategories(); + } + + const findNearestParentListing = (href, listingHrefs) => { + if (!href || !listingHrefs) { + return undefined; + } + // Look up the tree for a nearby linting and use that if we find one + const relativeParts = href.substring(1).split("/"); + while (relativeParts.length > 0) { + const path = relativeParts.join("/"); + for (const listingHref of listingHrefs) { + if (listingHref.startsWith(path)) { + return listingHref; + } + } + relativeParts.pop(); + } + + return undefined; + }; + + const manageSidebarVisiblity = (el, placeholderDescriptor) => { + let isVisible = true; + let elRect; + + return (hiddenRegions) => { + if (el === null) { + return; + } + + // Find the last element of the TOC + const lastChildEl = el.lastElementChild; + + if (lastChildEl) { + // Converts the sidebar to a menu + const convertToMenu = () => { + for (const child of el.children) { + child.style.opacity = 0; + child.style.overflow = "hidden"; + child.style.pointerEvents = "none"; + } + + nexttick(() => { + const toggleContainer = window.document.createElement("div"); + toggleContainer.style.width = "100%"; + toggleContainer.classList.add("zindex-over-content"); + toggleContainer.classList.add("quarto-sidebar-toggle"); + toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom + toggleContainer.id = placeholderDescriptor.id; + toggleContainer.style.position = "fixed"; + + const toggleIcon = window.document.createElement("i"); + toggleIcon.classList.add("quarto-sidebar-toggle-icon"); + toggleIcon.classList.add("bi"); + toggleIcon.classList.add("bi-caret-down-fill"); + + const toggleTitle = window.document.createElement("div"); + const titleEl = window.document.body.querySelector( + placeholderDescriptor.titleSelector + ); + if (titleEl) { + toggleTitle.append( + titleEl.textContent || titleEl.innerText, + toggleIcon + ); + } + toggleTitle.classList.add("zindex-over-content"); + toggleTitle.classList.add("quarto-sidebar-toggle-title"); + toggleContainer.append(toggleTitle); + + const toggleContents = window.document.createElement("div"); + toggleContents.classList = el.classList; + toggleContents.classList.add("zindex-over-content"); + toggleContents.classList.add("quarto-sidebar-toggle-contents"); + for (const child of el.children) { + if (child.id === "toc-title") { + continue; + } + + const clone = child.cloneNode(true); + clone.style.opacity = 1; + clone.style.pointerEvents = null; + clone.style.display = null; + toggleContents.append(clone); + } + toggleContents.style.height = "0px"; + const positionToggle = () => { + // position the element (top left of parent, same width as parent) + if (!elRect) { + elRect = el.getBoundingClientRect(); + } + toggleContainer.style.left = `${elRect.left}px`; + toggleContainer.style.top = `${elRect.top}px`; + toggleContainer.style.width = `${elRect.width}px`; + }; + positionToggle(); + + toggleContainer.append(toggleContents); + el.parentElement.prepend(toggleContainer); + + // Process clicks + let tocShowing = false; + // Allow the caller to control whether this is dismissed + // when it is clicked (e.g. sidebar navigation supports + // opening and closing the nav tree, so don't dismiss on click) + const clickEl = placeholderDescriptor.dismissOnClick + ? toggleContainer + : toggleTitle; + + const closeToggle = () => { + if (tocShowing) { + toggleContainer.classList.remove("expanded"); + toggleContents.style.height = "0px"; + tocShowing = false; + } + }; + + // Get rid of any expanded toggle if the user scrolls + window.document.addEventListener( + "scroll", + throttle(() => { + closeToggle(); + }, 50) + ); + + // Handle positioning of the toggle + window.addEventListener( + "resize", + throttle(() => { + elRect = undefined; + positionToggle(); + }, 50) + ); + + window.addEventListener("quarto-hrChanged", () => { + elRect = undefined; + }); + + // Process the click + clickEl.onclick = () => { + if (!tocShowing) { + toggleContainer.classList.add("expanded"); + toggleContents.style.height = null; + tocShowing = true; + } else { + closeToggle(); + } + }; + }); + }; + + // Converts a sidebar from a menu back to a sidebar + const convertToSidebar = () => { + for (const child of el.children) { + child.style.opacity = 1; + child.style.overflow = null; + child.style.pointerEvents = null; + } + + const placeholderEl = window.document.getElementById( + placeholderDescriptor.id + ); + if (placeholderEl) { + placeholderEl.remove(); + } + + el.classList.remove("rollup"); + }; + + if (isReaderMode()) { + convertToMenu(); + isVisible = false; + } else { + // Find the top and bottom o the element that is being managed + const elTop = el.offsetTop; + const elBottom = + elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight; + + if (!isVisible) { + // If the element is current not visible reveal if there are + // no conflicts with overlay regions + if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToSidebar(); + isVisible = true; + } + } else { + // If the element is visible, hide it if it conflicts with overlay regions + // and insert a placeholder toggle (or if we're in reader mode) + if (inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToMenu(); + isVisible = false; + } + } + } + } + }; + }; + + const tabEls = document.querySelectorAll('a[data-bs-toggle="tab"]'); + for (const tabEl of tabEls) { + const id = tabEl.getAttribute("data-bs-target"); + if (id) { + const columnEl = document.querySelector( + `${id} .column-margin, .tabset-margin-content` + ); + if (columnEl) + tabEl.addEventListener("shown.bs.tab", function (event) { + const el = event.srcElement; + if (el) { + const visibleCls = `${el.id}-margin-content`; + // walk up until we find a parent tabset + let panelTabsetEl = el.parentElement; + while (panelTabsetEl) { + if (panelTabsetEl.classList.contains("panel-tabset")) { + break; + } + panelTabsetEl = panelTabsetEl.parentElement; + } + + if (panelTabsetEl) { + const prevSib = panelTabsetEl.previousElementSibling; + if ( + prevSib && + prevSib.classList.contains("tabset-margin-container") + ) { + const childNodes = prevSib.querySelectorAll( + ".tabset-margin-content" + ); + for (const childEl of childNodes) { + if (childEl.classList.contains(visibleCls)) { + childEl.classList.remove("collapse"); + } else { + childEl.classList.add("collapse"); + } + } + } + } + } + + layoutMarginEls(); + }); + } + } + + // Manage the visibility of the toc and the sidebar + const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, { + id: "quarto-toc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, { + id: "quarto-sidebarnav-toggle", + titleSelector: ".title", + dismissOnClick: false, + }); + let tocLeftScrollVisibility; + if (leftTocEl) { + tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, { + id: "quarto-lefttoc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + } + + // Find the first element that uses formatting in special columns + const conflictingEls = window.document.body.querySelectorAll( + '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]' + ); + + // Filter all the possibly conflicting elements into ones + // the do conflict on the left or ride side + const arrConflictingEls = Array.from(conflictingEls); + const leftSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return false; + } + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + className.startsWith("column-") && + !className.endsWith("right") && + !className.endsWith("container") && + className !== "column-margin" + ); + }); + }); + const rightSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return true; + } + + const hasMarginCaption = Array.from(el.classList).find((className) => { + return className == "margin-caption"; + }); + if (hasMarginCaption) { + return true; + } + + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + !className.endsWith("container") && + className.startsWith("column-") && + !className.endsWith("left") + ); + }); + }); + + const kOverlapPaddingSize = 10; + function toRegions(els) { + return els.map((el) => { + const boundRect = el.getBoundingClientRect(); + const top = + boundRect.top + + document.documentElement.scrollTop - + kOverlapPaddingSize; + return { + top, + bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize, + }; + }); + } + + let hasObserved = false; + const visibleItemObserver = (els) => { + let visibleElements = [...els]; + const intersectionObserver = new IntersectionObserver( + (entries, _observer) => { + entries.forEach((entry) => { + if (entry.isIntersecting) { + if (visibleElements.indexOf(entry.target) === -1) { + visibleElements.push(entry.target); + } + } else { + visibleElements = visibleElements.filter((visibleEntry) => { + return visibleEntry !== entry; + }); + } + }); + + if (!hasObserved) { + hideOverlappedSidebars(); + } + hasObserved = true; + }, + {} + ); + els.forEach((el) => { + intersectionObserver.observe(el); + }); + + return { + getVisibleEntries: () => { + return visibleElements; + }, + }; + }; + + const rightElementObserver = visibleItemObserver(rightSideConflictEls); + const leftElementObserver = visibleItemObserver(leftSideConflictEls); + + const hideOverlappedSidebars = () => { + marginScrollVisibility(toRegions(rightElementObserver.getVisibleEntries())); + sidebarScrollVisiblity(toRegions(leftElementObserver.getVisibleEntries())); + if (tocLeftScrollVisibility) { + tocLeftScrollVisibility( + toRegions(leftElementObserver.getVisibleEntries()) + ); + } + }; + + window.quartoToggleReader = () => { + // Applies a slow class (or removes it) + // to update the transition speed + const slowTransition = (slow) => { + const manageTransition = (id, slow) => { + const el = document.getElementById(id); + if (el) { + if (slow) { + el.classList.add("slow"); + } else { + el.classList.remove("slow"); + } + } + }; + + manageTransition("TOC", slow); + manageTransition("quarto-sidebar", slow); + }; + const readerMode = !isReaderMode(); + setReaderModeValue(readerMode); + + // If we're entering reader mode, slow the transition + if (readerMode) { + slowTransition(readerMode); + } + highlightReaderToggle(readerMode); + hideOverlappedSidebars(); + + // If we're exiting reader mode, restore the non-slow transition + if (!readerMode) { + slowTransition(!readerMode); + } + }; + + const highlightReaderToggle = (readerMode) => { + const els = document.querySelectorAll(".quarto-reader-toggle"); + if (els) { + els.forEach((el) => { + if (readerMode) { + el.classList.add("reader"); + } else { + el.classList.remove("reader"); + } + }); + } + }; + + const setReaderModeValue = (val) => { + if (window.location.protocol !== "file:") { + window.localStorage.setItem("quarto-reader-mode", val); + } else { + localReaderMode = val; + } + }; + + const isReaderMode = () => { + if (window.location.protocol !== "file:") { + return window.localStorage.getItem("quarto-reader-mode") === "true"; + } else { + return localReaderMode; + } + }; + let localReaderMode = null; + + const tocOpenDepthStr = tocEl?.getAttribute("data-toc-expanded"); + const tocOpenDepth = tocOpenDepthStr ? Number(tocOpenDepthStr) : 1; + + // Walk the TOC and collapse/expand nodes + // Nodes are expanded if: + // - they are top level + // - they have children that are 'active' links + // - they are directly below an link that is 'active' + const walk = (el, depth) => { + // Tick depth when we enter a UL + if (el.tagName === "UL") { + depth = depth + 1; + } + + // It this is active link + let isActiveNode = false; + if (el.tagName === "A" && el.classList.contains("active")) { + isActiveNode = true; + } + + // See if there is an active child to this element + let hasActiveChild = false; + for (const child of el.children) { + hasActiveChild = walk(child, depth) || hasActiveChild; + } + + // Process the collapse state if this is an UL + if (el.tagName === "UL") { + if (tocOpenDepth === -1 && depth > 1) { + // toc-expand: false + el.classList.add("collapse"); + } else if ( + depth <= tocOpenDepth || + hasActiveChild || + prevSiblingIsActiveLink(el) + ) { + el.classList.remove("collapse"); + } else { + el.classList.add("collapse"); + } + + // untick depth when we leave a UL + depth = depth - 1; + } + return hasActiveChild || isActiveNode; + }; + + // walk the TOC and expand / collapse any items that should be shown + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + + // Throttle the scroll event and walk peridiocally + window.document.addEventListener( + "scroll", + throttle(() => { + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 5) + ); + window.addEventListener( + "resize", + throttle(() => { + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 10) + ); + hideOverlappedSidebars(); + highlightReaderToggle(isReaderMode()); +}); + +tabsets.init(); +axe.init(); + +function throttle(func, wait) { + let waiting = false; + return function () { + if (!waiting) { + func.apply(this, arguments); + waiting = true; + setTimeout(function () { + waiting = false; + }, wait); + } + }; +} + +function nexttick(func) { + return setTimeout(func, 0); +} diff --git a/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/quarto-html/tabsets/tabsets.js b/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/quarto-html/tabsets/tabsets.js new file mode 100644 index 0000000..51345d0 --- /dev/null +++ b/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/quarto-html/tabsets/tabsets.js @@ -0,0 +1,95 @@ +// grouped tabsets + +export function init() { + window.addEventListener("pageshow", (_event) => { + function getTabSettings() { + const data = localStorage.getItem("quarto-persistent-tabsets-data"); + if (!data) { + localStorage.setItem("quarto-persistent-tabsets-data", "{}"); + return {}; + } + if (data) { + return JSON.parse(data); + } + } + + function setTabSettings(data) { + localStorage.setItem( + "quarto-persistent-tabsets-data", + JSON.stringify(data) + ); + } + + function setTabState(groupName, groupValue) { + const data = getTabSettings(); + data[groupName] = groupValue; + setTabSettings(data); + } + + function toggleTab(tab, active) { + const tabPanelId = tab.getAttribute("aria-controls"); + const tabPanel = document.getElementById(tabPanelId); + if (active) { + tab.classList.add("active"); + tabPanel.classList.add("active"); + } else { + tab.classList.remove("active"); + tabPanel.classList.remove("active"); + } + } + + function toggleAll(selectedGroup, selectorsToSync) { + for (const [thisGroup, tabs] of Object.entries(selectorsToSync)) { + const active = selectedGroup === thisGroup; + for (const tab of tabs) { + toggleTab(tab, active); + } + } + } + + function findSelectorsToSyncByLanguage() { + const result = {}; + const tabs = Array.from( + document.querySelectorAll(`div[data-group] a[id^='tabset-']`) + ); + for (const item of tabs) { + const div = item.parentElement.parentElement.parentElement; + const group = div.getAttribute("data-group"); + if (!result[group]) { + result[group] = {}; + } + const selectorsToSync = result[group]; + const value = item.innerHTML; + if (!selectorsToSync[value]) { + selectorsToSync[value] = []; + } + selectorsToSync[value].push(item); + } + return result; + } + + function setupSelectorSync() { + const selectorsToSync = findSelectorsToSyncByLanguage(); + Object.entries(selectorsToSync).forEach(([group, tabSetsByValue]) => { + Object.entries(tabSetsByValue).forEach(([value, items]) => { + items.forEach((item) => { + item.addEventListener("click", (_event) => { + setTabState(group, value); + toggleAll(value, selectorsToSync[group]); + }); + }); + }); + }); + return selectorsToSync; + } + + const selectorsToSync = setupSelectorSync(); + for (const [group, selectedName] of Object.entries(getTabSettings())) { + const selectors = selectorsToSync[group]; + // it's possible that stale state gives us empty selections, so we explicitly check here. + if (selectors) { + toggleAll(selectedName, selectors); + } + } + }); +} diff --git a/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/quarto-html/tippy.css b/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/quarto-html/tippy.css new file mode 100644 index 0000000..e6ae635 --- /dev/null +++ b/course/02_FilePaths/homeworks/claude-chew/Week2Homework_files/libs/quarto-html/tippy.css @@ -0,0 +1 @@ +.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 10px)}.tippy-box{position:relative;background-color:#333;color:#fff;border-radius:4px;font-size:14px;line-height:1.4;white-space:normal;outline:0;transition-property:transform,visibility,opacity}.tippy-box[data-placement^=top]>.tippy-arrow{bottom:0}.tippy-box[data-placement^=top]>.tippy-arrow:before{bottom:-7px;left:0;border-width:8px 8px 0;border-top-color:initial;transform-origin:center 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This week we will learn about file.path, namely, how to communicate to our computer (and R) where various files are stored. - -:::{.callout-important} -Before getting started, please make sure you have completed the creating a [GitHub](/course/00_GitHub/index.qmd) and [Workstation Setup](/course/00_WorkstationSetup/index.qmd) walk-throughs, since we will begin where they left off once the required software was successfully installed. Having read-through how to use [version control](/course/00_Git/index.qmd) using Git will additionally be useful. -::: - -# Background - -```{r} -#| include: FALSE -library(BiocStyle) -``` - -When flow cytometrist first start learning how to code, we tend to think big picture: "I want to take my files, normalize them, cluster them, analyze them, and finally plot them". When we first start writing code, we tend to plan what we will write in similarly broad strokes. - -Our computers by contrast "think" in small incremental steps: "First locate this folder, list the files present, select these specific ones, import them into R, load the normalization package, pass the first file in, etc.". These steps when combined algorithmically add up to form the bigger picture. - -The challenge when first starting to learn how to code is developing a coding mindset in which we think not in broad strokes, but about what the next step will be programmatically. - -
- ---- - -We will start working on our own "coding mindsets" by working with file paths, as they communicate to our computer where to find our experiment files, and tend to be one of the early points of conflict and frustration. In the process, we will also cover additional concepts of R programming generally, including how to create/name variables, and look up the class/type of a particular object. - -
- ---- - -## Set Up - -Before we begin, let's make sure you get the data needed for today transferred to your local computer, and then get the .fcs files copied over from there to your own working project folder. This is the process you will repeat each week throughout the course. - -### New Repository - -First off, login to your GitHub account. Once there, you will select the options to create a new repository (similar to what you did during [Using GitHub](/course/00_GitHub/index.qmd#github-repository)) - -![](images/0001_NewRepo.png) - -
- ---- - -For this week, let's set this new repository up as a private repository, and call it Week2. This will keep things consistent with the file.paths we will be showing in the examples. - -![](images/0002_PrivateRepo.png) - -
- ---- - -Once the new repository has been created, copy the URL. - -![](images/0003_Url.png) - -
- ---- - -Next, open up Positron, set the interpreter to use R, and then select the option to bring in a "New Folder from Git". - -![](images/0004_NewGit.png) - -
- ---- - -Paste in your new repository's url. Additionally, if you want to match file.paths shown in the examples, set your storage location to your local Documents folder (please note the start of the file.path will look differently depending on whether you are on Windows, MacOS, or Linux). - -![](images/0005_SaveDocuments.png) - -
- ---- - -Your new repository will then be imported from GitHub. Once this is done, create two subfolders (data and images) and a new .qmd file (naming it filepaths.qmd). - -![](images/0006_BasicInfrastructure.png) - -
- ---- - -### Sync - -With this done, return to GitHub and open your [forked version](/course/00_GitHub/index.qmd#forking-cytometryinr) of the CytometryInR course folder. If you haven't yet done so, click on [sync](/course/00_Homeworks/index.qmd#sync-your-fork) to bring in this week's code and datasets. - -![](images/0008_Sync.png) - -
- ---- - -Returning to Positron, you will need to switch Project Folders, switching from Week2 over to CytometryInR. - -![](images/0007_SwitchFolders.png) - -
- ---- - -### Pull - -Once CytometryInR project folder has opened, you will need to [pull](/course/00_Git/index.qmd#pull) in the new data from GitHub to your local computer. - -![](images/0007_PullCytometryInR.png) - -
- ---- - -### Copy Files to Week2 - -Once this is done, you will see within the course folder, containing this weeks folder (02_FilePaths). Within it there is a data folder with .fcs files. To avoid causing conflicts when bringing in next week's materials, you will want to manually copy over these .fcs files (via your File Explorer) to the data folder within your "Week2" Project Folder. - -![](images/0009_Copy.png) - -
- ---- - -### Commit and Push - -When you reopen your Week2 project folder in Positron, you should now be able to see the .fcs files within the data folder. Next, from the action bar on the far left, select the Source Control tab. Stage all the changes (as was done in [Using Git](/course/00_Git/)), and write a short commit message. - -![](images/0010_Commit.png) - -
- ---- - -With these files now being tracked by version control, push (ie. send) your changes to GitHub so that they are remotely backed up. - -![](images/0011_Push.png) - -
- ---- - -And with this setup complete, you are now ready to proceed. Remember, run code and write notes in your working project folder (Week2 or otherwise named) to avoid conflicts next week in the CytometryInR folder when you are trying to bring in the Week #3 code and datasets. - -
- ---- - -# Walk Through - -## Working Directory - -Now that we are back in our Week2 folder, let's start by seeing our current location similarly to how our computer perceives it. - -We will use `getwd()` function (ie. get working directory) to return the location of the folder we are currently inside of. For example, when `getwd()` is run within my Week2 project folder, I see the following location - -```{r} -#| eval: FALSE -getwd() -``` - -![](images/0000_ReplacementGetWD.png) - -This returns a file path. The final location (Week2 in this case) is the **Working Directory**. Your computer when working in R will be descern other locations in relation to this directory. - -
- ---- - -## Directories - -Within this working directory, we have a variety of project folders and files related to the course. We can see the folders that are present using the `list.dirs()` function. - -```{r} -#| eval: FALSE -list.dirs(path=".", full.names=FALSE, recursive=FALSE) -``` - -![](images/0000_ReplacementListFiles.png) - -Within this `list.dirs()` function, we are specifying two arguments with which we will be working with later today, *full.names* and *recursive*. For now, lets set their arguments to FALSE, which means they conditions they implement are inactive (turned off). - -
- ---- - -The path argument is currently set to ".", which is a stand-in for the present directory. In R, if an argument is not specified directly, it is inferred based on an order of expected arguments. Thus, if not present, we could still get the same output as seen before. - -```{r} -#| eval: FALSE -list.dirs(full.names=FALSE, recursive=FALSE) -``` - -![](images/0000_ReplacementListFiles.png) - -
- ---- - -Within Positron, in addition to visible folders, we also have *hidden folders* (denoted by the "." in front of the folder name when using `list.dirs()`). In the case of one of our course website folders, we can see a ".quarto" folder shown in a lighter gray . The ".git" folder we saw from `list.dirs()` is typically hidden when viewing from Positron. - -![](images/02_HiddenFolder.png) - -In the case of Week2, the two not-hidden folders we created are listed. We will see how to navigate these in a second. - -
- ---- - -![](images/0000_ReplacementView.png) - -
- ---- - -## Variables - -Before exploring file paths, we need to have some basic R code knowledge that we can use to work with them. Within R, we have the ability to assign particular values (be they character strings, numbers or logicals) to objects (ie. variables) that can be used when called upon later. - -For example: - -```{r} -#| eval: FALSE -WhatDayDidIWriteThis <- "Saturday" -``` - -In this case, the variable name is what the assignment arrow ("<-") is pointing at. In this case, WhatDayDidIWriteThis - -
- ---- - -When we run this, we create a variable, that will appear within the right-sidebar. - -```{r} -#| eval: TRUE -WhatDayDidIWriteThis <- "Saturday" -``` - -![](images/04_VariableList.png) - -
- ---- - -These variables can subsequently be retrieved by printing (ie. running) the name of the variable - -```{r} -WhatDayDidIWriteThis -``` - -
- ---- - -You can create variables with almost any name you can think of - -```{r} -TopSecretMeetingDay <- "Saturday" -``` - -
- ---- - -With a few exceptions. R doesn't play well with spaces: - -```{r} -#| error: TRUE -Top Secret Meeting Day <- "Saturday" -``` - -
- ---- - -But does play well with underscores: - -```{r} -Top_Secret_Meeting_Day <- "Saturday" -``` - -
- ---- - -The above (with individual words separated by _) is collectively known as snake case. The alternate way to help delineate variable names is "camelCase", with first letter of each word being capitalized (seen in the previous example). - -![](images/CamelCase.jpeg) - -
- ---- - -```{r} -TopSecretMeetingDay -``` - -
- ---- - -You can overwrite a Variable name by assigning a different value to it: - -```{r} -TopSecretMeetingDay <- "Monday" -``` - -```{r} -TopSecretMeetingDay -``` - -
- ---- - -You can also remove individual variables via the `rm` function - -```{r} -rm(Top_Secret_Meeting_Day) -``` - -
- ---- - -Or if trying to remove all, via the right sidebar - -![](images/10_RemoveVariables.png) - - -
- ---- - -In the prior case, we are creating a variable that is a "string" of character values, due to our use of "" around the word. We can see this when we use the `str()` function. - -```{r} -Fluorophores <- "FITC" -str(Fluorophores) -``` - -The "chr" in front denotating that Fluorophores contains a character string. - -
- ---- - -This could also be retrieved using the `class()` function. - -```{r} -class(Fluorophores) -``` - -
- ---- - -Alternatively, we could assign a numeric value to a variable - -```{r} -Fluorophores <- 29 -str(Fluorophores) -``` - -Which returns "num", ie. numeric. - -
- ---- - -We can also specify a logical (ie. True or FALSE) to a particular object - -```{r} -IsPerCPCy5AGoodFluorophore <- FALSE -str(IsPerCPCy5AGoodFluorophore) -``` - -Which returns logi in front, denoting this variable contains a logical value. - -
- ---- - -Last week, when we were installing `dplyr`, the reason that installation failed was `install.packages()` expects a character string. However, when we left off the "", it looked within our local environments created variables for the dplyr variable, couldn't find it, and thus failed. - -We could of course, have assigned a character value to a variable name, and then used that variable name, which would have worked. - -```{r} -#| eval: FALSE - -PackageToInstall <- "dplyr" - -install.packages(PackageToInstall) -``` - -
- ---- - -## Indexing - -Not all variables contain single objects. - -For example, we can modify Fluorophores and add additional entries: - -```{r} -Fluorophores <- c("BV421", "FITC", "PE", "APC") -str(Fluorophores) -``` - -The c stands for concatenate. It concatenates the objects into a larger object, known as a vector. - -In this case, you notice in addition to the specification the values are characters, we get a [1:4], denoting four objects are present. - -
- ---- - -We can similarly retrieve this information using the `length()` function - -```{r} -length(Fluorophores) -``` - -
- ---- - -When multiple objects are present, we can specify them individidually by providing their index number within square brackets []. - -```{r} -Fluorophores[1] -``` - -
- ---- - -```{r} -Fluorophores[3] -``` - -
- ---- - -Or specify in sequence using a colon (:) - -```{r} -Fluorophores[3:4] -``` - -
- ---- - -Or if not adjacent, reusing `c` within the square brackets - -```{r} -Fluorophores[c(1,4)] -``` - -
- ---- - -We will revisit these concepts throughout the course, with what we have covered today, this will help us create file.paths and select fcs files that we want to work with via index number. - -## Listing Files - -After this detour into variables and indexing, let's return our focus to how to use these in context of file paths. Working from within our Week2 project folder, let's see what directories (folders) are present - -```{r} -#| eval: FALSE -list.dirs(path=".", full.names=FALSE, recursive=FALSE) -``` - -![](images/00.png) - -
- ---- - -We can also list any files that are present within our working directory using the `list.files()` function. - -```{r} -#| eval: FALSE -list.files() -``` - -![](images/01.png) - -In this case, in addition to our filepaths.qmd file, we can see the LICENSE and README files created when we set up the repository. - -
- ---- - -We can also specify a particular folder we want to show items present within by changing the path argument. For example, if we wanted to see the contents of the "data" folder - -```{r} -#| eval: FALSE -list.files(path="data", full.names=FALSE, recursive=FALSE) -``` - -![](images/02.png) - -Which in this case returns the fcs files we copied over at the start of this lesson. - -
- ---- - -In this case, there are no folders under "data". Let's go ahead and create a new one, calling it target. - -![](images/03.png) - -
- ---- - -## Creating directories - -Alternatively, we can also create a folder via R using the `dir.create()` function. Since we want it within data, we would modify the path accordingly - -```{r} -#| eval: FALSE -NewFolderLocation <- file.path("data", "target2") - -dir.create(path=NewFolderLocation) -``` - -![](images/04.png) - -
- ---- - -Before continuing, let's copy the first two .fcs files into both target and target2. - -
- -![](images/06.png) - ---- - -Given our working directory is set the top-level of the Week2 project folder, we can't just check inside nested target folders directly. If we attempt to: - -```{r} -list.files(path="target", full.names=FALSE, recursive=FALSE) -``` - -
- ---- - -No files are returned (ie, character(0)), since from our computers perspective, "target" doesn't exist within the active working directory. - -```{r} -file.exists("target") -``` - -
- ---- - -On the other hand, within it's view, it knows that the data folder exist - -```{r} -#| eval: FALSE -file.exists("data") -``` - -![](images/05.png) - -So here we encounter the first challenge when communicating to our computer where to search for and find files. We need to provide a file.path that incorporates the path of folders between where the computer is currently at (ie. the working directory) and the target file itself. - -
- ---- - -## File Paths - -One way we can do this is through a file.path argument. We could potentially provide this by adding either a / or a \ into the path argument, depending on your computers operating system. - -```{r} -#| eval: FALSE -list.files(path="data/target", full.names=FALSE, recursive=FALSE) -``` - -![](images/07.png) - -
- -While this works in your particular context, if you are sharing the code with others who have a different operating system, these hard-coded "/" or "\" will cause the code for them to error out at these particular steps. - ---- - -For that reason, it is better to assemble a file.path using the `file.path()` function. This function takes into account the operating system, removing your need to have to worry about this particular computing nuance, and write code that is reproducible and replicable for everyone. - -```{r} -FolderLocation <- file.path("data", "target") -FolderLocation -``` - -```{r} -#| eval: FALSE -list.files(path=FolderLocation, full.names=FALSE, recursive=FALSE) -``` - -![](images/07.png) - -
- ---- - -We can also append additional locations to existing file paths, by including the variable name within the `file.path()` we are creating. - -```{r} -FolderLocation <- "data" -ScreenshotFolder <- file.path(FolderLocation, "target") -ScreenshotFolder -``` - -```{r} -#| eval: FALSE - -list.files(path=ScreenshotFolder, full.names=FALSE, recursive=FALSE) -``` - -![](images/07.png) - -
- ---- - -Additionally, `list.files()` has the ability to filter for files that contain a particular character string. This can be useful is we are searching for ".fcs" or ".csv" files, but also for files that contain a particular word. In the case of the ScreenshotFolders - -```{r} -#| eval: FALSE -list.files(path=ScreenshotFolder, pattern="ND050", full.names=FALSE, recursive=FALSE) -``` - -![](images/08.png) - -You will notice, the index numbers are in the context of what is filtered, not all the folder contents. - -
- ---- - -## Selecting for Patterns - -If we currently listed the files within data, we get a return that looks like this: - -```{r} -#| eval: FALSE -list.files("data", full.names=FALSE, recursive=FALSE) -``` - -![](images/09.png) - -
- ---- - -As you can see, we are getting back both folders and individual .fcs files. We could consequently change the pattern to provide a character string that will only return the .fcs files. We will go ahead and assign this list to a variable named files, for later retrieval. - -```{r} -#| eval: FALSE -files <- list.files("data", pattern=".fcs", full.names=FALSE, recursive=FALSE) -files -``` - -![](images/10.png) - -
- ---- - -One of the R packages we will be using througout the course is the `stringr` package. It contains two functions that can be useful when identifying more complicated character strings. In this case, if we run the `str_detect()` function to identify which of the .fcs files within the files variable contains the "INF" character string, we get a vector of logical (ie. True or FALSE) outputs corresponding to each file. - -```{r} -# install.packages("stringr") # CRAN -library(stringr) -``` - -```{r} -#| eval: FALSE -str_detect(files, "INF") -``` - -![](images/11.png) - -
- ---- - -Similar to how we indexed the Fluorophore list (ex. Fluorophore[1:2]) which returned a subset, we can similarly use this logical vector to subset files that returned as TRUE for containing the pattern "INF" - -```{r} -#| eval: FALSE -files[str_detect(files, "INF")] -``` - -![](images/12.png) - -
- ---- - -Let's go ahead and save these subsetted file names to a new variable, called Infants. - -```{r} -#| eval: FALSE -Infants <- files[str_detect(files, "INF")] -``` - -## Conditionals - -One useful thing is that within R, we can set conditions on whether something is carried out. The most typical conditional you will encounter are the "If" statements. They typically take a form that resembles the following. - -```{r} -#| eval: FALSE - -NeedCoffee <- TRUE - -if (NeedCoffee){ - print("Take a break") -} -``` - -
- ---- - -In this case of the above, if the variable within the () is equal to true, the code within the {} will be executed. - -```{r} - -NeedCoffee <- TRUE - -if (NeedCoffee){ - print("Take a break") -} -``` - -
- ---- - -By contrast, when the variable within the () is equal to false, the code within the {} will not be executed. - -```{r} -NeedCoffee <- FALSE - -if (NeedCoffee){ - print("Take a break") -} -``` - -
- ---- - -These "If" statements will trigger as long as the specified condition within the () is TRUE. For a different example: - -```{r} -RowNumber <- 299 -2 + RowNumber > 300 -``` - -```{r} -if (2 + RowNumber > 3){ - print("Stop Iterating") -} -``` - -
- ---- - -When you add an ! in front a conditional, it flips the expected outcome. - -```{r} -ItsRaining <- TRUE - -if (ItsRaining){print("Bring an Umbrella")} -``` - -```{r} -!ItsRaining -``` - -```{r} -if (!ItsRaining){print("Bring an Umbrella")} -``` - -```{r} -ItsRaining <- TRUE - -if (!ItsRaining){print("Bring Sunglasses")} - -``` - -
- ---- - -We will explore more complicated conditionals throughout the course, but for now, let's implement a couple simple ones in the context of copying over the .fcs files in Infants over to a new target3 folder. - -## Conditionals in practice - -First off, let's write a conditional to check if there is a target3 folder within data. - -```{r} -#| eval: FALSE -files_present <- list.files("data", full.names=FALSE, recursive=FALSE) -files_present -``` - -![](images/13.png) - -
- ---- - -```{r} -#| eval: FALSE - -FolderTarget3 <- file.path("data", "target3") -dir.exists(FolderTarget3) -``` - -![](images/14.png) - -
- ---- - -We can write a conditional to create a folder if one does not yet exist. - -```{r} -#| eval: FALSE -if (!dir.exists(FolderTarget3)){ - dir.create(FolderTarget3) -} -``` - -![](images/15.png) - -
- ---- - -## Copying Files - -To copy files to another folder location, we use the `file.copy()` function. It has two arguments that we will be working with, from being the .fcs files, and to being the folder location we wish to transfer them to. If we tried using them as we currently have them: - -```{r} -#| eval: FALSE - -# Variable Infants containing 4 .fcs file names - -file.copy(from=Infants, to=FolderTarget3) -``` - -![](images/16.png) - -
- ---- - -The reason for this error is we are only working with a partial file path, as viewed from our Working directory. In this case, what is needed is the full file.path, so the file.path should also include the upstream folders from your current working directory. - -```{r} -#| eval: FALSE -getwd() -``` - -![](images/17.png) - -
- ---- - - -In this case, we can update the .fcs files location by switching the full.names argument within `list.files()` from FALSE, to TRUE. - -```{r} -#| eval: FALSE -files_present <- list.files("data", full.names=TRUE, recursive=FALSE) -files_present -``` - -![](images/18.png) - -And filter for those containing "INF" again - -```{r} -#| eval: FALSE -Infants <- files_present[str_detect(files_present, "INF")] -``` - -And then try again: - -```{r} -#| eval: FALSE - -# Variable Infants containing 4 .fcs file names - -file.copy(from=Infants, to=FolderTarget3) -``` - -![](images/19.png) - -
- ---- - -## Removing files. - -Just like we can add files via R, we can also remove them. However, when we remove them via this route, they are removed permanently, not sent to the recycle bin. We will revisit how later on in the course after you have gained additional experience with file.paths. - -```{r} -#| eval: FALSE -?unlink() -``` - -## Basename - -If we look at Infants with the full.names=TRUE, we see the additional pathing folder has been added, allowing us to successfully copy over the files. - -```{r} -#| eval: FALSE -Infants -``` - -![](images/20.png) - -
- ---- - -If we were trying to retrieve just the local file names from the full.names, we could do so with `basename()` function. We will use this in combination with additional arguments later in the course - -```{r} -#| eval: FALSE - -basename(Infants) -``` - -![](images/22.png) - -## Recursive - -And finally that we have created additional nested folders and populated them with fcs files, let's see what setting `list.files()` recursive argument to TRUE - -```{r} -#| eval: FALSE -all_files_present <- list.files(full.names=TRUE, recursive=TRUE) -all_files_present -``` - -![](images/RecursiveTrue.png) - -
- ---- - -In this case, all files in all folders within the working directory are shown. This can be useful when exploring folder contents, but if there are a lot of files present within the folder, it will take a while to return the list. - -
- ---- - - -## Saving changes to Version Control - -And as is good practice, to maintain version control, let's stage all the files and folders we created today within the Week2 Project Folder, write a commit message, and send these files back to GitHub until they are needed again next time. - -![](images/23.png) - ---- - -# Wrap-Up - -In this session, we started to learn about working directories, file.paths and how to locate files of interest. We also learned how variables (objects) are created in R using the assignment arrow, how they are named, and the general structure (character, numeric, logical) that they are represented as. - -This will prove valuable in the next several weeks when working with .fcs files, as the majority of functions we will use for Bioconductor project R packages need file.paths to locate both .fcs files as well as .csv files that contain metadata. - -One of the most frequent errors that beginners encounter when trying to load in .fcs files into the `flowCore` package is not providing the full file.path to the .fcs file of interest. - -Next week, having installed the required R packages, and learned a little about variables and file.paths, we will dive into our first cytometry focused session. We will be cracking open an .fcs file and exploring how things are stored within. In the process of seeing how the file contents are organized, we will continue to learn and practice how to create variables, and general object structure types within R. Until then, have a wonderful week! - -![](images/Week2Exit.jpg) - -# Additional Resources - -[Riffomonas: Using paths in R and why you shouldn't be using setwd (CC179)](https://youtu.be/StqDYjM6ULo?si=ba2on5rNphQ9AL-B) - -[Project-oriented workflow](https://tidyverse.org/blog/2017/12/workflow-vs-script/) - -[Paths, working directories, and projects in R; Learn R Video 13](https://youtu.be/lJcuXBFP7Co?si=dqptQ3UGGjmTYqnB) - -[Demystifying File Paths in R: Navigate Nested Folders with Dr. Padilla](https://youtu.be/yeiT5Kj_uG8?si=UySsolzbTxbgGMF6) - -# Take-home Problems - -:::{.callout-tip title="Problem 1"} -Plug in an external hard-drive or USB into your computer. Manually, create a folder within called "TargetFolder". Try to programmatically specify the file path to identify the folders and files present on your external drive. Then, try to copy your .fcs files from their current folder on your desktop to the TargetFolder on your drive using R. Remember, just copy, no deletion, you need to walk before you can run :D -::: - -:::{.callout-tip title="Problem 2"} -In this session, we used `list.files()` with the "full.names argument" set to TRUE, as well as the `basename()` function to identify specific files. But what if you wanted a particular directory. Run `list.files()` with "full.names argument" and "recursive" argument set to TRUE, and then search online to find an R function that would retrieve the "" individual directory folders. -::: - -:::{.callout-tip title="Problem 3"} -R packages often come with internal datasets, that are typically used for use in the help documentation examples. These can be accessed through the use of the `system.file()` function. See an example below. - -```{r} -#| eval: FALSE -system.file("extdata", package = "FlowSOM") -``` - -Using what we have learned about file.path navigation, search your way down the file.directory of the `FlowSOM` and `flowWorkspace` packages, and identify any .fcs files that are present for use in the documentation. -::: - - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) -::: +--- +title: "02 - File Paths" +author: "David Rach" +date: 02-09-2026 +format: html +toc: true +toc-depth: 5 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://www.youtube.com/live/fwSu97DYlaU?si=R3DpH9dRuUCexJMN) + + + + +For screen-shot slides, click [here](/course/02_FilePaths/slides.qmd) + +--- + +Welcome to the second week of [Cytometry in R](/Schedule.qmd)! This week we will learn about file.path, namely, how to communicate to our computer (and R) where various files are stored. + +:::{.callout-important} +Before getting started, please make sure you have completed the creating a [GitHub](/course/00_GitHub/index.qmd) and [Workstation Setup](/course/00_WorkstationSetup/index.qmd) walk-throughs, since we will begin where they left off once the required software was successfully installed. Having read-through how to use [version control](/course/00_Git/index.qmd) using Git will additionally be useful. +::: + +# Background + +```{r} +#| include: FALSE +library(BiocStyle) +``` + +When flow cytometrist first start learning how to code, we tend to think big picture: "I want to take my files, normalize them, cluster them, analyze them, and finally plot them". When we first start writing code, we tend to plan what we will write in similarly broad strokes. + +Our computers by contrast "think" in small incremental steps: "First locate this folder, list the files present, select these specific ones, import them into R, load the normalization package, pass the first file in, etc.". These steps when combined algorithmically add up to form the bigger picture. + +The challenge when first starting to learn how to code is developing a coding mindset in which we think not in broad strokes, but about what the next step will be programmatically. + +
+ +--- + +We will start working on our own "coding mindsets" by working with file paths, as they communicate to our computer where to find our experiment files, and tend to be one of the early points of conflict and frustration. In the process, we will also cover additional concepts of R programming generally, including how to create/name variables, and look up the class/type of a particular object. + +
+ +--- + +## Set Up + +Before we begin, let's make sure you get the data needed for today transferred to your local computer, and then get the .fcs files copied over from there to your own working project folder. This is the process you will repeat each week throughout the course. + +### New Repository + +First off, login to your GitHub account. Once there, you will select the options to create a new repository (similar to what you did during [Using GitHub](/course/00_GitHub/index.qmd#github-repository)) + +![](images/0001_NewRepo.png) + +
+ +--- + +For this week, let's set this new repository up as a private repository, and call it Week2. This will keep things consistent with the file.paths we will be showing in the examples. + +![](images/0002_PrivateRepo.png) + +
+ +--- + +Once the new repository has been created, copy the URL. + +![](images/0003_Url.png) + +
+ +--- + +Next, open up Positron, set the interpreter to use R, and then select the option to bring in a "New Folder from Git". + +![](images/0004_NewGit.png) + +
+ +--- + +Paste in your new repository's url. Additionally, if you want to match file.paths shown in the examples, set your storage location to your local Documents folder (please note the start of the file.path will look differently depending on whether you are on Windows, MacOS, or Linux). + +![](images/0005_SaveDocuments.png) + +
+ +--- + +Your new repository will then be imported from GitHub. Once this is done, create two subfolders (data and images) and a new .qmd file (naming it filepaths.qmd). + +![](images/0006_BasicInfrastructure.png) + +
+ +--- + +### Sync + +With this done, return to GitHub and open your [forked version](/course/00_GitHub/index.qmd#forking-cytometryinr) of the CytometryInR course folder. If you haven't yet done so, click on [sync](/course/00_Homeworks/index.qmd#sync-your-fork) to bring in this week's code and datasets. + +![](images/0008_Sync.png) + +
+ +--- + +Returning to Positron, you will need to switch Project Folders, switching from Week2 over to CytometryInR. + +![](images/0007_SwitchFolders.png) + +
+ +--- + +### Pull + +Once CytometryInR project folder has opened, you will need to [pull](/course/00_Git/index.qmd#pull) in the new data from GitHub to your local computer. + +![](images/0007_PullCytometryInR.png) + +
+ +--- + +### Copy Files to Week2 + +Once this is done, you will see within the course folder, containing this weeks folder (02_FilePaths). Within it there is a data folder with .fcs files. To avoid causing conflicts when bringing in next week's materials, you will want to manually copy over these .fcs files (via your File Explorer) to the data folder within your "Week2" Project Folder. + +![](images/0009_Copy.png) + +
+ +--- + +### Commit and Push + +When you reopen your Week2 project folder in Positron, you should now be able to see the .fcs files within the data folder. Next, from the action bar on the far left, select the Source Control tab. Stage all the changes (as was done in [Using Git](/course/00_Git/)), and write a short commit message. + +![](images/0010_Commit.png) + +
+ +--- + +With these files now being tracked by version control, push (ie. send) your changes to GitHub so that they are remotely backed up. + +![](images/0011_Push.png) + +
+ +--- + +And with this setup complete, you are now ready to proceed. Remember, run code and write notes in your working project folder (Week2 or otherwise named) to avoid conflicts next week in the CytometryInR folder when you are trying to bring in the Week #3 code and datasets. + +
+ +--- + +# Walk Through + +## Working Directory + +Now that we are back in our Week2 folder, let's start by seeing our current location similarly to how our computer perceives it. + +We will use `getwd()` function (ie. get working directory) to return the location of the folder we are currently inside of. For example, when `getwd()` is run within my Week2 project folder, I see the following location + +```{r} +#| eval: FALSE +getwd() +``` + +![](images/0000_ReplacementGetWD.png) + +This returns a file path. The final location (Week2 in this case) is the **Working Directory**. Your computer when working in R will be descern other locations in relation to this directory. + +
+ +--- + +## Directories + +Within this working directory, we have a variety of project folders and files related to the course. We can see the folders that are present using the `list.dirs()` function. + +```{r} +#| eval: FALSE +list.dirs(path=".", full.names=FALSE, recursive=FALSE) +``` + +![](images/0000_ReplacementListFiles.png) + +Within this `list.dirs()` function, we are specifying two arguments with which we will be working with later today, *full.names* and *recursive*. For now, lets set their arguments to FALSE, which means they conditions they implement are inactive (turned off). + +
+ +--- + +The path argument is currently set to ".", which is a stand-in for the present directory. In R, if an argument is not specified directly, it is inferred based on an order of expected arguments. Thus, if not present, we could still get the same output as seen before. + +```{r} +#| eval: FALSE +list.dirs(full.names=FALSE, recursive=FALSE) +``` + +![](images/0000_ReplacementListFiles.png) + +
+ +--- + +Within Positron, in addition to visible folders, we also have *hidden folders* (denoted by the "." in front of the folder name when using `list.dirs()`). In the case of one of our course website folders, we can see a ".quarto" folder shown in a lighter gray . The ".git" folder we saw from `list.dirs()` is typically hidden when viewing from Positron. + +![](images/02_HiddenFolder.png) + +In the case of Week2, the two not-hidden folders we created are listed. We will see how to navigate these in a second. + +
+ +--- + +![](images/0000_ReplacementView.png) + +
+ +--- + +## Variables + +Before exploring file paths, we need to have some basic R code knowledge that we can use to work with them. Within R, we have the ability to assign particular values (be they character strings, numbers or logicals) to objects (ie. variables) that can be used when called upon later. + +For example: + +```{r} +#| eval: FALSE +WhatDayDidIWriteThis <- "Saturday" +``` + +In this case, the variable name is what the assignment arrow ("<-") is pointing at. In this case, WhatDayDidIWriteThis + +
+ +--- + +When we run this, we create a variable, that will appear within the right-sidebar. + +```{r} +#| eval: TRUE +WhatDayDidIWriteThis <- "Saturday" +``` + +![](images/04_VariableList.png) + +
+ +--- + +These variables can subsequently be retrieved by printing (ie. running) the name of the variable + +```{r} +WhatDayDidIWriteThis +``` + +
+ +--- + +You can create variables with almost any name you can think of + +```{r} +TopSecretMeetingDay <- "Saturday" +``` + +
+ +--- + +With a few exceptions. R doesn't play well with spaces: + +```{r} +#| error: TRUE +Top Secret Meeting Day <- "Saturday" +``` + +
+ +--- + +But does play well with underscores: + +```{r} +Top_Secret_Meeting_Day <- "Saturday" +``` + +
+ +--- + +The above (with individual words separated by _) is collectively known as snake case. The alternate way to help delineate variable names is "camelCase", with first letter of each word being capitalized (seen in the previous example). + +![](images/CamelCase.jpeg) + +
+ +--- + +```{r} +TopSecretMeetingDay +``` + +
+ +--- + +You can overwrite a Variable name by assigning a different value to it: + +```{r} +TopSecretMeetingDay <- "Monday" +``` + +```{r} +TopSecretMeetingDay +``` + +
+ +--- + +You can also remove individual variables via the `rm` function + +```{r} +rm(Top_Secret_Meeting_Day) +``` + +
+ +--- + +Or if trying to remove all, via the right sidebar + +![](images/10_RemoveVariables.png) + + +
+ +--- + +In the prior case, we are creating a variable that is a "string" of character values, due to our use of "" around the word. We can see this when we use the `str()` function. + +```{r} +Fluorophores <- "FITC" +str(Fluorophores) +``` + +The "chr" in front denotating that Fluorophores contains a character string. + +
+ +--- + +This could also be retrieved using the `class()` function. + +```{r} +class(Fluorophores) +``` + +
+ +--- + +Alternatively, we could assign a numeric value to a variable + +```{r} +Fluorophores <- 29 +str(Fluorophores) +``` + +Which returns "num", ie. numeric. + +
+ +--- + +We can also specify a logical (ie. True or FALSE) to a particular object + +```{r} +IsPerCPCy5AGoodFluorophore <- FALSE +str(IsPerCPCy5AGoodFluorophore) +``` + +Which returns logi in front, denoting this variable contains a logical value. + +
+ +--- + +Last week, when we were installing `dplyr`, the reason that installation failed was `install.packages()` expects a character string. However, when we left off the "", it looked within our local environments created variables for the dplyr variable, couldn't find it, and thus failed. + +We could of course, have assigned a character value to a variable name, and then used that variable name, which would have worked. + +```{r} +#| eval: FALSE + +PackageToInstall <- "dplyr" + +install.packages(PackageToInstall) +``` + +
+ +--- + +## Indexing + +Not all variables contain single objects. + +For example, we can modify Fluorophores and add additional entries: + +```{r} +Fluorophores <- c("BV421", "FITC", "PE", "APC") +str(Fluorophores) +``` + +The c stands for concatenate. It concatenates the objects into a larger object, known as a vector. + +In this case, you notice in addition to the specification the values are characters, we get a [1:4], denoting four objects are present. + +
+ +--- + +We can similarly retrieve this information using the `length()` function + +```{r} +length(Fluorophores) +``` + +
+ +--- + +When multiple objects are present, we can specify them individidually by providing their index number within square brackets []. + +```{r} +Fluorophores[1] +``` + +
+ +--- + +```{r} +Fluorophores[3] +``` + +
+ +--- + +Or specify in sequence using a colon (:) + +```{r} +Fluorophores[3:4] +``` + +
+ +--- + +Or if not adjacent, reusing `c` within the square brackets + +```{r} +Fluorophores[c(1,4)] +``` + +
+ +--- + +We will revisit these concepts throughout the course, with what we have covered today, this will help us create file.paths and select fcs files that we want to work with via index number. + +## Listing Files + +After this detour into variables and indexing, let's return our focus to how to use these in context of file paths. Working from within our Week2 project folder, let's see what directories (folders) are present + +```{r} +#| eval: FALSE +list.dirs(path=".", full.names=FALSE, recursive=FALSE) +``` + +![](images/00.png) + +
+ +--- + +We can also list any files that are present within our working directory using the `list.files()` function. + +```{r} +#| eval: FALSE +list.files() +``` + +![](images/01.png) + +In this case, in addition to our filepaths.qmd file, we can see the LICENSE and README files created when we set up the repository. + +
+ +--- + +We can also specify a particular folder we want to show items present within by changing the path argument. For example, if we wanted to see the contents of the "data" folder + +```{r} +#| eval: FALSE +list.files(path="data", full.names=FALSE, recursive=FALSE) +``` + +![](images/02.png) + +Which in this case returns the fcs files we copied over at the start of this lesson. + +
+ +--- + +In this case, there are no folders under "data". Let's go ahead and create a new one, calling it target. + +![](images/03.png) + +
+ +--- + +## Creating directories + +Alternatively, we can also create a folder via R using the `dir.create()` function. Since we want it within data, we would modify the path accordingly + +```{r} +#| eval: FALSE +NewFolderLocation <- file.path("data", "target2") + +dir.create(path=NewFolderLocation) +``` + +![](images/04.png) + +
+ +--- + +Before continuing, let's copy the first two .fcs files into both target and target2. + +
+ +![](images/06.png) + +--- + +Given our working directory is set the top-level of the Week2 project folder, we can't just check inside nested target folders directly. If we attempt to: + +```{r} +list.files(path="target", full.names=FALSE, recursive=FALSE) +``` + +
+ +--- + +No files are returned (ie, character(0)), since from our computers perspective, "target" doesn't exist within the active working directory. + +```{r} +file.exists("target") +``` + +
+ +--- + +On the other hand, within it's view, it knows that the data folder exist + +```{r} +#| eval: FALSE +file.exists("data") +``` + +![](images/05.png) + +So here we encounter the first challenge when communicating to our computer where to search for and find files. We need to provide a file.path that incorporates the path of folders between where the computer is currently at (ie. the working directory) and the target file itself. + +
+ +--- + +## File Paths + +One way we can do this is through a file.path argument. We could potentially provide this by adding either a / or a \ into the path argument, depending on your computers operating system. + +```{r} +#| eval: FALSE +list.files(path="data/target", full.names=FALSE, recursive=FALSE) +``` + +![](images/07.png) + +
+ +While this works in your particular context, if you are sharing the code with others who have a different operating system, these hard-coded "/" or "\" will cause the code for them to error out at these particular steps. + +--- + +For that reason, it is better to assemble a file.path using the `file.path()` function. This function takes into account the operating system, removing your need to have to worry about this particular computing nuance, and write code that is reproducible and replicable for everyone. + +```{r} +FolderLocation <- file.path("data", "target") +FolderLocation +``` + +```{r} +#| eval: FALSE +list.files(path=FolderLocation, full.names=FALSE, recursive=FALSE) +``` + +![](images/07.png) + +
+ +--- + +We can also append additional locations to existing file paths, by including the variable name within the `file.path()` we are creating. + +```{r} +FolderLocation <- "data" +ScreenshotFolder <- file.path(FolderLocation, "target") +ScreenshotFolder +``` + +```{r} +#| eval: FALSE + +list.files(path=ScreenshotFolder, full.names=FALSE, recursive=FALSE) +``` + +![](images/07.png) + +
+ +--- + +Additionally, `list.files()` has the ability to filter for files that contain a particular character string. This can be useful is we are searching for ".fcs" or ".csv" files, but also for files that contain a particular word. In the case of the ScreenshotFolders + +```{r} +#| eval: FALSE +list.files(path=ScreenshotFolder, pattern="ND050", full.names=FALSE, recursive=FALSE) +``` + +![](images/08.png) + +You will notice, the index numbers are in the context of what is filtered, not all the folder contents. + +
+ +--- + +## Selecting for Patterns + +If we currently listed the files within data, we get a return that looks like this: + +```{r} +#| eval: FALSE +list.files("data", full.names=FALSE, recursive=FALSE) +``` + +![](images/09.png) + +
+ +--- + +As you can see, we are getting back both folders and individual .fcs files. We could consequently change the pattern to provide a character string that will only return the .fcs files. We will go ahead and assign this list to a variable named files, for later retrieval. + +```{r} +#| eval: FALSE +files <- list.files("data", pattern=".fcs", full.names=FALSE, recursive=FALSE) +files +``` + +![](images/10.png) + +
+ +--- + +One of the R packages we will be using througout the course is the `stringr` package. It contains two functions that can be useful when identifying more complicated character strings. In this case, if we run the `str_detect()` function to identify which of the .fcs files within the files variable contains the "INF" character string, we get a vector of logical (ie. True or FALSE) outputs corresponding to each file. + +```{r} +# install.packages("stringr") # CRAN +library(stringr) +``` + +```{r} +#| eval: FALSE +str_detect(files, "INF") +``` + +![](images/11.png) + +
+ +--- + +Similar to how we indexed the Fluorophore list (ex. Fluorophore[1:2]) which returned a subset, we can similarly use this logical vector to subset files that returned as TRUE for containing the pattern "INF" + +```{r} +#| eval: FALSE +files[str_detect(files, "INF")] +``` + +![](images/12.png) + +
+ +--- + +Let's go ahead and save these subsetted file names to a new variable, called Infants. + +```{r} +#| eval: FALSE +Infants <- files[str_detect(files, "INF")] +``` + +## Conditionals + +One useful thing is that within R, we can set conditions on whether something is carried out. The most typical conditional you will encounter are the "If" statements. They typically take a form that resembles the following. + +```{r} +#| eval: FALSE + +NeedCoffee <- TRUE + +if (NeedCoffee){ + print("Take a break") +} +``` + +
+ +--- + +In this case of the above, if the variable within the () is equal to true, the code within the {} will be executed. + +```{r} + +NeedCoffee <- TRUE + +if (NeedCoffee){ + print("Take a break") +} +``` + +
+ +--- + +By contrast, when the variable within the () is equal to false, the code within the {} will not be executed. + +```{r} +NeedCoffee <- FALSE + +if (NeedCoffee){ + print("Take a break") +} +``` + +
+ +--- + +These "If" statements will trigger as long as the specified condition within the () is TRUE. For a different example: + +```{r} +RowNumber <- 299 +2 + RowNumber > 300 +``` + +```{r} +if (2 + RowNumber > 3){ + print("Stop Iterating") +} +``` + +
+ +--- + +When you add an ! in front a conditional, it flips the expected outcome. + +```{r} +ItsRaining <- TRUE + +if (ItsRaining){print("Bring an Umbrella")} +``` + +```{r} +!ItsRaining +``` + +```{r} +if (!ItsRaining){print("Bring an Umbrella")} +``` + +```{r} +ItsRaining <- TRUE + +if (!ItsRaining){print("Bring Sunglasses")} + +``` + +
+ +--- + +We will explore more complicated conditionals throughout the course, but for now, let's implement a couple simple ones in the context of copying over the .fcs files in Infants over to a new target3 folder. + +## Conditionals in practice + +First off, let's write a conditional to check if there is a target3 folder within data. + +```{r} +#| eval: FALSE +files_present <- list.files("data", full.names=FALSE, recursive=FALSE) +files_present +``` + +![](images/13.png) + +
+ +--- + +```{r} +#| eval: FALSE + +FolderTarget3 <- file.path("data", "target3") +dir.exists(FolderTarget3) +``` + +![](images/14.png) + +
+ +--- + +We can write a conditional to create a folder if one does not yet exist. + +```{r} +#| eval: FALSE +if (!dir.exists(FolderTarget3)){ + dir.create(FolderTarget3) +} +``` + +![](images/15.png) + +
+ +--- + +## Copying Files + +To copy files to another folder location, we use the `file.copy()` function. It has two arguments that we will be working with, from being the .fcs files, and to being the folder location we wish to transfer them to. If we tried using them as we currently have them: + +```{r} +#| eval: FALSE + +# Variable Infants containing 4 .fcs file names + +file.copy(from=Infants, to=FolderTarget3) +``` + +![](images/16.png) + +
+ +--- + +The reason for this error is we are only working with a partial file path, as viewed from our Working directory. In this case, what is needed is the full file.path, so the file.path should also include the upstream folders from your current working directory. + +```{r} +#| eval: FALSE +getwd() +``` + +![](images/17.png) + +
+ +--- + + +In this case, we can update the .fcs files location by switching the full.names argument within `list.files()` from FALSE, to TRUE. + +```{r} +#| eval: FALSE +files_present <- list.files("data", full.names=TRUE, recursive=FALSE) +files_present +``` + +![](images/18.png) + +And filter for those containing "INF" again + +```{r} +#| eval: FALSE +Infants <- files_present[str_detect(files_present, "INF")] +``` + +And then try again: + +```{r} +#| eval: FALSE + +# Variable Infants containing 4 .fcs file names + +file.copy(from=Infants, to=FolderTarget3) +``` + +![](images/19.png) + +
+ +--- + +## Removing files. + +Just like we can add files via R, we can also remove them. However, when we remove them via this route, they are removed permanently, not sent to the recycle bin. We will revisit how later on in the course after you have gained additional experience with file.paths. + +```{r} +#| eval: FALSE +?unlink() +``` + +## Basename + +If we look at Infants with the full.names=TRUE, we see the additional pathing folder has been added, allowing us to successfully copy over the files. + +```{r} +#| eval: FALSE +Infants +``` + +![](images/20.png) + +
+ +--- + +If we were trying to retrieve just the local file names from the full.names, we could do so with `basename()` function. We will use this in combination with additional arguments later in the course + +```{r} +#| eval: FALSE + +basename(Infants) +``` + +![](images/22.png) + +## Recursive + +And finally that we have created additional nested folders and populated them with fcs files, let's see what setting `list.files()` recursive argument to TRUE + +```{r} +#| eval: FALSE +all_files_present <- list.files(full.names=TRUE, recursive=TRUE) +all_files_present +``` + +![](images/RecursiveTrue.png) + +
+ +--- + +In this case, all files in all folders within the working directory are shown. This can be useful when exploring folder contents, but if there are a lot of files present within the folder, it will take a while to return the list. + +
+ +--- + + +## Saving changes to Version Control + +And as is good practice, to maintain version control, let's stage all the files and folders we created today within the Week2 Project Folder, write a commit message, and send these files back to GitHub until they are needed again next time. + +![](images/23.png) + +--- + +# Wrap-Up + +In this session, we started to learn about working directories, file.paths and how to locate files of interest. We also learned how variables (objects) are created in R using the assignment arrow, how they are named, and the general structure (character, numeric, logical) that they are represented as. + +This will prove valuable in the next several weeks when working with .fcs files, as the majority of functions we will use for Bioconductor project R packages need file.paths to locate both .fcs files as well as .csv files that contain metadata. + +One of the most frequent errors that beginners encounter when trying to load in .fcs files into the `flowCore` package is not providing the full file.path to the .fcs file of interest. + +Next week, having installed the required R packages, and learned a little about variables and file.paths, we will dive into our first cytometry focused session. We will be cracking open an .fcs file and exploring how things are stored within. In the process of seeing how the file contents are organized, we will continue to learn and practice how to create variables, and general object structure types within R. Until then, have a wonderful week! + +![](images/Week2Exit.jpg) + +# Additional Resources + +[Riffomonas: Using paths in R and why you shouldn't be using setwd (CC179)](https://youtu.be/StqDYjM6ULo?si=ba2on5rNphQ9AL-B) + +[Project-oriented workflow](https://tidyverse.org/blog/2017/12/workflow-vs-script/) + +[Paths, working directories, and projects in R; Learn R Video 13](https://youtu.be/lJcuXBFP7Co?si=dqptQ3UGGjmTYqnB) + +[Demystifying File Paths in R: Navigate Nested Folders with Dr. Padilla](https://youtu.be/yeiT5Kj_uG8?si=UySsolzbTxbgGMF6) + +# Take-home Problems + +:::{.callout-tip title="Problem 1"} +Plug in an external hard-drive or USB into your computer. Manually, create a folder within called "TargetFolder". Try to programmatically specify the file path to identify the folders and files present on your external drive. Then, try to copy your .fcs files from their current folder on your desktop to the TargetFolder on your drive using R. Remember, just copy, no deletion, you need to walk before you can run :D +::: + +:::{.callout-tip title="Problem 2"} +In this session, we used `list.files()` with the "full.names argument" set to TRUE, as well as the `basename()` function to identify specific files. But what if you wanted a particular directory. Run `list.files()` with "full.names argument" and "recursive" argument set to TRUE, and then search online to find an R function that would retrieve the "" individual directory folders. +::: + +:::{.callout-tip title="Problem 3"} +R packages often come with internal datasets, that are typically used for use in the help documentation examples. These can be accessed through the use of the `system.file()` function. See an example below. + +```{r} +#| eval: FALSE +system.file("extdata", package = "FlowSOM") +``` + +Using what we have learned about file.path navigation, search your way down the file.directory of the `FlowSOM` and `flowWorkspace` packages, and identify any .fcs files that are present for use in the documentation. +::: + + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +::: diff --git a/course/02_FilePaths/slides.qmd b/course/02_FilePaths/slides.qmd index eb30bfc..76ee3b0 100644 --- a/course/02_FilePaths/slides.qmd +++ b/course/02_FilePaths/slides.qmd @@ -1,1723 +1,1723 @@ ---- -title: "02 - File Paths" -author: "David Rach" -date: 02-16-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Welcome to the second week of [Cytometry in R](/Schedule.qmd)! This week we will learn about file.path, namely, how to communicate to our computer (and R) where various files are stored. -::: -::: - -::: {.fragment} -:::{.callout-important} -Before getting started, please make sure you have completed the creating a [GitHub](/course/00_GitHub/index.qmd) and [Workstation Setup](/course/00_WorkstationSetup/index.qmd) walk-throughs, since we will begin where they left off once the required software was successfully installed. Having read-through how to use [version control](/course/00_Git/index.qmd) using Git will additionally be useful. -::: -::: - ---- - -# Background - -```{r} -#| include: FALSE -library(BiocStyle) -``` - - -::: {.fragment} -::: {.callout-tip title="."} -When flow cytometrist first start learning how to code, we tend to think big picture: "I want to take my files, normalize them, cluster them, analyze them, and finally plot them". When we first start writing code, we tend to plan what we will write in similarly broad strokes. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Our computers by contrast "think" in small incremental steps: "First locate this folder, list the files present, select these specific ones, import them into R, load the normalization package, pass the first file in, etc.". These steps when combined algorithmically add up to form the bigger picture. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The challenge when first starting to learn how to code is developing a coding mindset in which we think not in broad strokes, but about what the next step will be programmatically. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will start working on our own "coding mindsets" by working with file paths, as they communicate to our computer where to find our experiment files, and tend to be one of the early points of conflict and frustration. In the process, we will also cover additional concepts of R programming generally, including how to create/name variables, and look up the class/type of a particular object. -::: -::: - ---- - -## Set Up - - -::: {.fragment} -::: {.callout-tip title="."} -Before we begin, let's make sure you get the data needed for today transferred to your local computer, and then get the .fcs files copied over from there to your own working project folder. This is the process you will repeat each week throughout the course. -::: -::: - ---- - -### New Repository - -::: {.fragment} -::: {.callout-tip title="."} -First off, login to your GitHub account. Once there, you will select the options to create a new repository (similar to what you did during [Using GitHub](/course/00_GitHub/index.qmd#github-repository)) -::: -::: - ---- - -![](images/0001_NewRepo.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For this week, let's set this new repository up as a private repository, and call it Week2. This will keep things consistent with the file.paths we will be showing in the examples. -::: -::: - ---- - -![](images/0002_PrivateRepo.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Once the new repository has been created, copy the URL. -::: -::: - ---- - -![](images/0003_Url.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next, open up Positron, set the interpreter to use R, and then select the option to bring in a "New Folder from Git". -::: -::: - ---- - -![](images/0004_NewGit.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Paste in your new repository's url. Additionally, if you want to match file.paths shown in the examples, set your storage location to your local Documents folder (please note the start of the file.path will look differently depending on whether you are on Windows, MacOS, or Linux). -::: -::: - ---- - -![](images/0005_SaveDocuments.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Your new repository will then be imported from GitHub. Once this is done, create two subfolders (data and images) and a new .qmd file (naming it filepaths.qmd). -::: -::: - ---- - -![](images/0006_BasicInfrastructure.png) - ---- - -### Sync - -::: {.fragment} -::: {.callout-tip title="."} -With this done, return to GitHub and open your [forked version](/course/00_GitHub/index.qmd#forking-cytometryinr) of the CytometryInR course folder. If you haven't yet done so, click on [sync](/course/00_Homeworks/index.qmd#sync-your-fork) to bring in this week's code and datasets. -::: -::: - ---- - -![](images/0008_Sync.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Returning to Positron, you will need to switch Project Folders, switching from Week2 over to CytometryInR. -::: -::: - ---- - -![](images/0007_SwitchFolders.png) - ---- - -### Pull - -::: {.fragment} -::: {.callout-tip title="."} -Once CytometryInR project folder has opened, you will need to [pull](/course/00_Git/index.qmd#pull) in the new data from GitHub to your local computer. -::: -::: - ---- - -![](images/0007_PullCytometryInR.png) - ---- - -### Copy Files to Week2 - -::: {.fragment} -::: {.callout-tip title="."} -Once this is done, you will see within the course folder, containing this weeks folder (02_FilePaths). Within it there is a data folder with .fcs files. To avoid causing conflicts when bringing in next week's materials, you will want to manually copy over these .fcs files (via your File Explorer) to the data folder within your "Week2" Project Folder. -::: -::: - ---- - -![](images/0009_Copy.png) - ---- - -### Commit and Push - - -::: {.fragment} -::: {.callout-tip title="."} -When you reopen your Week2 project folder in Positron, you should now be able to see the .fcs files within the data folder. Next, from the action bar on the far left, select the Source Control tab. Stage all the changes (as was done in [Using Git](/course/00_Git/)), and write a short commit message. -::: -::: - ---- - -![](images/0010_Commit.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -With these files now being tracked by version control, push (ie. send) your changes to GitHub so that they are remotely backed up. -::: -::: - ---- - -![](images/0011_Push.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And with this setup complete, you are now ready to proceed. Remember, run code and write notes in your working project folder (Week2 or otherwise named) to avoid conflicts next week in the CytometryInR folder when you are trying to bring in the Week #3 code and datasets. -::: -::: - ---- - -# Walk Through - -## Working Directory - -::: {.fragment} -::: {.callout-tip title="."} -Now that we are back in our Week2 folder, let's start by seeing our current location similarly to how our computer perceives it. - -We will use `getwd()` function (ie. get working directory) to return the location of the folder we are currently inside of. For example, when `getwd()` is run within my Week2 project folder, I see the following location -::: -::: - ---- - -```{r} -#| eval: FALSE -getwd() -``` - -![](images/0000_ReplacementGetWD.png) - -::: {.fragment} -::: {.callout-tip title="."} - -This returns a file path. The final location (Week2 in this case) is the **Working Directory**. Your computer when working in R will be descern other locations in relation to this directory. - -::: -::: - ---- - -## Directories - -::: {.fragment} -::: {.callout-tip title="."} -Within this working directory, we have a variety of project folders and files related to the course. We can see the folders that are present using the `list.dirs()` function. -::: -::: - -::: {.fragment} -![](images/0000_ReplacementView.png) -::: - -::: fragment -```{r} -#| eval: FALSE -list.dirs(path=".", full.names=FALSE, recursive=FALSE) -``` - -![](images/0000_ReplacementListFiles.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Within this `list.dirs()` function, we are specifying two arguments with which we will be working with later today, *full.names* and *recursive*. For now, lets set their arguments to FALSE, which means they conditions they implement are inactive (turned off). -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The path argument is currently set to ".", which is a stand-in for the present directory. In R, if an argument is not specified directly, it is inferred based on an order of expected arguments. Thus, if not present, we could still get the same output as seen before. -::: -::: - -::: {.fragment} -```{r} -#| eval: FALSE -list.dirs(full.names=FALSE, recursive=FALSE) -``` - -![](images/0000_ReplacementListFiles.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Within Positron, in addition to visible folders, we also have *hidden folders* (denoted by the "." in front of the folder name when using `list.dirs()`). In the case of one of our course website folders, we can see a ".quarto" folder shown in a lighter gray . The ".git" folder we saw from `list.dirs()` is typically hidden when viewing from Positron. -::: -::: - -::: {.fragment} - -![](images/02_HiddenFolder.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In the case of Week2, the two not-hidden folders we created are listed. We will see how to navigate these in a second. -::: -::: - -::: {.fragment} - -![](images/0000_ReplacementView.png) - -::: - ---- - -## Variables - -::: {.fragment} -::: {.callout-tip title="."} -Before exploring file paths, we need to have some basic R code knowledge that we can use to work with them. Within R, we have the ability to assign particular values (be they character strings, numbers or logicals) to objects (ie. variables) that can be used when called upon later. - -For example: - -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -WhatDayDidIWriteThis <- "Saturday" -``` -::: - -::: {.fragment} -::: {.callout-tip title="."} -In this case, the variable name is what the assignment arrow ("<-") is pointing at. In this case, WhatDayDidIWriteThis -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When we run this, we create a variable, that will appear within the right-sidebar. -::: -::: - -::: {.fragment} - -```{r} -#| eval: TRUE -WhatDayDidIWriteThis <- "Saturday" -``` - -::: - ---- - -![](images/04_VariableList.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -These variables can subsequently be retrieved by printing (ie. running) the name of the variable -::: -::: - -::: {.fragment} - -```{r} -WhatDayDidIWriteThis -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You can create variables with almost any name you can think of -::: -::: - -::: {.fragment} - -```{r} -TopSecretMeetingDay <- "Saturday" -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -With a few exceptions. R doesn't play well with spaces: -::: -::: - -::: {.fragment} - -```{r} -#| error: TRUE -Top Secret Meeting Day <- "Saturday" -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -But does play well with underscores: -::: -::: - -::: {.fragment} - -```{r} -Top_Secret_Meeting_Day <- "Saturday" -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The above (with individual words separated by _) is collectively known as snake case. The alternate way to help delineate variable names is "camelCase", with first letter of each word being capitalized (seen in the previous example). -::: -::: - ---- - -![](images/CamelCase.jpeg) - ---- - -```{r} -TopSecretMeetingDay -``` - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You can overwrite a Variable name by assigning a different value to it: -::: -::: - -::: {.fragment} - -```{r} -TopSecretMeetingDay <- "Monday" -``` - -::: - -::: {.fragment} - -```{r} -TopSecretMeetingDay -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You can also remove individual variables via the `rm` function -::: -::: - -::: {.fragment} - -```{r} -rm(Top_Secret_Meeting_Day) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Or if trying to remove all, via the right sidebar -::: -::: - ---- - -![](images/10_RemoveVariables.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In the prior case, we are creating a variable that is a "string" of character values, due to our use of "" around the word. We can see this when we use the `str()` function. -::: -::: - -::: {.fragment} - -```{r} -Fluorophores <- "FITC" -str(Fluorophores) -``` - -::: - -::: {.fragment} -::: {.callout-tip title="."} -The "chr" in front denotating that Fluorophores contains a character string. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -This could also be retrieved using the `class()` function. -::: -::: - -::: {.fragment} - -```{r} -class(Fluorophores) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Alternatively, we could assign a numeric value to a variable -::: -::: - -::: {.fragment} - -```{r} -Fluorophores <- 29 -str(Fluorophores) -``` - -::: - -::: {.fragment} -::: {.callout-tip title="."} -Which returns "num", ie. numeric. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can also specify a logical (ie. True or FALSE) to a particular object -::: -::: - -::: {.fragment} - -```{r} -IsPerCPCy5AGoodFluorophore <- FALSE -str(IsPerCPCy5AGoodFluorophore) -``` - -::: - -::: {.fragment} -::: {.callout-tip title="."} -Which returns logi in front, denoting this variable contains a logical value. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Last week, when we were installing `dplyr`, the reason that installation failed was `install.packages()` expects a character string. However, when we left off the "", it looked within our local environments created variables for the dplyr variable, couldn't find it, and thus failed. - -We could of course, have assigned a character value to a variable name, and then used that variable name, which would have worked. -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE - -PackageToInstall <- "dplyr" - -install.packages(PackageToInstall) -``` - -::: - ---- - -## Indexing - -::: {.fragment} -::: {.callout-tip title="."} -Not all variables contain single objects. - -For example, we can modify Fluorophores and add additional entries: -::: -::: - -::: {.fragment} - -```{r} -Fluorophores <- c("BV421", "FITC", "PE", "APC") -str(Fluorophores) -``` - -::: - -::: {.fragment} -::: {.callout-tip title="."} -The c stands for concatenate. It concatenates the objects into a larger object, known as a vector. - -In this case, you notice in addition to the specification the values are characters, we get a [1:4], denoting four objects are present. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can similarly retrieve this information using the `length()` function -::: -::: - -::: {.fragment} - -```{r} -length(Fluorophores) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When multiple objects are present, we can specify them individidually by providing their index number within square brackets []. -::: -::: - - -::: {.fragment} - -```{r} -Fluorophores[1] -``` - -::: - ---- - -::: {.fragment} - -```{r} -Fluorophores[3] -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Or specify in sequence using a colon (:) -::: -::: - -::: {.fragment} - -```{r} -Fluorophores[3:4] -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Or if not adjacent, reusing `c` within the square brackets -::: -::: - -::: {.fragment} - -```{r} -Fluorophores[c(1,4)] -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will revisit these concepts throughout the course, with what we have covered today, this will help us create file.paths and select fcs files that we want to work with via index number. -::: -::: - -## Listing Files - -::: {.fragment} -::: {.callout-tip title="."} -After this detour into variables and indexing, let's return our focus to how to use these in context of file paths. Working from within our Week2 project folder, let's see what directories (folders) are present -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -list.dirs(path=".", full.names=FALSE, recursive=FALSE) -``` - -::: - -::: {.fragment} - -![](images/00.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can also list any files that are present within our working directory using the `list.files()` function. -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -list.files() -``` - -::: - -::: {.fragment} - -![](images/01.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In this case, in addition to our filepaths.qmd file, we can see the LICENSE and README files created when we set up the repository. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can also specify a particular folder we want to show items present within by changing the path argument. For example, if we wanted to see the contents of the "data" folder -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -list.files(path="data", full.names=FALSE, recursive=FALSE) -``` - -::: - -::: {.fragment} - -![](images/02.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Which in this case returns the fcs files we copied over at the start of this lesson. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In this case, there are no folders under "data". Let's go ahead and create a new one, calling it target. -::: -::: - ---- - -![](images/03.png) - ---- - -## Creating directories - -::: {.fragment} -::: {.callout-tip title="."} -Alternatively, we can also create a folder via R using the `dir.create()` function. Since we want it within data, we would modify the path accordingly -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -NewFolderLocation <- file.path("data", "target2") - -dir.create(path=NewFolderLocation) -``` - -::: - ---- - -![](images/04.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Before continuing, let's copy the first two .fcs files into both target and target2. -::: -::: - ---- - -![](images/06.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Given our working directory is set the top-level of the Week2 project folder, we can't just check inside nested target folders directly. If we attempt to: -::: -::: - -::: {.fragment} - -```{r} -list.files(path="target", full.names=FALSE, recursive=FALSE) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -No files are returned (ie, character(0)), since from our computers perspective, "target" doesn't exist within the active working directory. -::: -::: - -::: {.fragment} - -```{r} -file.exists("target") -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -On the other hand, within it's view, it knows that the data folder exist -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -file.exists("data") -``` - -::: - -::: {.fragment} - -![](images/05.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -So here we encounter the first challenge when communicating to our computer where to search for and find files. We need to provide a file.path that incorporates the path of folders between where the computer is currently at (ie. the working directory) and the target file itself. -::: -::: - ---- - -## File Paths - -::: {.fragment} -::: {.callout-tip title="."} -One way we can do this is through a file.path argument. We could potentially provide this by adding either a "/" or a "\" into the path argument, depending on your computers operating system. -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -list.files(path="data/target", full.names=FALSE, recursive=FALSE) -``` - -::: - -::: {.fragment} - -![](images/07.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -While this works in your particular context, if you are sharing the code with others who have a different operating system, these hard-coded / or \ will cause the code for them to error out at these particular steps. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For that reason, it is better to assemble a file.path using the `file.path()` function. This function takes into account the operating system, removing your need to have to worry about this particular computing nuance, and write code that is reproducible and replicable for everyone. -::: -::: - -::: {.fragment} - -```{r} -FolderLocation <- file.path("data", "target") -FolderLocation -``` - -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -list.files(path=FolderLocation, full.names=FALSE, recursive=FALSE) -``` - -::: - -::: {.fragment} - -![](images/07.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can also append additional locations to existing file paths, by including the variable name within the `file.path()` we are creating. -::: -::: - -::: {.fragment} - -```{r} -FolderLocation <- "data" -ScreenshotFolder <- file.path(FolderLocation, "target") -ScreenshotFolder -``` - -::: - -::: {.fragment} - -```{r} -#| eval: FALSE - -list.files(path=ScreenshotFolder, full.names=FALSE, recursive=FALSE) -``` - -::: - -::: {.fragment} - -![](images/07.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Additionally, `list.files()` has the ability to filter for files that contain a particular character string. This can be useful is we are searching for ".fcs" or ".csv" files, but also for files that contain a particular word. In the case of the ScreenshotFolders -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -list.files(path=ScreenshotFolder, pattern="ND050", full.names=FALSE, recursive=FALSE) -``` - -::: - -::: {.fragment} - -![](images/08.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will notice, the index numbers are in the context of what is filtered, not all the folder contents. -::: -::: - ---- - -## Selecting for Patterns - -::: {.fragment} -::: {.callout-tip title="."} -If we currently listed the files within data, we get a return that looks like this: -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -list.files("data", full.names=FALSE, recursive=FALSE) -``` - -::: - -::: {.fragment} - -![](images/09.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -As you can see, we are getting back both folders and individual .fcs files. We could consequently change the pattern to provide a character string that will only return the .fcs files. We will go ahead and assign this list to a variable named files, for later retrieval. -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -files <- list.files("data", pattern=".fcs", full.names=FALSE, recursive=FALSE) -files -``` - -::: - -::: {.fragment} - -![](images/10.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -One of the R packages we will be using througout the course is the `stringr` package. It contains two functions that can be useful when identifying more complicated character strings. In this case, if we run the `str_detect()` function to identify which of the .fcs files within the files variable contains the "INF" character string, we get a vector of logical (ie. True or FALSE) outputs corresponding to each file. -::: -::: - -::: {.fragment} - -```{r} -# install.packages("stringr") # CRAN -library(stringr) -``` - -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -str_detect(files, "INF") -``` - -::: - -::: {.fragment} - -![](images/11.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Similar to how we indexed the Fluorophore list (ex. Fluorophore[1:2]) which returned a subset, we can similarly use this logical vector to subset files that returned as TRUE for containing the pattern "INF" -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -files[str_detect(files, "INF")] -``` - -::: - -::: {.fragment} - -![](images/12.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Let's go ahead and save these subsetted file names to a new variable, called Infants. -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -Infants <- files[str_detect(files, "INF")] -``` - -::: - -## Conditionals - -::: {.fragment} -::: {.callout-tip title="."} -One useful thing is that within R, we can set conditions on whether something is carried out. The most typical conditional you will encounter are the "If" statements. They typically take a form that resembles the following. -::: -::: - - -::: {.fragment} - -```{r} -#| eval: FALSE - -NeedCoffee <- TRUE - -if (NeedCoffee){ - print("Take a break") -} -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In this case of the above, if the variable within the () is equal to true, the code within the {} will be executed. -::: -::: - -::: {.fragment} - -```{r} - -NeedCoffee <- TRUE - -if (NeedCoffee){ - print("Take a break") -} -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -By contrast, when the variable within the () is equal to false, the code within the {} will not be executed. -::: -::: - -::: {.fragment} - -```{r} -NeedCoffee <- FALSE - -if (NeedCoffee){ - print("Take a break") -} -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -These "If" statements will trigger as long as the specified condition within the () is TRUE. For a different example: -::: -::: - -::: {.fragment} - -```{r} -RowNumber <- 299 -2 + RowNumber > 300 -``` - -::: - -::: {.fragment} - -```{r} -if (2 + RowNumber > 3){ - print("Stop Iterating") -} -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When you add an ! in front a conditional, it flips the expected outcome. -::: -::: - -::: {.fragment} - -```{r} -ItsRaining <- TRUE - -if (ItsRaining){print("Bring an Umbrella")} -``` - -::: - -::: {.fragment} - -```{r} -!ItsRaining -``` - -::: - -::: {.fragment} - -```{r} -if (!ItsRaining){print("Bring an Umbrella")} -``` - -::: - -::: {.fragment} - -```{r} -ItsRaining <- TRUE - -if (!ItsRaining){print("Bring Sunglasses")} - -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will explore more complicated conditionals throughout the course, but for now, let's implement a couple simple ones in the context of copying over the .fcs files in Infants over to a new target3 folder. -::: -::: - -## Conditionals in practice - -::: {.fragment} -::: {.callout-tip title="."} -First off, let's write a conditional to check if there is a target3 folder within data. -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -files_present <- list.files("data", full.names=FALSE, recursive=FALSE) -files_present -``` - -::: - -::: {.fragment} - -![](images/13.png) - -::: - ---- - -```{r} -#| eval: FALSE - -FolderTarget3 <- file.path("data", "target3") -dir.exists(FolderTarget3) -``` - -::: {.fragment} - -![](images/14.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can write a conditional to create a folder if one does not yet exist. -::: -::: - - -::: {.fragment} - -```{r} -#| eval: FALSE -if (!dir.exists(FolderTarget3)){ - dir.create(FolderTarget3) -} -``` - -::: - -::: {.fragment} - -![](images/15.png) - -::: - ---- - -## Copying Files - -::: {.fragment} -::: {.callout-tip title="."} -To copy files to another folder location, we use the `file.copy()` function. It has two arguments that we will be working with, from being the .fcs files, and to being the folder location we wish to transfer them to. If we tried using them as we currently have them: -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE - -# Variable Infants containing 4 .fcs file names - -file.copy(from=Infants, to=FolderTarget3) -``` - -::: - -::: {.fragment} - -![](images/16.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The reason for this error is we are only working with a partial file path, as viewed from our Working directory. In this case, what is needed is the full file.path, so the file.path should also include the upstream folders from your current working directory. -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -getwd() -``` - -::: - -::: {.fragment} - -![](images/17.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In this case, we can update the .fcs files location by switching the full.names argument within `list.files()` from FALSE, to TRUE. -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -files_present <- list.files("data", full.names=TRUE, recursive=FALSE) -files_present -``` - -::: - -::: {.fragment} - -![](images/18.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And filter for those containing "INF" again -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -Infants <- files_present[str_detect(files_present, "INF")] -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And then try again: -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE - -# Variable Infants containing 4 .fcs file names - -file.copy(from=Infants, to=FolderTarget3) -``` - -::: - -::: {.fragment} - -![](images/19.png) - -::: - ---- - -## Removing files. - -::: {.fragment} -::: {.callout-tip title="."} -Just like we can add files via R, we can also remove them. However, when we remove them via this route, they are removed permanently, not sent to the recycle bin. We will revisit how later on in the course after you have gained additional experience with file.paths. -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -?unlink() -``` - -::: - -## Basename - -::: {.fragment} -::: {.callout-tip title="."} -If we look at Infants with the full.names=TRUE, we see the additional pathing folder has been added, allowing us to successfully copy over the files. -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -Infants -``` - -::: - -::: {.fragment} - -![](images/20.png) - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If we were trying to retrieve just the local file names from the full.names, we could do so with `basename()` function. We will use this in combination with additional arguments later in the course -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE - -basename(Infants) -``` - -::: - -::: {.fragment} - -![](images/22.png) - -::: - ---- - -## Recursive - - -::: {.fragment} -::: {.callout-tip title="."} -And finally that we have created additional nested folders and populated them with fcs files, let's see what setting `list.files()` recursive argument to TRUE -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE -all_files_present <- list.files(full.names=TRUE, recursive=TRUE) -all_files_present -``` - -::: - ---- - -![](images/RecursiveTrue.png) - ---- - - -::: {.fragment} -::: {.callout-tip title="."} - -In this case, all files in all folders within the working directory are shown. This can be useful when exploring folder contents, but if there are a lot of files present within the folder, it will take a while to return the list. - -::: -::: - - -## Saving changes to Version Control - -::: {.fragment} -::: {.callout-tip title="."} -And as is good practice, to maintain version control, let's stage all the files and folders we created today within the Week2 Project Folder, write a commit message, and send these files back to GitHub until they are needed again next time. -::: -::: - ---- - -![](images/23.png) - ---- - -# Wrap-Up - -::: {.fragment} -::: {.callout-tip title="."} -In this session, we started to learn about working directories, file.paths and how to locate files of interest. We also learned how variables (objects) are created in R using the assignment arrow, how they are named, and the general structure (character, numeric, logical) that they are represented as. - -This will prove valuable in the next several weeks when working with .fcs files, as the majority of functions we will use for Bioconductor project R packages need file.paths to locate both .fcs files as well as .csv files that contain metadata. -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} -One of the most frequent errors that beginners encounter when trying to load in .fcs files into the `flowCore` package is not providing the full file.path to the .fcs file of interest. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next week, having installed the required R packages, and learned a little about variables and file.paths, we will dive into our first cytometry focused session. We will be cracking open an .fcs file and exploring how things are stored within. In the process of seeing how the file contents are organized, we will continue to learn and practice how to create variables, and general object structure types within R. Until then, have a wonderful week! -::: -::: - ---- - -![](images/Week2Exit.jpg) - ---- - -# Additional Resources - -[Riffomonas: Using paths in R and why you shouldn't be using setwd (CC179)](https://youtu.be/StqDYjM6ULo?si=ba2on5rNphQ9AL-B) - -[Project-oriented workflow](https://tidyverse.org/blog/2017/12/workflow-vs-script/) - -[Paths, working directories, and projects in R; Learn R Video 13](https://youtu.be/lJcuXBFP7Co?si=dqptQ3UGGjmTYqnB) - -[Demystifying File Paths in R: Navigate Nested Folders with Dr. Padilla](https://youtu.be/yeiT5Kj_uG8?si=UySsolzbTxbgGMF6) - -# Take-home Problems - -:::{.callout-tip title="Problem 1"} -Plug in an external hard-drive or USB into your computer. Manually, create a folder within called "TargetFolder". Try to programmatically specify the file path to identify the folders and files present on your external drive. Then, try to copy your .fcs files from their current folder on your desktop to the TargetFolder on your drive using R. Remember, just copy, no deletion, you need to walk before you can run :D -::: - ---- - -:::{.callout-tip title="Problem 2"} -In this session, we used `list.files()` with the "full.names argument" set to TRUE, as well as the `basename()` function to identify specific files. But what if you wanted a particular directory. Run `list.files()` with "full.names argument" and "recursive" argument set to TRUE, and then search online to find an R function that would retrieve the "" individual directory folders. -::: - ---- - -:::{.callout-tip title="Problem 3"} -R packages often come with internal datasets, that are typically used for use in the help documentation examples. These can be accessed through the use of the `system.file()` function. See an example code below. - -```{r} -#| eval: FALSE -system.file("extdata", package = "FlowSOM") -``` - -Using what we have learned about file.path navigation, search your way down the file.directory of the `FlowSOM` and `flowWorkspace` packages, and identify any .fcs files that are present for use in the documentation. -::: - ---- - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) -::: +--- +title: "02 - File Paths" +author: "David Rach" +date: 02-16-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Welcome to the second week of [Cytometry in R](/Schedule.qmd)! This week we will learn about file.path, namely, how to communicate to our computer (and R) where various files are stored. +::: +::: + +::: {.fragment} +:::{.callout-important} +Before getting started, please make sure you have completed the creating a [GitHub](/course/00_GitHub/index.qmd) and [Workstation Setup](/course/00_WorkstationSetup/index.qmd) walk-throughs, since we will begin where they left off once the required software was successfully installed. Having read-through how to use [version control](/course/00_Git/index.qmd) using Git will additionally be useful. +::: +::: + +--- + +# Background + +```{r} +#| include: FALSE +library(BiocStyle) +``` + + +::: {.fragment} +::: {.callout-tip title="."} +When flow cytometrist first start learning how to code, we tend to think big picture: "I want to take my files, normalize them, cluster them, analyze them, and finally plot them". When we first start writing code, we tend to plan what we will write in similarly broad strokes. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Our computers by contrast "think" in small incremental steps: "First locate this folder, list the files present, select these specific ones, import them into R, load the normalization package, pass the first file in, etc.". These steps when combined algorithmically add up to form the bigger picture. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The challenge when first starting to learn how to code is developing a coding mindset in which we think not in broad strokes, but about what the next step will be programmatically. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will start working on our own "coding mindsets" by working with file paths, as they communicate to our computer where to find our experiment files, and tend to be one of the early points of conflict and frustration. In the process, we will also cover additional concepts of R programming generally, including how to create/name variables, and look up the class/type of a particular object. +::: +::: + +--- + +## Set Up + + +::: {.fragment} +::: {.callout-tip title="."} +Before we begin, let's make sure you get the data needed for today transferred to your local computer, and then get the .fcs files copied over from there to your own working project folder. This is the process you will repeat each week throughout the course. +::: +::: + +--- + +### New Repository + +::: {.fragment} +::: {.callout-tip title="."} +First off, login to your GitHub account. Once there, you will select the options to create a new repository (similar to what you did during [Using GitHub](/course/00_GitHub/index.qmd#github-repository)) +::: +::: + +--- + +![](images/0001_NewRepo.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For this week, let's set this new repository up as a private repository, and call it Week2. This will keep things consistent with the file.paths we will be showing in the examples. +::: +::: + +--- + +![](images/0002_PrivateRepo.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once the new repository has been created, copy the URL. +::: +::: + +--- + +![](images/0003_Url.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next, open up Positron, set the interpreter to use R, and then select the option to bring in a "New Folder from Git". +::: +::: + +--- + +![](images/0004_NewGit.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Paste in your new repository's url. Additionally, if you want to match file.paths shown in the examples, set your storage location to your local Documents folder (please note the start of the file.path will look differently depending on whether you are on Windows, MacOS, or Linux). +::: +::: + +--- + +![](images/0005_SaveDocuments.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Your new repository will then be imported from GitHub. Once this is done, create two subfolders (data and images) and a new .qmd file (naming it filepaths.qmd). +::: +::: + +--- + +![](images/0006_BasicInfrastructure.png) + +--- + +### Sync + +::: {.fragment} +::: {.callout-tip title="."} +With this done, return to GitHub and open your [forked version](/course/00_GitHub/index.qmd#forking-cytometryinr) of the CytometryInR course folder. If you haven't yet done so, click on [sync](/course/00_Homeworks/index.qmd#sync-your-fork) to bring in this week's code and datasets. +::: +::: + +--- + +![](images/0008_Sync.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Returning to Positron, you will need to switch Project Folders, switching from Week2 over to CytometryInR. +::: +::: + +--- + +![](images/0007_SwitchFolders.png) + +--- + +### Pull + +::: {.fragment} +::: {.callout-tip title="."} +Once CytometryInR project folder has opened, you will need to [pull](/course/00_Git/index.qmd#pull) in the new data from GitHub to your local computer. +::: +::: + +--- + +![](images/0007_PullCytometryInR.png) + +--- + +### Copy Files to Week2 + +::: {.fragment} +::: {.callout-tip title="."} +Once this is done, you will see within the course folder, containing this weeks folder (02_FilePaths). Within it there is a data folder with .fcs files. To avoid causing conflicts when bringing in next week's materials, you will want to manually copy over these .fcs files (via your File Explorer) to the data folder within your "Week2" Project Folder. +::: +::: + +--- + +![](images/0009_Copy.png) + +--- + +### Commit and Push + + +::: {.fragment} +::: {.callout-tip title="."} +When you reopen your Week2 project folder in Positron, you should now be able to see the .fcs files within the data folder. Next, from the action bar on the far left, select the Source Control tab. Stage all the changes (as was done in [Using Git](/course/00_Git/)), and write a short commit message. +::: +::: + +--- + +![](images/0010_Commit.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +With these files now being tracked by version control, push (ie. send) your changes to GitHub so that they are remotely backed up. +::: +::: + +--- + +![](images/0011_Push.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And with this setup complete, you are now ready to proceed. Remember, run code and write notes in your working project folder (Week2 or otherwise named) to avoid conflicts next week in the CytometryInR folder when you are trying to bring in the Week #3 code and datasets. +::: +::: + +--- + +# Walk Through + +## Working Directory + +::: {.fragment} +::: {.callout-tip title="."} +Now that we are back in our Week2 folder, let's start by seeing our current location similarly to how our computer perceives it. + +We will use `getwd()` function (ie. get working directory) to return the location of the folder we are currently inside of. For example, when `getwd()` is run within my Week2 project folder, I see the following location +::: +::: + +--- + +```{r} +#| eval: FALSE +getwd() +``` + +![](images/0000_ReplacementGetWD.png) + +::: {.fragment} +::: {.callout-tip title="."} + +This returns a file path. The final location (Week2 in this case) is the **Working Directory**. Your computer when working in R will be descern other locations in relation to this directory. + +::: +::: + +--- + +## Directories + +::: {.fragment} +::: {.callout-tip title="."} +Within this working directory, we have a variety of project folders and files related to the course. We can see the folders that are present using the `list.dirs()` function. +::: +::: + +::: {.fragment} +![](images/0000_ReplacementView.png) +::: + +::: fragment +```{r} +#| eval: FALSE +list.dirs(path=".", full.names=FALSE, recursive=FALSE) +``` + +![](images/0000_ReplacementListFiles.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Within this `list.dirs()` function, we are specifying two arguments with which we will be working with later today, *full.names* and *recursive*. For now, lets set their arguments to FALSE, which means they conditions they implement are inactive (turned off). +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The path argument is currently set to ".", which is a stand-in for the present directory. In R, if an argument is not specified directly, it is inferred based on an order of expected arguments. Thus, if not present, we could still get the same output as seen before. +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +list.dirs(full.names=FALSE, recursive=FALSE) +``` + +![](images/0000_ReplacementListFiles.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Within Positron, in addition to visible folders, we also have *hidden folders* (denoted by the "." in front of the folder name when using `list.dirs()`). In the case of one of our course website folders, we can see a ".quarto" folder shown in a lighter gray . The ".git" folder we saw from `list.dirs()` is typically hidden when viewing from Positron. +::: +::: + +::: {.fragment} + +![](images/02_HiddenFolder.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In the case of Week2, the two not-hidden folders we created are listed. We will see how to navigate these in a second. +::: +::: + +::: {.fragment} + +![](images/0000_ReplacementView.png) + +::: + +--- + +## Variables + +::: {.fragment} +::: {.callout-tip title="."} +Before exploring file paths, we need to have some basic R code knowledge that we can use to work with them. Within R, we have the ability to assign particular values (be they character strings, numbers or logicals) to objects (ie. variables) that can be used when called upon later. + +For example: + +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +WhatDayDidIWriteThis <- "Saturday" +``` +::: + +::: {.fragment} +::: {.callout-tip title="."} +In this case, the variable name is what the assignment arrow ("<-") is pointing at. In this case, WhatDayDidIWriteThis +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When we run this, we create a variable, that will appear within the right-sidebar. +::: +::: + +::: {.fragment} + +```{r} +#| eval: TRUE +WhatDayDidIWriteThis <- "Saturday" +``` + +::: + +--- + +![](images/04_VariableList.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +These variables can subsequently be retrieved by printing (ie. running) the name of the variable +::: +::: + +::: {.fragment} + +```{r} +WhatDayDidIWriteThis +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You can create variables with almost any name you can think of +::: +::: + +::: {.fragment} + +```{r} +TopSecretMeetingDay <- "Saturday" +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +With a few exceptions. R doesn't play well with spaces: +::: +::: + +::: {.fragment} + +```{r} +#| error: TRUE +Top Secret Meeting Day <- "Saturday" +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +But does play well with underscores: +::: +::: + +::: {.fragment} + +```{r} +Top_Secret_Meeting_Day <- "Saturday" +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The above (with individual words separated by _) is collectively known as snake case. The alternate way to help delineate variable names is "camelCase", with first letter of each word being capitalized (seen in the previous example). +::: +::: + +--- + +![](images/CamelCase.jpeg) + +--- + +```{r} +TopSecretMeetingDay +``` + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You can overwrite a Variable name by assigning a different value to it: +::: +::: + +::: {.fragment} + +```{r} +TopSecretMeetingDay <- "Monday" +``` + +::: + +::: {.fragment} + +```{r} +TopSecretMeetingDay +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You can also remove individual variables via the `rm` function +::: +::: + +::: {.fragment} + +```{r} +rm(Top_Secret_Meeting_Day) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Or if trying to remove all, via the right sidebar +::: +::: + +--- + +![](images/10_RemoveVariables.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In the prior case, we are creating a variable that is a "string" of character values, due to our use of "" around the word. We can see this when we use the `str()` function. +::: +::: + +::: {.fragment} + +```{r} +Fluorophores <- "FITC" +str(Fluorophores) +``` + +::: + +::: {.fragment} +::: {.callout-tip title="."} +The "chr" in front denotating that Fluorophores contains a character string. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This could also be retrieved using the `class()` function. +::: +::: + +::: {.fragment} + +```{r} +class(Fluorophores) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, we could assign a numeric value to a variable +::: +::: + +::: {.fragment} + +```{r} +Fluorophores <- 29 +str(Fluorophores) +``` + +::: + +::: {.fragment} +::: {.callout-tip title="."} +Which returns "num", ie. numeric. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can also specify a logical (ie. True or FALSE) to a particular object +::: +::: + +::: {.fragment} + +```{r} +IsPerCPCy5AGoodFluorophore <- FALSE +str(IsPerCPCy5AGoodFluorophore) +``` + +::: + +::: {.fragment} +::: {.callout-tip title="."} +Which returns logi in front, denoting this variable contains a logical value. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Last week, when we were installing `dplyr`, the reason that installation failed was `install.packages()` expects a character string. However, when we left off the "", it looked within our local environments created variables for the dplyr variable, couldn't find it, and thus failed. + +We could of course, have assigned a character value to a variable name, and then used that variable name, which would have worked. +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE + +PackageToInstall <- "dplyr" + +install.packages(PackageToInstall) +``` + +::: + +--- + +## Indexing + +::: {.fragment} +::: {.callout-tip title="."} +Not all variables contain single objects. + +For example, we can modify Fluorophores and add additional entries: +::: +::: + +::: {.fragment} + +```{r} +Fluorophores <- c("BV421", "FITC", "PE", "APC") +str(Fluorophores) +``` + +::: + +::: {.fragment} +::: {.callout-tip title="."} +The c stands for concatenate. It concatenates the objects into a larger object, known as a vector. + +In this case, you notice in addition to the specification the values are characters, we get a [1:4], denoting four objects are present. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can similarly retrieve this information using the `length()` function +::: +::: + +::: {.fragment} + +```{r} +length(Fluorophores) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When multiple objects are present, we can specify them individidually by providing their index number within square brackets []. +::: +::: + + +::: {.fragment} + +```{r} +Fluorophores[1] +``` + +::: + +--- + +::: {.fragment} + +```{r} +Fluorophores[3] +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Or specify in sequence using a colon (:) +::: +::: + +::: {.fragment} + +```{r} +Fluorophores[3:4] +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Or if not adjacent, reusing `c` within the square brackets +::: +::: + +::: {.fragment} + +```{r} +Fluorophores[c(1,4)] +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will revisit these concepts throughout the course, with what we have covered today, this will help us create file.paths and select fcs files that we want to work with via index number. +::: +::: + +## Listing Files + +::: {.fragment} +::: {.callout-tip title="."} +After this detour into variables and indexing, let's return our focus to how to use these in context of file paths. Working from within our Week2 project folder, let's see what directories (folders) are present +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +list.dirs(path=".", full.names=FALSE, recursive=FALSE) +``` + +::: + +::: {.fragment} + +![](images/00.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can also list any files that are present within our working directory using the `list.files()` function. +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +list.files() +``` + +::: + +::: {.fragment} + +![](images/01.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this case, in addition to our filepaths.qmd file, we can see the LICENSE and README files created when we set up the repository. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can also specify a particular folder we want to show items present within by changing the path argument. For example, if we wanted to see the contents of the "data" folder +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +list.files(path="data", full.names=FALSE, recursive=FALSE) +``` + +::: + +::: {.fragment} + +![](images/02.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Which in this case returns the fcs files we copied over at the start of this lesson. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this case, there are no folders under "data". Let's go ahead and create a new one, calling it target. +::: +::: + +--- + +![](images/03.png) + +--- + +## Creating directories + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, we can also create a folder via R using the `dir.create()` function. Since we want it within data, we would modify the path accordingly +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +NewFolderLocation <- file.path("data", "target2") + +dir.create(path=NewFolderLocation) +``` + +::: + +--- + +![](images/04.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Before continuing, let's copy the first two .fcs files into both target and target2. +::: +::: + +--- + +![](images/06.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Given our working directory is set the top-level of the Week2 project folder, we can't just check inside nested target folders directly. If we attempt to: +::: +::: + +::: {.fragment} + +```{r} +list.files(path="target", full.names=FALSE, recursive=FALSE) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +No files are returned (ie, character(0)), since from our computers perspective, "target" doesn't exist within the active working directory. +::: +::: + +::: {.fragment} + +```{r} +file.exists("target") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +On the other hand, within it's view, it knows that the data folder exist +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +file.exists("data") +``` + +::: + +::: {.fragment} + +![](images/05.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +So here we encounter the first challenge when communicating to our computer where to search for and find files. We need to provide a file.path that incorporates the path of folders between where the computer is currently at (ie. the working directory) and the target file itself. +::: +::: + +--- + +## File Paths + +::: {.fragment} +::: {.callout-tip title="."} +One way we can do this is through a file.path argument. We could potentially provide this by adding either a "/" or a "\" into the path argument, depending on your computers operating system. +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +list.files(path="data/target", full.names=FALSE, recursive=FALSE) +``` + +::: + +::: {.fragment} + +![](images/07.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +While this works in your particular context, if you are sharing the code with others who have a different operating system, these hard-coded / or \ will cause the code for them to error out at these particular steps. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For that reason, it is better to assemble a file.path using the `file.path()` function. This function takes into account the operating system, removing your need to have to worry about this particular computing nuance, and write code that is reproducible and replicable for everyone. +::: +::: + +::: {.fragment} + +```{r} +FolderLocation <- file.path("data", "target") +FolderLocation +``` + +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +list.files(path=FolderLocation, full.names=FALSE, recursive=FALSE) +``` + +::: + +::: {.fragment} + +![](images/07.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can also append additional locations to existing file paths, by including the variable name within the `file.path()` we are creating. +::: +::: + +::: {.fragment} + +```{r} +FolderLocation <- "data" +ScreenshotFolder <- file.path(FolderLocation, "target") +ScreenshotFolder +``` + +::: + +::: {.fragment} + +```{r} +#| eval: FALSE + +list.files(path=ScreenshotFolder, full.names=FALSE, recursive=FALSE) +``` + +::: + +::: {.fragment} + +![](images/07.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Additionally, `list.files()` has the ability to filter for files that contain a particular character string. This can be useful is we are searching for ".fcs" or ".csv" files, but also for files that contain a particular word. In the case of the ScreenshotFolders +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +list.files(path=ScreenshotFolder, pattern="ND050", full.names=FALSE, recursive=FALSE) +``` + +::: + +::: {.fragment} + +![](images/08.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will notice, the index numbers are in the context of what is filtered, not all the folder contents. +::: +::: + +--- + +## Selecting for Patterns + +::: {.fragment} +::: {.callout-tip title="."} +If we currently listed the files within data, we get a return that looks like this: +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +list.files("data", full.names=FALSE, recursive=FALSE) +``` + +::: + +::: {.fragment} + +![](images/09.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As you can see, we are getting back both folders and individual .fcs files. We could consequently change the pattern to provide a character string that will only return the .fcs files. We will go ahead and assign this list to a variable named files, for later retrieval. +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +files <- list.files("data", pattern=".fcs", full.names=FALSE, recursive=FALSE) +files +``` + +::: + +::: {.fragment} + +![](images/10.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +One of the R packages we will be using througout the course is the `stringr` package. It contains two functions that can be useful when identifying more complicated character strings. In this case, if we run the `str_detect()` function to identify which of the .fcs files within the files variable contains the "INF" character string, we get a vector of logical (ie. True or FALSE) outputs corresponding to each file. +::: +::: + +::: {.fragment} + +```{r} +# install.packages("stringr") # CRAN +library(stringr) +``` + +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +str_detect(files, "INF") +``` + +::: + +::: {.fragment} + +![](images/11.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Similar to how we indexed the Fluorophore list (ex. Fluorophore[1:2]) which returned a subset, we can similarly use this logical vector to subset files that returned as TRUE for containing the pattern "INF" +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +files[str_detect(files, "INF")] +``` + +::: + +::: {.fragment} + +![](images/12.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Let's go ahead and save these subsetted file names to a new variable, called Infants. +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +Infants <- files[str_detect(files, "INF")] +``` + +::: + +## Conditionals + +::: {.fragment} +::: {.callout-tip title="."} +One useful thing is that within R, we can set conditions on whether something is carried out. The most typical conditional you will encounter are the "If" statements. They typically take a form that resembles the following. +::: +::: + + +::: {.fragment} + +```{r} +#| eval: FALSE + +NeedCoffee <- TRUE + +if (NeedCoffee){ + print("Take a break") +} +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this case of the above, if the variable within the () is equal to true, the code within the {} will be executed. +::: +::: + +::: {.fragment} + +```{r} + +NeedCoffee <- TRUE + +if (NeedCoffee){ + print("Take a break") +} +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +By contrast, when the variable within the () is equal to false, the code within the {} will not be executed. +::: +::: + +::: {.fragment} + +```{r} +NeedCoffee <- FALSE + +if (NeedCoffee){ + print("Take a break") +} +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +These "If" statements will trigger as long as the specified condition within the () is TRUE. For a different example: +::: +::: + +::: {.fragment} + +```{r} +RowNumber <- 299 +2 + RowNumber > 300 +``` + +::: + +::: {.fragment} + +```{r} +if (2 + RowNumber > 3){ + print("Stop Iterating") +} +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When you add an ! in front a conditional, it flips the expected outcome. +::: +::: + +::: {.fragment} + +```{r} +ItsRaining <- TRUE + +if (ItsRaining){print("Bring an Umbrella")} +``` + +::: + +::: {.fragment} + +```{r} +!ItsRaining +``` + +::: + +::: {.fragment} + +```{r} +if (!ItsRaining){print("Bring an Umbrella")} +``` + +::: + +::: {.fragment} + +```{r} +ItsRaining <- TRUE + +if (!ItsRaining){print("Bring Sunglasses")} + +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will explore more complicated conditionals throughout the course, but for now, let's implement a couple simple ones in the context of copying over the .fcs files in Infants over to a new target3 folder. +::: +::: + +## Conditionals in practice + +::: {.fragment} +::: {.callout-tip title="."} +First off, let's write a conditional to check if there is a target3 folder within data. +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +files_present <- list.files("data", full.names=FALSE, recursive=FALSE) +files_present +``` + +::: + +::: {.fragment} + +![](images/13.png) + +::: + +--- + +```{r} +#| eval: FALSE + +FolderTarget3 <- file.path("data", "target3") +dir.exists(FolderTarget3) +``` + +::: {.fragment} + +![](images/14.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can write a conditional to create a folder if one does not yet exist. +::: +::: + + +::: {.fragment} + +```{r} +#| eval: FALSE +if (!dir.exists(FolderTarget3)){ + dir.create(FolderTarget3) +} +``` + +::: + +::: {.fragment} + +![](images/15.png) + +::: + +--- + +## Copying Files + +::: {.fragment} +::: {.callout-tip title="."} +To copy files to another folder location, we use the `file.copy()` function. It has two arguments that we will be working with, from being the .fcs files, and to being the folder location we wish to transfer them to. If we tried using them as we currently have them: +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE + +# Variable Infants containing 4 .fcs file names + +file.copy(from=Infants, to=FolderTarget3) +``` + +::: + +::: {.fragment} + +![](images/16.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The reason for this error is we are only working with a partial file path, as viewed from our Working directory. In this case, what is needed is the full file.path, so the file.path should also include the upstream folders from your current working directory. +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +getwd() +``` + +::: + +::: {.fragment} + +![](images/17.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this case, we can update the .fcs files location by switching the full.names argument within `list.files()` from FALSE, to TRUE. +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +files_present <- list.files("data", full.names=TRUE, recursive=FALSE) +files_present +``` + +::: + +::: {.fragment} + +![](images/18.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And filter for those containing "INF" again +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +Infants <- files_present[str_detect(files_present, "INF")] +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And then try again: +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE + +# Variable Infants containing 4 .fcs file names + +file.copy(from=Infants, to=FolderTarget3) +``` + +::: + +::: {.fragment} + +![](images/19.png) + +::: + +--- + +## Removing files. + +::: {.fragment} +::: {.callout-tip title="."} +Just like we can add files via R, we can also remove them. However, when we remove them via this route, they are removed permanently, not sent to the recycle bin. We will revisit how later on in the course after you have gained additional experience with file.paths. +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +?unlink() +``` + +::: + +## Basename + +::: {.fragment} +::: {.callout-tip title="."} +If we look at Infants with the full.names=TRUE, we see the additional pathing folder has been added, allowing us to successfully copy over the files. +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +Infants +``` + +::: + +::: {.fragment} + +![](images/20.png) + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we were trying to retrieve just the local file names from the full.names, we could do so with `basename()` function. We will use this in combination with additional arguments later in the course +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE + +basename(Infants) +``` + +::: + +::: {.fragment} + +![](images/22.png) + +::: + +--- + +## Recursive + + +::: {.fragment} +::: {.callout-tip title="."} +And finally that we have created additional nested folders and populated them with fcs files, let's see what setting `list.files()` recursive argument to TRUE +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE +all_files_present <- list.files(full.names=TRUE, recursive=TRUE) +all_files_present +``` + +::: + +--- + +![](images/RecursiveTrue.png) + +--- + + +::: {.fragment} +::: {.callout-tip title="."} + +In this case, all files in all folders within the working directory are shown. This can be useful when exploring folder contents, but if there are a lot of files present within the folder, it will take a while to return the list. + +::: +::: + + +## Saving changes to Version Control + +::: {.fragment} +::: {.callout-tip title="."} +And as is good practice, to maintain version control, let's stage all the files and folders we created today within the Week2 Project Folder, write a commit message, and send these files back to GitHub until they are needed again next time. +::: +::: + +--- + +![](images/23.png) + +--- + +# Wrap-Up + +::: {.fragment} +::: {.callout-tip title="."} +In this session, we started to learn about working directories, file.paths and how to locate files of interest. We also learned how variables (objects) are created in R using the assignment arrow, how they are named, and the general structure (character, numeric, logical) that they are represented as. + +This will prove valuable in the next several weeks when working with .fcs files, as the majority of functions we will use for Bioconductor project R packages need file.paths to locate both .fcs files as well as .csv files that contain metadata. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +One of the most frequent errors that beginners encounter when trying to load in .fcs files into the `flowCore` package is not providing the full file.path to the .fcs file of interest. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next week, having installed the required R packages, and learned a little about variables and file.paths, we will dive into our first cytometry focused session. We will be cracking open an .fcs file and exploring how things are stored within. In the process of seeing how the file contents are organized, we will continue to learn and practice how to create variables, and general object structure types within R. Until then, have a wonderful week! +::: +::: + +--- + +![](images/Week2Exit.jpg) + +--- + +# Additional Resources + +[Riffomonas: Using paths in R and why you shouldn't be using setwd (CC179)](https://youtu.be/StqDYjM6ULo?si=ba2on5rNphQ9AL-B) + +[Project-oriented workflow](https://tidyverse.org/blog/2017/12/workflow-vs-script/) + +[Paths, working directories, and projects in R; Learn R Video 13](https://youtu.be/lJcuXBFP7Co?si=dqptQ3UGGjmTYqnB) + +[Demystifying File Paths in R: Navigate Nested Folders with Dr. Padilla](https://youtu.be/yeiT5Kj_uG8?si=UySsolzbTxbgGMF6) + +# Take-home Problems + +:::{.callout-tip title="Problem 1"} +Plug in an external hard-drive or USB into your computer. Manually, create a folder within called "TargetFolder". Try to programmatically specify the file path to identify the folders and files present on your external drive. Then, try to copy your .fcs files from their current folder on your desktop to the TargetFolder on your drive using R. Remember, just copy, no deletion, you need to walk before you can run :D +::: + +--- + +:::{.callout-tip title="Problem 2"} +In this session, we used `list.files()` with the "full.names argument" set to TRUE, as well as the `basename()` function to identify specific files. But what if you wanted a particular directory. Run `list.files()` with "full.names argument" and "recursive" argument set to TRUE, and then search online to find an R function that would retrieve the "" individual directory folders. +::: + +--- + +:::{.callout-tip title="Problem 3"} +R packages often come with internal datasets, that are typically used for use in the help documentation examples. These can be accessed through the use of the `system.file()` function. See an example code below. + +```{r} +#| eval: FALSE +system.file("extdata", package = "FlowSOM") +``` + +Using what we have learned about file.path navigation, search your way down the file.directory of the `FlowSOM` and `flowWorkspace` packages, and identify any .fcs files that are present for use in the documentation. +::: + +--- + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +::: diff --git a/course/03_InsideFCSFile/data/BioconductorDownloads.csv b/course/03_InsideFCSFile/data/BioconductorDownloads.csv index 4ca5bee..14f3689 100644 --- a/course/03_InsideFCSFile/data/BioconductorDownloads.csv +++ b/course/03_InsideFCSFile/data/BioconductorDownloads.csv @@ -1,885 +1,885 @@ -"Year","Month","Nb_of_distinct_IPs","Nb_of_downloads","package" -2025,"Jan",2233,4445,"flowCore" -2025,"Feb",2376,4254,"flowCore" -2025,"Mar",2691,5218,"flowCore" -2025,"Apr",2660,5098,"flowCore" -2025,"May",2643,5838,"flowCore" -2025,"Jun",2523,5070,"flowCore" -2025,"Jul",2887,5789,"flowCore" -2025,"Aug",2592,15192,"flowCore" -2025,"Sep",3039,38024,"flowCore" -2025,"Oct",2958,15956,"flowCore" -2025,"Nov",3645,10389,"flowCore" -2025,"Dec",3982,14260,"flowCore" -2025,"all",26720,129533,"flowCore" -2025,"Jan",2501,4902,"cytolib" -2025,"Feb",2588,4534,"cytolib" -2025,"Mar",2755,5463,"cytolib" -2025,"Apr",2741,4785,"cytolib" -2025,"May",2545,4725,"cytolib" -2025,"Jun",2325,3897,"cytolib" -2025,"Jul",2731,4705,"cytolib" -2025,"Aug",2358,14116,"cytolib" -2025,"Sep",2868,37708,"cytolib" -2025,"Oct",2867,15757,"cytolib" -2025,"Nov",3500,9793,"cytolib" -2025,"Dec",3167,12209,"cytolib" -2025,"all",25638,122594,"cytolib" -2025,"Jan",1006,2206,"flowWorkspace" -2025,"Feb",980,1802,"flowWorkspace" -2025,"Mar",1386,2734,"flowWorkspace" -2025,"Apr",1330,2614,"flowWorkspace" -2025,"May",1381,3229,"flowWorkspace" -2025,"Jun",1200,2420,"flowWorkspace" -2025,"Jul",1469,2894,"flowWorkspace" -2025,"Aug",1242,6409,"flowWorkspace" -2025,"Sep",1515,22768,"flowWorkspace" -2025,"Oct",1506,8677,"flowWorkspace" -2025,"Nov",1936,5480,"flowWorkspace" -2025,"Dec",2406,9893,"flowWorkspace" -2025,"all",13542,71126,"flowWorkspace" -2025,"Jan",1066,2080,"ncdfFlow" -2025,"Feb",1038,1758,"ncdfFlow" -2025,"Mar",1246,2295,"ncdfFlow" -2025,"Apr",1235,2103,"ncdfFlow" -2025,"May",1251,2417,"ncdfFlow" -2025,"Jun",1040,1635,"ncdfFlow" -2025,"Jul",1227,1962,"ncdfFlow" -2025,"Aug",1157,5939,"ncdfFlow" -2025,"Sep",1410,22562,"ncdfFlow" -2025,"Oct",1438,8643,"ncdfFlow" -2025,"Nov",1846,4987,"ncdfFlow" -2025,"Dec",2465,8821,"ncdfFlow" -2025,"all",12958,65202,"ncdfFlow" -2025,"Jan",869,1692,"flowViz" -2025,"Feb",851,1372,"flowViz" -2025,"Mar",1014,1763,"flowViz" -2025,"Apr",1000,1762,"flowViz" -2025,"May",1042,1879,"flowViz" 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+2025,"Sep",148,257,"cyanoFilter" +2025,"Oct",144,256,"cyanoFilter" +2025,"Nov",139,223,"cyanoFilter" +2025,"Dec",209,276,"cyanoFilter" +2025,"all",1745,3479,"cyanoFilter" +2025,"Jan",171,310,"optimalFlow" +2025,"Feb",132,230,"optimalFlow" +2025,"Mar",154,271,"optimalFlow" +2025,"Apr",174,347,"optimalFlow" +2025,"May",208,427,"optimalFlow" +2025,"Jun",162,284,"optimalFlow" +2025,"Jul",220,340,"optimalFlow" +2025,"Aug",167,260,"optimalFlow" +2025,"Sep",165,264,"optimalFlow" +2025,"Oct",131,247,"optimalFlow" +2025,"Nov",129,218,"optimalFlow" +2025,"Dec",244,305,"optimalFlow" +2025,"all",1858,3503,"optimalFlow" +2025,"Jan",161,298,"CytoGLMM" +2025,"Feb",140,252,"CytoGLMM" +2025,"Mar",153,264,"CytoGLMM" +2025,"Apr",134,289,"CytoGLMM" +2025,"May",152,359,"CytoGLMM" +2025,"Jun",159,255,"CytoGLMM" +2025,"Jul",246,353,"CytoGLMM" +2025,"Aug",166,336,"CytoGLMM" +2025,"Sep",156,266,"CytoGLMM" +2025,"Oct",169,275,"CytoGLMM" +2025,"Nov",130,221,"CytoGLMM" +2025,"Dec",261,336,"CytoGLMM" +2025,"all",1891,3504,"CytoGLMM" +2025,"Jan",146,284,"scifer" +2025,"Feb",134,215,"scifer" +2025,"Mar",129,261,"scifer" +2025,"Apr",154,353,"scifer" +2025,"May",173,394,"scifer" +2025,"Jun",191,306,"scifer" +2025,"Jul",216,338,"scifer" +2025,"Aug",156,275,"scifer" +2025,"Sep",149,260,"scifer" +2025,"Oct",120,240,"scifer" +2025,"Nov",122,199,"scifer" +2025,"Dec",332,414,"scifer" +2025,"all",1828,3539,"scifer" +2025,"Jan",167,323,"cytoKernel" +2025,"Feb",136,228,"cytoKernel" +2025,"Mar",146,253,"cytoKernel" +2025,"Apr",144,305,"cytoKernel" +2025,"May",185,389,"cytoKernel" +2025,"Jun",173,294,"cytoKernel" +2025,"Jul",241,365,"cytoKernel" +2025,"Aug",152,263,"cytoKernel" +2025,"Sep",154,255,"cytoKernel" +2025,"Oct",120,221,"cytoKernel" +2025,"Nov",159,239,"cytoKernel" +2025,"Dec",239,305,"cytoKernel" +2025,"all",1864,3440,"cytoKernel" +2025,"Jan",138,252,"CytoPipeline" +2025,"Feb",134,230,"CytoPipeline" +2025,"Mar",147,273,"CytoPipeline" +2025,"Apr",175,342,"CytoPipeline" 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+2025,"Oct",126,225,"flowCyBar" +2025,"Nov",168,267,"flowCyBar" +2025,"Dec",195,266,"flowCyBar" +2025,"all",1765,3476,"flowCyBar" +2025,"Jan",96,172,"reconsi" +2025,"Feb",147,254,"reconsi" +2025,"Mar",139,248,"reconsi" +2025,"Apr",121,286,"reconsi" +2025,"May",193,412,"reconsi" +2025,"Jun",150,244,"reconsi" +2025,"Jul",219,355,"reconsi" +2025,"Aug",168,286,"reconsi" +2025,"Sep",154,259,"reconsi" +2025,"Oct",132,240,"reconsi" +2025,"Nov",123,211,"reconsi" +2025,"Dec",190,260,"reconsi" +2025,"all",1705,3227,"reconsi" +2025,"Jan",151,266,"MACSQuantifyR" +2025,"Feb",120,221,"MACSQuantifyR" +2025,"Mar",111,223,"MACSQuantifyR" +2025,"Apr",169,331,"MACSQuantifyR" +2025,"May",193,387,"MACSQuantifyR" +2025,"Jun",164,281,"MACSQuantifyR" +2025,"Jul",210,319,"MACSQuantifyR" +2025,"Aug",170,295,"MACSQuantifyR" +2025,"Sep",146,246,"MACSQuantifyR" +2025,"Oct",129,243,"MACSQuantifyR" +2025,"Nov",128,209,"MACSQuantifyR" +2025,"Dec",125,190,"MACSQuantifyR" +2025,"all",1625,3211,"MACSQuantifyR" +2025,"Jan",141,222,"CytoMDS" +2025,"Feb",116,196,"CytoMDS" +2025,"Mar",107,194,"CytoMDS" +2025,"Apr",121,266,"CytoMDS" +2025,"May",152,347,"CytoMDS" +2025,"Jun",126,222,"CytoMDS" +2025,"Jul",180,263,"CytoMDS" +2025,"Aug",146,240,"CytoMDS" +2025,"Sep",126,208,"CytoMDS" +2025,"Oct",124,225,"CytoMDS" +2025,"Nov",112,188,"CytoMDS" +2025,"Dec",165,327,"CytoMDS" +2025,"all",1507,2898,"CytoMDS" +2025,"Jan",135,212,"CytoPipelineGUI" +2025,"Feb",112,188,"CytoPipelineGUI" +2025,"Mar",118,201,"CytoPipelineGUI" +2025,"Apr",132,278,"CytoPipelineGUI" +2025,"May",149,359,"CytoPipelineGUI" +2025,"Jun",131,225,"CytoPipelineGUI" +2025,"Jul",154,239,"CytoPipelineGUI" +2025,"Aug",127,228,"CytoPipelineGUI" +2025,"Sep",141,223,"CytoPipelineGUI" +2025,"Oct",122,225,"CytoPipelineGUI" +2025,"Nov",123,209,"CytoPipelineGUI" +2025,"Dec",142,207,"CytoPipelineGUI" +2025,"all",1471,2794,"CytoPipelineGUI" +2025,"Jan",126,204,"MAPFX" +2025,"Feb",114,188,"MAPFX" +2025,"Mar",112,199,"MAPFX" +2025,"Apr",123,247,"MAPFX" 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+2025,"Nov",110,190,"tidyFlowCore" +2025,"Dec",132,193,"tidyFlowCore" +2025,"all",1350,2632,"tidyFlowCore" +2025,"Jan",39,84,"CyTOFpower" +2025,"Feb",37,46,"CyTOFpower" +2025,"Mar",60,76,"CyTOFpower" +2025,"Apr",57,95,"CyTOFpower" +2025,"May",32,55,"CyTOFpower" +2025,"Jun",57,74,"CyTOFpower" +2025,"Jul",149,201,"CyTOFpower" +2025,"Aug",139,295,"CyTOFpower" +2025,"Sep",136,233,"CyTOFpower" +2025,"Oct",110,211,"CyTOFpower" +2025,"Nov",135,239,"CyTOFpower" +2025,"Dec",197,275,"CyTOFpower" +2025,"all",1085,1884,"CyTOFpower" +2025,"Jan",116,211,"tidytof" +2025,"Feb",103,173,"tidytof" +2025,"Mar",103,192,"tidytof" +2025,"Apr",112,248,"tidytof" +2025,"May",142,333,"tidytof" +2025,"Jun",150,261,"tidytof" +2025,"Jul",164,270,"tidytof" +2025,"Aug",137,237,"tidytof" +2025,"Sep",141,231,"tidytof" +2025,"Oct",61,91,"tidytof" +2025,"Nov",23,24,"tidytof" +2025,"Dec",33,34,"tidytof" +2025,"all",1198,2305,"tidytof" +2025,"Jan",0,0,"SuperCellCyto" +2025,"Feb",0,0,"SuperCellCyto" +2025,"Mar",0,0,"SuperCellCyto" +2025,"Apr",0,0,"SuperCellCyto" +2025,"May",0,0,"SuperCellCyto" +2025,"Jun",0,0,"SuperCellCyto" +2025,"Jul",0,0,"SuperCellCyto" +2025,"Aug",0,0,"SuperCellCyto" +2025,"Sep",0,0,"SuperCellCyto" +2025,"Oct",101,190,"SuperCellCyto" +2025,"Nov",115,195,"SuperCellCyto" +2025,"Dec",128,195,"SuperCellCyto" +2025,"all",336,580,"SuperCellCyto" diff --git a/course/03_InsideFCSFile/data/BioconductorFlow.csv b/course/03_InsideFCSFile/data/BioconductorFlow.csv index e516213..5e2537f 100644 --- a/course/03_InsideFCSFile/data/BioconductorFlow.csv +++ b/course/03_InsideFCSFile/data/BioconductorFlow.csv @@ -1,69 +1,69 @@ -"package","since","license","version" -"flowCore",19,"Artistic-2.0","3.22" -"cytolib",8.5,"AGPL-3.0-only","3.22" -"flowWorkspace",14.5,"AGPL-3.0-only","3.22" -"ncdfFlow",14.5,"AGPL-3.0-only","3.22" -"flowViz",19,"Artistic-2.0","3.22" -"FlowSOM",11,"GPL (>= 2)","3.22" -"ggcyto",10,"file LICENSE","3.22" -"openCyto",12.5,"AGPL-3.0-only","3.22" 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+"flowClean",11.5,"Artistic-2.0","3.22" +"flowPeaks",13.5,"Artistic-1.0","3.22" +"COMPASS",12,"Artistic-2.0","3.22" +"SamSPECTRAL",16,"GPL (>= 2)","3.22" +"flowVS",11,"Artistic-2.0","3.22" +"cydar",9,"GPL (>= 3)","3.22" +"flowMerge",16.5,"Artistic-2.0","3.22" +"flowTrans",16,"Artistic-2.0","3.22" +"distinct",6,"GPL (>= 3)","3.22" +"flowCut",5.5,"Artistic-2.0","3.22" +"flowMatch",12,"Artistic-2.0","3.22" +"flowBeads",12.5,"Artistic-2.0","3.22" +"flowTime",9,"Artistic-2.0","3.22" +"sccomp",4,"GPL (>= 3)","3.22" +"flowCHIC",11.5,"GPL (>= 2)","3.22" +"flowSpecs",6.5,"MIT + file LICENSE","3.22" +"DepecheR",7,"MIT + file LICENSE","3.22" +"treekoR",4.5,"GPL (>= 3)","3.22" +"flowBin",12,"Artistic-2.0","3.22" +"MetaCyto",8.5,"GPL (>= 2)","3.22" +"immunoClust",11,"Artistic-2.0","3.22" +"scDataviz",5.5,"GPL (>= 3)","3.22" +"cytoMEM",4,"GPL (>= 3)","3.22" +"flowPloidy",9.5,"GPL (>= 3)","3.22" +"plotGrouper",7.5,"GPL (>= 3)","3.22" +"CytoDx",8,"GPL (>= 2)","3.22" +"Sconify",8,"Artistic-2.0","3.22" +"flowPlots",15,"Artistic-2.0","3.22" +"GateFinder",8,"Artistic-2.0","3.22" +"flowGate",3,"MIT + file LICENSE","3.22" +"flowGraph",4.5,"Artistic-2.0","3.22" +"infinityFlow",5.5,"GPL (>= 3)","3.22" +"cyanoFilter",4.5,"MIT + file LICENSE","3.22" +"optimalFlow",6,"Artistic-2.0","3.22" +"CytoGLMM",4.5,"LGPL-3","3.22" +"scifer",3.5,"MIT + file LICENSE","3.22" +"cytoKernel",4.5,"GPL (>= 3)","3.22" +"CytoPipeline",3,"GPL (>= 3)","3.22" +"censcyt",4.5,"MIT + file LICENSE","3.22" +"flowCyBar",12,"GPL (>= 2)","3.22" +"reconsi",6,"GPL (>= 2)","3.22" +"MACSQuantifyR",6.5,"Artistic-2.0","3.22" +"CytoMDS",2,"GPL (>= 3)","3.22" +"CytoPipelineGUI",2.5,"GPL (>= 3)","3.22" +"MAPFX",2,"GPL (>= 2)","3.22" +"spillR",2,"LGPL-3","3.22" +"tidyFlowCore",1.5,"MIT + file LICENSE","3.22" +"CyTOFpower",4.5,"LGPL-3","3.22" +"tidytof",1.5,"MIT + file LICENSE","3.22" +"SuperCellCyto",0,"GPL (>= 3)","3.22" diff --git a/course/03_InsideFCSFile/homeworks/README.md b/course/03_InsideFCSFile/homeworks/README.md index 2818b5e..fe53443 100644 --- a/course/03_InsideFCSFile/homeworks/README.md +++ b/course/03_InsideFCSFile/homeworks/README.md @@ -1,5 +1,5 @@ -# Turning In Optional Take-Home Problems - -This folder is for the use of submitting your completed Take-Home Problems for evaluation by course instructors. Please see [Getting Help](/course/00_Homeworks/index.qmd) walkthrough for more detailed instructions. - +# Turning In Optional Take-Home Problems + +This folder is for the use of submitting your completed Take-Home Problems for evaluation by course instructors. Please see [Getting Help](/course/00_Homeworks/index.qmd) walkthrough for more detailed instructions. + Within your branch, inside this "homeworks" folder, create a new folder (name it with your GitHub username). Then copy all files you will be submitting within your folder. Then commit the change to git, and push to GitHub. See [Getting Help](/course/00_Homeworks/index.qmd)for details on submitting the pull request to the UMGCCCFCSR/CytometryInR homework branch. \ No newline at end of file diff --git a/course/03_InsideFCSFile/homeworks/claude-chew/.vscode/settings.json b/course/03_InsideFCSFile/homeworks/claude-chew/.vscode/settings.json new file mode 100644 index 0000000..a490b61 --- /dev/null +++ b/course/03_InsideFCSFile/homeworks/claude-chew/.vscode/settings.json @@ -0,0 +1,5 @@ +{ + "githubPullRequests.ignoredPullRequestBranches": [ + "main" + ] +} \ No newline at end of file diff --git a/course/03_InsideFCSFile/homeworks/claude-chew/Week3Class.qmd b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Class.qmd new file mode 100644 index 0000000..ee4a14e --- /dev/null +++ b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Class.qmd @@ -0,0 +1,270 @@ +# Week 3 Class + +# Set up File Paths +```{r} +PathToDataFolder <- file.path("data") +PathToDataFolder +``` + +# Locate .fcs files +```{r} +fcs_files <- list.files(PathToDataFolder, pattern=".fcs", full.names=TRUE) +fcs_files +basename(fcs_files) +``` + +# flowCore +```{r} +# I have attached this code for anyone that is interested in seeing how these plots were made. The content is not part of today's lesson, so if you are just starting off, we will cover the details of data-tidying and creating ggplot objects over the next several weeks. Best, David + +# Load required packages via a library call + +library(dplyr) # CRAN +library(stringr) # CRAN +library(ggplot2) # CRAN +library(plotly) # Using the :: to access + +# Loading in the dataset contained within the .csv file +BioconductorFlow_path <- file.path(PathToDataFolder, "BioconductorFlow.csv") +BioconductorFlowPackages <- read.csv(BioconductorFlow_path, check.names=FALSE) +BioconductorFlowPackages <- BioconductorFlowPackages |> + arrange(desc(since)) |> mutate(package = factor(package, levels = package)) + +# Newer Base R Pipe : |> +# Older mostly equivalent Magrittr Pipe %>% +``` + + +```{r} +# Notice the code-chunk eval arguments above dictate the shape of the final rendered plot. + +# Taking the imported dataset and passing it to ggplot2 to create the first plot. + +plot <- ggplot(BioconductorFlowPackages, + aes(x = 0, xend = since, y = package, yend = package)) + + geom_segment(linewidth = 2, color = "steelblue") + + scale_x_continuous(trans = "reverse", + breaks = seq(0, max(BioconductorFlowPackages$since), by = 5)) + + labs( + x = "Years in Bioconductor", + y = NULL, + title = "Bioconductor Flow Cytometry R packages" + ) + + theme_bw() + +# Taking the static plot and making it interactive using the plotly package + +plotly::ggplotly(plot) +``` + +```{r} +# Retrieving the names of Bioconductor flow cytometry R packages in correct release order. + +HistoricalOrder <- BioconductorFlowPackages |> pull(package) + +# Bringing in 2025 package usage dataset from a .csv file +BioconductorUsage_path <- file.path(PathToDataFolder, "BioconductorDownloads.csv") +BioconductorUsage <- read.csv(BioconductorUsage_path, check.names=FALSE) +BioconductorUsage <- BioconductorUsage |> dplyr::filter(Month %in% "all") + +# Note, dplyr::filter is used due to flowCore also having a filter function, which causes conflicts once it is attached to the local environment. + +# Combining both data.frames for use in the plot + +Dataset <- left_join(BioconductorFlowPackages, BioconductorUsage, by="package") + +# Rearranging the order in which packages are displayed + +Dataset$package <- factor(Dataset$package, levels=HistoricalOrder) +``` + + +```{r} +# Generating the 2nd plot with ggplot2 + +plot <- ggplot(Dataset, aes(x = since, y = Nb_of_distinct_IPs)) + + geom_point(aes(color = package), size = 3, alpha = 0.7) + + labs( + x = "Years in Bioconductor", + y = "Number of Yearly Downloads", + title = "", + color = "Package" + ) + + theme_bw() + +# Making it interactive with plotly + +plotly::ggplotly(plot) +``` + + +```{r} +library(flowCore) +# Or when in Positron, hovering over the highlighted function name within the code-chunk + +?flowCore::read.FCS +``` + +```{r} +firstfile <- fcs_files[1] +firstfile +``` + +# flowFrame + +```{r} +read.FCS(filename=firstfile) +flowFrame <- read.FCS(filename=firstfile, transformation = FALSE, truncate_max_range=FALSE) +class(flowFrame) + +MFI_Matrix <- flowFrame@exprs +MFI_Matrix_Alternate <- exprs(flowFrame) +head(MFI_Matrix, 5) + +ColumnNames <- colnames(MFI_Matrix) +ColumnNames +str(ColumnNames) +class(ColumnNames) +unname(ColumnNames) + +MFI_Matrix[,1] +MFI_Matrix[,61] +MFI_Matrix[,350] +MFI_Matrix[1,] +MFI_Matrix[1,2] +``` + +# parameters +```{r} +ParameterData <- flowFrame@parameters@data +head(ParameterData, 10) +ParameterData_Alternate <- parameters(flowFrame)@data +str(ParameterData) + +ParameterData@ +ParameterData$name + +ParameterData[,1] +``` + +# dimLabels +```{r} +flowFrame@parameters@dimLabels +``` + +# classVersion +```{r} +flowFrame@parameters@.__classVersion__ +``` + +# Description +```{r} +DescriptionList <- flowFrame@description +DescriptionList +head(DescriptionList,5) +DescriptionList[1:10] +DescriptionList_Alternate <- keyword(flowFrame) +class(DescriptionList) + +Fluorophores <- c("BV421", "FITC","PE","APC") +class(Fluorophores) + +PanelAntibodyCounts <- c(5,12,19,26,34,46,51) +class(PanelAntibodyCounts) + +SpecimenIndexToKeep <- c(TRUE, TRUE, FALSE, TRUE) +class(SpecimenIndexToKeep) + +MyListofVectors <- list(Fluorophores, PanelAntibodyCounts, SpecimenIndexToKeep) +str(MyListofVectors) + +str(DescriptionList[1:10]) + +MyNamedListofVectors <- list(FluorophoresNamed=Fluorophores, PanelAntibodyCountsNamed=PanelAntibodyCounts, SpecimenIndexToKeepNamed=SpecimenIndexToKeep) + +str(MyNamedListofVectors) + +MyNamedListofVectors$FluorophoresNamed +MyNamedListofVectors[1] +``` + +# Keyword Madness + +```{r} +Subset <- DescriptionList[1:18] +DescriptionList$`$BTIM` +DescriptionList$`$CYT` +DescriptionList$`$CYTSN` +DescriptionList$`$DATE` +DescriptionList$`$ETIM` +DescriptionList$`$FIL` +DescriptionList$`$OP` +``` + +# Detector Values + +```{r} +Detectors <- DescriptionList[20:384] +Detectors + +DescriptionList$`$P7B` +DescriptionList$`$P7E` +DescriptionList$`$P7N` +DescriptionList$`$P7R` +DescriptionList$`$P7TYPE` +DescriptionList$`$P7V` +``` + +# Middle Metadata + +```{r} +Detectors <- DescriptionList[385:398] +Detectors + +DescriptionList$`$PROJ` +DescriptionList$`$SPILLOVER` +DescriptionList$`$TOT` +DescriptionList$`$VOL` +DescriptionList$CREATOR + +Detectors <- DescriptionList[390:398] +Detectors +DescriptionList$FILENAME +DescriptionList$GROUPNAME +``` + +# Laser Metadata + +```{r} +Detectors <- DescriptionList[399:410] +Detectors +``` + +# Display + +```{r} +Detectors <- DescriptionList[412:472] +Detectors + +Detectors <- DescriptionList[473:476] +Detectors +``` + +# flowCore Parameters + +```{r} +flowCoreCheck <-read.FCS(filename=firstfile, transformation=TRUE, truncate_max_range=FALSE) + +flowCoreCheck + +YesChange <-keyword(flowCoreCheck) +Detectors <- YesChange [476:500] +Detectors + +flowCoreCheck <-read.FCS(filename=firstfile, transformation=FALSE, truncate_max_range=FALSE) + +NoChange <- keyword(flowCoreCheck) +Detectors <- NoChange[476:500] +Detectors + +``` \ No newline at end of file diff --git a/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework.html b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework.html new file mode 100644 index 0000000..79fda98 --- /dev/null +++ b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework.html @@ -0,0 +1,4137 @@ + + + + + + + + + +week3homework + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+ + + + +
+

Problem 1

+

Today’s walkthrough focused on a raw spectral flow cytometry file. Within a subfolder in data you will also find an unmixed .fcs file (2025_07_26…). Using what learned to day, investigate it, and see if you can catalog the main differences that occured to the keyword, parameters and exprs. Did any keywords get added, changed, deleted entirely? etc.

+
+
+

Problem 1 Code

+
+
PathToDataFolder <- file.path("data/AdditionalFCSFiles")
+PathToDataFolder
+
+
[1] "data/AdditionalFCSFiles"
+
+
# Locate .fcs files
+fcs_files <- list.files(PathToDataFolder, pattern=".fcs", full.names=TRUE)
+fcs_files
+
+
[1] "data/AdditionalFCSFiles/2025-10_22_Contrad.fcs"            
+[2] "data/AdditionalFCSFiles/2025_07_26_AB_02_NY068_02_Ctrl.fcs"
+
+
# Locate unmixed .fcs file
+unmixed_file <- list.files(PathToDataFolder, pattern="2025_07_26", full.names=TRUE)
+unmixed_file
+
+
[1] "data/AdditionalFCSFiles/2025_07_26_AB_02_NY068_02_Ctrl.fcs"
+
+
# Read unmixed .fcs file
+library(flowCore)
+read.FCS(filename=unmixed_file)
+
+
flowFrame object '2025_07_26_AB_02_NY068_02_Ctrl.fcs'
+with 100 cells and 43 observables:
+               name      desc     range  minRange    maxRange
+$P1            Time        NA    516839         0     506.501
+$P2           SSC-W        NA   4194304         0 4194303.000
+$P3           SSC-H        NA   4194304         0 4194303.000
+$P4           SSC-A        NA   4194304         0 4194303.000
+$P5           FSC-W        NA   4194304         0 4194303.000
+...             ...       ...       ...       ...         ...
+$P39     APC-R700-A    CD107a   4194304      -111     4192506
+$P40   Zombie NIR-A Viability   4194304      -111     4192506
+$P41 APC-Fire 750-A      CD27   4194304      -111     4192506
+$P42 APC-Fire 810-A      CCR7   4194304      -111     4192506
+$P43           AF-A        NA   4194304      -111     4194303
+472 keywords are stored in the 'description' slot
+
+
flowFrame <- read.FCS(filename=unmixed_file, transformation = TRUE, truncate_max_range = FALSE)
+class(flowFrame)
+
+
[1] "flowFrame"
+attr(,"package")
+[1] "flowCore"
+
+
MFI_Matrix <- flowFrame@exprs
+ColumnNames <- colnames(MFI_Matrix)
+class(ColumnNames)
+
+
[1] "character"
+
+
# Explore parameters
+ParameterData <- flowFrame@parameters@data
+str(ParameterData)
+
+
'data.frame':   43 obs. of  5 variables:
+ $ name    : 'AsIs' Named chr  "Time" "SSC-W" "SSC-H" "SSC-A" ...
+  ..- attr(*, "names")= chr [1:43] "$P1N" "$P2N" "$P3N" "$P4N" ...
+ $ desc    : 'AsIs' Named chr  NA NA NA NA ...
+  ..- attr(*, "names")= chr [1:43] NA NA NA NA ...
+ $ range   : num  516839 4194304 4194304 4194304 4194304 ...
+ $ minRange: num  0 0 0 0 0 0 0 0 0 0 ...
+ $ maxRange: num  507 4194303 4194303 4194303 4194303 ...
+
+
# Explore Description
+DescriptionList <- flowFrame@description
+DescriptionList
+
+
$`$BEGINANALYSIS`
+[1] "0"
+
+$`$BEGINDATA`
+[1] "18357"
+
+$`$BEGINSTEXT`
+[1] "0"
+
+$`$BTIM`
+[1] "21:30:10.27"
+
+$`$BYTEORD`
+[1] "4,3,2,1"
+
+$`$CYT`
+[1] "Aurora"
+
+$`$CYTOLIB_VERSION`
+[1] "2.22.0"
+
+$`$CYTSN`
+[1] "U1368"
+
+$`$DATATYPE`
+[1] "F"
+
+$`$DATE`
+[1] "26-Jul-2025"
+
+$`$ENDANALYSIS`
+[1] "0"
+
+$`$ENDDATA`
+[1] "35556"
+
+$`$ENDSTEXT`
+[1] "0"
+
+$`$ETIM`
+[1] "21:31:01.86"
+
+$`$FIL`
+[1] "Ctrl.fcs"
+
+$`$INST`
+[1] "Cytekbio"
+
+$`$MODE`
+[1] "L"
+
+$`$NEXTDATA`
+[1] "0"
+
+$`$OP`
+[1] "David Rach"
+
+$`$P10B`
+[1] "32"
+
+$`$P10E`
+[1] "0,0"
+
+$`$P10N`
+[1] "SSC-B-A"
+
+$`$P10R`
+[1] "4194304"
+
+$`$P10TYPE`
+[1] "Side_Scatter"
+
+$`$P10V`
+[1] "266"
+
+$`$P11B`
+[1] "32"
+
+$`$P11E`
+[1] "0,0"
+
+$`$P11N`
+[1] "BUV395-A"
+
+$`$P11R`
+[1] "4194304"
+
+$`$P11S`
+[1] "CD62L"
+
+$`$P11TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P11V`
+[1] "0"
+
+$`$P12B`
+[1] "32"
+
+$`$P12E`
+[1] "0,0"
+
+$`$P12N`
+[1] "BUV563-A"
+
+$`$P12R`
+[1] "4194304"
+
+$`$P12S`
+[1] "CD69"
+
+$`$P12TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P12V`
+[1] "0"
+
+$`$P13B`
+[1] "32"
+
+$`$P13E`
+[1] "0,0"
+
+$`$P13N`
+[1] "BUV615-A"
+
+$`$P13R`
+[1] "4194304"
+
+$`$P13S`
+[1] "CCR4"
+
+$`$P13TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P13V`
+[1] "0"
+
+$`$P14B`
+[1] "32"
+
+$`$P14E`
+[1] "0,0"
+
+$`$P14N`
+[1] "BUV661-A"
+
+$`$P14R`
+[1] "4194304"
+
+$`$P14S`
+[1] "Vd2"
+
+$`$P14TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P14V`
+[1] "0"
+
+$`$P15B`
+[1] "32"
+
+$`$P15E`
+[1] "0,0"
+
+$`$P15N`
+[1] "BUV737-A"
+
+$`$P15R`
+[1] "4194304"
+
+$`$P15S`
+[1] "CD38"
+
+$`$P15TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P15V`
+[1] "0"
+
+$`$P16B`
+[1] "32"
+
+$`$P16E`
+[1] "0,0"
+
+$`$P16N`
+[1] "BUV805-A"
+
+$`$P16R`
+[1] "4194304"
+
+$`$P16S`
+[1] "CD4"
+
+$`$P16TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P16V`
+[1] "0"
+
+$`$P17B`
+[1] "32"
+
+$`$P17E`
+[1] "0,0"
+
+$`$P17N`
+[1] "Pacific Blue-A"
+
+$`$P17R`
+[1] "4194304"
+
+$`$P17S`
+[1] "Dump"
+
+$`$P17TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P17V`
+[1] "0"
+
+$`$P18B`
+[1] "32"
+
+$`$P18E`
+[1] "0,0"
+
+$`$P18N`
+[1] "BV480-A"
+
+$`$P18R`
+[1] "4194304"
+
+$`$P18S`
+[1] "CD161"
+
+$`$P18TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P18V`
+[1] "0"
+
+$`$P19B`
+[1] "32"
+
+$`$P19E`
+[1] "0,0"
+
+$`$P19N`
+[1] "BV570-A"
+
+$`$P19R`
+[1] "4194304"
+
+$`$P19S`
+[1] "CD16"
+
+$`$P19TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P19V`
+[1] "0"
+
+$`$P1B`
+[1] "32"
+
+$`$P1E`
+[1] "0,0"
+
+$`$P1N`
+[1] "Time"
+
+$`$P1R`
+[1] "516839"
+
+$`$P1TYPE`
+[1] "Time"
+
+$`$P20B`
+[1] "32"
+
+$`$P20E`
+[1] "0,0"
+
+$`$P20N`
+[1] "BV605-A"
+
+$`$P20R`
+[1] "4194304"
+
+$`$P20S`
+[1] "CD45RA"
+
+$`$P20TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P20V`
+[1] "0"
+
+$`$P21B`
+[1] "32"
+
+$`$P21E`
+[1] "0,0"
+
+$`$P21N`
+[1] "BV650-A"
+
+$`$P21R`
+[1] "4194304"
+
+$`$P21S`
+[1] "CD8"
+
+$`$P21TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P21V`
+[1] "0"
+
+$`$P22B`
+[1] "32"
+
+$`$P22E`
+[1] "0,0"
+
+$`$P22N`
+[1] "BV711-A"
+
+$`$P22R`
+[1] "4194304"
+
+$`$P22S`
+[1] "Va7.2"
+
+$`$P22TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P22V`
+[1] "0"
+
+$`$P23B`
+[1] "32"
+
+$`$P23E`
+[1] "0,0"
+
+$`$P23N`
+[1] "BV750-A"
+
+$`$P23R`
+[1] "4194304"
+
+$`$P23S`
+[1] "IFNg"
+
+$`$P23TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P23V`
+[1] "0"
+
+$`$P24B`
+[1] "32"
+
+$`$P24E`
+[1] "0,0"
+
+$`$P24N`
+[1] "BV786-A"
+
+$`$P24R`
+[1] "4194304"
+
+$`$P24S`
+[1] "CCR6"
+
+$`$P24TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P24V`
+[1] "0"
+
+$`$P25B`
+[1] "32"
+
+$`$P25E`
+[1] "0,0"
+
+$`$P25N`
+[1] "Alexa Fluor 488-A"
+
+$`$P25R`
+[1] "4194304"
+
+$`$P25S`
+[1] "FoxP3"
+
+$`$P25TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P25V`
+[1] "0"
+
+$`$P26B`
+[1] "32"
+
+$`$P26E`
+[1] "0,0"
+
+$`$P26N`
+[1] "Spark Blue 550-A"
+
+$`$P26R`
+[1] "4194304"
+
+$`$P26S`
+[1] "CD3"
+
+$`$P26TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P26V`
+[1] "0"
+
+$`$P27B`
+[1] "32"
+
+$`$P27E`
+[1] "0,0"
+
+$`$P27N`
+[1] "Spark Blue 574-A"
+
+$`$P27R`
+[1] "4194304"
+
+$`$P27S`
+[1] "CD45"
+
+$`$P27TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P27V`
+[1] "0"
+
+$`$P28B`
+[1] "32"
+
+$`$P28E`
+[1] "0,0"
+
+$`$P28N`
+[1] "RB613-A"
+
+$`$P28R`
+[1] "4194304"
+
+$`$P28S`
+[1] "PD1"
+
+$`$P28TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P28V`
+[1] "0"
+
+$`$P29B`
+[1] "32"
+
+$`$P29E`
+[1] "0,0"
+
+$`$P29N`
+[1] "RB705-A"
+
+$`$P29R`
+[1] "4194304"
+
+$`$P29S`
+[1] "CD26"
+
+$`$P29TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P29V`
+[1] "0"
+
+$`$P2B`
+[1] "32"
+
+$`$P2E`
+[1] "0,0"
+
+$`$P2N`
+[1] "SSC-W"
+
+$`$P2R`
+[1] "4194304"
+
+$`$P2TYPE`
+[1] "Side_Scatter"
+
+$`$P2V`
+[1] "350"
+
+$`$P30B`
+[1] "32"
+
+$`$P30E`
+[1] "0,0"
+
+$`$P30N`
+[1] "RB780-A"
+
+$`$P30R`
+[1] "4194304"
+
+$`$P30S`
+[1] "CXCR5"
+
+$`$P30TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P30V`
+[1] "0"
+
+$`$P31B`
+[1] "32"
+
+$`$P31E`
+[1] "0,0"
+
+$`$P31N`
+[1] "PE-A"
+
+$`$P31R`
+[1] "4194304"
+
+$`$P31S`
+[1] "ICOS"
+
+$`$P31TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P31V`
+[1] "0"
+
+$`$P32B`
+[1] "32"
+
+$`$P32E`
+[1] "0,0"
+
+$`$P32N`
+[1] "PE-Dazzle594-A"
+
+$`$P32R`
+[1] "4194304"
+
+$`$P32S`
+[1] "TNFa"
+
+$`$P32TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P32V`
+[1] "0"
+
+$`$P33B`
+[1] "32"
+
+$`$P33E`
+[1] "0,0"
+
+$`$P33N`
+[1] "PE-Cy5-A"
+
+$`$P33R`
+[1] "4194304"
+
+$`$P33S`
+[1] "CXCR3"
+
+$`$P33TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P33V`
+[1] "0"
+
+$`$P34B`
+[1] "32"
+
+$`$P34E`
+[1] "0,0"
+
+$`$P34N`
+[1] "PE-Fire 700-A"
+
+$`$P34R`
+[1] "4194304"
+
+$`$P34S`
+[1] "CD127"
+
+$`$P34TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P34V`
+[1] "0"
+
+$`$P35B`
+[1] "32"
+
+$`$P35E`
+[1] "0,0"
+
+$`$P35N`
+[1] "PE-Fire 744-A"
+
+$`$P35R`
+[1] "4194304"
+
+$`$P35S`
+[1] "CD25"
+
+$`$P35TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P35V`
+[1] "0"
+
+$`$P36B`
+[1] "32"
+
+$`$P36E`
+[1] "0,0"
+
+$`$P36N`
+[1] "PE-Vio770-A"
+
+$`$P36R`
+[1] "4194304"
+
+$`$P36S`
+[1] "HLA-DR"
+
+$`$P36TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P36V`
+[1] "0"
+
+$`$P37B`
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+$`$P37S`
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+$`$P38B`
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+$`$P38E`
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+$`$P38N`
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+$`$P38R`
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+$`$P38S`
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+$`$P38TYPE`
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+$`$P39S`
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+$`$P40E`
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+$`$P40S`
+[1] "Viability"
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+$`$PAR`
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+
+$`$PROJ`
+[1] "2025_07_26_AB_02"
+
+$`$SPILLOVER`
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+ [1,]    1e+00        0        0        0        0        0              0
+ [2,]    1e-06        1        0        0        0        0              0
+ [3,]    0e+00        0        1        0        0        0              0
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+[32,]    0e+00        0        0        0        0        0              0
+[33,]    0e+00        0        0        0        0        0              0
+      BV480-A BV570-A BV605-A BV650-A BV711-A BV750-A BV786-A Alexa Fluor 488-A
+ [1,]       0       0       0       0       0       0       0                 0
+ [2,]       0       0       0       0       0       0       0                 0
+ [3,]       0       0       0       0       0       0       0                 0
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+ [9,]       0       1       0       0       0       0       0                 0
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+[25,]       0       0       0       0       0       0       0                 0
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+[32,]       0       0       0       0       0       0       0                 0
+[33,]       0       0       0       0       0       0       0                 0
+      Spark Blue 550-A Spark Blue 574-A RB613-A RB705-A RB780-A PE-A
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+ [2,]                0                0       0       0       0    0
+ [3,]                0                0       0       0       0    0
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+[30,]                0                0       0       0       0    0
+[31,]                0                0       0       0       0    0
+[32,]                0                0       0       0       0    0
+[33,]                0                0       0       0       0    0
+      PE-Dazzle594-A PE-Cy5-A PE-Fire 700-A PE-Fire 744-A PE-Vio770-A APC-A
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+ [2,]              0        0             0             0           0     0
+ [3,]              0        0             0             0           0     0
+ [4,]              0        0             0             0           0     0
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+[32,]              0        0             0             0           0     0
+[33,]              0        0             0             0           0     0
+      Alexa Fluor 647-A APC-R700-A Zombie NIR-A APC-Fire 750-A APC-Fire 810-A
+ [1,]                 0          0            0              0              0
+ [2,]                 0          0            0              0              0
+ [3,]                 0          0            0              0              0
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+      AF-A
+ [1,]    0
+ [2,]    0
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+$`$TIMESTEP`
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+$`$TOT`
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+$`APPLY COMPENSATION`
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+$CHARSET
+[1] "utf-8"
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+$FCSversion
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+$`flowCore_$P40Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P41Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P41Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P42Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P42Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P43Rmax`
+[1] "4194303"
+
+$`flowCore_$P43Rmin`
+[1] "-111"
+
+$`flowCore_$P4Rmax`
+[1] "4194303"
+
+$`flowCore_$P4Rmin`
+[1] "0"
+
+$`flowCore_$P5Rmax`
+[1] "4194303"
+
+$`flowCore_$P5Rmin`
+[1] "0"
+
+$`flowCore_$P6Rmax`
+[1] "4194303"
+
+$`flowCore_$P6Rmin`
+[1] "0"
+
+$`flowCore_$P7Rmax`
+[1] "4194303"
+
+$`flowCore_$P7Rmin`
+[1] "0"
+
+$`flowCore_$P8Rmax`
+[1] "4194303"
+
+$`flowCore_$P8Rmin`
+[1] "0"
+
+$`flowCore_$P9Rmax`
+[1] "4194303"
+
+$`flowCore_$P9Rmin`
+[1] "0"
+
+$`FSC ASF`
+[1] "1.18"
+
+$GROUPNAME
+[1] "NY068_02"
+
+$GUID
+[1] "2025_07_26_AB_02_NY068_02_Ctrl.fcs"
+
+$LASER1ASF
+[1] "1.12"
+
+$LASER1DELAY
+[1] "-39.65"
+
+$LASER1NAME
+[1] "YellowGreen"
+
+$LASER2ASF
+[1] "1.09"
+
+$LASER2DELAY
+[1] "-19.825"
+
+$LASER2NAME
+[1] "Violet"
+
+$LASER3ASF
+[1] "1.15"
+
+$LASER3DELAY
+[1] "0"
+
+$LASER3NAME
+[1] "Blue"
+
+$LASER4ASF
+[1] "1.04"
+
+$LASER4DELAY
+[1] "20.3"
+
+$LASER4NAME
+[1] "Red"
+
+$LASER5ASF
+[1] "1.09"
+
+$LASER5DELAY
+[1] "39.8"
+
+$LASER5NAME
+[1] "UV"
+
+$ORIGINALGUID
+[1] "2025_07_26_AB_02_NY068_02_Ctrl.fcs"
+
+$P10DISPLAY
+[1] "LIN"
+
+$P11DISPLAY
+[1] "LOG"
+
+$P12DISPLAY
+[1] "LOG"
+
+$P13DISPLAY
+[1] "LOG"
+
+$P14DISPLAY
+[1] "LOG"
+
+$P15DISPLAY
+[1] "LOG"
+
+$P16DISPLAY
+[1] "LOG"
+
+$P17DISPLAY
+[1] "LOG"
+
+$P18DISPLAY
+[1] "LOG"
+
+$P19DISPLAY
+[1] "LOG"
+
+$P1DISPLAY
+[1] "LOG"
+
+$P20DISPLAY
+[1] "LOG"
+
+$P21DISPLAY
+[1] "LOG"
+
+$P22DISPLAY
+[1] "LOG"
+
+$P23DISPLAY
+[1] "LOG"
+
+$P24DISPLAY
+[1] "LOG"
+
+$P25DISPLAY
+[1] "LOG"
+
+$P26DISPLAY
+[1] "LOG"
+
+$P27DISPLAY
+[1] "LOG"
+
+$P28DISPLAY
+[1] "LOG"
+
+$P29DISPLAY
+[1] "LOG"
+
+$P2DISPLAY
+[1] "LIN"
+
+$P30DISPLAY
+[1] "LOG"
+
+$P31DISPLAY
+[1] "LOG"
+
+$P32DISPLAY
+[1] "LOG"
+
+$P33DISPLAY
+[1] "LOG"
+
+$P34DISPLAY
+[1] "LOG"
+
+$P35DISPLAY
+[1] "LOG"
+
+$P36DISPLAY
+[1] "LOG"
+
+$P37DISPLAY
+[1] "LOG"
+
+$P38DISPLAY
+[1] "LOG"
+
+$P39DISPLAY
+[1] "LOG"
+
+$P3DISPLAY
+[1] "LIN"
+
+$P40DISPLAY
+[1] "LOG"
+
+$P41DISPLAY
+[1] "LOG"
+
+$P42DISPLAY
+[1] "LOG"
+
+$P43DISPLAY
+[1] "LOG"
+
+$P4DISPLAY
+[1] "LIN"
+
+$P5DISPLAY
+[1] "LIN"
+
+$P6DISPLAY
+[1] "LIN"
+
+$P7DISPLAY
+[1] "LIN"
+
+$P8DISPLAY
+[1] "LIN"
+
+$P9DISPLAY
+[1] "LIN"
+
+$THRESHOLD
+[1] "(FSC,600000)"
+
+$transformation
+[1] "custom"
+
+$TUBENAME
+[1] "Ctrl"
+
+$USERSETTINGNAME
+[1] "DR_2025_AB_Nuclear"
+
+$`WINDOW EXTENSION`
+[1] "3"
+
+
class(DescriptionList)
+
+
[1] "list"
+
+
str(DescriptionList)
+
+
List of 472
+ $ $BEGINANALYSIS    : chr "0"
+ $ $BEGINDATA        : chr "18357"
+ $ $BEGINSTEXT       : chr "0"
+ $ $BTIM             : chr "21:30:10.27"
+ $ $BYTEORD          : chr "4,3,2,1"
+ $ $CYT              : chr "Aurora"
+ $ $CYTOLIB_VERSION  : chr "2.22.0"
+ $ $CYTSN            : chr "U1368"
+ $ $DATATYPE         : chr "F"
+ $ $DATE             : chr "26-Jul-2025"
+ $ $ENDANALYSIS      : chr "0"
+ $ $ENDDATA          : chr "35556"
+ $ $ENDSTEXT         : chr "0"
+ $ $ETIM             : chr "21:31:01.86"
+ $ $FIL              : chr "Ctrl.fcs"
+ $ $INST             : chr "Cytekbio"
+ $ $MODE             : chr "L"
+ $ $NEXTDATA         : chr "0"
+ $ $OP               : chr "David Rach"
+ $ $P10B             : chr "32"
+ $ $P10E             : chr "0,0"
+ $ $P10N             : chr "SSC-B-A"
+ $ $P10R             : chr "4194304"
+ $ $P10TYPE          : chr "Side_Scatter"
+ $ $P10V             : chr "266"
+ $ $P11B             : chr "32"
+ $ $P11E             : chr "0,0"
+ $ $P11N             : chr "BUV395-A"
+ $ $P11R             : chr "4194304"
+ $ $P11S             : chr "CD62L"
+ $ $P11TYPE          : chr "Unmixed_Fluorescence"
+ $ $P11V             : chr "0"
+ $ $P12B             : chr "32"
+ $ $P12E             : chr "0,0"
+ $ $P12N             : chr "BUV563-A"
+ $ $P12R             : chr "4194304"
+ $ $P12S             : chr "CD69"
+ $ $P12TYPE          : chr "Unmixed_Fluorescence"
+ $ $P12V             : chr "0"
+ $ $P13B             : chr "32"
+ $ $P13E             : chr "0,0"
+ $ $P13N             : chr "BUV615-A"
+ $ $P13R             : chr "4194304"
+ $ $P13S             : chr "CCR4"
+ $ $P13TYPE          : chr "Unmixed_Fluorescence"
+ $ $P13V             : chr "0"
+ $ $P14B             : chr "32"
+ $ $P14E             : chr "0,0"
+ $ $P14N             : chr "BUV661-A"
+ $ $P14R             : chr "4194304"
+ $ $P14S             : chr "Vd2"
+ $ $P14TYPE          : chr "Unmixed_Fluorescence"
+ $ $P14V             : chr "0"
+ $ $P15B             : chr "32"
+ $ $P15E             : chr "0,0"
+ $ $P15N             : chr "BUV737-A"
+ $ $P15R             : chr "4194304"
+ $ $P15S             : chr "CD38"
+ $ $P15TYPE          : chr "Unmixed_Fluorescence"
+ $ $P15V             : chr "0"
+ $ $P16B             : chr "32"
+ $ $P16E             : chr "0,0"
+ $ $P16N             : chr "BUV805-A"
+ $ $P16R             : chr "4194304"
+ $ $P16S             : chr "CD4"
+ $ $P16TYPE          : chr "Unmixed_Fluorescence"
+ $ $P16V             : chr "0"
+ $ $P17B             : chr "32"
+ $ $P17E             : chr "0,0"
+ $ $P17N             : chr "Pacific Blue-A"
+ $ $P17R             : chr "4194304"
+ $ $P17S             : chr "Dump"
+ $ $P17TYPE          : chr "Unmixed_Fluorescence"
+ $ $P17V             : chr "0"
+ $ $P18B             : chr "32"
+ $ $P18E             : chr "0,0"
+ $ $P18N             : chr "BV480-A"
+ $ $P18R             : chr "4194304"
+ $ $P18S             : chr "CD161"
+ $ $P18TYPE          : chr "Unmixed_Fluorescence"
+ $ $P18V             : chr "0"
+ $ $P19B             : chr "32"
+ $ $P19E             : chr "0,0"
+ $ $P19N             : chr "BV570-A"
+ $ $P19R             : chr "4194304"
+ $ $P19S             : chr "CD16"
+ $ $P19TYPE          : chr "Unmixed_Fluorescence"
+ $ $P19V             : chr "0"
+ $ $P1B              : chr "32"
+ $ $P1E              : chr "0,0"
+ $ $P1N              : chr "Time"
+ $ $P1R              : chr "516839"
+ $ $P1TYPE           : chr "Time"
+ $ $P20B             : chr "32"
+ $ $P20E             : chr "0,0"
+ $ $P20N             : chr "BV605-A"
+ $ $P20R             : chr "4194304"
+ $ $P20S             : chr "CD45RA"
+ $ $P20TYPE          : chr "Unmixed_Fluorescence"
+  [list output truncated]
+
+
DescriptionList$`$SPILLOVER`
+
+
      BUV395-A BUV563-A BUV615-A BUV661-A BUV737-A BUV805-A Pacific Blue-A
+ [1,]    1e+00        0        0        0        0        0              0
+ [2,]    1e-06        1        0        0        0        0              0
+ [3,]    0e+00        0        1        0        0        0              0
+ [4,]    0e+00        0        0        1        0        0              0
+ [5,]    0e+00        0        0        0        1        0              0
+ [6,]    0e+00        0        0        0        0        1              0
+ [7,]    0e+00        0        0        0        0        0              1
+ [8,]    0e+00        0        0        0        0        0              0
+ [9,]    0e+00        0        0        0        0        0              0
+[10,]    0e+00        0        0        0        0        0              0
+[11,]    0e+00        0        0        0        0        0              0
+[12,]    0e+00        0        0        0        0        0              0
+[13,]    0e+00        0        0        0        0        0              0
+[14,]    0e+00        0        0        0        0        0              0
+[15,]    0e+00        0        0        0        0        0              0
+[16,]    0e+00        0        0        0        0        0              0
+[17,]    0e+00        0        0        0        0        0              0
+[18,]    0e+00        0        0        0        0        0              0
+[19,]    0e+00        0        0        0        0        0              0
+[20,]    0e+00        0        0        0        0        0              0
+[21,]    0e+00        0        0        0        0        0              0
+[22,]    0e+00        0        0        0        0        0              0
+[23,]    0e+00        0        0        0        0        0              0
+[24,]    0e+00        0        0        0        0        0              0
+[25,]    0e+00        0        0        0        0        0              0
+[26,]    0e+00        0        0        0        0        0              0
+[27,]    0e+00        0        0        0        0        0              0
+[28,]    0e+00        0        0        0        0        0              0
+[29,]    0e+00        0        0        0        0        0              0
+[30,]    0e+00        0        0        0        0        0              0
+[31,]    0e+00        0        0        0        0        0              0
+[32,]    0e+00        0        0        0        0        0              0
+[33,]    0e+00        0        0        0        0        0              0
+      BV480-A BV570-A BV605-A BV650-A BV711-A BV750-A BV786-A Alexa Fluor 488-A
+ [1,]       0       0       0       0       0       0       0                 0
+ [2,]       0       0       0       0       0       0       0                 0
+ [3,]       0       0       0       0       0       0       0                 0
+ [4,]       0       0       0       0       0       0       0                 0
+ [5,]       0       0       0       0       0       0       0                 0
+ [6,]       0       0       0       0       0       0       0                 0
+ [7,]       0       0       0       0       0       0       0                 0
+ [8,]       1       0       0       0       0       0       0                 0
+ [9,]       0       1       0       0       0       0       0                 0
+[10,]       0       0       1       0       0       0       0                 0
+[11,]       0       0       0       1       0       0       0                 0
+[12,]       0       0       0       0       1       0       0                 0
+[13,]       0       0       0       0       0       1       0                 0
+[14,]       0       0       0       0       0       0       1                 0
+[15,]       0       0       0       0       0       0       0                 1
+[16,]       0       0       0       0       0       0       0                 0
+[17,]       0       0       0       0       0       0       0                 0
+[18,]       0       0       0       0       0       0       0                 0
+[19,]       0       0       0       0       0       0       0                 0
+[20,]       0       0       0       0       0       0       0                 0
+[21,]       0       0       0       0       0       0       0                 0
+[22,]       0       0       0       0       0       0       0                 0
+[23,]       0       0       0       0       0       0       0                 0
+[24,]       0       0       0       0       0       0       0                 0
+[25,]       0       0       0       0       0       0       0                 0
+[26,]       0       0       0       0       0       0       0                 0
+[27,]       0       0       0       0       0       0       0                 0
+[28,]       0       0       0       0       0       0       0                 0
+[29,]       0       0       0       0       0       0       0                 0
+[30,]       0       0       0       0       0       0       0                 0
+[31,]       0       0       0       0       0       0       0                 0
+[32,]       0       0       0       0       0       0       0                 0
+[33,]       0       0       0       0       0       0       0                 0
+      Spark Blue 550-A Spark Blue 574-A RB613-A RB705-A RB780-A PE-A
+ [1,]                0                0       0       0       0    0
+ [2,]                0                0       0       0       0    0
+ [3,]                0                0       0       0       0    0
+ [4,]                0                0       0       0       0    0
+ [5,]                0                0       0       0       0    0
+ [6,]                0                0       0       0       0    0
+ [7,]                0                0       0       0       0    0
+ [8,]                0                0       0       0       0    0
+ [9,]                0                0       0       0       0    0
+[10,]                0                0       0       0       0    0
+[11,]                0                0       0       0       0    0
+[12,]                0                0       0       0       0    0
+[13,]                0                0       0       0       0    0
+[14,]                0                0       0       0       0    0
+[15,]                0                0       0       0       0    0
+[16,]                1                0       0       0       0    0
+[17,]                0                1       0       0       0    0
+[18,]                0                0       1       0       0    0
+[19,]                0                0       0       1       0    0
+[20,]                0                0       0       0       1    0
+[21,]                0                0       0       0       0    1
+[22,]                0                0       0       0       0    0
+[23,]                0                0       0       0       0    0
+[24,]                0                0       0       0       0    0
+[25,]                0                0       0       0       0    0
+[26,]                0                0       0       0       0    0
+[27,]                0                0       0       0       0    0
+[28,]                0                0       0       0       0    0
+[29,]                0                0       0       0       0    0
+[30,]                0                0       0       0       0    0
+[31,]                0                0       0       0       0    0
+[32,]                0                0       0       0       0    0
+[33,]                0                0       0       0       0    0
+      PE-Dazzle594-A PE-Cy5-A PE-Fire 700-A PE-Fire 744-A PE-Vio770-A APC-A
+ [1,]              0        0             0             0           0     0
+ [2,]              0        0             0             0           0     0
+ [3,]              0        0             0             0           0     0
+ [4,]              0        0             0             0           0     0
+ [5,]              0        0             0             0           0     0
+ [6,]              0        0             0             0           0     0
+ [7,]              0        0             0             0           0     0
+ [8,]              0        0             0             0           0     0
+ [9,]              0        0             0             0           0     0
+[10,]              0        0             0             0           0     0
+[11,]              0        0             0             0           0     0
+[12,]              0        0             0             0           0     0
+[13,]              0        0             0             0           0     0
+[14,]              0        0             0             0           0     0
+[15,]              0        0             0             0           0     0
+[16,]              0        0             0             0           0     0
+[17,]              0        0             0             0           0     0
+[18,]              0        0             0             0           0     0
+[19,]              0        0             0             0           0     0
+[20,]              0        0             0             0           0     0
+[21,]              0        0             0             0           0     0
+[22,]              1        0             0             0           0     0
+[23,]              0        1             0             0           0     0
+[24,]              0        0             1             0           0     0
+[25,]              0        0             0             1           0     0
+[26,]              0        0             0             0           1     0
+[27,]              0        0             0             0           0     1
+[28,]              0        0             0             0           0     0
+[29,]              0        0             0             0           0     0
+[30,]              0        0             0             0           0     0
+[31,]              0        0             0             0           0     0
+[32,]              0        0             0             0           0     0
+[33,]              0        0             0             0           0     0
+      Alexa Fluor 647-A APC-R700-A Zombie NIR-A APC-Fire 750-A APC-Fire 810-A
+ [1,]                 0          0            0              0              0
+ [2,]                 0          0            0              0              0
+ [3,]                 0          0            0              0              0
+ [4,]                 0          0            0              0              0
+ [5,]                 0          0            0              0              0
+ [6,]                 0          0            0              0              0
+ [7,]                 0          0            0              0              0
+ [8,]                 0          0            0              0              0
+ [9,]                 0          0            0              0              0
+[10,]                 0          0            0              0              0
+[11,]                 0          0            0              0              0
+[12,]                 0          0            0              0              0
+[13,]                 0          0            0              0              0
+[14,]                 0          0            0              0              0
+[15,]                 0          0            0              0              0
+[16,]                 0          0            0              0              0
+[17,]                 0          0            0              0              0
+[18,]                 0          0            0              0              0
+[19,]                 0          0            0              0              0
+[20,]                 0          0            0              0              0
+[21,]                 0          0            0              0              0
+[22,]                 0          0            0              0              0
+[23,]                 0          0            0              0              0
+[24,]                 0          0            0              0              0
+[25,]                 0          0            0              0              0
+[26,]                 0          0            0              0              0
+[27,]                 0          0            0              0              0
+[28,]                 1          0            0              0              0
+[29,]                 0          1            0              0              0
+[30,]                 0          0            1              0              0
+[31,]                 0          0            0              1              0
+[32,]                 0          0            0              0              1
+[33,]                 0          0            0              0              0
+      AF-A
+ [1,]    0
+ [2,]    0
+ [3,]    0
+ [4,]    0
+ [5,]    0
+ [6,]    0
+ [7,]    0
+ [8,]    0
+ [9,]    0
+[10,]    0
+[11,]    0
+[12,]    0
+[13,]    0
+[14,]    0
+[15,]    0
+[16,]    0
+[17,]    0
+[18,]    0
+[19,]    0
+[20,]    0
+[21,]    0
+[22,]    0
+[23,]    0
+[24,]    0
+[25,]    0
+[26,]    0
+[27,]    0
+[28,]    0
+[29,]    0
+[30,]    0
+[31,]    0
+[32,]    0
+[33,]    1
+
+
Subset <- DescriptionList[1:18]
+DescriptionList$`$BTIM`
+
+
[1] "21:30:10.27"
+
+
DescriptionList$`$CYT`
+
+
[1] "Aurora"
+
+
DescriptionList$`$CYTSN`
+
+
[1] "U1368"
+
+
DescriptionList$`$DATE`
+
+
[1] "26-Jul-2025"
+
+
DescriptionList$`$ETIM`
+
+
[1] "21:31:01.86"
+
+
DescriptionList$`$FIL`
+
+
[1] "Ctrl.fcs"
+
+
DescriptionList$`$OP`
+
+
[1] "David Rach"
+
+
Detectors <- DescriptionList[20:384]
+Detectors
+
+
$`$P10B`
+[1] "32"
+
+$`$P10E`
+[1] "0,0"
+
+$`$P10N`
+[1] "SSC-B-A"
+
+$`$P10R`
+[1] "4194304"
+
+$`$P10TYPE`
+[1] "Side_Scatter"
+
+$`$P10V`
+[1] "266"
+
+$`$P11B`
+[1] "32"
+
+$`$P11E`
+[1] "0,0"
+
+$`$P11N`
+[1] "BUV395-A"
+
+$`$P11R`
+[1] "4194304"
+
+$`$P11S`
+[1] "CD62L"
+
+$`$P11TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P11V`
+[1] "0"
+
+$`$P12B`
+[1] "32"
+
+$`$P12E`
+[1] "0,0"
+
+$`$P12N`
+[1] "BUV563-A"
+
+$`$P12R`
+[1] "4194304"
+
+$`$P12S`
+[1] "CD69"
+
+$`$P12TYPE`
+[1] "Unmixed_Fluorescence"
+
+$`$P12V`
+[1] "0"
+
+$`$P13B`
+[1] "32"
+
+$`$P13E`
+[1] "0,0"
+
+$`$P13N`
+[1] "BUV615-A"
+
+$`$P13R`
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+$`$SPILLOVER`
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+ [2,]    1e-06        1        0        0        0        0              0
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+      Spark Blue 550-A Spark Blue 574-A RB613-A RB705-A RB780-A PE-A
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+[19,]                0                0       0       1       0    0
+[20,]                0                0       0       0       1    0
+[21,]                0                0       0       0       0    1
+[22,]                0                0       0       0       0    0
+[23,]                0                0       0       0       0    0
+[24,]                0                0       0       0       0    0
+[25,]                0                0       0       0       0    0
+[26,]                0                0       0       0       0    0
+[27,]                0                0       0       0       0    0
+[28,]                0                0       0       0       0    0
+[29,]                0                0       0       0       0    0
+[30,]                0                0       0       0       0    0
+[31,]                0                0       0       0       0    0
+[32,]                0                0       0       0       0    0
+[33,]                0                0       0       0       0    0
+      PE-Dazzle594-A PE-Cy5-A PE-Fire 700-A PE-Fire 744-A PE-Vio770-A APC-A
+ [1,]              0        0             0             0           0     0
+ [2,]              0        0             0             0           0     0
+ [3,]              0        0             0             0           0     0
+ [4,]              0        0             0             0           0     0
+ [5,]              0        0             0             0           0     0
+ [6,]              0        0             0             0           0     0
+ [7,]              0        0             0             0           0     0
+ [8,]              0        0             0             0           0     0
+ [9,]              0        0             0             0           0     0
+[10,]              0        0             0             0           0     0
+[11,]              0        0             0             0           0     0
+[12,]              0        0             0             0           0     0
+[13,]              0        0             0             0           0     0
+[14,]              0        0             0             0           0     0
+[15,]              0        0             0             0           0     0
+[16,]              0        0             0             0           0     0
+[17,]              0        0             0             0           0     0
+[18,]              0        0             0             0           0     0
+[19,]              0        0             0             0           0     0
+[20,]              0        0             0             0           0     0
+[21,]              0        0             0             0           0     0
+[22,]              1        0             0             0           0     0
+[23,]              0        1             0             0           0     0
+[24,]              0        0             1             0           0     0
+[25,]              0        0             0             1           0     0
+[26,]              0        0             0             0           1     0
+[27,]              0        0             0             0           0     1
+[28,]              0        0             0             0           0     0
+[29,]              0        0             0             0           0     0
+[30,]              0        0             0             0           0     0
+[31,]              0        0             0             0           0     0
+[32,]              0        0             0             0           0     0
+[33,]              0        0             0             0           0     0
+      Alexa Fluor 647-A APC-R700-A Zombie NIR-A APC-Fire 750-A APC-Fire 810-A
+ [1,]                 0          0            0              0              0
+ [2,]                 0          0            0              0              0
+ [3,]                 0          0            0              0              0
+ [4,]                 0          0            0              0              0
+ [5,]                 0          0            0              0              0
+ [6,]                 0          0            0              0              0
+ [7,]                 0          0            0              0              0
+ [8,]                 0          0            0              0              0
+ [9,]                 0          0            0              0              0
+[10,]                 0          0            0              0              0
+[11,]                 0          0            0              0              0
+[12,]                 0          0            0              0              0
+[13,]                 0          0            0              0              0
+[14,]                 0          0            0              0              0
+[15,]                 0          0            0              0              0
+[16,]                 0          0            0              0              0
+[17,]                 0          0            0              0              0
+[18,]                 0          0            0              0              0
+[19,]                 0          0            0              0              0
+[20,]                 0          0            0              0              0
+[21,]                 0          0            0              0              0
+[22,]                 0          0            0              0              0
+[23,]                 0          0            0              0              0
+[24,]                 0          0            0              0              0
+[25,]                 0          0            0              0              0
+[26,]                 0          0            0              0              0
+[27,]                 0          0            0              0              0
+[28,]                 1          0            0              0              0
+[29,]                 0          1            0              0              0
+[30,]                 0          0            1              0              0
+[31,]                 0          0            0              1              0
+[32,]                 0          0            0              0              1
+[33,]                 0          0            0              0              0
+      AF-A
+ [1,]    0
+ [2,]    0
+ [3,]    0
+ [4,]    0
+ [5,]    0
+ [6,]    0
+ [7,]    0
+ [8,]    0
+ [9,]    0
+[10,]    0
+[11,]    0
+[12,]    0
+[13,]    0
+[14,]    0
+[15,]    0
+[16,]    0
+[17,]    0
+[18,]    0
+[19,]    0
+[20,]    0
+[21,]    0
+[22,]    0
+[23,]    0
+[24,]    0
+[25,]    0
+[26,]    0
+[27,]    0
+[28,]    0
+[29,]    0
+[30,]    0
+[31,]    0
+[32,]    0
+[33,]    1
+
+$`$TIMESTEP`
+[1] "0.0001"
+
+$`$TOT`
+[1] "100"
+
+$`$VOL`
+[1] "60.66"
+
+$`APPLY COMPENSATION`
+[1] "FALSE"
+
+$CHARSET
+[1] "utf-8"
+
+$CREATOR
+[1] "SpectroFlo 3.3.0"
+
+$FCSversion
+[1] "3"
+
+$FILENAME
+[1] "data/AdditionalFCSFiles/2025_07_26_AB_02_NY068_02_Ctrl.fcs"
+
+$`flowCore_$P10Rmax`
+[1] "4194303"
+
+$`flowCore_$P10Rmin`
+[1] "0"
+
+$`flowCore_$P11Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P11Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P12Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P12Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P13Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P13Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P14Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P14Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P15Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P15Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P16Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P16Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P17Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P17Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P18Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P18Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P19Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P19Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P1Rmax`
+[1] "506.501251220703"
+
+$`flowCore_$P1Rmin`
+[1] "0"
+
+$`flowCore_$P20Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P20Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P21Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P21Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P22Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P22Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P23Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P23Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P24Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P24Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P25Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P25Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P26Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P26Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P27Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P27Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P28Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P28Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P29Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P29Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P2Rmax`
+[1] "4194303"
+
+$`flowCore_$P2Rmin`
+[1] "0"
+
+$`flowCore_$P30Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P30Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P31Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P31Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P32Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P32Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P33Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P33Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P34Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P34Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P35Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P35Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P36Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P36Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P37Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P37Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P38Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P38Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P39Rmax`
+[1] "4192505.75"
+
+$`flowCore_$P39Rmin`
+[1] "-111.00008392334"
+
+$`flowCore_$P3Rmax`
+[1] "4194303"
+
+
DescriptionList$`$P7B`
+
+
[1] "32"
+
+
DescriptionList$`$P7E`
+
+
[1] "0,0"
+
+
DescriptionList$`$P7N`
+
+
[1] "FSC-A"
+
+
DescriptionList$`$P7R`
+
+
[1] "4194304"
+
+
DescriptionList$`$P7TYPE`
+
+
[1] "Forward_Scatter"
+
+
DescriptionList$`$P7V`
+
+
[1] "64"
+
+
# keyword(flowFrame)
+
+
+
+

Differences with raw file

+
    +
  • Instead of raw channel names such as “UV1-A”, “UV2-A” etc., there are fluorophore names such as “BUV395-A”.
    • +
  • There are 43 columns instead of 61, indicating that raw channels have been removed and only unmixed channels remain in the data file. +
      +
    • \(`\)PAR` keyword is 43 in this file vs 61 in raw file
      • +
    • +
  • There is now a “TYPE” keyword added: +
      +
    • e.g. \(`\)P40TYPE` that gives a value of “Unmixed_fluorescence”
      • +
    • +
  • There are marker names such as “CD107a” in the desc column.
    • +
  • “$transformation” keyword now has “custom” value
    • +
+
+
+

Problem 2

+

Today’s files were for spectral .fcs files from a Cytek Aurora within a subfolder in data you will also find a conventional flow cytometry file (2025-10_22…). Similarly, explore and see if you find any major differences (beyond the different detector or fluorophore names which will vary based on antibody panel used, etc)

+
+
PathToDataFolder <- file.path("data/AdditionalFCSFiles")
+PathToDataFolder
+
+
[1] "data/AdditionalFCSFiles"
+
+
# Locate .fcs files
+fcs_files <- list.files(PathToDataFolder, pattern=".fcs", full.names=TRUE)
+fcs_files
+
+
[1] "data/AdditionalFCSFiles/2025-10_22_Contrad.fcs"            
+[2] "data/AdditionalFCSFiles/2025_07_26_AB_02_NY068_02_Ctrl.fcs"
+
+
# Locate unmixed .fcs file
+conventional_file <- list.files(PathToDataFolder, pattern="2025-10_22", full.names=TRUE)
+conventional_file
+
+
[1] "data/AdditionalFCSFiles/2025-10_22_Contrad.fcs"
+
+
# Read unmixed .fcs file
+library(flowCore)
+read.FCS(filename=conventional_file)
+
+
flowFrame object '5855c3b6-7adc-45da-8921-191c97c559f5'
+with 1852 cells and 33 observables:
+       name   desc     range  minRange  maxRange
+$P1    Time     NA    262144       0.0    262143
+$P2   FSC-A     NA    262144       0.0    262143
+$P3   FSC-H     NA    262144       0.0    262143
+$P4   FSC-W     NA    262144       0.0    262143
+$P5   SSC-A     NA    262144     -44.8    262143
+...     ...    ...       ...       ...       ...
+$P29 Y615-H     NA    262144      0.00    262143
+$P30 Y710-A     NA    262144   -111.00    262143
+$P31 Y710-H     NA    262144      0.00    262143
+$P32 Y780-A     NA    262144    -87.33    262143
+$P33 Y780-H     NA    262144      0.00    262143
+397 keywords are stored in the 'description' slot
+
+
flowFrame <- read.FCS(filename=conventional_file, transformation = TRUE, truncate_max_range = FALSE)
+class(flowFrame)
+
+
[1] "flowFrame"
+attr(,"package")
+[1] "flowCore"
+
+
MFI_Matrix <- flowFrame@exprs
+ColumnNames <- colnames(MFI_Matrix)
+class(ColumnNames)
+
+
[1] "character"
+
+
# Explore parameters
+ParameterData <- flowFrame@parameters@data
+str(ParameterData)
+
+
'data.frame':   33 obs. of  5 variables:
+ $ name    : 'AsIs' Named chr  "Time" "FSC-A" "FSC-H" "FSC-W" ...
+  ..- attr(*, "names")= chr [1:33] "$P1N" "$P2N" "$P3N" "$P4N" ...
+ $ desc    : 'AsIs' Named chr  NA NA NA NA ...
+  ..- attr(*, "names")= chr [1:33] NA NA NA NA ...
+ $ range   : num  262144 262144 262144 262144 262144 ...
+ $ minRange: num  0 0 0 0 -44.8 ...
+ $ maxRange: num  262143 262143 262143 262143 262143 ...
+
+
# Explore Description
+DescriptionList <- flowFrame@description
+class(DescriptionList)
+
+
[1] "list"
+
+
str(DescriptionList)
+
+
List of 397
+ $ FCSversion        : chr "3"
+ $ $BEGINANALYSIS    : chr "0"
+ $ $ENDANALYSIS      : chr "0"
+ $ $BEGINSTEXT       : chr "0"
+ $ $ENDSTEXT         : chr "0"
+ $ $BEGINDATA        : chr "4378"
+ $ $ENDDATA          : chr "248841             "
+ $ $FIL              : chr "44633.fcs"
+ $ $SYS              : chr "Windows 7 6.1"
+ $ $TOT              : chr "1852               "
+ $ $PAR              : chr "33"
+ $ $MODE             : chr "L"
+ $ $BYTEORD          : chr "4,3,2,1"
+ $ $DATATYPE         : chr "F"
+ $ $NEXTDATA         : chr "0"
+ $ CREATOR           : chr "BD FACSDiva Software Version 8.0.2"
+ $ TUBE NAME         : chr "WE_22_DR_00"
+ $ $SRC              : chr "2025-10"
+ $ EXPERIMENT NAME   : chr "QC_2025-10"
+ $ GUID              : chr "5855c3b6-7adc-45da-8921-191c97c559f5"
+ $ $DATE             : chr "22-OCT-2025"
+ $ $BTIM             : chr "08:44:52"
+ $ $ETIM             : chr "09:16:22"
+ $ SETTINGS          : chr "Cytometer"
+ $ WINDOW EXTENSION  : chr "0.00"
+ $ EXPORT USER NAME  : chr "Administrator"
+ $ EXPORT TIME       : chr "22-OCT-2025-08:44:51"
+ $ FSC ASF           : chr "0.77"
+ $ AUTOBS            : chr "TRUE"
+ $ $INST             : chr " "
+ $ $TIMESTEP         : chr "0.01"
+ $ SPILL             : num [1:13, 1:13] 1 0 0 0 0 0 0 0 0 0 ...
+  ..- attr(*, "dimnames")=List of 2
+  .. ..$ : NULL
+  .. ..$ : chr [1:13] "R670-A" "R730-A" "R780-A" "B530-A" ...
+ $ APPLY COMPENSATION: chr "TRUE"
+ $ THRESHOLD         : chr "FSC,10000"
+ $ $P1N              : chr "Time"
+ $ $P1R              : chr "262144"
+ $ $P1B              : chr "32"
+ $ $P1E              : chr "0,0"
+ $ $P1G              : chr "0.01"
+ $ P1BS              : chr "0"
+ $ P1MS              : chr "0"
+ $ $P2N              : chr "FSC-A"
+ $ $P2R              : chr "262144"
+ $ $P2B              : chr "32"
+ $ $P2E              : chr "0,0"
+ $ $P2V              : chr "600"
+ $ $P2G              : chr "1.0"
+ $ P2DISPLAY         : chr "LIN"
+ $ P2BS              : chr "0"
+ $ P2MS              : chr "0"
+ $ $P3N              : chr "FSC-H"
+ $ $P3R              : chr "262144"
+ $ $P3B              : chr "32"
+ $ $P3E              : chr "0,0"
+ $ $P3V              : chr "600"
+ $ $P3G              : chr "1.0"
+ $ P3DISPLAY         : chr "LIN"
+ $ P3BS              : chr "0"
+ $ P3MS              : chr "0"
+ $ $P4N              : chr "FSC-W"
+ $ $P4R              : chr "262144"
+ $ $P4B              : chr "32"
+ $ $P4E              : chr "0,0"
+ $ $P4V              : chr "600"
+ $ $P4G              : chr "1.0"
+ $ P4BS              : chr "-1"
+ $ P4MS              : chr "0"
+ $ $P5N              : chr "SSC-A"
+ $ $P5R              : chr "262144"
+ $ $P5B              : chr "32"
+ $ $P5E              : chr "0,0"
+ $ $P5V              : chr "280"
+ $ $P5G              : chr "1.0"
+ $ P5DISPLAY         : chr "LIN"
+ $ P5BS              : chr "0"
+ $ P5MS              : chr "0"
+ $ $P6N              : chr "SSC-H"
+ $ $P6R              : chr "262144"
+ $ $P6B              : chr "32"
+ $ $P6E              : chr "0,0"
+ $ $P6V              : chr "280"
+ $ $P6G              : chr "1.0"
+ $ P6DISPLAY         : chr "LIN"
+ $ P6BS              : chr "0"
+ $ P6MS              : chr "0"
+ $ $P7N              : chr "SSC-W"
+ $ $P7R              : chr "262144"
+ $ $P7B              : chr "32"
+ $ $P7E              : chr "0,0"
+ $ $P7V              : chr "280"
+ $ $P7G              : chr "1.0"
+ $ P7BS              : chr "-1"
+ $ P7MS              : chr "0"
+ $ $P8N              : chr "R670-A"
+ $ $P8R              : chr "262144"
+ $ $P8B              : chr "32"
+ $ $P8E              : chr "0,0"
+ $ $P8V              : chr "511"
+ $ $P8G              : chr "1.0"
+  [list output truncated]
+
+
DescriptionList$SPILL
+
+
      R670-A R730-A R780-A B530-A B710-A V450-A V525-A V610-A V670-A Y590-A
+ [1,]      1      0      0      0      0      0      0      0      0      0
+ [2,]      0      1      0      0      0      0      0      0      0      0
+ [3,]      0      0      1      0      0      0      0      0      0      0
+ [4,]      0      0      0      1      0      0      0      0      0      0
+ [5,]      0      0      0      0      1      0      0      0      0      0
+ [6,]      0      0      0      0      0      1      0      0      0      0
+ [7,]      0      0      0      0      0      0      1      0      0      0
+ [8,]      0      0      0      0      0      0      0      1      0      0
+ [9,]      0      0      0      0      0      0      0      0      1      0
+[10,]      0      0      0      0      0      0      0      0      0      1
+[11,]      0      0      0      0      0      0      0      0      0      0
+[12,]      0      0      0      0      0      0      0      0      0      0
+[13,]      0      0      0      0      0      0      0      0      0      0
+      Y615-A Y710-A Y780-A
+ [1,]      0      0      0
+ [2,]      0      0      0
+ [3,]      0      0      0
+ [4,]      0      0      0
+ [5,]      0      0      0
+ [6,]      0      0      0
+ [7,]      0      0      0
+ [8,]      0      0      0
+ [9,]      0      0      0
+[10,]      0      0      0
+[11,]      1      0      0
+[12,]      0      1      0
+[13,]      0      0      1
+
+
# keyword(flowFrame)
+
+
+
+

Differences in conventional file

+
    +
  • Channel names show both area and height parameters
    • +
  • There are 33 columns, i.e. 33 parameters
    • +
  • There is an “APPLY COMPENSATION” keyword that has the value “TRUE”
    • +
  • “CREATOR” keyword indicates an old cytometer using FACSDiva 8.0.2
    • +
  • “$SYS” keyword indicates old PC running Windows 7.6.1
    • +
  • The parameter keywords for each parameter have 7 variations instead of 6 in spectral file
    • +
  • “SPILL” keyword displays compensation matrix vs “$SPILLOVER” keyword in Aurora data
    • +
+
+
+

Problem 3

+

If you have access to commercial software, take one of the .fcs files and try to see if you can see similar internal information from within the software. For those without commercial access, try the equivalent process using Floreada.io.

+

+
+ +
+ + +
+ + + + + \ No newline at end of file diff --git a/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework.qmd b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework.qmd new file mode 100644 index 0000000..22814bb --- /dev/null +++ b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework.qmd @@ -0,0 +1,116 @@ +# Problem 1 +Today’s walkthrough focused on a raw spectral flow cytometry file. Within a subfolder in data you will also find an unmixed .fcs file (2025_07_26…). Using what learned to day, investigate it, and see if you can catalog the main differences that occured to the keyword, parameters and exprs. Did any keywords get added, changed, deleted entirely? etc. + + +# Problem 1 Code +```{r} +PathToDataFolder <- file.path("data/AdditionalFCSFiles") +PathToDataFolder + +# Locate .fcs files +fcs_files <- list.files(PathToDataFolder, pattern=".fcs", full.names=TRUE) +fcs_files + +# Locate unmixed .fcs file +unmixed_file <- list.files(PathToDataFolder, pattern="2025_07_26", full.names=TRUE) +unmixed_file + +# Read unmixed .fcs file +library(flowCore) +read.FCS(filename=unmixed_file) +flowFrame <- read.FCS(filename=unmixed_file, transformation = TRUE, truncate_max_range = FALSE) +class(flowFrame) +MFI_Matrix <- flowFrame@exprs +ColumnNames <- colnames(MFI_Matrix) +class(ColumnNames) + +# Explore parameters +ParameterData <- flowFrame@parameters@data +str(ParameterData) + +# Explore Description +DescriptionList <- flowFrame@description +DescriptionList +class(DescriptionList) +str(DescriptionList) +DescriptionList$`$SPILLOVER` +Subset <- DescriptionList[1:18] +DescriptionList$`$BTIM` +DescriptionList$`$CYT` +DescriptionList$`$CYTSN` +DescriptionList$`$DATE` +DescriptionList$`$ETIM` +DescriptionList$`$FIL` +DescriptionList$`$OP` +Detectors <- DescriptionList[20:384] +Detectors +DescriptionList$`$P7B` +DescriptionList$`$P7E` +DescriptionList$`$P7N` +DescriptionList$`$P7R` +DescriptionList$`$P7TYPE` +DescriptionList$`$P7V` +# keyword(flowFrame) +``` + +# Differences with raw file +- Instead of raw channel names such as "UV1-A", "UV2-A" etc., there are fluorophore names such as "BUV395-A". +- There are 43 columns instead of 61, indicating that raw channels have been removed and only unmixed channels remain in the data file. + - $`$PAR` keyword is 43 in this file vs 61 in raw file +- There is now a "TYPE" keyword added: + - e.g. $`$P40TYPE` that gives a value of "Unmixed_fluorescence" +- There are marker names such as "CD107a" in the desc column. +- "$transformation" keyword now has "custom" value + +# Problem 2 +Today’s files were for spectral .fcs files from a Cytek Aurora within a subfolder in data you will also find a conventional flow cytometry file (2025-10_22…). Similarly, explore and see if you find any major differences (beyond the different detector or fluorophore names which will vary based on antibody panel used, etc) + + +```{r} +PathToDataFolder <- file.path("data/AdditionalFCSFiles") +PathToDataFolder + +# Locate .fcs files +fcs_files <- list.files(PathToDataFolder, pattern=".fcs", full.names=TRUE) +fcs_files + +# Locate unmixed .fcs file +conventional_file <- list.files(PathToDataFolder, pattern="2025-10_22", full.names=TRUE) +conventional_file + +# Read unmixed .fcs file +library(flowCore) +read.FCS(filename=conventional_file) +flowFrame <- read.FCS(filename=conventional_file, transformation = TRUE, truncate_max_range = FALSE) +class(flowFrame) +MFI_Matrix <- flowFrame@exprs +ColumnNames <- colnames(MFI_Matrix) +class(ColumnNames) + +# Explore parameters +ParameterData <- flowFrame@parameters@data +str(ParameterData) + +# Explore Description +DescriptionList <- flowFrame@description +class(DescriptionList) +str(DescriptionList) +DescriptionList$SPILL +# keyword(flowFrame) +``` + +# Differences in conventional file +- Channel names show both area and height parameters +- There are 33 columns, i.e. 33 parameters +- There is an "APPLY COMPENSATION" keyword that has the value "TRUE" +- "CREATOR" keyword indicates an old cytometer using FACSDiva 8.0.2 +- "$SYS" keyword indicates old PC running Windows 7.6.1 +- The parameter keywords for each parameter have 7 variations instead of 6 in spectral file +- "SPILL" keyword displays compensation matrix vs "$SPILLOVER" keyword in Aurora data + + +# Problem 3 +If you have access to commercial software, take one of the .fcs files and try to see if you can see similar internal information from within the software. For those without commercial access, try the equivalent process using Floreada.io. + +![](images/Problem3_1.png) +![](images/Problem3_2.png) diff --git a/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/bootstrap/bootstrap-9e3ffae467580fdb927a41352e75a2e0.min.css b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/bootstrap/bootstrap-9e3ffae467580fdb927a41352e75a2e0.min.css new file mode 100644 index 0000000..29be797 --- /dev/null +++ b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/bootstrap/bootstrap-9e3ffae467580fdb927a41352e75a2e0.min.css @@ -0,0 +1,12 @@ +/*! + * Bootstrap v5.3.1 (https://getbootstrap.com/) + * Copyright 2011-2023 The Bootstrap Authors + * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE) + */:root,[data-bs-theme=light]{--bs-blue: #0d6efd;--bs-indigo: #6610f2;--bs-purple: #6f42c1;--bs-pink: #d63384;--bs-red: #dc3545;--bs-orange: #fd7e14;--bs-yellow: #ffc107;--bs-green: 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1rem;--bs-nav-link-padding-y: 0.5rem;--bs-nav-link-font-weight: ;--bs-nav-link-color: #0d6efd;--bs-nav-link-hover-color: rgb(10.4, 88, 202.4);--bs-nav-link-disabled-color: rgba(33, 37, 41, 0.75);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding-left:0;margin-bottom:0;list-style:none}.nav-link{display:block;padding:var(--bs-nav-link-padding-y) var(--bs-nav-link-padding-x);font-size:var(--bs-nav-link-font-size);font-weight:var(--bs-nav-link-font-weight);color:var(--bs-nav-link-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background:none;border:0;transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out}@media(prefers-reduced-motion: reduce){.nav-link{transition:none}}.nav-link:hover,.nav-link:focus{color:var(--bs-nav-link-hover-color)}.nav-link:focus-visible{outline:0;box-shadow:0 0 0 .25rem 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0);--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgb%28253.26, 253.63, 253.98%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}[data-bs-theme=dark] .navbar-toggler-icon{--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgb%28253.26, 253.63, 253.98%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}.card{--bs-card-spacer-y: 1rem;--bs-card-spacer-x: 1rem;--bs-card-title-spacer-y: 0.5rem;--bs-card-title-color: ;--bs-card-subtitle-color: ;--bs-card-border-width: 1px;--bs-card-border-color: rgba(0, 0, 0, 0.175);--bs-card-border-radius: 0.375rem;--bs-card-box-shadow: ;--bs-card-inner-border-radius: calc(0.375rem - 1px);--bs-card-cap-padding-y: 0.5rem;--bs-card-cap-padding-x: 1rem;--bs-card-cap-bg: 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var(--bs-card-spacer-x);color:var(--bs-card-color)}.card-title{margin-bottom:var(--bs-card-title-spacer-y);color:var(--bs-card-title-color)}.card-subtitle{margin-top:calc(-0.5*var(--bs-card-title-spacer-y));margin-bottom:0;color:var(--bs-card-subtitle-color)}.card-text:last-child{margin-bottom:0}.card-link+.card-link{margin-left:var(--bs-card-spacer-x)}.card-header{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);margin-bottom:0;color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-bottom:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-header:first-child{border-radius:var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius) 0 0}.card-footer{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-top:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-footer:last-child{border-radius:0 0 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.nav-link.active{background-color:var(--bs-card-bg);border-bottom-color:var(--bs-card-bg)}.card-header-pills{margin-right:calc(-0.5*var(--bs-card-cap-padding-x));margin-left:calc(-0.5*var(--bs-card-cap-padding-x))}.card-img-overlay{position:absolute;top:0;right:0;bottom:0;left:0;padding:var(--bs-card-img-overlay-padding);border-radius:var(--bs-card-inner-border-radius)}.card-img,.card-img-top,.card-img-bottom{width:100%}.card-img,.card-img-top{border-top-left-radius:var(--bs-card-inner-border-radius);border-top-right-radius:var(--bs-card-inner-border-radius)}.card-img,.card-img-bottom{border-bottom-right-radius:var(--bs-card-inner-border-radius);border-bottom-left-radius:var(--bs-card-inner-border-radius)}.card-group>.card{margin-bottom:var(--bs-card-group-margin)}@media(min-width: 576px){.card-group{display:flex;display:-webkit-flex;flex-flow:row wrap;-webkit-flex-flow:row wrap}.card-group>.card{flex:1 0 0%;-webkit-flex:1 0 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ease;--bs-accordion-border-color: rgb(221.7, 222.3, 222.9);--bs-accordion-border-width: 1px;--bs-accordion-border-radius: 0.375rem;--bs-accordion-inner-border-radius: calc(0.375rem - 1px);--bs-accordion-btn-padding-x: 1.25rem;--bs-accordion-btn-padding-y: 1rem;--bs-accordion-btn-color: #212529;--bs-accordion-btn-bg: #ffffff;--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23212529'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-icon-width: 1.25rem;--bs-accordion-btn-icon-transform: rotate(-180deg);--bs-accordion-btn-icon-transition: transform 0.2s ease-in-out;--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%285.2, 44, 101.2%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-focus-border-color: rgb(134, 182.5, 254);--bs-accordion-btn-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: rgb(5.2, 44, 101.2);--bs-accordion-active-bg: rgb(206.6, 226, 254.6)}.accordion-button{position:relative;display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;border-radius:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media(prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1*var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media(prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:first-of-type{border-top-left-radius:var(--bs-accordion-border-radius);border-top-right-radius:var(--bs-accordion-border-radius)}.accordion-item:first-of-type .accordion-button{border-top-left-radius:var(--bs-accordion-inner-border-radius);border-top-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:not(:first-of-type){border-top:0}.accordion-item:last-of-type{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-item:last-of-type .accordion-button.collapsed{border-bottom-right-radius:var(--bs-accordion-inner-border-radius);border-bottom-left-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0;border-radius:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme=dark] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%28109.8, 168, 253.8%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%28109.8, 168, 253.8%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: 0;--bs-breadcrumb-padding-y: 0;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color: rgba(33, 37, 41, 0.75);--bs-breadcrumb-item-padding-x: 0.5rem;--bs-breadcrumb-item-active-color: rgba(33, 37, 41, 0.75);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg);border-radius:var(--bs-breadcrumb-border-radius)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, ">") /* rtl: var(--bs-breadcrumb-divider, ">") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: 0.75rem;--bs-pagination-padding-y: 0.375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: #0d6efd;--bs-pagination-bg: #ffffff;--bs-pagination-border-width: 1px;--bs-pagination-border-color: rgb(221.7, 222.3, 222.9);--bs-pagination-border-radius: 0.375rem;--bs-pagination-hover-color: rgb(10.4, 88, 202.4);--bs-pagination-hover-bg: #f8f9fa;--bs-pagination-hover-border-color: rgb(221.7, 222.3, 222.9);--bs-pagination-focus-color: rgb(10.4, 88, 202.4);--bs-pagination-focus-bg: #e9ecef;--bs-pagination-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-pagination-active-color: #ffffff;--bs-pagination-active-bg: #0d6efd;--bs-pagination-active-border-color: #0d6efd;--bs-pagination-disabled-color: rgba(33, 37, 41, 0.75);--bs-pagination-disabled-bg: #e9ecef;--bs-pagination-disabled-border-color: rgb(221.7, 222.3, 222.9);display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out}@media(prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(1px*-1)}.page-item:first-child .page-link{border-top-left-radius:var(--bs-pagination-border-radius);border-bottom-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-top-right-radius:var(--bs-pagination-border-radius);border-bottom-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: 0.75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: 0.5rem}.pagination-sm{--bs-pagination-padding-x: 0.5rem;--bs-pagination-padding-y: 0.25rem;--bs-pagination-font-size:0.875rem;--bs-pagination-border-radius: 0.25rem}.badge{--bs-badge-padding-x: 0.65em;--bs-badge-padding-y: 0.35em;--bs-badge-font-size:0.75em;--bs-badge-font-weight: 700;--bs-badge-color: #ffffff;--bs-badge-border-radius: 0.375rem;display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:var(--bs-badge-border-radius)}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: 1px solid var(--bs-alert-border-color);--bs-alert-border-radius: 0.375rem;--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height: 1rem;--bs-progress-font-size:0.75rem;--bs-progress-bg: #e9ecef;--bs-progress-border-radius: 0.375rem;--bs-progress-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.075);--bs-progress-bar-color: #ffffff;--bs-progress-bar-bg: #0d6efd;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media(prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media(prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: #212529;--bs-list-group-bg: #ffffff;--bs-list-group-border-color: rgb(221.7, 222.3, 222.9);--bs-list-group-border-width: 1px;--bs-list-group-border-radius: 0.375rem;--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: 0.5rem;--bs-list-group-action-color: rgba(33, 37, 41, 0.75);--bs-list-group-action-hover-color: #000;--bs-list-group-action-hover-bg: #f8f9fa;--bs-list-group-action-active-color: #212529;--bs-list-group-action-active-bg: #e9ecef;--bs-list-group-disabled-color: rgba(33, 37, 41, 0.75);--bs-list-group-disabled-bg: #ffffff;--bs-list-group-active-color: #ffffff;--bs-list-group-active-bg: #0d6efd;--bs-list-group-active-border-color: #0d6efd;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;border-radius:var(--bs-list-group-border-radius)}.list-group-numbered{list-style-type:none;counter-reset:section}.list-group-numbered>.list-group-item::before{content:counters(section, ".") ". ";counter-increment:section}.list-group-item-action{width:100%;color:var(--bs-list-group-action-color);text-align:inherit}.list-group-item-action:hover,.list-group-item-action:focus{z-index:1;color:var(--bs-list-group-action-hover-color);text-decoration:none;background-color:var(--bs-list-group-action-hover-bg)}.list-group-item-action:active{color:var(--bs-list-group-action-active-color);background-color:var(--bs-list-group-action-active-bg)}.list-group-item{position:relative;display:block;padding:var(--bs-list-group-item-padding-y) var(--bs-list-group-item-padding-x);color:var(--bs-list-group-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-list-group-bg);border:var(--bs-list-group-border-width) solid 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576px){.list-group-horizontal-sm{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-sm>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-sm>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-sm>.list-group-item.active{margin-top:0}.list-group-horizontal-sm>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-sm>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 768px){.list-group-horizontal-md{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-md>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-md>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-md>.list-group-item.active{margin-top:0}.list-group-horizontal-md>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-md>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 992px){.list-group-horizontal-lg{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-lg>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-lg>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1200px){.list-group-horizontal-xl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1400px){.list-group-horizontal-xxl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xxl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xxl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xxl>.list-group-item.active{margin-top:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}.list-group-flush{border-radius:0}.list-group-flush>.list-group-item{border-width:0 0 var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-default{--bs-list-group-color: var(--bs-default-text-emphasis);--bs-list-group-bg: var(--bs-default-bg-subtle);--bs-list-group-border-color: var(--bs-default-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-default-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-default-border-subtle);--bs-list-group-active-color: var(--bs-default-bg-subtle);--bs-list-group-active-bg: var(--bs-default-text-emphasis);--bs-list-group-active-border-color: var(--bs-default-text-emphasis)}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' 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0.375rem;--bs-toast-box-shadow: 0 0.5rem 1rem rgba(0, 0, 0, 0.15);--bs-toast-header-color: rgba(33, 37, 41, 0.75);--bs-toast-header-bg: rgba(255, 255, 255, 0.85);--bs-toast-header-border-color: rgba(0, 0, 0, 0.175);width:var(--bs-toast-max-width);max-width:100%;font-size:var(--bs-toast-font-size);color:var(--bs-toast-color);pointer-events:auto;background-color:var(--bs-toast-bg);background-clip:padding-box;border:var(--bs-toast-border-width) solid var(--bs-toast-border-color);box-shadow:var(--bs-toast-box-shadow);border-radius:var(--bs-toast-border-radius)}.toast.showing{opacity:0}.toast:not(.show){display:none}.toast-container{--bs-toast-zindex: 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;--quarto-scss-export-dropdown-dark-link-color: #dee2e6;--quarto-scss-export-dropdown-dark-link-hover-color: #ffffff;--quarto-scss-export-dropdown-dark-link-hover-bg: rgba(255, 255, 255, 0.15);--quarto-scss-export-dropdown-dark-link-active-color: #ffffff;--quarto-scss-export-dropdown-dark-link-active-bg: #0d6efd;--quarto-scss-export-dropdown-dark-link-disabled-color: #adb5bd;--quarto-scss-export-dropdown-dark-header-color: #adb5bd;--quarto-scss-export-pagination-color: #0d6efd;--quarto-scss-export-pagination-bg: #ffffff;--quarto-scss-export-pagination-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-pagination-focus-color: rgb(10.4, 88, 202.4);--quarto-scss-export-pagination-focus-bg: #e9ecef;--quarto-scss-export-pagination-hover-color: rgb(10.4, 88, 202.4);--quarto-scss-export-pagination-hover-bg: #f8f9fa;--quarto-scss-export-pagination-hover-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-pagination-active-color: #ffffff;--quarto-scss-export-pagination-active-bg: #0d6efd;--quarto-scss-export-pagination-active-border-color: #0d6efd;--quarto-scss-export-pagination-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-pagination-disabled-bg: #e9ecef;--quarto-scss-export-pagination-disabled-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-card-title-color: ;--quarto-scss-export-card-subtitle-color: ;--quarto-scss-export-card-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-card-box-shadow: ;--quarto-scss-export-card-cap-bg: rgba(33, 37, 41, 0.03);--quarto-scss-export-card-cap-color: ;--quarto-scss-export-card-height: ;--quarto-scss-export-card-color: ;--quarto-scss-export-card-bg: #ffffff;--quarto-scss-export-accordion-color: #212529;--quarto-scss-export-accordion-bg: #ffffff;--quarto-scss-export-accordion-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-accordion-button-color: #212529;--quarto-scss-export-accordion-button-bg: #ffffff;--quarto-scss-export-accordion-button-active-bg: rgb(206.6, 226, 254.6);--quarto-scss-export-accordion-button-active-color: rgb(5.2, 44, 101.2);--quarto-scss-export-accordion-button-focus-border-color: rgb(134, 182.5, 254);--quarto-scss-export-accordion-icon-color: #212529;--quarto-scss-export-accordion-icon-active-color: rgb(5.2, 44, 101.2);--quarto-scss-export-tooltip-color: #ffffff;--quarto-scss-export-tooltip-bg: #000;--quarto-scss-export-tooltip-margin: ;--quarto-scss-export-tooltip-arrow-color: ;--quarto-scss-export-form-feedback-tooltip-line-height: ;--quarto-scss-export-popover-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-popover-header-bg: #e9ecef;--quarto-scss-export-popover-body-color: #212529;--quarto-scss-export-popover-arrow-color: #ffffff;--quarto-scss-export-popover-arrow-outer-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-toast-color: ;--quarto-scss-export-toast-background-color: rgba(255, 255, 255, 0.85);--quarto-scss-export-toast-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-toast-header-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-toast-header-background-color: rgba(255, 255, 255, 0.85);--quarto-scss-export-toast-header-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-badge-color: #ffffff;--quarto-scss-export-modal-content-color: ;--quarto-scss-export-modal-content-bg: #ffffff;--quarto-scss-export-modal-content-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-modal-backdrop-bg: #000;--quarto-scss-export-modal-header-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-modal-footer-bg: ;--quarto-scss-export-modal-footer-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-progress-bg: #e9ecef;--quarto-scss-export-progress-bar-color: #ffffff;--quarto-scss-export-progress-bar-bg: #0d6efd;--quarto-scss-export-list-group-color: #212529;--quarto-scss-export-list-group-bg: #ffffff;--quarto-scss-export-list-group-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-list-group-hover-bg: #f8f9fa;--quarto-scss-export-list-group-active-bg: #0d6efd;--quarto-scss-export-list-group-active-color: #ffffff;--quarto-scss-export-list-group-active-border-color: #0d6efd;--quarto-scss-export-list-group-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-list-group-disabled-bg: #ffffff;--quarto-scss-export-list-group-action-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-list-group-action-hover-color: #000;--quarto-scss-export-list-group-action-active-color: #212529;--quarto-scss-export-list-group-action-active-bg: #e9ecef;--quarto-scss-export-thumbnail-bg: #ffffff;--quarto-scss-export-thumbnail-border-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-figure-caption-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-font-size: ;--quarto-scss-export-breadcrumb-bg: ;--quarto-scss-export-breadcrumb-divider-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-active-color: rgba(33, 37, 41, 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rgba(var(--bs-emphasis-color-rgb, 0, 0, 0), 0.05);--quarto-scss-export-bslib-sidebar-toggle-bg: rgba(var(--bs-emphasis-color-rgb, 0, 0, 0), 0.1);--quarto-scss-export-mermaid-bg-color: #ffffff;--quarto-scss-export-mermaid-edge-color: #6c757d;--quarto-scss-export-mermaid-node-fg-color: #212529;--quarto-scss-export-mermaid-fg-color: #212529;--quarto-scss-export-mermaid-fg-color--lighter: rgb(55.7432432432, 62.5, 69.2567567568);--quarto-scss-export-mermaid-fg-color--lightest: rgb(78.4864864865, 88, 97.5135135135);--quarto-scss-export-mermaid-label-bg-color: #ffffff;--quarto-scss-export-mermaid-label-fg-color: #0d6efd;--quarto-scss-export-mermaid-node-bg-color: rgba(13, 110, 253, 0.1);--quarto-scss-export-code-block-border-left-color: rgb(221.7, 222.3, 222.9);--quarto-scss-export-callout-color-note: #0d6efd;--quarto-scss-export-callout-color-tip: #198754;--quarto-scss-export-callout-color-important: #dc3545;--quarto-scss-export-callout-color-caution: 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J,Z="x"===y?zt:Vt,tt="x"===y?Rt:qt,et=A[w],it="y"===w?"height":"width",nt=et+g[Z],st=et-g[tt],ot=-1!==[zt,Vt].indexOf(_),rt=null!=(J=null==x?void 0:x[w])?J:0,at=ot?nt:et-E[it]-T[it]-rt+O.altAxis,lt=ot?et+E[it]+T[it]-rt-O.altAxis:st,ct=f&&ot?function(t,e,i){var n=Ne(t,e,i);return n>i?i:n}(at,et,lt):Ne(f?at:nt,et,f?lt:st);A[w]=ct,k[w]=ct-et}e.modifiersData[n]=k}},requiresIfExists:["offset"]};function di(t,e,i){void 0===i&&(i=!1);var n,s,o=me(e),r=me(e)&&function(t){var e=t.getBoundingClientRect(),i=we(e.width)/t.offsetWidth||1,n=we(e.height)/t.offsetHeight||1;return 1!==i||1!==n}(e),a=Le(e),l=Te(t,r,i),c={scrollLeft:0,scrollTop:0},h={x:0,y:0};return(o||!o&&!i)&&(("body"!==ue(e)||Ue(a))&&(c=(n=e)!==fe(n)&&me(n)?{scrollLeft:(s=n).scrollLeft,scrollTop:s.scrollTop}:Xe(n)),me(e)?((h=Te(e,!0)).x+=e.clientLeft,h.y+=e.clientTop):a&&(h.x=Ye(a))),{x:l.left+c.scrollLeft-h.x,y:l.top+c.scrollTop-h.y,width:l.width,height:l.height}}function ui(t){var e=new Map,i=new Set,n=[];function s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var fi={placement:"bottom",modifiers:[],strategy:"absolute"};function pi(){for(var t=arguments.length,e=new Array(t),i=0;iNumber.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(F.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...g(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=z.find(".dropdown-menu 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e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ei,Ti].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ii)?this:z.prev(this,Ii)[0]||z.next(this,Ii)[0]||z.findOne(Ii,t.delegateTarget.parentNode),o=qi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}N.on(document,Si,Ii,qi.dataApiKeydownHandler),N.on(document,Si,Pi,qi.dataApiKeydownHandler),N.on(document,Li,qi.clearMenus),N.on(document,Di,qi.clearMenus),N.on(document,Li,Ii,(function(t){t.preventDefault(),qi.getOrCreateInstance(this).toggle()})),m(qi);const Vi="backdrop",Ki="show",Qi=`mousedown.bs.${Vi}`,Xi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Yi={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Ui extends H{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Yi}static get NAME(){return Vi}show(t){if(!this._config.isVisible)return void g(t);this._append();const e=this._getElement();this._config.isAnimated&&d(e),e.classList.add(Ki),this._emulateAnimation((()=>{g(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),g(t)}))):g(t)}dispose(){this._isAppended&&(N.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=r(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),N.on(t,Qi,(()=>{g(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){_(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends H{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),N.off(document,Gi),N.on(document,Ji,(t=>this._handleFocusin(t))),N.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,N.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=z.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===tn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?tn:"forward")}}const on=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",rn=".sticky-top",an="padding-right",ln="margin-right";class cn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,an,(e=>e+t)),this._setElementAttributes(on,an,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,an),this._resetElementAttributes(on,an),this._resetElementAttributes(rn,ln)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&F.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=F.getDataAttribute(t,e);null!==i?(F.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(o(t))e(t);else for(const i of z.find(t,this._element))e(i)}}const hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",An="show",En="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends W{constructor(t,e){super(t,e),this._dialog=z.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||N.trigger(this._element,pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(wn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(N.trigger(this._element,dn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){N.off(window,hn),N.off(this._dialog,hn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Ui({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=z.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),d(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,N.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){N.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),N.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),N.on(this._element,bn,(t=>{N.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),N.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(N.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(En)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(En),this._queueCallback((()=>{this._element.classList.remove(En),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=p()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=p()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=On.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}N.on(document,yn,'[data-bs-toggle="modal"]',(function(t){const e=z.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),N.one(e,pn,(t=>{t.defaultPrevented||N.one(e,fn,(()=>{a(this)&&this.focus()}))}));const i=z.findOne(".modal.show");i&&On.getInstance(i).hide(),On.getOrCreateInstance(e).toggle(this)})),R(On),m(On);const xn=".bs.offcanvas",kn=".data-api",Ln=`load${xn}${kn}`,Sn="show",Dn="showing",$n="hiding",In=".offcanvas.show",Nn=`show${xn}`,Pn=`shown${xn}`,Mn=`hide${xn}`,jn=`hidePrevented${xn}`,Fn=`hidden${xn}`,Hn=`resize${xn}`,Wn=`click${xn}${kn}`,Bn=`keydown.dismiss${xn}`,zn={backdrop:!0,keyboard:!0,scroll:!1},Rn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class qn extends W{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||N.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),N.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(N.trigger(this._element,Mn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),N.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():N.trigger(this._element,jn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){N.on(this._element,Bn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():N.trigger(this._element,jn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}N.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=z.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),l(this))return;N.one(e,Fn,(()=>{a(this)&&this.focus()}));const i=z.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),N.on(window,Ln,(()=>{for(const t of z.find(In))qn.getOrCreateInstance(t).show()})),N.on(window,Hn,(()=>{for(const t of z.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),R(qn),m(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Yn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"
"},Un={allowList:"object",content:"object",extraClass:"(string|function)",html:"boolean",sanitize:"boolean",sanitizeFn:"(null|function)",template:"string"},Gn={entry:"(string|element|function|null)",selector:"(string|element)"};class Jn extends H{constructor(t){super(),this._config=this._getConfig(t)}static get Default(){return Yn}static get DefaultType(){return Un}static get NAME(){return"TemplateFactory"}getContent(){return Object.values(this._config.content).map((t=>this._resolvePossibleFunction(t))).filter(Boolean)}hasContent(){return this.getContent().length>0}changeContent(t){return this._checkContent(t),this._config.content={...this._config.content,...t},this}toHtml(){const t=document.createElement("div");t.innerHTML=this._maybeSanitize(this._config.template);for(const[e,i]of Object.entries(this._config.content))this._setContent(t,i,e);const e=t.children[0],i=this._resolvePossibleFunction(this._config.extraClass);return i&&e.classList.add(...i.split(" ")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=z.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?o(e)?this._putElementInTemplate(r(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return 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axeResult; + this.options = options; + } + + report() { + throw new Error("report() is an abstract method"); + } +} + +class QuartoAxeJsonReporter extends QuartoAxeReporter { + constructor(axeResult, options) { + super(axeResult, options); + } + + report() { + console.log(JSON.stringify(this.axeResult, null, 2)); + } +} + +class QuartoAxeConsoleReporter extends QuartoAxeReporter { + constructor(axeResult, options) { + super(axeResult, options); + } + + report() { + for (const violation of this.axeResult.violations) { + console.log(violation.description); + for (const node of violation.nodes) { + for (const target of node.target) { + console.log(target); + console.log(document.querySelector(target)); + } + } + } + } +} + +class QuartoAxeDocumentReporter extends QuartoAxeReporter { + constructor(axeResult, options) { + super(axeResult, options); + } + + createViolationElement(violation) { + const violationElement = document.createElement("div"); + + const descriptionElement = document.createElement("div"); + descriptionElement.className = "quarto-axe-violation-description"; + descriptionElement.innerText = `${violation.impact.replace(/^[a-z]/, match => match.toLocaleUpperCase())}: ${violation.description}`; + violationElement.appendChild(descriptionElement); + + const helpElement = document.createElement("div"); + helpElement.className = "quarto-axe-violation-help"; + helpElement.innerText = violation.help; + violationElement.appendChild(helpElement); + + const nodesElement = document.createElement("div"); + nodesElement.className = "quarto-axe-violation-nodes"; + violationElement.appendChild(nodesElement); + const nodeElement = document.createElement("div"); + nodeElement.className = "quarto-axe-violation-selector"; + for (const node of violation.nodes) { + for (const target of node.target) { + const targetElement = document.createElement("span"); + targetElement.className = "quarto-axe-violation-target"; + targetElement.innerText = target; + nodeElement.appendChild(targetElement); + nodeElement.addEventListener("mouseenter", () => { + const element = document.querySelector(target); + if (element) { + element.scrollIntoView({ behavior: "smooth", block: "center" }); + element.classList.add("quarto-axe-hover-highlight"); + setTimeout(() => { + element.style.border = ""; + }, 2000); + } + }); + nodeElement.addEventListener("mouseleave", () => { + const element = document.querySelector(target); + if (element) { + element.classList.remove("quarto-axe-hover-highlight"); + } + }); + nodeElement.addEventListener("click", () => { + console.log(document.querySelector(target)); + }); + nodeElement.appendChild(targetElement); + } + nodesElement.appendChild(nodeElement); + } + return violationElement; + } + + report() { + const violations = this.axeResult.violations; + const reportElement = document.createElement("div"); + reportElement.className = "quarto-axe-report"; + if (violations.length === 0) { + const noViolationsElement = document.createElement("div"); + noViolationsElement.className = "quarto-axe-no-violations"; + noViolationsElement.innerText = "No axe-core violations found."; + reportElement.appendChild(noViolationsElement); + } + violations.forEach((violation) => { + reportElement.appendChild(this.createViolationElement(violation)); + }); + document.querySelector("main").appendChild(reportElement); + } +} + +const reporters = { + json: QuartoAxeJsonReporter, + console: QuartoAxeConsoleReporter, + document: QuartoAxeDocumentReporter, +}; + +class QuartoAxeChecker { + constructor(opts) { + this.options = opts; + } + async init() { + const axe = (await import("https://cdn.skypack.dev/pin/axe-core@v4.10.3-aVOFXWsJaCpVrtv89pCa/mode=imports,min/optimized/axe-core.js")).default; + const result = await axe.run({ + exclude: [ + // https://github.com/microsoft/tabster/issues/288 + // MS has claimed they won't fix this, so we need to add an exclusion to + // all tabster elements + "[data-tabster-dummy]" + ], + preload: { assets: ['cssom'], timeout: 50000 } + }); + const reporter = this.options === true ? new QuartoAxeConsoleReporter(result) : new reporters[this.options.output](result, this.options); + reporter.report(); + } +} + +export async function init() { + const opts = document.querySelector("#quarto-axe-checker-options"); + if (opts) { + const jsonOptions = JSON.parse(atob(opts.textContent)); + const checker = new QuartoAxeChecker(jsonOptions); + await checker.init(); + } +} \ No newline at end of file diff --git a/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/quarto-html/popper.min.js b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/quarto-html/popper.min.js new file mode 100644 index 0000000..e3726d7 --- /dev/null +++ b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/quarto-html/popper.min.js @@ -0,0 +1,6 @@ +/** + * @popperjs/core v2.11.7 - MIT License + */ + +!function(e,t){"object"==typeof 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b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/quarto-html/quarto-syntax-highlighting-ed96de9b727972fe78a7b5d16c58bf87.css new file mode 100644 index 0000000..7bb4f73 --- /dev/null +++ b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/quarto-html/quarto-syntax-highlighting-ed96de9b727972fe78a7b5d16c58bf87.css @@ -0,0 +1,236 @@ +/* quarto syntax highlight colors */ +:root { + --quarto-hl-ot-color: #003B4F; + --quarto-hl-at-color: #657422; + --quarto-hl-ss-color: #20794D; + --quarto-hl-an-color: #5E5E5E; + --quarto-hl-fu-color: #4758AB; + --quarto-hl-st-color: #20794D; + --quarto-hl-cf-color: #003B4F; + --quarto-hl-op-color: #5E5E5E; + --quarto-hl-er-color: #AD0000; + --quarto-hl-bn-color: #AD0000; + --quarto-hl-al-color: #AD0000; + --quarto-hl-va-color: #111111; + --quarto-hl-bu-color: inherit; + --quarto-hl-ex-color: inherit; + --quarto-hl-pp-color: #AD0000; + --quarto-hl-in-color: #5E5E5E; + --quarto-hl-vs-color: #20794D; + --quarto-hl-wa-color: #5E5E5E; + --quarto-hl-do-color: #5E5E5E; + --quarto-hl-im-color: #00769E; + --quarto-hl-ch-color: #20794D; + --quarto-hl-dt-color: #AD0000; + --quarto-hl-fl-color: #AD0000; + --quarto-hl-co-color: #5E5E5E; + --quarto-hl-cv-color: #5E5E5E; + --quarto-hl-cn-color: #8f5902; + --quarto-hl-sc-color: #5E5E5E; + --quarto-hl-dv-color: #AD0000; + --quarto-hl-kw-color: #003B4F; +} + +/* other quarto variables */ +:root { + --quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace; +} + +/* syntax highlight based on Pandoc's rules */ +pre > code.sourceCode > span { + color: #003B4F; +} + +code.sourceCode > span { + color: #003B4F; +} + +div.sourceCode, +div.sourceCode pre.sourceCode { + color: #003B4F; +} + +/* Normal */ +code span { + color: #003B4F; +} + +/* Alert */ +code span.al { + color: #AD0000; + font-style: inherit; +} + +/* Annotation */ +code span.an { + color: #5E5E5E; + font-style: inherit; +} + +/* Attribute */ +code span.at { + color: #657422; + font-style: inherit; +} + +/* BaseN */ +code span.bn { + color: #AD0000; + font-style: inherit; +} + +/* BuiltIn */ +code span.bu { + font-style: inherit; +} + +/* ControlFlow */ +code span.cf { + color: #003B4F; + font-weight: bold; + font-style: inherit; +} + +/* Char */ +code span.ch { + color: #20794D; + font-style: inherit; +} + +/* Constant */ +code span.cn { + color: #8f5902; + font-style: inherit; +} + +/* Comment */ +code span.co { + color: #5E5E5E; + font-style: inherit; +} + +/* CommentVar */ +code span.cv { + color: #5E5E5E; + font-style: italic; +} + +/* Documentation */ +code span.do { + color: #5E5E5E; + font-style: italic; +} + +/* DataType */ +code span.dt { + color: #AD0000; + font-style: inherit; +} + +/* DecVal */ +code span.dv { + color: #AD0000; + font-style: inherit; +} + +/* Error */ +code span.er { + color: #AD0000; + font-style: inherit; +} + +/* Extension */ +code span.ex { + font-style: inherit; +} + +/* Float */ +code span.fl { + color: #AD0000; + font-style: inherit; +} + +/* Function */ +code span.fu { + color: #4758AB; + font-style: inherit; +} + +/* Import */ +code span.im { + color: #00769E; + font-style: inherit; +} + +/* Information */ +code span.in { + color: #5E5E5E; + font-style: inherit; +} + +/* Keyword */ +code span.kw { + color: #003B4F; + font-weight: bold; + font-style: inherit; +} + +/* Operator */ +code span.op { + color: #5E5E5E; + font-style: inherit; +} + +/* Other */ +code span.ot { + color: #003B4F; + font-style: inherit; +} + +/* Preprocessor */ +code span.pp { + color: #AD0000; + font-style: inherit; +} + +/* SpecialChar */ +code span.sc { + color: #5E5E5E; + font-style: inherit; +} + +/* SpecialString */ +code span.ss { + color: #20794D; + font-style: inherit; +} + +/* String */ +code span.st { + color: #20794D; + font-style: inherit; +} + +/* Variable */ +code span.va { + color: #111111; + font-style: inherit; +} + +/* VerbatimString */ +code span.vs { + color: #20794D; + font-style: inherit; +} + +/* Warning */ +code span.wa { + color: #5E5E5E; + font-style: italic; +} + +.prevent-inlining { + content: " { + // Find any conflicting margin elements and add margins to the + // top to prevent overlap + const marginChildren = window.document.querySelectorAll( + ".column-margin.column-container > *, .margin-caption, .aside" + ); + + let lastBottom = 0; + for (const marginChild of marginChildren) { + if (marginChild.offsetParent !== null) { + // clear the top margin so we recompute it + marginChild.style.marginTop = null; + const top = marginChild.getBoundingClientRect().top + window.scrollY; + if (top < lastBottom) { + const marginChildStyle = window.getComputedStyle(marginChild); + const marginBottom = parseFloat(marginChildStyle["marginBottom"]); + const margin = lastBottom - top + marginBottom; + marginChild.style.marginTop = `${margin}px`; + } + const styles = window.getComputedStyle(marginChild); + const marginTop = parseFloat(styles["marginTop"]); + lastBottom = top + marginChild.getBoundingClientRect().height + marginTop; + } + } +}; + +window.document.addEventListener("DOMContentLoaded", function (_event) { + // Recompute the position of margin elements anytime the body size changes + if (window.ResizeObserver) { + const resizeObserver = new window.ResizeObserver( + throttle(() => { + layoutMarginEls(); + if ( + window.document.body.getBoundingClientRect().width < 990 && + isReaderMode() + ) { + quartoToggleReader(); + } + }, 50) + ); + resizeObserver.observe(window.document.body); + } + + const tocEl = window.document.querySelector('nav.toc-active[role="doc-toc"]'); + const sidebarEl = window.document.getElementById("quarto-sidebar"); + const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left"); + const marginSidebarEl = window.document.getElementById( + "quarto-margin-sidebar" + ); + // function to determine whether the element has a previous sibling that is active + const prevSiblingIsActiveLink = (el) => { + const sibling = el.previousElementSibling; + if (sibling && sibling.tagName === "A") { + return sibling.classList.contains("active"); + } else { + return false; + } + }; + + // dispatch for htmlwidgets + // they use slideenter event to trigger resize + function fireSlideEnter() { + const event = window.document.createEvent("Event"); + event.initEvent("slideenter", true, true); + window.document.dispatchEvent(event); + } + + const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]'); + tabs.forEach((tab) => { + tab.addEventListener("shown.bs.tab", fireSlideEnter); + }); + + // dispatch for shiny + // they use BS shown and hidden events to trigger rendering + function distpatchShinyEvents(previous, current) { + if (window.jQuery) { + if (previous) { + window.jQuery(previous).trigger("hidden"); + } + if (current) { + window.jQuery(current).trigger("shown"); + } + } + } + + // tabby.js listener: Trigger event for htmlwidget and shiny + document.addEventListener( + "tabby", + function (event) { + fireSlideEnter(); + distpatchShinyEvents(event.detail.previousTab, event.detail.tab); + }, + false + ); + + // Track scrolling and mark TOC links as active + // get table of contents and sidebar (bail if we don't have at least one) + const tocLinks = tocEl + ? [...tocEl.querySelectorAll("a[data-scroll-target]")] + : []; + const makeActive = (link) => tocLinks[link].classList.add("active"); + const removeActive = (link) => tocLinks[link].classList.remove("active"); + const removeAllActive = () => + [...Array(tocLinks.length).keys()].forEach((link) => removeActive(link)); + + // activate the anchor for a section associated with this TOC entry + tocLinks.forEach((link) => { + link.addEventListener("click", () => { + if (link.href.indexOf("#") !== -1) { + const anchor = link.href.split("#")[1]; + const heading = window.document.querySelector( + `[data-anchor-id="${anchor}"]` + ); + if (heading) { + // Add the class + heading.classList.add("reveal-anchorjs-link"); + + // function to show the anchor + const handleMouseout = () => { + heading.classList.remove("reveal-anchorjs-link"); + heading.removeEventListener("mouseout", handleMouseout); + }; + + // add a function to clear the anchor when the user mouses out of it + heading.addEventListener("mouseout", handleMouseout); + } + } + }); + }); + + const sections = tocLinks.map((link) => { + const target = link.getAttribute("data-scroll-target"); + if (target.startsWith("#")) { + return window.document.getElementById(decodeURI(`${target.slice(1)}`)); + } else { + return window.document.querySelector(decodeURI(`${target}`)); + } + }); + + const sectionMargin = 200; + let currentActive = 0; + // track whether we've initialized state the first time + let init = false; + + const updateActiveLink = () => { + // The index from bottom to top (e.g. reversed list) + let sectionIndex = -1; + if ( + window.innerHeight + window.pageYOffset >= + window.document.body.offsetHeight + ) { + // This is the no-scroll case where last section should be the active one + sectionIndex = 0; + } else { + // This finds the last section visible on screen that should be made active + sectionIndex = [...sections].reverse().findIndex((section) => { + if (section) { + return window.pageYOffset >= section.offsetTop - sectionMargin; + } else { + return false; + } + }); + } + if (sectionIndex > -1) { + const current = sections.length - sectionIndex - 1; + if (current !== currentActive) { + removeAllActive(); + currentActive = current; + makeActive(current); + if (init) { + window.dispatchEvent(sectionChanged); + } + init = true; + } + } + }; + + const inHiddenRegion = (top, bottom, hiddenRegions) => { + for (const region of hiddenRegions) { + if (top <= region.bottom && bottom >= region.top) { + return true; + } + } + return false; + }; + + const categorySelector = "header.quarto-title-block .quarto-category"; + const activateCategories = (href) => { + // Find any categories + // Surround them with a link pointing back to: + // #category=Authoring + try { + const categoryEls = window.document.querySelectorAll(categorySelector); + for (const categoryEl of categoryEls) { + const categoryText = categoryEl.textContent; + if (categoryText) { + const link = `${href}#category=${encodeURIComponent(categoryText)}`; + const linkEl = window.document.createElement("a"); + linkEl.setAttribute("href", link); + for (const child of categoryEl.childNodes) { + linkEl.append(child); + } + categoryEl.appendChild(linkEl); + } + } + } catch { + // Ignore errors + } + }; + function hasTitleCategories() { + return window.document.querySelector(categorySelector) !== null; + } + + function offsetRelativeUrl(url) { + const offset = getMeta("quarto:offset"); + return offset ? offset + url : url; + } + + function offsetAbsoluteUrl(url) { + const offset = getMeta("quarto:offset"); + const baseUrl = new URL(offset, window.location); + + const projRelativeUrl = url.replace(baseUrl, ""); + if (projRelativeUrl.startsWith("/")) { + return projRelativeUrl; + } else { + return "/" + projRelativeUrl; + } + } + + // read a meta tag value + function getMeta(metaName) { + const metas = window.document.getElementsByTagName("meta"); + for (let i = 0; i < metas.length; i++) { + if (metas[i].getAttribute("name") === metaName) { + return metas[i].getAttribute("content"); + } + } + return ""; + } + + async function findAndActivateCategories() { + // Categories search with listing only use path without query + const currentPagePath = offsetAbsoluteUrl( + window.location.origin + window.location.pathname + ); + const response = await fetch(offsetRelativeUrl("listings.json")); + if (response.status == 200) { + return response.json().then(function (listingPaths) { + const listingHrefs = []; + for (const listingPath of listingPaths) { + const pathWithoutLeadingSlash = listingPath.listing.substring(1); + for (const item of listingPath.items) { + const encodedItem = encodeURI(item); + if ( + encodedItem === currentPagePath || + encodedItem === currentPagePath + "index.html" + ) { + // Resolve this path against the offset to be sure + // we already are using the correct path to the listing + // (this adjusts the listing urls to be rooted against + // whatever root the page is actually running against) + const relative = offsetRelativeUrl(pathWithoutLeadingSlash); + const baseUrl = window.location; + const resolvedPath = new URL(relative, baseUrl); + listingHrefs.push(resolvedPath.pathname); + break; + } + } + } + + // Look up the tree for a nearby linting and use that if we find one + const nearestListing = findNearestParentListing( + offsetAbsoluteUrl(window.location.pathname), + listingHrefs + ); + if (nearestListing) { + activateCategories(nearestListing); + } else { + // See if the referrer is a listing page for this item + const referredRelativePath = offsetAbsoluteUrl(document.referrer); + const referrerListing = listingHrefs.find((listingHref) => { + const isListingReferrer = + listingHref === referredRelativePath || + listingHref === referredRelativePath + "index.html"; + return isListingReferrer; + }); + + if (referrerListing) { + // Try to use the referrer if possible + activateCategories(referrerListing); + } else if (listingHrefs.length > 0) { + // Otherwise, just fall back to the first listing + activateCategories(listingHrefs[0]); + } + } + }); + } + } + if (hasTitleCategories()) { + findAndActivateCategories(); + } + + const findNearestParentListing = (href, listingHrefs) => { + if (!href || !listingHrefs) { + return undefined; + } + // Look up the tree for a nearby linting and use that if we find one + const relativeParts = href.substring(1).split("/"); + while (relativeParts.length > 0) { + const path = relativeParts.join("/"); + for (const listingHref of listingHrefs) { + if (listingHref.startsWith(path)) { + return listingHref; + } + } + relativeParts.pop(); + } + + return undefined; + }; + + const manageSidebarVisiblity = (el, placeholderDescriptor) => { + let isVisible = true; + let elRect; + + return (hiddenRegions) => { + if (el === null) { + return; + } + + // Find the last element of the TOC + const lastChildEl = el.lastElementChild; + + if (lastChildEl) { + // Converts the sidebar to a menu + const convertToMenu = () => { + for (const child of el.children) { + child.style.opacity = 0; + child.style.overflow = "hidden"; + child.style.pointerEvents = "none"; + } + + nexttick(() => { + const toggleContainer = window.document.createElement("div"); + toggleContainer.style.width = "100%"; + toggleContainer.classList.add("zindex-over-content"); + toggleContainer.classList.add("quarto-sidebar-toggle"); + toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom + toggleContainer.id = placeholderDescriptor.id; + toggleContainer.style.position = "fixed"; + + const toggleIcon = window.document.createElement("i"); + toggleIcon.classList.add("quarto-sidebar-toggle-icon"); + toggleIcon.classList.add("bi"); + toggleIcon.classList.add("bi-caret-down-fill"); + + const toggleTitle = window.document.createElement("div"); + const titleEl = window.document.body.querySelector( + placeholderDescriptor.titleSelector + ); + if (titleEl) { + toggleTitle.append( + titleEl.textContent || titleEl.innerText, + toggleIcon + ); + } + toggleTitle.classList.add("zindex-over-content"); + toggleTitle.classList.add("quarto-sidebar-toggle-title"); + toggleContainer.append(toggleTitle); + + const toggleContents = window.document.createElement("div"); + toggleContents.classList = el.classList; + toggleContents.classList.add("zindex-over-content"); + toggleContents.classList.add("quarto-sidebar-toggle-contents"); + for (const child of el.children) { + if (child.id === "toc-title") { + continue; + } + + const clone = child.cloneNode(true); + clone.style.opacity = 1; + clone.style.pointerEvents = null; + clone.style.display = null; + toggleContents.append(clone); + } + toggleContents.style.height = "0px"; + const positionToggle = () => { + // position the element (top left of parent, same width as parent) + if (!elRect) { + elRect = el.getBoundingClientRect(); + } + toggleContainer.style.left = `${elRect.left}px`; + toggleContainer.style.top = `${elRect.top}px`; + toggleContainer.style.width = `${elRect.width}px`; + }; + positionToggle(); + + toggleContainer.append(toggleContents); + el.parentElement.prepend(toggleContainer); + + // Process clicks + let tocShowing = false; + // Allow the caller to control whether this is dismissed + // when it is clicked (e.g. sidebar navigation supports + // opening and closing the nav tree, so don't dismiss on click) + const clickEl = placeholderDescriptor.dismissOnClick + ? toggleContainer + : toggleTitle; + + const closeToggle = () => { + if (tocShowing) { + toggleContainer.classList.remove("expanded"); + toggleContents.style.height = "0px"; + tocShowing = false; + } + }; + + // Get rid of any expanded toggle if the user scrolls + window.document.addEventListener( + "scroll", + throttle(() => { + closeToggle(); + }, 50) + ); + + // Handle positioning of the toggle + window.addEventListener( + "resize", + throttle(() => { + elRect = undefined; + positionToggle(); + }, 50) + ); + + window.addEventListener("quarto-hrChanged", () => { + elRect = undefined; + }); + + // Process the click + clickEl.onclick = () => { + if (!tocShowing) { + toggleContainer.classList.add("expanded"); + toggleContents.style.height = null; + tocShowing = true; + } else { + closeToggle(); + } + }; + }); + }; + + // Converts a sidebar from a menu back to a sidebar + const convertToSidebar = () => { + for (const child of el.children) { + child.style.opacity = 1; + child.style.overflow = null; + child.style.pointerEvents = null; + } + + const placeholderEl = window.document.getElementById( + placeholderDescriptor.id + ); + if (placeholderEl) { + placeholderEl.remove(); + } + + el.classList.remove("rollup"); + }; + + if (isReaderMode()) { + convertToMenu(); + isVisible = false; + } else { + // Find the top and bottom o the element that is being managed + const elTop = el.offsetTop; + const elBottom = + elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight; + + if (!isVisible) { + // If the element is current not visible reveal if there are + // no conflicts with overlay regions + if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToSidebar(); + isVisible = true; + } + } else { + // If the element is visible, hide it if it conflicts with overlay regions + // and insert a placeholder toggle (or if we're in reader mode) + if (inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToMenu(); + isVisible = false; + } + } + } + } + }; + }; + + const tabEls = document.querySelectorAll('a[data-bs-toggle="tab"]'); + for (const tabEl of tabEls) { + const id = tabEl.getAttribute("data-bs-target"); + if (id) { + const columnEl = document.querySelector( + `${id} .column-margin, .tabset-margin-content` + ); + if (columnEl) + tabEl.addEventListener("shown.bs.tab", function (event) { + const el = event.srcElement; + if (el) { + const visibleCls = `${el.id}-margin-content`; + // walk up until we find a parent tabset + let panelTabsetEl = el.parentElement; + while (panelTabsetEl) { + if (panelTabsetEl.classList.contains("panel-tabset")) { + break; + } + panelTabsetEl = panelTabsetEl.parentElement; + } + + if (panelTabsetEl) { + const prevSib = panelTabsetEl.previousElementSibling; + if ( + prevSib && + prevSib.classList.contains("tabset-margin-container") + ) { + const childNodes = prevSib.querySelectorAll( + ".tabset-margin-content" + ); + for (const childEl of childNodes) { + if (childEl.classList.contains(visibleCls)) { + childEl.classList.remove("collapse"); + } else { + childEl.classList.add("collapse"); + } + } + } + } + } + + layoutMarginEls(); + }); + } + } + + // Manage the visibility of the toc and the sidebar + const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, { + id: "quarto-toc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, { + id: "quarto-sidebarnav-toggle", + titleSelector: ".title", + dismissOnClick: false, + }); + let tocLeftScrollVisibility; + if (leftTocEl) { + tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, { + id: "quarto-lefttoc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + } + + // Find the first element that uses formatting in special columns + const conflictingEls = window.document.body.querySelectorAll( + '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]' + ); + + // Filter all the possibly conflicting elements into ones + // the do conflict on the left or ride side + const arrConflictingEls = Array.from(conflictingEls); + const leftSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return false; + } + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + className.startsWith("column-") && + !className.endsWith("right") && + !className.endsWith("container") && + className !== "column-margin" + ); + }); + }); + const rightSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return true; + } + + const hasMarginCaption = Array.from(el.classList).find((className) => { + return className == "margin-caption"; + }); + if (hasMarginCaption) { + return true; + } + + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + !className.endsWith("container") && + className.startsWith("column-") && + !className.endsWith("left") + ); + }); + }); + + const kOverlapPaddingSize = 10; + function toRegions(els) { + return els.map((el) => { + const boundRect = el.getBoundingClientRect(); + const top = + boundRect.top + + document.documentElement.scrollTop - + kOverlapPaddingSize; + return { + top, + bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize, + }; + }); + } + + let hasObserved = false; + const visibleItemObserver = (els) => { + let visibleElements = [...els]; + const intersectionObserver = new IntersectionObserver( + (entries, _observer) => { + entries.forEach((entry) => { + if (entry.isIntersecting) { + if (visibleElements.indexOf(entry.target) === -1) { + visibleElements.push(entry.target); + } + } else { + visibleElements = visibleElements.filter((visibleEntry) => { + return visibleEntry !== entry; + }); + } + }); + + if (!hasObserved) { + hideOverlappedSidebars(); + } + hasObserved = true; + }, + {} + ); + els.forEach((el) => { + intersectionObserver.observe(el); + }); + + return { + getVisibleEntries: () => { + return visibleElements; + }, + }; + }; + + const rightElementObserver = visibleItemObserver(rightSideConflictEls); + const leftElementObserver = visibleItemObserver(leftSideConflictEls); + + const hideOverlappedSidebars = () => { + marginScrollVisibility(toRegions(rightElementObserver.getVisibleEntries())); + sidebarScrollVisiblity(toRegions(leftElementObserver.getVisibleEntries())); + if (tocLeftScrollVisibility) { + tocLeftScrollVisibility( + toRegions(leftElementObserver.getVisibleEntries()) + ); + } + }; + + window.quartoToggleReader = () => { + // Applies a slow class (or removes it) + // to update the transition speed + const slowTransition = (slow) => { + const manageTransition = (id, slow) => { + const el = document.getElementById(id); + if (el) { + if (slow) { + el.classList.add("slow"); + } else { + el.classList.remove("slow"); + } + } + }; + + manageTransition("TOC", slow); + manageTransition("quarto-sidebar", slow); + }; + const readerMode = !isReaderMode(); + setReaderModeValue(readerMode); + + // If we're entering reader mode, slow the transition + if (readerMode) { + slowTransition(readerMode); + } + highlightReaderToggle(readerMode); + hideOverlappedSidebars(); + + // If we're exiting reader mode, restore the non-slow transition + if (!readerMode) { + slowTransition(!readerMode); + } + }; + + const highlightReaderToggle = (readerMode) => { + const els = document.querySelectorAll(".quarto-reader-toggle"); + if (els) { + els.forEach((el) => { + if (readerMode) { + el.classList.add("reader"); + } else { + el.classList.remove("reader"); + } + }); + } + }; + + const setReaderModeValue = (val) => { + if (window.location.protocol !== "file:") { + window.localStorage.setItem("quarto-reader-mode", val); + } else { + localReaderMode = val; + } + }; + + const isReaderMode = () => { + if (window.location.protocol !== "file:") { + return window.localStorage.getItem("quarto-reader-mode") === "true"; + } else { + return localReaderMode; + } + }; + let localReaderMode = null; + + const tocOpenDepthStr = tocEl?.getAttribute("data-toc-expanded"); + const tocOpenDepth = tocOpenDepthStr ? Number(tocOpenDepthStr) : 1; + + // Walk the TOC and collapse/expand nodes + // Nodes are expanded if: + // - they are top level + // - they have children that are 'active' links + // - they are directly below an link that is 'active' + const walk = (el, depth) => { + // Tick depth when we enter a UL + if (el.tagName === "UL") { + depth = depth + 1; + } + + // It this is active link + let isActiveNode = false; + if (el.tagName === "A" && el.classList.contains("active")) { + isActiveNode = true; + } + + // See if there is an active child to this element + let hasActiveChild = false; + for (const child of el.children) { + hasActiveChild = walk(child, depth) || hasActiveChild; + } + + // Process the collapse state if this is an UL + if (el.tagName === "UL") { + if (tocOpenDepth === -1 && depth > 1) { + // toc-expand: false + el.classList.add("collapse"); + } else if ( + depth <= tocOpenDepth || + hasActiveChild || + prevSiblingIsActiveLink(el) + ) { + el.classList.remove("collapse"); + } else { + el.classList.add("collapse"); + } + + // untick depth when we leave a UL + depth = depth - 1; + } + return hasActiveChild || isActiveNode; + }; + + // walk the TOC and expand / collapse any items that should be shown + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + + // Throttle the scroll event and walk peridiocally + window.document.addEventListener( + "scroll", + throttle(() => { + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 5) + ); + window.addEventListener( + "resize", + throttle(() => { + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 10) + ); + hideOverlappedSidebars(); + highlightReaderToggle(isReaderMode()); +}); + +tabsets.init(); +axe.init(); + +function throttle(func, wait) { + let waiting = false; + return function () { + if (!waiting) { + func.apply(this, arguments); + waiting = true; + setTimeout(function () { + waiting = false; + }, wait); + } + }; +} + +function nexttick(func) { + return setTimeout(func, 0); +} diff --git a/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/quarto-html/tabsets/tabsets.js b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/quarto-html/tabsets/tabsets.js new file mode 100644 index 0000000..51345d0 --- /dev/null +++ b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/quarto-html/tabsets/tabsets.js @@ -0,0 +1,95 @@ +// grouped tabsets + +export function init() { + window.addEventListener("pageshow", (_event) => { + function getTabSettings() { + const data = localStorage.getItem("quarto-persistent-tabsets-data"); + if (!data) { + localStorage.setItem("quarto-persistent-tabsets-data", "{}"); + return {}; + } + if (data) { + return JSON.parse(data); + } + } + + function setTabSettings(data) { + localStorage.setItem( + "quarto-persistent-tabsets-data", + JSON.stringify(data) + ); + } + + function setTabState(groupName, groupValue) { + const data = getTabSettings(); + data[groupName] = groupValue; + setTabSettings(data); + } + + function toggleTab(tab, active) { + const tabPanelId = tab.getAttribute("aria-controls"); + const tabPanel = document.getElementById(tabPanelId); + if (active) { + tab.classList.add("active"); + tabPanel.classList.add("active"); + } else { + tab.classList.remove("active"); + tabPanel.classList.remove("active"); + } + } + + function toggleAll(selectedGroup, selectorsToSync) { + for (const [thisGroup, tabs] of Object.entries(selectorsToSync)) { + const active = selectedGroup === thisGroup; + for (const tab of tabs) { + toggleTab(tab, active); + } + } + } + + function findSelectorsToSyncByLanguage() { + const result = {}; + const tabs = Array.from( + document.querySelectorAll(`div[data-group] a[id^='tabset-']`) + ); + for (const item of tabs) { + const div = item.parentElement.parentElement.parentElement; + const group = div.getAttribute("data-group"); + if (!result[group]) { + result[group] = {}; + } + const selectorsToSync = result[group]; + const value = item.innerHTML; + if (!selectorsToSync[value]) { + selectorsToSync[value] = []; + } + selectorsToSync[value].push(item); + } + return result; + } + + function setupSelectorSync() { + const selectorsToSync = findSelectorsToSyncByLanguage(); + Object.entries(selectorsToSync).forEach(([group, tabSetsByValue]) => { + Object.entries(tabSetsByValue).forEach(([value, items]) => { + items.forEach((item) => { + item.addEventListener("click", (_event) => { + setTabState(group, value); + toggleAll(value, selectorsToSync[group]); + }); + }); + }); + }); + return selectorsToSync; + } + + const selectorsToSync = setupSelectorSync(); + for (const [group, selectedName] of Object.entries(getTabSettings())) { + const selectors = selectorsToSync[group]; + // it's possible that stale state gives us empty selections, so we explicitly check here. + if (selectors) { + toggleAll(selectedName, selectors); + } + } + }); +} diff --git a/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/quarto-html/tippy.css b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/quarto-html/tippy.css new file mode 100644 index 0000000..e6ae635 --- /dev/null +++ b/course/03_InsideFCSFile/homeworks/claude-chew/Week3Homework_files/libs/quarto-html/tippy.css @@ -0,0 +1 @@ +.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 10px)}.tippy-box{position:relative;background-color:#333;color:#fff;border-radius:4px;font-size:14px;line-height:1.4;white-space:normal;outline:0;transition-property:transform,visibility,opacity}.tippy-box[data-placement^=top]>.tippy-arrow{bottom:0}.tippy-box[data-placement^=top]>.tippy-arrow:before{bottom:-7px;left:0;border-width:8px 8px 0;border-top-color:initial;transform-origin:center 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a/course/03_InsideFCSFile/images/BioconductorInkscape.svg +++ b/course/03_InsideFCSFile/images/BioconductorInkscape.svg @@ -1,117 +1,117 @@ - - - -Mike et al. have2007Bioconductor Flow Cytometry Package + + + +Mike et al. have2007Bioconductor Flow Cytometry Package diff --git a/course/03_InsideFCSFile/index.qmd b/course/03_InsideFCSFile/index.qmd index edd6f44..f4df209 100644 --- a/course/03_InsideFCSFile/index.qmd +++ b/course/03_InsideFCSFile/index.qmd @@ -1,1117 +1,1117 @@ ---- -title: "03 - Inside an FCS File" -author: "David Rach" -date: 02-15-2026 -format: html -toc: true -toc-depth: 5 ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - -For the YouTube livestream recording, see [here](https://youtu.be/1wZ61x0i19o?t=278) - - - -For screen-shot slides, click [here](/course/03_InsideFCSFile/slides.qmd) - -
- ---- - -# Background - -Welcome to the Week #3! Having subjected everyone to two R-focused weeks, this week will have more of a cytometry-focus as we slice into an .fcs file. We will hopefully gather greater understanding of how an .fcs file is structured and what additional kinds of information we can retrieve (while becoming increasingly puzzled why different manufacturers insist on using different keyword names for the exact same things). - -We will also gain additional exposure to more object types in R (vectors, list, matrices and data.frames). Continuing the analogy from last week, if every function is the equivalent of a tool in a toolbox, each tool requires certain types of things to do its job properly (hammer ~ nail, screwdriver ~ screws, paintbrush ~ paint, etc.). Being able to identify what type/kind of object a particular variable we have created in R is will allow us to pass it to the correct function that will allow us to work with that object type. - -
- ---- - -:::{.callout-important title="Housekeeping"} -We are building off concepts that were covered in [Week #1 (Installing R packages)](/course/01_InstallingRPackages/index.qmd) and especially [Week #2 (File Paths)](/course/02_FilePaths/index.qmd). -For those who are flow cytometry beginners, please see [UChicago Flow](https://youtu.be/gC4brjHbLkk?si=li98x7KlLXUFWGX3) Flow Basics Series for additional context. -::: - - -:::{.callout-tip title="Today's Goal"} -If you find yourself at some point going "I have no idea what is going on", please pause, take a break, and circle back later in the day. Our goal is not to have you memorize how to quickly access 100 archaic keywords, but rather showcase a typical object exploration workflow. So don't power through, but rather circle back when you are in an exploring mindset. Consider what kind of information from within an .fcs file you'd like to retrieve, and then explore/navigate your way through the various paths until you find the information that you were looking for. -::: - ---- - -:::{.callout-important title="Housekeeping"} -As we do [every week](/course/02_FilePaths/index.qmd#new-repository), on GitHub, sync your forked-version of the CytometryInR course to bring in the most recent updates. Then within Positron, pull in those changes to your local computer. From there, copy the data folder to a separate project folder you have created. This will prevent any merge issues bringing in new data next week. -::: - ---- - -# Walk Through - ---- - -## Getting Set Up - ---- - -### Set up File Paths - -Having copied over the new data to your working project folder (Week 3 or whatever your chosen name), let's identify the file paths between our working directory and the fcs files. If you retained the same project organization structure we had during Week #2, it may look similar to the following: - -```{r} -#| eval: FALSE -#| include: FALSE - -# Please note, this code-chunk is only for use when writing the code. Please switch eval to false and next code blocks eval to true before rendering - -PathToDataFolder <- file.path(getwd(), "course", "03_InsideFCSFile", "data") -``` - -```{r} -#| eval: TRUE -PathToDataFolder <- file.path("data") -``` - -```{r} -PathToDataFolder -``` - -
- ---- - -### Locate .fcs files - -We will now locate our .fcs files. As we saw last week, our computer will need the full file.paths to these individual files, so we will set the `list.files()` "full.names" argument to TRUE. - -```{r} -#| eval: TRUE -fcs_files <- list.files(PathToDataFolder, pattern=".fcs", full.names=TRUE) -fcs_files -``` - -By contrast, if the "full.names" argument was set to FALSE, we would have retrieved just the file names - -```{r} -list.files(PathToDataFolder, pattern=".fcs", full.names=FALSE) -``` - -This would have been the equivalent of running the `basename` function on the "full.names=TRUE" output. -```{r} -basename(fcs_files) -``` - -
- ---- - -## flowCore - -We will be using the `flowCore` package, which is the oldest and most-frequently downloaded flow cytometry package on [Bioconductor](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry). - -```{r} -#| code-fold: TRUE -#| warning: FALSE -#| message: FALSE - -# I have attached this code for anyone that is interested in seeing how these plots were made. The content is not part of today's lesson, so if you are just starting off, we will cover the details of data-tidying and creating ggplot objects over the next several weeks. Best, David - -# Load required packages via a library call - -library(dplyr) # CRAN -library(stringr) # CRAN -library(ggplot2) # CRAN -#library(plotly) # Using the :: to access - -# Loading in the dataset contained within the .csv file -BioconductorFlow_path <- file.path(PathToDataFolder, "BioconductorFlow.csv") -BioconductorFlowPackages <- read.csv(BioconductorFlow_path, check.names=FALSE) -BioconductorFlowPackages <- BioconductorFlowPackages |> - arrange(desc(since)) |> mutate(package = factor(package, levels = package)) - -# Newer Base R Pipe : |> -# Older mostly equivalent Magrittr Pipe %>% -``` - -```{r} -#| code-fold: true -#| fig-height: 9 - -# Notice the code-chunk eval arguments above dictate the shape of the final rendered plot. - -# Taking the imported dataset and passing it to ggplot2 to create the first plot. - -plot <- ggplot(BioconductorFlowPackages, - aes(x = 0, xend = since, y = package, yend = package)) + - geom_segment(linewidth = 2, color = "steelblue") + - scale_x_continuous(trans = "reverse", - breaks = seq(0, max(BioconductorFlowPackages$since), by = 5)) + - labs( - x = "Years in Bioconductor", - y = NULL, - title = "Bioconductor Flow Cytometry R packages" - ) + - theme_bw() - -# Taking the static plot and making it interactive using the plotly package - -plotly::ggplotly(plot) -``` - -```{r} -#| code-fold: TRUE - -# Retrieving the names of Bioconductor flow cytometry R packages in correct release order. - -HistoricalOrder <- BioconductorFlowPackages |> pull(package) - -# Bringing in 2025 package usage dataset from a .csv file -BioconductorUsage_path <- file.path(PathToDataFolder, "BioconductorDownloads.csv") -BioconductorUsage <- read.csv(BioconductorUsage_path, check.names=FALSE) -BioconductorUsage <- BioconductorUsage |> dplyr::filter(Month %in% "all") - -# Note, dplyr::filter is used due to flowCore also having a filter function, which causes conflicts once it is attached to the local environment. - -# Combining both data.frames for use in the plot - -Dataset <- left_join(BioconductorFlowPackages, BioconductorUsage, by="package") - -# Rearranging the order in which packages are displayed - -Dataset$package <- factor(Dataset$package, levels=HistoricalOrder) -``` - -```{r} -#| code-fold: TRUE - -# Generating the 2nd plot with ggplot2 - -plot <- ggplot(Dataset, aes(x = since, y = Nb_of_distinct_IPs)) + - geom_point(aes(color = package), size = 3, alpha = 0.7) + - labs( - x = "Years in Bioconductor", - y = "Number of Yearly Downloads", - title = "", - color = "Package" - ) + - theme_bw() - -# Making it interactive with plotly - -plotly::ggplotly(plot) -``` - -flowCore is also one of the many Bioconductor packages maintained by [Mike Jiang](https://github.com/mikejiang). In many ways (as those who completed the optional take-home problems for Week #1 know) reminiscent of this [xkcd](https://xkcd.com/2347/) comic: - -![](images/BioconductorXKCD.png) - -As with all our R packages, we first need to make sure `flowCore` is attached to our local environment via the library call. - -```{r} -library(flowCore) -``` - -The function we will be using today is the `read.FCS()` function. Do you remember how to access the help documentation? - -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Or when in Positron, hovering over the highlighted function name within the code-chunk - -?flowCore::read.FCS -``` - -To start, lets select just the first .fcs file. We will do this by indexing the first item within fcs_files via the square brackets []. - -```{r} -firstfile <- fcs_files[1] -firstfile -``` - -## flowFrame - -For `read.FCS()`, it accepts several arguments. The argument "filename" is where we provide our file.path to .fcs file that we wish to load into R. Let's go ahead and do so - -```{r} -#| eval: FALSE - -read.FCS(filename=firstfile) - -``` - -Please note, if you are doing this with your own .fcs files, you will need to provide two additional arguments, "transformation" = FALSE, and "truncate_max_range" = FALSE for the files to be read in correctly. We will revisit the reasons why in Week #5. - -```{r} -read.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE) -``` - -In this case, we can see the .fcs file has been read into R as a "flowFrame" object. We can also see the file name, as well as details about the number of cells, and number of columns (whether detectors (for raw spectral flow data) or fluorophores (for unmixed spectral flow data)). - -![](images/00_flowFrame.png) - -Directly below we see what resembles a table. At first glance, the only column with an immediately discernable purpose is the one with the name column, which is listing the detectors present on a [Cytek Aurora](https://bpb-us-w2.wpmucdn.com/voices.uchicago.edu/dist/2/1824/files/2021/10/Aurora-Configuration.png). - -![](images/01_flowFrameDetectors.png) - -And finally, at the bottom we reach a line that tells us that for this .fcs files, 599 keyword can be found in a description slot. - -![](images/02_KeywordsFiveNineNine.png) - -
- ---- - -So let's get our bearings, we have loaded in an .fcs file to R, but let's use some of the concepts we covered last week to try to understand a bit about what type or class of object we are working with. From the output, we saw the words flowFrame object, so let's read it back in again, but assign it to an variable/object called flowFrame so that we can use the type-discerning functions we worked with last week on. - -```{r} -flowFrame <- read.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE) -``` - -As we create this variable, if we have the session tab selected on our right secondary side bar, we see it appear: - -![](images/03_SessionTab.png) - -If we were to use the type-determining functions we learned last week - -```{r} -#| eval: FALSE -#| include: FALSE -# This is the whole ball game -str(flowFrame) -``` - -```{r} -class(flowFrame) -``` - -flowFrames are a class of object with a structure defined within the `flowCore` package. They are used to work with the data contained within individual .fcs files. Looking again at the right secondary side bar, we can see that it shows up as a ""S4 class flowFrame package flowCore""" with 3 slots, with the words flowFrame adjacent to it. - -A perfectly valid first reaction to first reading this is "well how should I know what any of this means?". Powering through this initial discomfort, let's go ahead and click on the dropdown arrow next to the variables name and see if we get any additional clarity on the issue. - -![](images/04_Slots.png) - -When we do so, three additional drop-downs appear. Based on the previous line that mentioned 3 slots, we could infer that each line corresponds to one of those slots. - -What we are encountering with flowFrame is our first example of an S4 object type. These more-complicated object types are quite common for the various [Bioconductor](https://adv-r.hadley.nz/s4.html) affilitated R packages. - -These objects will usually appear with either S4 or S3 in their metadata, and are made up of various simpler object types that are cobbled together within the larger object, usually occupying individual slots. - -What advantage this bundling provides will be something we revisit throughout the course as you encounter more of these S4/S3 objects. - -
- ---- - -### exprs - -The first slot within the flowFrame object shows up with the name "exprs". For the exprs object, glancing at it's middle column, we can based on the 100 rows and 61 columns, that it is likely a matrix-style object. We might also recall we saw similar numbers in the printed output when we ran `read.FCS()`earlier. - -![](images/00_flowFrame.png) - -Which likely means that "exprs" slot is where the MFI data for the individual acquired cells within our .fcs file is being stored. Within Positron, for a matrix object, we can click on the little grid symbol on the far right to open up the table within editor. - -![](images/05_OpenTable.png) - -If we utilize the scroll bars, we can see that the individual detectors (in the case of uploading a raw spectral fcs file, they would appear as fluorophores for unmixed spectral or conventional fcs files) occupy the individual columns, which are named. The rows are not named, but number 100, matching the number of cells present in the .fcs file. Additionally, on the far left there is a little summary table about the overall data. - -![](images/06_TableInEditor.png) - -Let's go ahead and assign this matrix to a new variable/object so that we can explore it later. Since flowFrame is an S4 object, it's slots can be individually accessed by adding the @ symbol and the respective slot name. - -```{r} -MFI_Matrix <- flowFrame@exprs -``` - -Alternatively, we can use the Bioconductor helper function `exprs()` to get data held in that slot - -```{r} -MFI_Matrix_Alternate <- exprs(flowFrame) -``` - -In the case of the above, this displayed text output to the console would be unwiedly to display all at once. If we wanted to only see the first five rows, we could use the `head()` function, and provide a value of 5. - -```{r} -head(MFI_Matrix, 5) -``` - -This is much more workable, especially on a small laptop screen. We can see that there are names for each column corresponding to detector/fluorophore/metal depending on the .fcs file we are accessing. Lets retrieve these column names using the `colnames()` function. - -```{r} -ColumnNames <- colnames(MFI_Matrix) -ColumnNames -``` - -Something interesting occurred when this occurred, we can see in addition to the detector names directly above each a "$P#N" pattern appear, with # standing for increasing numbers. If we recall, we saw something similar in the first output column when we first ran `read.FCS()`. - -![](images/00_flowFrame.png) - -Lets break out the `str()` and `class()` functions from last week and see what we can find out about why this is occuring. - -```{r} -str(ColumnNames) -``` - -In this case we can see that we don't just have a vector (list) similar to what we saw with Fluorophores object last week, because instead of a chr [1:61] we get back a Named chr [1:61] designation. What we see is that in this case, each value has a corresponding index name as well. (ex. $P1N, $P2N, etc.) Let's double check with `class()` function. - -```{r} -class(ColumnNames) -``` - -We can see that everything is character, but it doesn't inform us that each index was named. This is one of the reasons it is best when trying to see what type of an object something is, to use multiple functions, to avoid missing some important details. - -If we were trying to remove the names, being left with just the values (similar to what we saw with the vector-style list last week), we could use the `unname()` function: - -```{r} -unname(ColumnNames) -``` - -
- ---- - -Let's return to the right sidebar to continue our exploration, by clicking on the dropdown arrow for exprs in the side-bar - -![](images/07_ExprsExpanded.png) - -The output is less user-friendly than what we saw when clicking on the little grid. If we scroll down far enough, we get down as far as [,61], which corresponds to the total number of columns. - -![](images/08_LessFriendly.png) - -In base R, column order can be defined by placing the corresponding column index number after a comma ",". So for this case, the first column would be designated would be [,1] while the last column would be designated [,61]. - -```{r} -MFI_Matrix[,1] -``` - -```{r} -MFI_Matrix[,61] -``` - -What would happen if used a column index number that didn't exist? Let's check. - -```{r} -#| error: TRUE - -MFI_Matrix[,350] -``` - -We get back an error message telling us the subscript is out of bounds. - -So if columns are specified by a number after the comma (ex. [,1]), how are rows specified? In R, rows would be specified by a number before the comma [1,] - -```{r} -MFI_Matrix[1,] -``` - -And while not the focus of today, we could retrieve individual values from a matrix by specifying both a row and a column index number. So for example, if we wanted the MFI value for the UV1-A detector for the first acquired cell (knowing that UV1-A is the 2nd column): - -```{r} -MFI_Matrix[1,2] -``` - -From our exploration, this looks to be all the information contained within the "exprs" slot, so let's back up and check on the next slot. - -
- ---- - -### parameters - -As we look at the next slot in the flowFrame object, we can see that parameters looks like it is going to be another more complex object, as it is showing up as an AnnotatedDataFrame object (defined by the Biobase R package, and itself contains 4 slots). - -![](images/09_Parameters.png) - ---- - -Having carved our way this far into the heart of an .fcs file, we are not about to call it quits now, so [CHARGE](https://youtu.be/92gP2J0CUjc?t=72) my fellow cytometrist!!! Click that drop-down arrow! - ---- - -Having survived our charge into the unknown, the four parameter slots appear to be "varMetadata", "data", "dimLabels" and "._classVersion_". - -![](images/10_ParameterSlots.png) - -#### varMetadata - -Fortunately for us, both "varMetadata" and "data" at least appear to be table-like objects of a type known as a "data.frame", so lets click on the grid to open in our editor window. - -In the case of varMetadata, we seem to have retrieved a column of metadata names. - -![](images/11_varMetadata.png) - -These look reminiscent of what we saw at the top of the `read.FCS()` column outputs previously - -![](images/12_varMetadata2.png) - -#### data - -Clicking on the grid for parameters's data slot will end opening the actual content that was displayed. - -![](images/13_data.png) - -Let's try to retrieve the data contained within this slot and save it as it's own variable/object within our R session. First, we need to open flowFrame object, then use @ to get inside its parameters slot. Since parameters is also a complex object (AnnotatedDataFrame specifically), we will need to use another @ to get inside its data slot: - -```{r} -ParameterData <- flowFrame@parameters@data - -head(ParameterData, 10) -``` - -And similarly, we could access with the Bioconductor helper function `parameters()`, but we would need to specify the accessor for data outside the parenthesis. - -```{r} -ParameterData_Alternate <- parameters(flowFrame)@data -``` - -If we ran the `str()` function, we get the following insight into ParameterData's object type - -```{r} -str(ParameterData) -``` - -We can see this class of object is a "data.frame". This is one of the more common object types in R, and we will be seeing these extensively throughout the course. We see that each of the columns appears to be designated by a $ followed by the column name, and then type of column (numeric, character, etc). - -![](images/15_dataframe.png) - -If we are trying to see these columns in R, we notice that data.frame is not like the previous S4 class objets we interacted with, as the @ symbol after doesn't bring up any suggestions - -```{r} -#| eval: FALSE - -ParameterData@ -``` - -By contrast, adding the $ we saw when using the `str()` function does retrieve the underlying information - -```{r} -#| eval: FALSE -ParameterData$ -``` - -![](images/15_Suggestions.png) - -As you become more familiar with R, remembering to check what kind of object you are working with, and how to access the contents will with practice become more familiar to you. - -Similar to what we saw with a matrix, we can subset a data.frame based on the column or row index using square brackets []. - -```{r} -ParameterData[,1] -``` - -The individual detectors or fluorophore appear under "name". For now, based on what we know, the $P# appears to be some sort of name being used as an internal consistent reference to the respective. - -"desc" is appearing empty for this raw spectral fcs file, but if you were to checked an unmixed file, this would be occupied the marker/ligand name assigned to it during the experiment setup. - -"range", "minRange" and "maxRange" are beyond the scope of today, but are used by both instrument manufacturers and software vendors when setting appropiate scaling for a plot. For the actual details, see the [Flow Cytometry Standard](https://web.archive.org/web/20150209122542/http://www.isac-net.org/images/stories/documents/Standards/fcs3.1_normativespecification_20090813.pdf) documentation. - -Having exhausted our options under parameters "varMetadata" and "data" slots, let's continue to the next slot. - -#### dimLabels - -![](images/16_DimLabels.png) - -In this case, not much is returned. Yey! - -```{r} -flowFrame@parameters@dimLabels -``` - -#### classVersion - -Continuing on to the last slot ".__classVersion__" - -```{r} -flowFrame@parameters@.__classVersion__ -``` - -Also mercifully short, both of these seem to be more involved in defining the S4 class object, and don't contain anything we need to retrieve today. - -
- -### Description - -At this point, we have explored both "exprs" and "parameter" slots for the flowFrame object we created. Let's tackle the final slot, named description. - -![](images/17_Description.png) - -When doing so, a very large list is opened within the Positron variables window. While we could scroll through it, it might be easier to retrieve certain number of rows via the console to make interpreting this more structured. - -![](images/18_List.png) - -To retrieve the list itself, we would need to access the description slot of the flowFrame object. Since it is a slot, we will need to use the @ accessor. - - - -```{r} -DescriptionList <- flowFrame@description -``` - -```{r} -#| class-output: "scroll-output" -DescriptionList -``` - -The returned list is a little too large to reasonably explore. We can attempt to subset using the `head()` function as shown below - -```{r} -head(DescriptionList, 5) -``` - -Alternatively, it might be better to subset based on position index - -```{r} -DescriptionList[1:10] -``` - -And just as we saw for exprs and parameters, there is also a Bioconductor helper `keyword()` function to access this same information directly from the flowFrame. - -```{r} -DescriptionList_Alternate <- keyword(flowFrame) -``` - -If we run the `class()` function, we can see that DescriptionList is an actual "list". - -```{r} -class(DescriptionList) -``` - -This is in contrast to the vectors we have previously generated. While these are also list like, they are what are known as as atomic list, which contain values that are all either characters, numerics or logicals. - -```{r} -Fluorophores <- c("BV421", "FITC", "PE", "APC") -class(Fluorophores) -``` - -```{r} -PanelAntibodyCounts <- c(5, 12, 19, 26, 34, 46, 51) -class(PanelAntibodyCounts) -``` - -```{r} -SpecimenIndexToKeep <- c(TRUE, TRUE, FALSE, TRUE) -class(SpecimenIndexToKeep) -``` - -A list on the other hand is not restricted to contain objects composed entirely of a certain atomic type. For example, I could include the three previous vectors into a list using the `list()` function. - -```{r} -MyListofVectors <- list(Fluorophores, PanelAntibodyCounts, SpecimenIndexToKeep) -str(MyListofVectors) -``` - -We can see that with the Description/Keyword list we retrieved from our flowFrame shares a somewhat similar format. - -```{r} -str(DescriptionList[1:10]) -``` - -But in this case, there are also names present ($BEGINANALYSIS, $BEGINDATA, etc). What if we had tried to provide names to our List of Vectors? Would the format match? - -When we assigned a name to each of the vectors (by providing an equal to = ), we get the same kind of structure format to what we see in Description. - -```{r} -MyNamedListofVectors <- list(FluorophoresNamed=Fluorophores, - PanelAntibodyCountsNamed=PanelAntibodyCounts, - SpecimenIndexToKeepNamed=SpecimenIndexToKeep) - -str(MyNamedListofVectors) -``` - -We could then subsequently be able to isolate items from that list using the $ operator. - -```{r} -#| eval: FALSE -MyNamedListofVectors$ -``` - -![](images/20_ListAccess.png) - -Alternatively, we could also access by list index position - -```{r} -MyNamedListofVectors[1] -``` - -Remembering back to the original output from `read.FCS()` we remember that it mentioned 599 keywords being in the description slot, so now we know that this is what was being referenced. - -![](images/00_flowFrame.png) - -# Keyword Madness - -Rather than go through the keywords individually (in which case we would be here through tomorrow), let's take a birds eye view of the contents of this list. - -```{r} -#| class-output: "scroll-output" -Subset <- DescriptionList[1:18] -Subset -``` - -## Early Metadata - -Within the initial portion, we are getting back metadata keywords related to where and how the particular file was acquired. Keywords of potential interest include: - -:::{.callout-tip title="Start Time"} -What time was the .fcs file acquired -::: - -::: {.fragment} - -```{r} -DescriptionList$`$BTIM` -``` -::: - - -:::{.callout-tip title="Cytometer"} -What type of cytometer was the .fcs file acquired on -::: - -::: {.fragment} - -```{r} -DescriptionList$`$CYT` -``` - -::: - -
- ---- - - -:::{.callout-tip title="Cytometer Serial Number"} -Manufacturer Serial Number of the Cytometer -::: - -::: {.fragment} -```{r} -DescriptionList$`$CYTSN` -``` - -::: - - -:::{.callout-tip title="FCS File Acquisition Date"} -What was the date of acquisition -::: - -::: {.fragment} -```{r} -DescriptionList$`$DATE` -``` - -::: - - -
- ---- - - -:::{.callout-tip title="Acquisition End Time"} -What time was acquisition stopped -::: - -::: {.fragment} - -```{r} -DescriptionList$`$ETIM` -``` - -::: - - -:::{.callout-tip title="File Name"} -Name of the .fcs file -::: - -::: {.fragment} - -```{r} -DescriptionList$`$FIL` -``` - -::: - -
- ---- - -:::{.callout-tip title="Operator"} -Who acquired the .fcs file -::: - -::: {.fragment} - -```{r} -DescriptionList$`$OP` -``` - -::: - -
- ---- - -## Detector Values - -The next major stretch of keywords encode parameter values associated with the individual detectors for at the time of acquisition. - -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[20:384] -Detectors -``` - -Fortunately for all involved, there is a consistently repeating pattern for the keywords corresponding to each detector. We can see that here for $P7B, $P7E, $P7N, $P7R, $P7TYPE, $P7V - -![](images/21_DetectorIteration.png) - -When referencing to the [Flow Cytometry Standard](https://web.archive.org/web/20150209122542/http://www.isac-net.org/images/stories/documents/Standards/fcs3.1_normativespecification_20090813.pdf) documentation, here are what the particular keyword letters mean: - -:::{.callout-tip title="B"} -Number of bits reserved for parameter number n -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7B` -``` - -::: - -:::{.callout-tip title="E"} -Amplification type for parameter n. -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7E` -``` - -::: - -
- ---- - -:::{.callout-tip title="N"} -Short Name for parameter n. -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7N` -``` - -::: - -:::{.callout-tip title="R"} -Range for parameter number n. -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7R` -``` - -::: - -
- ---- - -:::{.callout-tip title="TYPE"} -Detector type for parameter n. -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7TYPE` -``` - -::: - -:::{.callout-tip title="V"} -Detector voltage for parameter n. -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7V` -``` - -::: - -
- ---- - -While not immediately obvious, understanding what these keywords encoded has proven useful for our core. In our case, we have built an automated [InstrumentQC dashboard](https://umgccfcss.github.io/InstrumentQC/Aurora3L.html) for all the instruments at our core. - -![](images/InstrumentQC.png) - -
- ---- - -By extracting out from our daily QC bead .fcs files the stored **N (Detector Name)** and **V (Gain/Voltage)** values for all the individual detectors, it allows us to plot Levey-Jennings Plots for our individual instruments, giving us usually around a months warning before an individual laser begins to fail. This helps with scheduling the Field-Service Engineer visit before it starts impacting the actual data. - -![](images/LeveyJennings.png) - -
- ---- - -While most of the detectors keywords are similar (only changing there individual name and voltage) there are a couple exceptions. - -For the FSC/SSC parameters, instead of Raw_Fluorescence value for Type, we see the corresponding Scatter value get return. This in term is what is used by various commercial softwares to show those axis as linear instead of biexponential when selected. - -![](images/22_FSC.png) - -
- ---- - -This is similarly the case for the Time parameter, where in addition to Type being set to Time, the range also appears different to Raw/Scatters value. - -![](images/23_Time.png) - - -## Middle Metadata - -Once we are out of the detector keywords, we find the last of the $Metadata associated keywords. - -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[385:398] -Detectors -``` - -Among those of potential interest - -:::{.callout-tip title="Proj"} -Often corresponding to the experiment file name -::: - -::: {.fragment} - -```{r} -DescriptionList$`$PROJ` -``` - -::: - -:::{.callout-tip title="Spillover"} -Where the internal spillover matrix is stored (we will revisit during compensation) -::: - -::: {.fragment} - -```{r} -DescriptionList$`$SPILLOVER` -``` - -::: - - -:::{.callout-tip title="TOT"} -Total events (in this case my downsampled 100 cells) -::: - -::: {.fragment} - -```{r} -DescriptionList$`$TOT` -``` - -::: - -:::{.callout-tip title="Volume"} -Volume amount acquired during acquisition. -::: - -::: {.fragment} - -```{r} -DescriptionList$`$VOL` -``` - -::: - -:::{.callout-tip title="Software"} -Software used and version -::: - -::: {.fragment} - -```{r} -DescriptionList$CREATOR -``` - -::: - -You will notice at this point, the keyword names including a "$" symbol have stopped, so tick marks are no longer required (except when there is a space in the name). The only $ remaining is being used as a selector for a particular item in the list. - -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[390:398] -Detectors -``` - - -:::{.callout-tip title="FILENAME"} -Basically the full file.path to the .fcs file of interest. -::: - -::: {.fragment} - -```{r} -DescriptionList$FILENAME -``` - -::: - - -:::{.callout-tip title="GROUPNAME"} -The Name assigned to the acquisition Group. -::: - -::: {.fragment} - -```{r} -DescriptionList$GROUPNAME -``` - -::: - -## Laser Metadata - -Next up, there is a small stretch of keywords containing the values associated with the individual lasers as far as delays and area scaling factors for a particular day (also useful when [plotted](https://umgccfcss.github.io/InstrumentQC/Aurora5L.html)). - - -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[399:410] -Detectors -``` - - -## Display - -Then there is a stretch matching whether a particular detector needs to be displayed as linear (in the case of time and scatter) or as log (for individual detectors). - -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[412:472] -Detectors -``` - -And a few final keywords with threshold, window scaling and other user selected settings. - -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[473:476] -Detectors -``` - -## flowCore Parameters - -Depending on the arguments selected during `read.FCS()`, we might also encounter additional keywords that are added in by flowCore. For example, we do not see these keywords when "transformation" is set to FALSE. - -```{r} -flowCoreCheck <- read.FCS(filename=firstfile, - transformation = FALSE, truncate_max_range = FALSE) - -flowCoreCheck -``` - -```{r} -#| class-output: "scroll-output" -NoChange <- keyword(flowCoreCheck) -Detectors <- NoChange [476:500] -Detectors -``` - -By contrast, if we had set "transformation" to TRUE: - -```{r} -flowCoreCheck <- read.FCS(filename=firstfile, - transformation = TRUE, truncate_max_range = FALSE) - -flowCoreCheck -``` - -```{r} -#| class-output: "scroll-output" -YesChange <- keyword(flowCoreCheck) -Detectors <- YesChange [476:500] -Detectors -``` - -
- ---- - -For some flow cytometry R packages, you will notice when opening their exported .fcs outputs in commercial software that these flowCore keywords have ended up integrated. It is likely somewhere in the package code the author forgot to add set transformation to FALSE, which is why we are seeing these flowCore keywords after the fact. - -# Take Away - -Today we broke open an .fcs file and explored how the underlying data is organized and stored once it is brought into R. In the process, we continued to build familiarity with some of the basic R knowledge, going from smaller simpler objects we encountered in week 2 to matrices and data.frames, to complex objects with multiple slots typical of what we encounter in the Bioconductor packages. We will build on these initial observations on the weeks to come. - -In context of our continuing analogy, with each function being a tool, and an R package a toolbox, each tool in the toolbox works on different types of objects. A hammer needs nails, screwdrivers need screws, a paintbrush needs paint and a wall, etc. Object types help define these requirements, so when we use a function, knowing what type can help determine what we provide to it in order for it to work properly and not error out. - -Next week, we will dive into the world of [tidyverse](https://tidyverse.org/), working specifically with these intermediate object types matrices and data.frames. The basic premise is to think of all data as rows and columns, the reasoning behind this approach which can be found [here](https://vita.had.co.nz/papers/tidy-data.html). - -![](images/TakeAway.jpg) - -
- ---- - -# Additional Resources - -[Data File Standard for Flow Cytometry, Version FCS 3.1](https://pmc.ncbi.nlm.nih.gov/articles/PMC2892967/) - -[R Programming - R Data Types: Vectors and Lists](https://youtu.be/p01ckVx-678?si=BQp6SFTWfZzz2-wI) - -[Base Types vs. Object-Oriented Objects](https://adv-r.hadley.nz/base-types.html) - -
- ---- - -# Take-home Problems - -:::{.callout-tip title="Problem 1"} -Today's walkthrough focused on a raw spectral flow cytometry file. Within a subfolder in data you will also find an unmixed .fcs file (2025_07_26...). Using what learned to day, investigate it, and see if you can catalog the main differences that occured to the keyword, parameters and exprs. Did any keywords get added, changed, deleted entirely? etc. -::: - -:::{.callout-tip title="Problem 2"} -Today's files were for spectral .fcs files from a Cytek Aurora within a subfolder in data you will also find a conventional flow cytometry file (2025-10_22...). Similarly, explore and see if you find any major differences (beyond the different detector or fluorophore names which will vary based on antibody panel used, etc) -::: - -:::{.callout-tip title="Problem 3"} -If you have access to commercial software, take one of the .fcs files and try to see if you can see similar internal information from within the software. For those without commercial access, try the equivalent process using [Floreada.io](/course/00_Floreada/index.qmd). -::: - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "03 - Inside an FCS File" +author: "David Rach" +date: 02-15-2026 +format: html +toc: true +toc-depth: 5 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream recording, see [here](https://youtu.be/1wZ61x0i19o?t=278) + + + +For screen-shot slides, click [here](/course/03_InsideFCSFile/slides.qmd) + +
+ +--- + +# Background + +Welcome to the Week #3! Having subjected everyone to two R-focused weeks, this week will have more of a cytometry-focus as we slice into an .fcs file. We will hopefully gather greater understanding of how an .fcs file is structured and what additional kinds of information we can retrieve (while becoming increasingly puzzled why different manufacturers insist on using different keyword names for the exact same things). + +We will also gain additional exposure to more object types in R (vectors, list, matrices and data.frames). Continuing the analogy from last week, if every function is the equivalent of a tool in a toolbox, each tool requires certain types of things to do its job properly (hammer ~ nail, screwdriver ~ screws, paintbrush ~ paint, etc.). Being able to identify what type/kind of object a particular variable we have created in R is will allow us to pass it to the correct function that will allow us to work with that object type. + +
+ +--- + +:::{.callout-important title="Housekeeping"} +We are building off concepts that were covered in [Week #1 (Installing R packages)](/course/01_InstallingRPackages/index.qmd) and especially [Week #2 (File Paths)](/course/02_FilePaths/index.qmd). +For those who are flow cytometry beginners, please see [UChicago Flow](https://youtu.be/gC4brjHbLkk?si=li98x7KlLXUFWGX3) Flow Basics Series for additional context. +::: + + +:::{.callout-tip title="Today's Goal"} +If you find yourself at some point going "I have no idea what is going on", please pause, take a break, and circle back later in the day. Our goal is not to have you memorize how to quickly access 100 archaic keywords, but rather showcase a typical object exploration workflow. So don't power through, but rather circle back when you are in an exploring mindset. Consider what kind of information from within an .fcs file you'd like to retrieve, and then explore/navigate your way through the various paths until you find the information that you were looking for. +::: + +--- + +:::{.callout-important title="Housekeeping"} +As we do [every week](/course/02_FilePaths/index.qmd#new-repository), on GitHub, sync your forked-version of the CytometryInR course to bring in the most recent updates. Then within Positron, pull in those changes to your local computer. From there, copy the data folder to a separate project folder you have created. This will prevent any merge issues bringing in new data next week. +::: + +--- + +# Walk Through + +--- + +## Getting Set Up + +--- + +### Set up File Paths + +Having copied over the new data to your working project folder (Week 3 or whatever your chosen name), let's identify the file paths between our working directory and the fcs files. If you retained the same project organization structure we had during Week #2, it may look similar to the following: + +```{r} +#| eval: FALSE +#| include: FALSE + +# Please note, this code-chunk is only for use when writing the code. Please switch eval to false and next code blocks eval to true before rendering + +PathToDataFolder <- file.path(getwd(), "course", "03_InsideFCSFile", "data") +``` + +```{r} +#| eval: TRUE +PathToDataFolder <- file.path("data") +``` + +```{r} +PathToDataFolder +``` + +
+ +--- + +### Locate .fcs files + +We will now locate our .fcs files. As we saw last week, our computer will need the full file.paths to these individual files, so we will set the `list.files()` "full.names" argument to TRUE. + +```{r} +#| eval: TRUE +fcs_files <- list.files(PathToDataFolder, pattern=".fcs", full.names=TRUE) +fcs_files +``` + +By contrast, if the "full.names" argument was set to FALSE, we would have retrieved just the file names + +```{r} +list.files(PathToDataFolder, pattern=".fcs", full.names=FALSE) +``` + +This would have been the equivalent of running the `basename` function on the "full.names=TRUE" output. +```{r} +basename(fcs_files) +``` + +
+ +--- + +## flowCore + +We will be using the `flowCore` package, which is the oldest and most-frequently downloaded flow cytometry package on [Bioconductor](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry). + +```{r} +#| code-fold: TRUE +#| warning: FALSE +#| message: FALSE + +# I have attached this code for anyone that is interested in seeing how these plots were made. The content is not part of today's lesson, so if you are just starting off, we will cover the details of data-tidying and creating ggplot objects over the next several weeks. Best, David + +# Load required packages via a library call + +library(dplyr) # CRAN +library(stringr) # CRAN +library(ggplot2) # CRAN +#library(plotly) # Using the :: to access + +# Loading in the dataset contained within the .csv file +BioconductorFlow_path <- file.path(PathToDataFolder, "BioconductorFlow.csv") +BioconductorFlowPackages <- read.csv(BioconductorFlow_path, check.names=FALSE) +BioconductorFlowPackages <- BioconductorFlowPackages |> + arrange(desc(since)) |> mutate(package = factor(package, levels = package)) + +# Newer Base R Pipe : |> +# Older mostly equivalent Magrittr Pipe %>% +``` + +```{r} +#| code-fold: true +#| fig-height: 9 + +# Notice the code-chunk eval arguments above dictate the shape of the final rendered plot. + +# Taking the imported dataset and passing it to ggplot2 to create the first plot. + +plot <- ggplot(BioconductorFlowPackages, + aes(x = 0, xend = since, y = package, yend = package)) + + geom_segment(linewidth = 2, color = "steelblue") + + scale_x_continuous(trans = "reverse", + breaks = seq(0, max(BioconductorFlowPackages$since), by = 5)) + + labs( + x = "Years in Bioconductor", + y = NULL, + title = "Bioconductor Flow Cytometry R packages" + ) + + theme_bw() + +# Taking the static plot and making it interactive using the plotly package + +plotly::ggplotly(plot) +``` + +```{r} +#| code-fold: TRUE + +# Retrieving the names of Bioconductor flow cytometry R packages in correct release order. + +HistoricalOrder <- BioconductorFlowPackages |> pull(package) + +# Bringing in 2025 package usage dataset from a .csv file +BioconductorUsage_path <- file.path(PathToDataFolder, "BioconductorDownloads.csv") +BioconductorUsage <- read.csv(BioconductorUsage_path, check.names=FALSE) +BioconductorUsage <- BioconductorUsage |> dplyr::filter(Month %in% "all") + +# Note, dplyr::filter is used due to flowCore also having a filter function, which causes conflicts once it is attached to the local environment. + +# Combining both data.frames for use in the plot + +Dataset <- left_join(BioconductorFlowPackages, BioconductorUsage, by="package") + +# Rearranging the order in which packages are displayed + +Dataset$package <- factor(Dataset$package, levels=HistoricalOrder) +``` + +```{r} +#| code-fold: TRUE + +# Generating the 2nd plot with ggplot2 + +plot <- ggplot(Dataset, aes(x = since, y = Nb_of_distinct_IPs)) + + geom_point(aes(color = package), size = 3, alpha = 0.7) + + labs( + x = "Years in Bioconductor", + y = "Number of Yearly Downloads", + title = "", + color = "Package" + ) + + theme_bw() + +# Making it interactive with plotly + +plotly::ggplotly(plot) +``` + +flowCore is also one of the many Bioconductor packages maintained by [Mike Jiang](https://github.com/mikejiang). In many ways (as those who completed the optional take-home problems for Week #1 know) reminiscent of this [xkcd](https://xkcd.com/2347/) comic: + +![](images/BioconductorXKCD.png) + +As with all our R packages, we first need to make sure `flowCore` is attached to our local environment via the library call. + +```{r} +library(flowCore) +``` + +The function we will be using today is the `read.FCS()` function. Do you remember how to access the help documentation? + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Or when in Positron, hovering over the highlighted function name within the code-chunk + +?flowCore::read.FCS +``` + +To start, lets select just the first .fcs file. We will do this by indexing the first item within fcs_files via the square brackets []. + +```{r} +firstfile <- fcs_files[1] +firstfile +``` + +## flowFrame + +For `read.FCS()`, it accepts several arguments. The argument "filename" is where we provide our file.path to .fcs file that we wish to load into R. Let's go ahead and do so + +```{r} +#| eval: FALSE + +read.FCS(filename=firstfile) + +``` + +Please note, if you are doing this with your own .fcs files, you will need to provide two additional arguments, "transformation" = FALSE, and "truncate_max_range" = FALSE for the files to be read in correctly. We will revisit the reasons why in Week #5. + +```{r} +read.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE) +``` + +In this case, we can see the .fcs file has been read into R as a "flowFrame" object. We can also see the file name, as well as details about the number of cells, and number of columns (whether detectors (for raw spectral flow data) or fluorophores (for unmixed spectral flow data)). + +![](images/00_flowFrame.png) + +Directly below we see what resembles a table. At first glance, the only column with an immediately discernable purpose is the one with the name column, which is listing the detectors present on a [Cytek Aurora](https://bpb-us-w2.wpmucdn.com/voices.uchicago.edu/dist/2/1824/files/2021/10/Aurora-Configuration.png). + +![](images/01_flowFrameDetectors.png) + +And finally, at the bottom we reach a line that tells us that for this .fcs files, 599 keyword can be found in a description slot. + +![](images/02_KeywordsFiveNineNine.png) + +
+ +--- + +So let's get our bearings, we have loaded in an .fcs file to R, but let's use some of the concepts we covered last week to try to understand a bit about what type or class of object we are working with. From the output, we saw the words flowFrame object, so let's read it back in again, but assign it to an variable/object called flowFrame so that we can use the type-discerning functions we worked with last week on. + +```{r} +flowFrame <- read.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE) +``` + +As we create this variable, if we have the session tab selected on our right secondary side bar, we see it appear: + +![](images/03_SessionTab.png) + +If we were to use the type-determining functions we learned last week + +```{r} +#| eval: FALSE +#| include: FALSE +# This is the whole ball game +str(flowFrame) +``` + +```{r} +class(flowFrame) +``` + +flowFrames are a class of object with a structure defined within the `flowCore` package. They are used to work with the data contained within individual .fcs files. Looking again at the right secondary side bar, we can see that it shows up as a ""S4 class flowFrame package flowCore""" with 3 slots, with the words flowFrame adjacent to it. + +A perfectly valid first reaction to first reading this is "well how should I know what any of this means?". Powering through this initial discomfort, let's go ahead and click on the dropdown arrow next to the variables name and see if we get any additional clarity on the issue. + +![](images/04_Slots.png) + +When we do so, three additional drop-downs appear. Based on the previous line that mentioned 3 slots, we could infer that each line corresponds to one of those slots. + +What we are encountering with flowFrame is our first example of an S4 object type. These more-complicated object types are quite common for the various [Bioconductor](https://adv-r.hadley.nz/s4.html) affilitated R packages. + +These objects will usually appear with either S4 or S3 in their metadata, and are made up of various simpler object types that are cobbled together within the larger object, usually occupying individual slots. + +What advantage this bundling provides will be something we revisit throughout the course as you encounter more of these S4/S3 objects. + +
+ +--- + +### exprs + +The first slot within the flowFrame object shows up with the name "exprs". For the exprs object, glancing at it's middle column, we can based on the 100 rows and 61 columns, that it is likely a matrix-style object. We might also recall we saw similar numbers in the printed output when we ran `read.FCS()`earlier. + +![](images/00_flowFrame.png) + +Which likely means that "exprs" slot is where the MFI data for the individual acquired cells within our .fcs file is being stored. Within Positron, for a matrix object, we can click on the little grid symbol on the far right to open up the table within editor. + +![](images/05_OpenTable.png) + +If we utilize the scroll bars, we can see that the individual detectors (in the case of uploading a raw spectral fcs file, they would appear as fluorophores for unmixed spectral or conventional fcs files) occupy the individual columns, which are named. The rows are not named, but number 100, matching the number of cells present in the .fcs file. Additionally, on the far left there is a little summary table about the overall data. + +![](images/06_TableInEditor.png) + +Let's go ahead and assign this matrix to a new variable/object so that we can explore it later. Since flowFrame is an S4 object, it's slots can be individually accessed by adding the @ symbol and the respective slot name. + +```{r} +MFI_Matrix <- flowFrame@exprs +``` + +Alternatively, we can use the Bioconductor helper function `exprs()` to get data held in that slot + +```{r} +MFI_Matrix_Alternate <- exprs(flowFrame) +``` + +In the case of the above, this displayed text output to the console would be unwiedly to display all at once. If we wanted to only see the first five rows, we could use the `head()` function, and provide a value of 5. + +```{r} +head(MFI_Matrix, 5) +``` + +This is much more workable, especially on a small laptop screen. We can see that there are names for each column corresponding to detector/fluorophore/metal depending on the .fcs file we are accessing. Lets retrieve these column names using the `colnames()` function. + +```{r} +ColumnNames <- colnames(MFI_Matrix) +ColumnNames +``` + +Something interesting occurred when this occurred, we can see in addition to the detector names directly above each a "$P#N" pattern appear, with # standing for increasing numbers. If we recall, we saw something similar in the first output column when we first ran `read.FCS()`. + +![](images/00_flowFrame.png) + +Lets break out the `str()` and `class()` functions from last week and see what we can find out about why this is occuring. + +```{r} +str(ColumnNames) +``` + +In this case we can see that we don't just have a vector (list) similar to what we saw with Fluorophores object last week, because instead of a chr [1:61] we get back a Named chr [1:61] designation. What we see is that in this case, each value has a corresponding index name as well. (ex. $P1N, $P2N, etc.) Let's double check with `class()` function. + +```{r} +class(ColumnNames) +``` + +We can see that everything is character, but it doesn't inform us that each index was named. This is one of the reasons it is best when trying to see what type of an object something is, to use multiple functions, to avoid missing some important details. + +If we were trying to remove the names, being left with just the values (similar to what we saw with the vector-style list last week), we could use the `unname()` function: + +```{r} +unname(ColumnNames) +``` + +
+ +--- + +Let's return to the right sidebar to continue our exploration, by clicking on the dropdown arrow for exprs in the side-bar + +![](images/07_ExprsExpanded.png) + +The output is less user-friendly than what we saw when clicking on the little grid. If we scroll down far enough, we get down as far as [,61], which corresponds to the total number of columns. + +![](images/08_LessFriendly.png) + +In base R, column order can be defined by placing the corresponding column index number after a comma ",". So for this case, the first column would be designated would be [,1] while the last column would be designated [,61]. + +```{r} +MFI_Matrix[,1] +``` + +```{r} +MFI_Matrix[,61] +``` + +What would happen if used a column index number that didn't exist? Let's check. + +```{r} +#| error: TRUE + +MFI_Matrix[,350] +``` + +We get back an error message telling us the subscript is out of bounds. + +So if columns are specified by a number after the comma (ex. [,1]), how are rows specified? In R, rows would be specified by a number before the comma [1,] + +```{r} +MFI_Matrix[1,] +``` + +And while not the focus of today, we could retrieve individual values from a matrix by specifying both a row and a column index number. So for example, if we wanted the MFI value for the UV1-A detector for the first acquired cell (knowing that UV1-A is the 2nd column): + +```{r} +MFI_Matrix[1,2] +``` + +From our exploration, this looks to be all the information contained within the "exprs" slot, so let's back up and check on the next slot. + +
+ +--- + +### parameters + +As we look at the next slot in the flowFrame object, we can see that parameters looks like it is going to be another more complex object, as it is showing up as an AnnotatedDataFrame object (defined by the Biobase R package, and itself contains 4 slots). + +![](images/09_Parameters.png) + +--- + +Having carved our way this far into the heart of an .fcs file, we are not about to call it quits now, so [CHARGE](https://youtu.be/92gP2J0CUjc?t=72) my fellow cytometrist!!! Click that drop-down arrow! + +--- + +Having survived our charge into the unknown, the four parameter slots appear to be "varMetadata", "data", "dimLabels" and "._classVersion_". + +![](images/10_ParameterSlots.png) + +#### varMetadata + +Fortunately for us, both "varMetadata" and "data" at least appear to be table-like objects of a type known as a "data.frame", so lets click on the grid to open in our editor window. + +In the case of varMetadata, we seem to have retrieved a column of metadata names. + +![](images/11_varMetadata.png) + +These look reminiscent of what we saw at the top of the `read.FCS()` column outputs previously + +![](images/12_varMetadata2.png) + +#### data + +Clicking on the grid for parameters's data slot will end opening the actual content that was displayed. + +![](images/13_data.png) + +Let's try to retrieve the data contained within this slot and save it as it's own variable/object within our R session. First, we need to open flowFrame object, then use @ to get inside its parameters slot. Since parameters is also a complex object (AnnotatedDataFrame specifically), we will need to use another @ to get inside its data slot: + +```{r} +ParameterData <- flowFrame@parameters@data + +head(ParameterData, 10) +``` + +And similarly, we could access with the Bioconductor helper function `parameters()`, but we would need to specify the accessor for data outside the parenthesis. + +```{r} +ParameterData_Alternate <- parameters(flowFrame)@data +``` + +If we ran the `str()` function, we get the following insight into ParameterData's object type + +```{r} +str(ParameterData) +``` + +We can see this class of object is a "data.frame". This is one of the more common object types in R, and we will be seeing these extensively throughout the course. We see that each of the columns appears to be designated by a $ followed by the column name, and then type of column (numeric, character, etc). + +![](images/15_dataframe.png) + +If we are trying to see these columns in R, we notice that data.frame is not like the previous S4 class objets we interacted with, as the @ symbol after doesn't bring up any suggestions + +```{r} +#| eval: FALSE + +ParameterData@ +``` + +By contrast, adding the $ we saw when using the `str()` function does retrieve the underlying information + +```{r} +#| eval: FALSE +ParameterData$ +``` + +![](images/15_Suggestions.png) + +As you become more familiar with R, remembering to check what kind of object you are working with, and how to access the contents will with practice become more familiar to you. + +Similar to what we saw with a matrix, we can subset a data.frame based on the column or row index using square brackets []. + +```{r} +ParameterData[,1] +``` + +The individual detectors or fluorophore appear under "name". For now, based on what we know, the $P# appears to be some sort of name being used as an internal consistent reference to the respective. + +"desc" is appearing empty for this raw spectral fcs file, but if you were to checked an unmixed file, this would be occupied the marker/ligand name assigned to it during the experiment setup. + +"range", "minRange" and "maxRange" are beyond the scope of today, but are used by both instrument manufacturers and software vendors when setting appropiate scaling for a plot. For the actual details, see the [Flow Cytometry Standard](https://web.archive.org/web/20150209122542/http://www.isac-net.org/images/stories/documents/Standards/fcs3.1_normativespecification_20090813.pdf) documentation. + +Having exhausted our options under parameters "varMetadata" and "data" slots, let's continue to the next slot. + +#### dimLabels + +![](images/16_DimLabels.png) + +In this case, not much is returned. Yey! + +```{r} +flowFrame@parameters@dimLabels +``` + +#### classVersion + +Continuing on to the last slot ".__classVersion__" + +```{r} +flowFrame@parameters@.__classVersion__ +``` + +Also mercifully short, both of these seem to be more involved in defining the S4 class object, and don't contain anything we need to retrieve today. + +
+ +### Description + +At this point, we have explored both "exprs" and "parameter" slots for the flowFrame object we created. Let's tackle the final slot, named description. + +![](images/17_Description.png) + +When doing so, a very large list is opened within the Positron variables window. While we could scroll through it, it might be easier to retrieve certain number of rows via the console to make interpreting this more structured. + +![](images/18_List.png) + +To retrieve the list itself, we would need to access the description slot of the flowFrame object. Since it is a slot, we will need to use the @ accessor. + + + +```{r} +DescriptionList <- flowFrame@description +``` + +```{r} +#| class-output: "scroll-output" +DescriptionList +``` + +The returned list is a little too large to reasonably explore. We can attempt to subset using the `head()` function as shown below + +```{r} +head(DescriptionList, 5) +``` + +Alternatively, it might be better to subset based on position index + +```{r} +DescriptionList[1:10] +``` + +And just as we saw for exprs and parameters, there is also a Bioconductor helper `keyword()` function to access this same information directly from the flowFrame. + +```{r} +DescriptionList_Alternate <- keyword(flowFrame) +``` + +If we run the `class()` function, we can see that DescriptionList is an actual "list". + +```{r} +class(DescriptionList) +``` + +This is in contrast to the vectors we have previously generated. While these are also list like, they are what are known as as atomic list, which contain values that are all either characters, numerics or logicals. + +```{r} +Fluorophores <- c("BV421", "FITC", "PE", "APC") +class(Fluorophores) +``` + +```{r} +PanelAntibodyCounts <- c(5, 12, 19, 26, 34, 46, 51) +class(PanelAntibodyCounts) +``` + +```{r} +SpecimenIndexToKeep <- c(TRUE, TRUE, FALSE, TRUE) +class(SpecimenIndexToKeep) +``` + +A list on the other hand is not restricted to contain objects composed entirely of a certain atomic type. For example, I could include the three previous vectors into a list using the `list()` function. + +```{r} +MyListofVectors <- list(Fluorophores, PanelAntibodyCounts, SpecimenIndexToKeep) +str(MyListofVectors) +``` + +We can see that with the Description/Keyword list we retrieved from our flowFrame shares a somewhat similar format. + +```{r} +str(DescriptionList[1:10]) +``` + +But in this case, there are also names present ($BEGINANALYSIS, $BEGINDATA, etc). What if we had tried to provide names to our List of Vectors? Would the format match? + +When we assigned a name to each of the vectors (by providing an equal to = ), we get the same kind of structure format to what we see in Description. + +```{r} +MyNamedListofVectors <- list(FluorophoresNamed=Fluorophores, + PanelAntibodyCountsNamed=PanelAntibodyCounts, + SpecimenIndexToKeepNamed=SpecimenIndexToKeep) + +str(MyNamedListofVectors) +``` + +We could then subsequently be able to isolate items from that list using the $ operator. + +```{r} +#| eval: FALSE +MyNamedListofVectors$ +``` + +![](images/20_ListAccess.png) + +Alternatively, we could also access by list index position + +```{r} +MyNamedListofVectors[1] +``` + +Remembering back to the original output from `read.FCS()` we remember that it mentioned 599 keywords being in the description slot, so now we know that this is what was being referenced. + +![](images/00_flowFrame.png) + +# Keyword Madness + +Rather than go through the keywords individually (in which case we would be here through tomorrow), let's take a birds eye view of the contents of this list. + +```{r} +#| class-output: "scroll-output" +Subset <- DescriptionList[1:18] +Subset +``` + +## Early Metadata + +Within the initial portion, we are getting back metadata keywords related to where and how the particular file was acquired. Keywords of potential interest include: + +:::{.callout-tip title="Start Time"} +What time was the .fcs file acquired +::: + +::: {.fragment} + +```{r} +DescriptionList$`$BTIM` +``` +::: + + +:::{.callout-tip title="Cytometer"} +What type of cytometer was the .fcs file acquired on +::: + +::: {.fragment} + +```{r} +DescriptionList$`$CYT` +``` + +::: + +
+ +--- + + +:::{.callout-tip title="Cytometer Serial Number"} +Manufacturer Serial Number of the Cytometer +::: + +::: {.fragment} +```{r} +DescriptionList$`$CYTSN` +``` + +::: + + +:::{.callout-tip title="FCS File Acquisition Date"} +What was the date of acquisition +::: + +::: {.fragment} +```{r} +DescriptionList$`$DATE` +``` + +::: + + +
+ +--- + + +:::{.callout-tip title="Acquisition End Time"} +What time was acquisition stopped +::: + +::: {.fragment} + +```{r} +DescriptionList$`$ETIM` +``` + +::: + + +:::{.callout-tip title="File Name"} +Name of the .fcs file +::: + +::: {.fragment} + +```{r} +DescriptionList$`$FIL` +``` + +::: + +
+ +--- + +:::{.callout-tip title="Operator"} +Who acquired the .fcs file +::: + +::: {.fragment} + +```{r} +DescriptionList$`$OP` +``` + +::: + +
+ +--- + +## Detector Values + +The next major stretch of keywords encode parameter values associated with the individual detectors for at the time of acquisition. + +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[20:384] +Detectors +``` + +Fortunately for all involved, there is a consistently repeating pattern for the keywords corresponding to each detector. We can see that here for $P7B, $P7E, $P7N, $P7R, $P7TYPE, $P7V + +![](images/21_DetectorIteration.png) + +When referencing to the [Flow Cytometry Standard](https://web.archive.org/web/20150209122542/http://www.isac-net.org/images/stories/documents/Standards/fcs3.1_normativespecification_20090813.pdf) documentation, here are what the particular keyword letters mean: + +:::{.callout-tip title="B"} +Number of bits reserved for parameter number n +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7B` +``` + +::: + +:::{.callout-tip title="E"} +Amplification type for parameter n. +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7E` +``` + +::: + +
+ +--- + +:::{.callout-tip title="N"} +Short Name for parameter n. +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7N` +``` + +::: + +:::{.callout-tip title="R"} +Range for parameter number n. +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7R` +``` + +::: + +
+ +--- + +:::{.callout-tip title="TYPE"} +Detector type for parameter n. +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7TYPE` +``` + +::: + +:::{.callout-tip title="V"} +Detector voltage for parameter n. +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7V` +``` + +::: + +
+ +--- + +While not immediately obvious, understanding what these keywords encoded has proven useful for our core. In our case, we have built an automated [InstrumentQC dashboard](https://umgccfcss.github.io/InstrumentQC/Aurora3L.html) for all the instruments at our core. + +![](images/InstrumentQC.png) + +
+ +--- + +By extracting out from our daily QC bead .fcs files the stored **N (Detector Name)** and **V (Gain/Voltage)** values for all the individual detectors, it allows us to plot Levey-Jennings Plots for our individual instruments, giving us usually around a months warning before an individual laser begins to fail. This helps with scheduling the Field-Service Engineer visit before it starts impacting the actual data. + +![](images/LeveyJennings.png) + +
+ +--- + +While most of the detectors keywords are similar (only changing there individual name and voltage) there are a couple exceptions. + +For the FSC/SSC parameters, instead of Raw_Fluorescence value for Type, we see the corresponding Scatter value get return. This in term is what is used by various commercial softwares to show those axis as linear instead of biexponential when selected. + +![](images/22_FSC.png) + +
+ +--- + +This is similarly the case for the Time parameter, where in addition to Type being set to Time, the range also appears different to Raw/Scatters value. + +![](images/23_Time.png) + + +## Middle Metadata + +Once we are out of the detector keywords, we find the last of the $Metadata associated keywords. + +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[385:398] +Detectors +``` + +Among those of potential interest + +:::{.callout-tip title="Proj"} +Often corresponding to the experiment file name +::: + +::: {.fragment} + +```{r} +DescriptionList$`$PROJ` +``` + +::: + +:::{.callout-tip title="Spillover"} +Where the internal spillover matrix is stored (we will revisit during compensation) +::: + +::: {.fragment} + +```{r} +DescriptionList$`$SPILLOVER` +``` + +::: + + +:::{.callout-tip title="TOT"} +Total events (in this case my downsampled 100 cells) +::: + +::: {.fragment} + +```{r} +DescriptionList$`$TOT` +``` + +::: + +:::{.callout-tip title="Volume"} +Volume amount acquired during acquisition. +::: + +::: {.fragment} + +```{r} +DescriptionList$`$VOL` +``` + +::: + +:::{.callout-tip title="Software"} +Software used and version +::: + +::: {.fragment} + +```{r} +DescriptionList$CREATOR +``` + +::: + +You will notice at this point, the keyword names including a "$" symbol have stopped, so tick marks are no longer required (except when there is a space in the name). The only $ remaining is being used as a selector for a particular item in the list. + +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[390:398] +Detectors +``` + + +:::{.callout-tip title="FILENAME"} +Basically the full file.path to the .fcs file of interest. +::: + +::: {.fragment} + +```{r} +DescriptionList$FILENAME +``` + +::: + + +:::{.callout-tip title="GROUPNAME"} +The Name assigned to the acquisition Group. +::: + +::: {.fragment} + +```{r} +DescriptionList$GROUPNAME +``` + +::: + +## Laser Metadata + +Next up, there is a small stretch of keywords containing the values associated with the individual lasers as far as delays and area scaling factors for a particular day (also useful when [plotted](https://umgccfcss.github.io/InstrumentQC/Aurora5L.html)). + + +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[399:410] +Detectors +``` + + +## Display + +Then there is a stretch matching whether a particular detector needs to be displayed as linear (in the case of time and scatter) or as log (for individual detectors). + +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[412:472] +Detectors +``` + +And a few final keywords with threshold, window scaling and other user selected settings. + +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[473:476] +Detectors +``` + +## flowCore Parameters + +Depending on the arguments selected during `read.FCS()`, we might also encounter additional keywords that are added in by flowCore. For example, we do not see these keywords when "transformation" is set to FALSE. + +```{r} +flowCoreCheck <- read.FCS(filename=firstfile, + transformation = FALSE, truncate_max_range = FALSE) + +flowCoreCheck +``` + +```{r} +#| class-output: "scroll-output" +NoChange <- keyword(flowCoreCheck) +Detectors <- NoChange [476:500] +Detectors +``` + +By contrast, if we had set "transformation" to TRUE: + +```{r} +flowCoreCheck <- read.FCS(filename=firstfile, + transformation = TRUE, truncate_max_range = FALSE) + +flowCoreCheck +``` + +```{r} +#| class-output: "scroll-output" +YesChange <- keyword(flowCoreCheck) +Detectors <- YesChange [476:500] +Detectors +``` + +
+ +--- + +For some flow cytometry R packages, you will notice when opening their exported .fcs outputs in commercial software that these flowCore keywords have ended up integrated. It is likely somewhere in the package code the author forgot to add set transformation to FALSE, which is why we are seeing these flowCore keywords after the fact. + +# Take Away + +Today we broke open an .fcs file and explored how the underlying data is organized and stored once it is brought into R. In the process, we continued to build familiarity with some of the basic R knowledge, going from smaller simpler objects we encountered in week 2 to matrices and data.frames, to complex objects with multiple slots typical of what we encounter in the Bioconductor packages. We will build on these initial observations on the weeks to come. + +In context of our continuing analogy, with each function being a tool, and an R package a toolbox, each tool in the toolbox works on different types of objects. A hammer needs nails, screwdrivers need screws, a paintbrush needs paint and a wall, etc. Object types help define these requirements, so when we use a function, knowing what type can help determine what we provide to it in order for it to work properly and not error out. + +Next week, we will dive into the world of [tidyverse](https://tidyverse.org/), working specifically with these intermediate object types matrices and data.frames. The basic premise is to think of all data as rows and columns, the reasoning behind this approach which can be found [here](https://vita.had.co.nz/papers/tidy-data.html). + +![](images/TakeAway.jpg) + +
+ +--- + +# Additional Resources + +[Data File Standard for Flow Cytometry, Version FCS 3.1](https://pmc.ncbi.nlm.nih.gov/articles/PMC2892967/) + +[R Programming - R Data Types: Vectors and Lists](https://youtu.be/p01ckVx-678?si=BQp6SFTWfZzz2-wI) + +[Base Types vs. Object-Oriented Objects](https://adv-r.hadley.nz/base-types.html) + +
+ +--- + +# Take-home Problems + +:::{.callout-tip title="Problem 1"} +Today's walkthrough focused on a raw spectral flow cytometry file. Within a subfolder in data you will also find an unmixed .fcs file (2025_07_26...). Using what learned to day, investigate it, and see if you can catalog the main differences that occured to the keyword, parameters and exprs. Did any keywords get added, changed, deleted entirely? etc. +::: + +:::{.callout-tip title="Problem 2"} +Today's files were for spectral .fcs files from a Cytek Aurora within a subfolder in data you will also find a conventional flow cytometry file (2025-10_22...). Similarly, explore and see if you find any major differences (beyond the different detector or fluorophore names which will vary based on antibody panel used, etc) +::: + +:::{.callout-tip title="Problem 3"} +If you have access to commercial software, take one of the .fcs files and try to see if you can see similar internal information from within the software. For those without commercial access, try the equivalent process using [Floreada.io](/course/00_Floreada/index.qmd). +::: + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/03_InsideFCSFile/slides.qmd b/course/03_InsideFCSFile/slides.qmd index 45dd6d1..67ece4d 100644 --- a/course/03_InsideFCSFile/slides.qmd +++ b/course/03_InsideFCSFile/slides.qmd @@ -1,1976 +1,1976 @@ ---- -title: "03 - Inside an FCS File" -author: "David Rach" -date: 02-16-2026 -format: - revealjs: - theme: default - slide-number: true - incremental: true -page-layout: full -execute: - echo: true - warning: false - message: false ---- - -![](/images/WebsiteBanner.png) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) -::: - ---- - -# Background - - -::: {.fragment} -::: {.callout-tip title="."} -Welcome to the Week #3! Having subjected everyone to two R-focused weeks, this week will have more of a cytometry-focus as we slice into an .fcs file. - -We will hopefully gather greater understanding of how an .fcs file is structured and what additional kinds of information we can retrieve (while becoming increasingly puzzled why different manufacturers insist on using different keyword names for the exact same things). -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We will also gain additional exposure to more object types in R (vectors, list, matrices and data.frames). - - Continuing the analogy from last week, if every function is the equivalent of a tool in a toolbox, each tool requires certain types of things to do its job properly (hammer ~ nail, screwdriver ~ screws, paintbrush ~ paint, etc.). - - Being able to identify what type/kind of object a particular variable we have created in R is will allow us to pass it to the correct function that will allow us to work with that object type. -::: -::: - ---- - -:::{.callout-important title="Housekeeping"} -We are building off concepts that were covered in [Week #1 (Installing R packages)](/course/01_InstallingRPackages/index.qmd) and especially [Week #2 (File Paths)](/course/02_FilePaths/index.qmd). -For those who are flow cytometry beginners, please see [UChicago Flow](https://youtu.be/gC4brjHbLkk?si=li98x7KlLXUFWGX3) Flow Basics Series for additional context. -::: - - -:::{.callout-tip title="Today's Goal"} -If you find yourself at some point going "I have no idea what is going on", please pause, take a break, and circle back later in the day. Our goal is not to have you memorize how to quickly access 100 archaic keywords, but rather showcase a typical object exploration workflow. - -So don't power through, but rather circle back when you are in an exploring mindset. Consider what kind of information from within an .fcs file you'd like to retrieve, and then explore/navigate your way through the various paths until you find the information that you were looking for. -::: - ---- - -:::{.callout-important title="Housekeeping"} -As we do [every week](/course/02_FilePaths/index.qmd#new-repository), on GitHub, sync your forked-version of the CytometryInR course to bring in the most recent updates. Then within Positron, pull in those changes to your local computer. From there, copy the data folder to a separate project folder you have created. This will prevent any merge issues bringing in new data next week. -::: - ---- - -# Walk Through - ---- - -## Getting Set Up - ---- - -### Set up File Paths - -::: {.fragment} -::: {.callout-tip title="."} -Having copied over the new data to your working project folder (Week 3 or whatever your chosen name), let's identify the file paths between our working directory and the fcs files. If you retained the same project organization structure we had during Week #2, it may look similar to the following: -::: -::: - -::: {.fragment} -```{r} -#| eval: FALSE -#| include: FALSE - -# Please note, this code-chunk is only for use when writing the code. Please switch eval to false and next code blocks eval to true before rendering - -PathToDataFolder <- file.path(getwd(), "course", "03_InsideFCSFile", "data") -``` - -```{r} -#| eval: TRUE -PathToDataFolder <- file.path("data") -``` - -```{r} -PathToDataFolder -``` - -::: - ---- - -### Locate .fcs files - -::: {.fragment} -::: {.callout-tip title="."} -We will now locate our .fcs files. As we saw last week, our computer will need the full file.paths to these individual files, so we will set the `list.files()` "full.names" argument to TRUE. -::: -::: - -::: {.fragment} -```{r} -#| eval: TRUE -fcs_files <- list.files(PathToDataFolder, pattern=".fcs", full.names=TRUE) -fcs_files -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -By contrast, if the "full.names" argument was set to FALSE, we would have retrieved just the file names -::: -::: - -::: {.fragment} -```{r} -list.files(PathToDataFolder, pattern=".fcs", full.names=FALSE) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -This would have been the equivalent of running the `basename` function on the "full.names=TRUE" output. -::: -::: - -::: {.fragment} -```{r} -basename(fcs_files) -``` - -::: - - ---- - -## flowCore - -::: {.fragment} -::: {.callout-tip title="."} -We will be using the `flowCore` package, which is the oldest and most-frequently downloaded flow cytometry package on [Bioconductor](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry). -::: -::: - ---- - -::: {.fragment} - -```{r} -#| include: FALSE -#| warning: FALSE -#| message: FALSE - -# I have attached this code for anyone that is interested in seeing how these plots were made. The content is not part of today's lesson, so if you are just starting off, we will cover the details of data-tidying and creating ggplot objects over the next several weeks. Best, David - -# Load required packages via a library call - -library(dplyr) # CRAN -library(stringr) # CRAN -library(ggplot2) # CRAN -#library(plotly) # Using the :: to access - -# Loading in the dataset contained within the .csv file -BioconductorFlow_path <- file.path(PathToDataFolder, "BioconductorFlow.csv") -BioconductorFlowPackages <- read.csv(BioconductorFlow_path, check.names=FALSE) -BioconductorFlowPackages <- BioconductorFlowPackages |> - arrange(desc(since)) |> mutate(package = factor(package, levels = package)) - -# Newer Base R Pipe : |> -# Older mostly equivalent Magrittr Pipe %>% -``` - ---- - -```{r} -#| echo: FALSE -#| fig-height: 9 - -# Notice the code-chunk eval arguments above dictate the shape of the final rendered plot. - -# Taking the imported dataset and passing it to ggplot2 to create the first plot. - -plot <- ggplot(BioconductorFlowPackages, - aes(x = 0, xend = since, y = package, yend = package)) + - geom_segment(linewidth = 2, color = "steelblue") + - scale_x_continuous(trans = "reverse", - breaks = seq(0, max(BioconductorFlowPackages$since), by = 5)) + - labs( - x = "Years in Bioconductor", - y = NULL, - title = "Bioconductor Flow Cytometry R packages" - ) + - theme_bw() - -# Taking the static plot and making it interactive using the plotly package - -plotly::ggplotly(plot) -``` - -::: - ---- - -::: {.fragment} - -```{r} -#| include: FALSE - -# Retrieving the names of Bioconductor flow cytometry R packages in correct release order. - -HistoricalOrder <- BioconductorFlowPackages |> pull(package) - -# Bringing in 2025 package usage dataset from a .csv file -BioconductorUsage_path <- file.path(PathToDataFolder, "BioconductorDownloads.csv") -BioconductorUsage <- read.csv(BioconductorUsage_path, check.names=FALSE) -BioconductorUsage <- BioconductorUsage |> dplyr::filter(Month %in% "all") - -# Note, dplyr::filter is used due to flowCore also having a filter function, which causes conflicts once it is attached to the local environment. - -# Combining both data.frames for use in the plot - -Dataset <- left_join(BioconductorFlowPackages, BioconductorUsage, by="package") - -# Rearranging the order in which packages are displayed - -Dataset$package <- factor(Dataset$package, levels=HistoricalOrder) -``` - ---- - -```{r} -#| echo: FALSE - -# Generating the 2nd plot with ggplot2 - -plot <- ggplot(Dataset, aes(x = since, y = Nb_of_distinct_IPs)) + - geom_point(aes(color = package), size = 3, alpha = 0.7) + - labs( - x = "Years in Bioconductor", - y = "Number of Yearly Downloads", - title = "", - color = "Package" - ) + - theme_bw() - -# Making it interactive with plotly - -plotly::ggplotly(plot) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -flowCore is also one of the many Bioconductor packages maintained by [Mike Jiang](https://github.com/mikejiang). In many ways (as those who completed the optional take-home problems for Week #1 know) reminiscent of this [xkcd](https://xkcd.com/2347/) comic: -::: -::: - ---- - -![](images/BioconductorXKCD.png) - - ---- - -::: {.fragment} -::: {.callout-tip title="."} -As with all our R packages, we first need to make sure `flowCore` is attached to our local environment via the library call. -::: -::: - -::: {.fragment} -```{r} -library(flowCore) -``` -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The function we will be using today is the `read.FCS()` function. Do you remember how to access the help documentation? -::: -::: - -::: {.fragment} -```{r} -#| code-fold: TRUE -#| eval: FALSE - -# Or when in Positron, hovering over the highlighted function name within the code-chunk - -?flowCore::read.FCS -``` -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -To start, lets select just the first .fcs file. We will do this by indexing the first item within fcs_files via the square brackets []. -::: -::: - -::: {.fragment} -```{r} -firstfile <- fcs_files[1] -firstfile -``` -::: - ---- - -## flowFrame - -::: {.fragment} -::: {.callout-tip title="."} -For `read.FCS()`, it accepts several arguments. The argument "filename" is where we provide our file.path to .fcs file that we wish to load into R. Let's go ahead and do so -::: -::: - -::: {.fragment} - -```{r} -#| eval: FALSE - -read.FCS(filename=firstfile) - -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Please note, if you are doing this with your own .fcs files, you will need to provide two additional arguments, "transformation" = FALSE, and "truncate_max_range" = FALSE for the files to be read in correctly. We will revisit the reasons why in Week #5. -::: -::: - -::: {.fragment} -```{r} -read.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE) -``` -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In this case, we can see the .fcs file has been read into R as a "flowFrame" object. We can also see the file name, as well as details about the number of cells, and number of columns (whether detectors (for raw spectral flow data) or fluorophores (for unmixed spectral flow data)). -::: -::: - ---- - -![](images/00_flowFrame.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Directly below we see what resembles a table. At first glance, the only column with an immediately discernable purpose is the one with the name column, which is listing the detectors present on a [Cytek Aurora](https://bpb-us-w2.wpmucdn.com/voices.uchicago.edu/dist/2/1824/files/2021/10/Aurora-Configuration.png). -::: -::: - ---- - -![](images/01_flowFrameDetectors.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And finally, at the bottom we reach a line that tells us that for this .fcs files, 599 keyword can be found in a description slot. -::: -::: - ---- - -![](images/02_KeywordsFiveNineNine.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -So let's get our bearings, we have loaded in an .fcs file to R, but let's use some of the concepts we covered last week to try to understand a bit about what type or class of object we are working with. From the output, we saw the words flowFrame object, so let's read it back in again, but assign it to an variable/object called flowFrame so that we can use the type-discerning functions we worked with last week on. -::: -::: - -::: {.fragment} -```{r} -flowFrame <- read.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE) -``` -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -As we create this variable, if we have the session tab selected on our right secondary side bar, we see it appear: -::: -::: - ---- - -![](images/03_SessionTab.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If we were to use the type-determining functions we learned last week -::: -::: - -::: {.fragment} -```{r} -#| eval: FALSE -#| include: FALSE -# This is the whole ball game -str(flowFrame) -``` - -```{r} -class(flowFrame) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -flowFrames are a class of object with a structure defined within the `flowCore` package. They are used to work with the data contained within individual .fcs files. Looking again at the right secondary side bar, we can see that it shows up as a ""S4 class flowFrame package flowCore""" with 3 slots, with the words flowFrame adjacent to it. -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} -A perfectly valid first reaction to first reading this is "well how should I know what any of this means?". Powering through this initial discomfort, let's go ahead and click on the dropdown arrow next to the variables name and see if we get any additional clarity on the issue. -::: -::: - ---- - -![](images/04_Slots.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When we do so, three additional drop-downs appear. Based on the previous line that mentioned 3 slots, we could infer that each line corresponds to one of those slots. -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} -What we are encountering with flowFrame is our first example of an S4 object type. These more-complicated object types are quite common for the various [Bioconductor](https://adv-r.hadley.nz/s4.html) affilitated R packages. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -These objects will usually appear with either S4 or S3 in their metadata, and are made up of various simpler object types that are cobbled together within the larger object, usually occupying individual slots. -::: -::: - - -::: {.fragment} -::: {.callout-tip title="."} -What advantage this bundling provides will be something we revisit throughout the course as you encounter more of these S4/S3 objects. -::: -::: - ---- - -### exprs - -::: {.fragment} -::: {.callout-tip title="."} -The first slot within the flowFrame object shows up with the name "exprs". For the exprs object, glancing at it's middle column, we can based on the 100 rows and 61 columns, that it is likely a matrix-style object. We might also recall we saw similar numbers in the printed output when we ran `read.FCS()`earlier. -::: -::: - ---- - -![](images/00_flowFrame.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Which likely means that "exprs" slot is where the MFI data for the individual acquired cells within our .fcs file is being stored. Within Positron, for a matrix object, we can click on the little grid symbol on the far right to open up the table within editor. -::: -::: - ---- - -![](images/05_OpenTable.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If we utilize the scroll bars, we can see that the individual detectors (in the case of uploading a raw spectral fcs file, they would appear as fluorophores for unmixed spectral or conventional fcs files) occupy the individual columns, which are named. The rows are not named, but number 100, matching the number of cells present in the .fcs file. Additionally, on the far left there is a little summary table about the overall data. -::: -::: - ---- - -![](images/06_TableInEditor.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Let's go ahead and assign this matrix to a new variable/object so that we can explore it later. Since flowFrame is an S4 object, it's slots can be individually accessed by adding the @ symbol and the respective slot name. -::: -::: - -::: {.fragment} -```{r} -MFI_Matrix <- flowFrame@exprs -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Alternatively, we can use the Bioconductor helper function `exprs()` to get data held in that slot -::: -::: - -::: {.fragment} -```{r} -MFI_Matrix_Alternate <- exprs(flowFrame) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In the case of the above, this displayed text output to the console would be unwiedly to display all at once. If we wanted to only see the first five rows, we could use the `head()` function, and provide a value of 5. -::: -::: - -::: {.fragment} -```{r} -head(MFI_Matrix, 5) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -This is much more workable, especially on a small laptop screen. We can see that there are names for each column corresponding to detector/fluorophore/metal depending on the .fcs file we are accessing. Lets retrieve these column names using the `colnames()` function. -::: -::: - -::: {.fragment} - -```{r} -ColumnNames <- colnames(MFI_Matrix) -ColumnNames -``` - -::: - -::: {.fragment} -::: {.callout-tip title="."} -Something interesting occurred when this occurred, we can see in addition to the detector names directly above each a "$P#N" pattern appear, with # standing for increasing numbers. If we recall, we saw something similar in the first output column when we first ran `read.FCS()`. -::: -::: - ---- - -![](images/00_flowFrame.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Lets break out the `str()` and `class()` functions from last week and see what we can find out about why this is occuring. -::: -::: - -::: {.fragment} - -```{r} -str(ColumnNames) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In this case we can see that we don't just have a vector (list) similar to what we saw with Fluorophores object last week, because instead of a chr [1:61] we get back a Named chr [1:61] designation. What we see is that in this case, each value has a corresponding index name as well. (ex. $P1N, $P2N, etc.) Let's double check with `class()` function. -::: -::: - -::: {.fragment} - -```{r} -class(ColumnNames) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can see that everything is character, but it doesn't inform us that each index was named. This is one of the reasons it is best when trying to see what type of an object something is, to use multiple functions, to avoid missing some important details. -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} -If we were trying to remove the names, being left with just the values (similar to what we saw with the vector-style list last week), we could use the `unname()` function: -::: -::: - -::: {.fragment} - -```{r} -unname(ColumnNames) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Let's return to the right sidebar to continue our exploration, by clicking on the dropdown arrow for exprs in the side-bar -::: -::: - ---- - -![](images/07_ExprsExpanded.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The output is less user-friendly than what we saw when clicking on the little grid. If we scroll down far enough, we get down as far as [,61], which corresponds to the total number of columns. -::: -::: - ---- - -![](images/08_LessFriendly.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In base R, column order can be defined by placing the corresponding column index number after a comma ",". So for this case, the first column would be designated would be [,1] while the last column would be designated [,61]. -::: -::: - -::: {.fragment} -```{r} -MFI_Matrix[,1] -``` - -::: - ---- - -::: {.fragment} -```{r} -MFI_Matrix[,61] -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -What would happen if used a column index number that didn't exist? Let's check. -::: -::: - -::: {.fragment} -```{r} -#| error: TRUE - -MFI_Matrix[,350] -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We get back an error message telling us the subscript is out of bounds. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -So if columns are specified by a number after the comma (ex. [,1]), how are rows specified? In R, rows would be specified by a number before the comma [1,] -::: -::: - -::: {.fragment} -```{r} -MFI_Matrix[1,] -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And while not the focus of today, we could retrieve individual values from a matrix by specifying both a row and a column index number. So for example, if we wanted the MFI value for the UV1-A detector for the first acquired cell (knowing that UV1-A is the 2nd column): -::: -::: - -::: {.fragment} -```{r} -MFI_Matrix[1,2] -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -From our exploration, this looks to be all the information contained within the "exprs" slot, so let's back up and check on the next slot. -::: -::: - ---- - -### parameters - -::: {.fragment} -::: {.callout-tip title="."} -As we look at the next slot in the flowFrame object, we can see that parameters looks like it is going to be another more complex object, as it is showing up as an AnnotatedDataFrame object (defined by the Biobase R package, and itself contains 4 slots). -::: -::: - ---- - -![](images/09_Parameters.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Having carved our way this far into the heart of an .fcs file, we are not about to call it quits now, so [CHARGE](https://youtu.be/92gP2J0CUjc?t=72) my fellow cytometrist!!! Click that drop-down arrow! -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Having survived our charge into the unknown, the four parameter slots appear to be "varMetadata", "data", "dimLabels" and "._classVersion_". -::: -::: - ---- - -![](images/10_ParameterSlots.png) - ---- - -#### varMetadata - -::: {.fragment} -::: {.callout-tip title="."} -Fortunately for us, both "varMetadata" and "data" at least appear to be table-like objects of a type known as a "data.frame", so lets click on the grid to open in our editor window. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In the case of varMetadata, we seem to have retrieved a column of metadata names. -::: -::: - ---- - -![](images/11_varMetadata.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -These look reminiscent of what we saw at the top of the `read.FCS()` column outputs previously -::: -::: - ---- - -![](images/12_varMetadata2.png) - ---- - -#### data - -::: {.fragment} -::: {.callout-tip title="."} -Clicking on the grid for parameters's data slot will end opening the actual content that was displayed. -::: -::: - ---- - -![](images/13_data.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Let's try to retrieve the data contained within this slot and save it as it's own variable/object within our R session. First, we need to open flowFrame object, then use @ to get inside its parameters slot. Since parameters is also a complex object (AnnotatedDataFrame specifically), we will need to use another @ to get inside its data slot: -::: -::: - -::: {.fragment} -```{r} -ParameterData <- flowFrame@parameters@data - -head(ParameterData, 10) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And similarly, we could access with the Bioconductor helper function `parameters()`, but we would need to specify the accessor for data outside the parenthesis. -::: -::: - -::: {.fragment} -```{r} -ParameterData_Alternate <- parameters(flowFrame)@data -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If we ran the `str()` function, we get the following insight into ParameterData's object type -::: -::: - -::: {.fragment} -```{r} -str(ParameterData) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can see this class of object is a "data.frame". This is one of the more common object types in R, and we will be seeing these extensively throughout the course. We see that each of the columns appears to be designated by a $ followed by the column name, and then type of column (numeric, character, etc). -::: -::: - ---- - -![](images/15_dataframe.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If we are trying to see these columns in R, we notice that data.frame is not like the previous S4 class objets we interacted with, as the @ symbol after doesn't bring up any suggestions -::: -::: - -::: {.fragment} -```{r} -#| eval: FALSE - -ParameterData@ -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -By contrast, adding the $ we saw when using the `str()` function does retrieve the underlying information -::: -::: - -::: {.fragment} -```{r} -#| eval: FALSE -ParameterData$ -``` -::: - ---- - -![](images/15_Suggestions.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -As you become more familiar with R, remembering to check what kind of object you are working with, and how to access the contents will with practice become more familiar to you. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Similar to what we saw with a matrix, we can subset a data.frame based on the column or row index using square brackets []. -::: -::: - -::: {.fragment} -```{r} -ParameterData[,1] -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The individual detectors or fluorophore appear under "name". For now, based on what we know, the $P# appears to be some sort of name being used as an internal consistent reference to the respective. -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} -"desc" is appearing empty for this raw spectral fcs file, but if you were to checked an unmixed file, this would be occupied the marker/ligand name assigned to it during the experiment setup. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -"range", "minRange" and "maxRange" are beyond the scope of today, but are used by both instrument manufacturers and software vendors when setting appropiate scaling for a plot. For the actual details, see the [Flow Cytometry Standard](https://web.archive.org/web/20150209122542/http://www.isac-net.org/images/stories/documents/Standards/fcs3.1_normativespecification_20090813.pdf) documentation. -::: -::: - -::: {.fragment} -::: {.callout-tip title="."} -Having exhausted our options under parameters "varMetadata" and "data" slots, let's continue to the next slot. -::: -::: - ---- - -#### dimLabels - -![](images/16_DimLabels.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In this case, not much is returned. Yey! -::: -::: - -::: {.fragment} -```{r} -flowFrame@parameters@dimLabels -``` - -::: - ---- - -#### classVersion - -::: {.fragment} -::: {.callout-tip title="."} -Continuing on to the last slot ".__classVersion__" -::: -::: - -::: {.fragment} -```{r} -flowFrame@parameters@.__classVersion__ -``` -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Also mercifully short, both of these seem to be more involved in defining the S4 class object, and don't contain anything we need to retrieve today. -::: -::: - ---- - -### Description - -::: {.fragment} -::: {.callout-tip title="."} -At this point, we have explored both "exprs" and "parameter" slots for the flowFrame object we created. Let's tackle the final slot, named description. -::: -::: - -::: {.fragment} -![](images/17_Description.png) -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When doing so, a very large list is opened within the Positron variables window. While we could scroll through it, it might be easier to retrieve certain number of rows via the console to make interpreting this more structured. -::: -::: - ---- - -![](images/18_List.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -To retrieve the list itself, we would need to access the description slot of the flowFrame object. Since it is a slot, we will need to use the @ accessor. -::: -::: - - - - -::: {.fragment} -```{r} -DescriptionList <- flowFrame@description -``` -::: - ---- - -::: {.fragment} -```{r} -#| class-output: "scroll-output" -DescriptionList -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -The returned list is a little too large to reasonably explore. We can attempt to subset using the `head()` function as shown below -::: -::: - -::: {.fragment} -```{r} -head(DescriptionList, 5) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Alternatively, it might be better to subset based on position index -::: -::: - -::: {.fragment} -```{r} -DescriptionList[1:10] -``` -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And just as we saw for exprs and parameters, there is also a Bioconductor helper `keyword()` function to access this same information directly from the flowFrame. -::: -::: - -::: {.fragment} -```{r} -DescriptionList_Alternate <- keyword(flowFrame) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -If we run the `class()` function, we can see that DescriptionList is an actual "list". -::: -::: - -::: {.fragment} -```{r} -class(DescriptionList) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -This is in contrast to the vectors we have previously generated. While these are also list like, they are what are known as as atomic list, which contain values that are all either characters, numerics or logicals. -::: -::: - -::: {.fragment} -```{r} -Fluorophores <- c("BV421", "FITC", "PE", "APC") -class(Fluorophores) -``` - -::: - -::: {.fragment} -```{r} -PanelAntibodyCounts <- c(5, 12, 19, 26, 34, 46, 51) -class(PanelAntibodyCounts) -``` - -::: - -::: {.fragment} -```{r} -SpecimenIndexToKeep <- c(TRUE, TRUE, FALSE, TRUE) -class(SpecimenIndexToKeep) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -A list on the other hand is not restricted to contain objects composed entirely of a certain atomic type. For example, I could include the three previous vectors into a list using the `list()` function. -::: -::: - -::: {.fragment} -```{r} -MyListofVectors <- list(Fluorophores, PanelAntibodyCounts, SpecimenIndexToKeep) -str(MyListofVectors) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We can see that with the Description/Keyword list we retrieved from our flowFrame shares a somewhat similar format. -::: -::: - -::: {.fragment} -```{r} -str(DescriptionList[1:10]) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -But in this case, there are also names present ($BEGINANALYSIS, $BEGINDATA, etc). What if we had tried to provide names to our List of Vectors? Would the format match? -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When we assigned a name to each of the vectors (by providing an equal to = ), we get the same kind of structure format to what we see in Description. -::: -::: - -::: {.fragment} -```{r} -MyNamedListofVectors <- list(FluorophoresNamed=Fluorophores, - PanelAntibodyCountsNamed=PanelAntibodyCounts, - SpecimenIndexToKeepNamed=SpecimenIndexToKeep) - -str(MyNamedListofVectors) -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -We could then subsequently be able to isolate items from that list using the $ operator. -::: -::: - -::: {.fragment} -```{r} -#| eval: FALSE -MyNamedListofVectors$ -``` - -::: - -::: {.fragment} -![](images/20_ListAccess.png) -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Alternatively, we could also access by list index position -::: -::: - -::: {.fragment} -```{r} -MyNamedListofVectors[1] -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Remembering back to the original output from `read.FCS()` we remember that it mentioned 599 keywords being in the description slot, so now we know that this is what was being referenced. -::: -::: - ---- - -![](images/00_flowFrame.png) - ---- - -# Keyword Madness - -::: {.fragment} -::: {.callout-tip title="."} -Rather than go through the keywords individually (in which case we would be here through tomorrow), let's take a birds eye view of the contents of this list. -::: -::: - -::: {.fragment} -```{r} -#| class-output: "scroll-output" -Subset <- DescriptionList[1:18] -Subset -``` - -::: - ---- - -## Early Metadata - -::: {.fragment} -::: {.callout-tip title="."} -Within the initial portion, we are getting back metadata keywords related to where and how the particular file was acquired. Keywords of potential interest include: -::: -::: - -::: {.fragment} -:::{.callout-tip title="Start Time"} -What time was the .fcs file acquired -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$BTIM` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="Cytometer"} -What type of cytometer was the .fcs file acquired on -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$CYT` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="Cytometer Serial Number"} -Manufacturer Serial Number of the Cytometer -::: -::: - -::: {.fragment} -```{r} -DescriptionList$`$CYTSN` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="FCS File Acquisition Date"} -What was the date of acquisition -::: -::: - -::: {.fragment} -```{r} -DescriptionList$`$DATE` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="Acquisition End Time"} -What time was acquisition stopped -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$ETIM` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="File Name"} -Name of the .fcs file -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$FIL` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="Operator"} -Who acquired the .fcs file -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$OP` -``` - -::: - ---- - -## Detector Values - -::: {.fragment} -::: {.callout-tip title="."} -The next major stretch of keywords encode parameter values associated with the individual detectors for at the time of acquisition. -::: -::: - -::: {.fragment} -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[20:384] -Detectors -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Fortunately for all involved, there is a consistently repeating pattern for the keywords corresponding to each detector. We can see that here for $P7B, $P7E, $P7N, $P7R, $P7TYPE, $P7V -::: -::: - ---- - -![](images/21_DetectorIteration.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -When referencing to the [Flow Cytometry Standard](https://web.archive.org/web/20150209122542/http://www.isac-net.org/images/stories/documents/Standards/fcs3.1_normativespecification_20090813.pdf) documentation, here are what the particular keyword letters mean: -::: -::: - ---- - -::: {.fragment} -:::{.callout-tip title="B"} -Number of bits reserved for parameter number n -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7B` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="E"} -Amplification type for parameter n. -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7E` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="N"} -Short Name for parameter n. -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7N` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="R"} -Range for parameter number n. -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7R` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="TYPE"} -Detector type for parameter n. -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7TYPE` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="V"} -Detector voltage for parameter n. -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$P7V` -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -While not immediately obvious, understanding what these keywords encoded has proven useful for our core. In our case, we have built an automated [InstrumentQC dashboard](https://umgccfcss.github.io/InstrumentQC/Aurora3L.html) for all the instruments at our core. -::: -::: - ---- - -![](images/InstrumentQC.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -By extracting out from our daily QC bead .fcs files the stored **N (Detector Name)** and **V (Gain/Voltage)** values for all the individual detectors, it allows us to plot Levey-Jennings Plots for our individual instruments, giving us usually around a months warning before an individual laser begins to fail. This helps with scheduling the Field-Service Engineer visit before it starts impacting the actual data. -::: -::: - ---- - -![](images/LeveyJennings.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -While most of the detectors keywords are similar (only changing there individual name and voltage) there are a couple exceptions. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -For the FSC/SSC parameters, instead of Raw_Fluorescence value for Type, we see the corresponding Scatter value get return. This in term is what is used by various commercial softwares to show those axis as linear instead of biexponential when selected. -::: -::: - ---- - -![](images/22_FSC.png) - ---- - -::: {.fragment} -::: {.callout-tip title="."} -This is similarly the case for the Time parameter, where in addition to Type being set to Time, the range also appears different to Raw/Scatters value. -::: -::: - ---- - -![](images/23_Time.png) - ---- - -## Middle Metadata - -::: {.fragment} -::: {.callout-tip title="."} -Once we are out of the detector keywords, we find the last of the $Metadata associated keywords. -::: -::: - -::: {.fragment} -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[385:398] -Detectors -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Among those of potential interest -::: -::: - -::: {.fragment} -:::{.callout-tip title="Proj"} -Often corresponding to the experiment file name -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$PROJ` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="Spillover"} -Where the internal spillover matrix is stored (we will revisit during compensation) -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$SPILLOVER` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="TOT"} -Total events (in this case my downsampled 100 cells) -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$TOT` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="Volume"} -Volume amount acquired during acquisition. -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$`$VOL` -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="Software"} -Software used and version -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$CREATOR -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -You will notice at this point, the keyword names including a "$" symbol have stopped, so tick marks are no longer required (except when there is a space in the name). The only $ remaining is being used as a selector for a particular item in the list. -::: -::: - -::: {.fragment} -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[390:398] -Detectors -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="FILENAME"} -Basically the full file.path to the .fcs file of interest. -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$FILENAME -``` - -::: - ---- - -::: {.fragment} -:::{.callout-tip title="GROUPNAME"} -The Name assigned to the acquisition Group. -::: -::: - -::: {.fragment} - -```{r} -DescriptionList$GROUPNAME -``` - -::: - ---- - -## Laser Metadata - -::: {.fragment} -::: {.callout-tip title="."} -Next up, there is a small stretch of keywords containing the values associated with the individual lasers as far as delays and area scaling factors for a particular day (also useful when [plotted](https://umgccfcss.github.io/InstrumentQC/Aurora5L.html)). -::: -::: - -::: {.fragment} -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[399:410] -Detectors -``` - -::: - ---- - -## Display - -::: {.fragment} -::: {.callout-tip title="."} -Then there is a stretch matching whether a particular detector needs to be displayed as linear (in the case of time and scatter) or as log (for individual detectors). -::: -::: - -::: {.fragment} -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[412:472] -Detectors -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -And a few final keywords with threshold, window scaling and other user selected settings. -::: -::: - -::: {.fragment} -```{r} -#| class-output: "scroll-output" -Detectors <- DescriptionList[473:476] -Detectors -``` - -::: - ---- - -## flowCore Parameters - -::: {.fragment} -::: {.callout-tip title="."} -Depending on the arguments selected during `read.FCS()`, we might also encounter additional keywords that are added in by flowCore. For example, we do not see these keywords when "transformation" is set to FALSE. -::: -::: - -::: {.fragment} -```{r} -flowCoreCheck <- read.FCS(filename=firstfile, - transformation = FALSE, truncate_max_range = FALSE) - -flowCoreCheck -``` - -::: - ---- - -::: {.fragment} -```{r} -#| class-output: "scroll-output" -NoChange <- keyword(flowCoreCheck) -Detectors <- NoChange [476:500] -Detectors -``` - -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -By contrast, if we had set "transformation" to TRUE: -::: -::: - -::: {.fragment} -```{r} -flowCoreCheck <- read.FCS(filename=firstfile, - transformation = TRUE, truncate_max_range = FALSE) - -flowCoreCheck -``` - -::: - ---- - -::: {.fragment} -```{r} -#| class-output: "scroll-output" -YesChange <- keyword(flowCoreCheck) -Detectors <- YesChange [476:500] -Detectors -``` - -::: ---- - -::: {.fragment} -::: {.callout-tip title="."} -For some flow cytometry R packages, you will notice when opening their exported .fcs outputs in commercial software that these flowCore keywords have ended up integrated. It is likely somewhere in the package code the author forgot to add set transformation to FALSE, which is why we are seeing these flowCore keywords after the fact. -::: -::: - ---- - -# Take Away - -::: {.fragment} -::: {.callout-tip title="."} -Today we broke open an .fcs file and explored how the underlying data is organized and stored once it is brought into R. In the process, we continued to build familiarity with some of the basic R knowledge, going from smaller simpler objects we encountered in week 2 to matrices and data.frames, to complex objects with multiple slots typical of what we encounter in the Bioconductor packages. We will build on these initial observations on the weeks to come. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -In context of our continuing analogy, with each function being a tool, and an R package a toolbox, each tool in the toolbox works on different types of objects. A hammer needs nails, screwdrivers need screws, a paintbrush needs paint and a wall, etc. Object types help define these requirements, so when we use a function, knowing what type can help determine what we provide to it in order for it to work properly and not error out. -::: -::: - ---- - -::: {.fragment} -::: {.callout-tip title="."} -Next week, we will dive into the world of [tidyverse](https://tidyverse.org/), working specifically with these intermediate object types matrices and data.frames. The basic premise is to think of all data as rows and columns, the reasoning behind this approach which can be found [here](https://vita.had.co.nz/papers/tidy-data.html). -::: -::: - ---- - -![](images/TakeAway.jpg) - ---- - -# Additional Resources - -[Data File Standard for Flow Cytometry, Version FCS 3.1](https://pmc.ncbi.nlm.nih.gov/articles/PMC2892967/) - -[R Programming - R Data Types: Vectors and Lists](https://youtu.be/p01ckVx-678?si=BQp6SFTWfZzz2-wI) - -[Base Types vs. Object-Oriented Objects](https://adv-r.hadley.nz/base-types.html) - ---- - -# Take-home Problems - -:::{.callout-tip title="Problem 1"} -Today's walkthrough focused on a raw spectral flow cytometry file. Within a subfolder in data you will also find an unmixed .fcs file (2025_07_26...). Using what learned to day, investigate it, and see if you can catalog the main differences that occured to the keyword, parameters and exprs. Did any keywords get added, changed, deleted entirely? etc. -::: - ---- - -:::{.callout-tip title="Problem 2"} -Today's files were for spectral .fcs files from a Cytek Aurora within a subfolder in data you will also find a conventional flow cytometry file (2025-10_22...). Similarly, explore and see if you find any major differences (beyond the different detector or fluorophore names which will vary based on antibody panel used, etc) -::: - ---- - -:::{.callout-tip title="Problem 3"} -If you have access to commercial software, take one of the .fcs files and try to see if you can see similar internal information from within the software. For those without commercial access, try the equivalent process using [Floreada.io](/course/00_Floreada/index.qmd). -::: - ---- - -![](images/TakeAway.jpg) - -::: {style="text-align: right;"} -[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +--- +title: "03 - Inside an FCS File" +author: "David Rach" +date: 02-16-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +--- + +# Background + + +::: {.fragment} +::: {.callout-tip title="."} +Welcome to the Week #3! Having subjected everyone to two R-focused weeks, this week will have more of a cytometry-focus as we slice into an .fcs file. + +We will hopefully gather greater understanding of how an .fcs file is structured and what additional kinds of information we can retrieve (while becoming increasingly puzzled why different manufacturers insist on using different keyword names for the exact same things). +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will also gain additional exposure to more object types in R (vectors, list, matrices and data.frames). + + Continuing the analogy from last week, if every function is the equivalent of a tool in a toolbox, each tool requires certain types of things to do its job properly (hammer ~ nail, screwdriver ~ screws, paintbrush ~ paint, etc.). + + Being able to identify what type/kind of object a particular variable we have created in R is will allow us to pass it to the correct function that will allow us to work with that object type. +::: +::: + +--- + +:::{.callout-important title="Housekeeping"} +We are building off concepts that were covered in [Week #1 (Installing R packages)](/course/01_InstallingRPackages/index.qmd) and especially [Week #2 (File Paths)](/course/02_FilePaths/index.qmd). +For those who are flow cytometry beginners, please see [UChicago Flow](https://youtu.be/gC4brjHbLkk?si=li98x7KlLXUFWGX3) Flow Basics Series for additional context. +::: + + +:::{.callout-tip title="Today's Goal"} +If you find yourself at some point going "I have no idea what is going on", please pause, take a break, and circle back later in the day. Our goal is not to have you memorize how to quickly access 100 archaic keywords, but rather showcase a typical object exploration workflow. + +So don't power through, but rather circle back when you are in an exploring mindset. Consider what kind of information from within an .fcs file you'd like to retrieve, and then explore/navigate your way through the various paths until you find the information that you were looking for. +::: + +--- + +:::{.callout-important title="Housekeeping"} +As we do [every week](/course/02_FilePaths/index.qmd#new-repository), on GitHub, sync your forked-version of the CytometryInR course to bring in the most recent updates. Then within Positron, pull in those changes to your local computer. From there, copy the data folder to a separate project folder you have created. This will prevent any merge issues bringing in new data next week. +::: + +--- + +# Walk Through + +--- + +## Getting Set Up + +--- + +### Set up File Paths + +::: {.fragment} +::: {.callout-tip title="."} +Having copied over the new data to your working project folder (Week 3 or whatever your chosen name), let's identify the file paths between our working directory and the fcs files. If you retained the same project organization structure we had during Week #2, it may look similar to the following: +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +#| include: FALSE + +# Please note, this code-chunk is only for use when writing the code. Please switch eval to false and next code blocks eval to true before rendering + +PathToDataFolder <- file.path(getwd(), "course", "03_InsideFCSFile", "data") +``` + +```{r} +#| eval: TRUE +PathToDataFolder <- file.path("data") +``` + +```{r} +PathToDataFolder +``` + +::: + +--- + +### Locate .fcs files + +::: {.fragment} +::: {.callout-tip title="."} +We will now locate our .fcs files. As we saw last week, our computer will need the full file.paths to these individual files, so we will set the `list.files()` "full.names" argument to TRUE. +::: +::: + +::: {.fragment} +```{r} +#| eval: TRUE +fcs_files <- list.files(PathToDataFolder, pattern=".fcs", full.names=TRUE) +fcs_files +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +By contrast, if the "full.names" argument was set to FALSE, we would have retrieved just the file names +::: +::: + +::: {.fragment} +```{r} +list.files(PathToDataFolder, pattern=".fcs", full.names=FALSE) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This would have been the equivalent of running the `basename` function on the "full.names=TRUE" output. +::: +::: + +::: {.fragment} +```{r} +basename(fcs_files) +``` + +::: + + +--- + +## flowCore + +::: {.fragment} +::: {.callout-tip title="."} +We will be using the `flowCore` package, which is the oldest and most-frequently downloaded flow cytometry package on [Bioconductor](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry). +::: +::: + +--- + +::: {.fragment} + +```{r} +#| include: FALSE +#| warning: FALSE +#| message: FALSE + +# I have attached this code for anyone that is interested in seeing how these plots were made. The content is not part of today's lesson, so if you are just starting off, we will cover the details of data-tidying and creating ggplot objects over the next several weeks. Best, David + +# Load required packages via a library call + +library(dplyr) # CRAN +library(stringr) # CRAN +library(ggplot2) # CRAN +#library(plotly) # Using the :: to access + +# Loading in the dataset contained within the .csv file +BioconductorFlow_path <- file.path(PathToDataFolder, "BioconductorFlow.csv") +BioconductorFlowPackages <- read.csv(BioconductorFlow_path, check.names=FALSE) +BioconductorFlowPackages <- BioconductorFlowPackages |> + arrange(desc(since)) |> mutate(package = factor(package, levels = package)) + +# Newer Base R Pipe : |> +# Older mostly equivalent Magrittr Pipe %>% +``` + +--- + +```{r} +#| echo: FALSE +#| fig-height: 9 + +# Notice the code-chunk eval arguments above dictate the shape of the final rendered plot. + +# Taking the imported dataset and passing it to ggplot2 to create the first plot. + +plot <- ggplot(BioconductorFlowPackages, + aes(x = 0, xend = since, y = package, yend = package)) + + geom_segment(linewidth = 2, color = "steelblue") + + scale_x_continuous(trans = "reverse", + breaks = seq(0, max(BioconductorFlowPackages$since), by = 5)) + + labs( + x = "Years in Bioconductor", + y = NULL, + title = "Bioconductor Flow Cytometry R packages" + ) + + theme_bw() + +# Taking the static plot and making it interactive using the plotly package + +plotly::ggplotly(plot) +``` + +::: + +--- + +::: {.fragment} + +```{r} +#| include: FALSE + +# Retrieving the names of Bioconductor flow cytometry R packages in correct release order. + +HistoricalOrder <- BioconductorFlowPackages |> pull(package) + +# Bringing in 2025 package usage dataset from a .csv file +BioconductorUsage_path <- file.path(PathToDataFolder, "BioconductorDownloads.csv") +BioconductorUsage <- read.csv(BioconductorUsage_path, check.names=FALSE) +BioconductorUsage <- BioconductorUsage |> dplyr::filter(Month %in% "all") + +# Note, dplyr::filter is used due to flowCore also having a filter function, which causes conflicts once it is attached to the local environment. + +# Combining both data.frames for use in the plot + +Dataset <- left_join(BioconductorFlowPackages, BioconductorUsage, by="package") + +# Rearranging the order in which packages are displayed + +Dataset$package <- factor(Dataset$package, levels=HistoricalOrder) +``` + +--- + +```{r} +#| echo: FALSE + +# Generating the 2nd plot with ggplot2 + +plot <- ggplot(Dataset, aes(x = since, y = Nb_of_distinct_IPs)) + + geom_point(aes(color = package), size = 3, alpha = 0.7) + + labs( + x = "Years in Bioconductor", + y = "Number of Yearly Downloads", + title = "", + color = "Package" + ) + + theme_bw() + +# Making it interactive with plotly + +plotly::ggplotly(plot) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +flowCore is also one of the many Bioconductor packages maintained by [Mike Jiang](https://github.com/mikejiang). In many ways (as those who completed the optional take-home problems for Week #1 know) reminiscent of this [xkcd](https://xkcd.com/2347/) comic: +::: +::: + +--- + +![](images/BioconductorXKCD.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As with all our R packages, we first need to make sure `flowCore` is attached to our local environment via the library call. +::: +::: + +::: {.fragment} +```{r} +library(flowCore) +``` +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The function we will be using today is the `read.FCS()` function. Do you remember how to access the help documentation? +::: +::: + +::: {.fragment} +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# Or when in Positron, hovering over the highlighted function name within the code-chunk + +?flowCore::read.FCS +``` +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To start, lets select just the first .fcs file. We will do this by indexing the first item within fcs_files via the square brackets []. +::: +::: + +::: {.fragment} +```{r} +firstfile <- fcs_files[1] +firstfile +``` +::: + +--- + +## flowFrame + +::: {.fragment} +::: {.callout-tip title="."} +For `read.FCS()`, it accepts several arguments. The argument "filename" is where we provide our file.path to .fcs file that we wish to load into R. Let's go ahead and do so +::: +::: + +::: {.fragment} + +```{r} +#| eval: FALSE + +read.FCS(filename=firstfile) + +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Please note, if you are doing this with your own .fcs files, you will need to provide two additional arguments, "transformation" = FALSE, and "truncate_max_range" = FALSE for the files to be read in correctly. We will revisit the reasons why in Week #5. +::: +::: + +::: {.fragment} +```{r} +read.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE) +``` +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this case, we can see the .fcs file has been read into R as a "flowFrame" object. We can also see the file name, as well as details about the number of cells, and number of columns (whether detectors (for raw spectral flow data) or fluorophores (for unmixed spectral flow data)). +::: +::: + +--- + +![](images/00_flowFrame.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Directly below we see what resembles a table. At first glance, the only column with an immediately discernable purpose is the one with the name column, which is listing the detectors present on a [Cytek Aurora](https://bpb-us-w2.wpmucdn.com/voices.uchicago.edu/dist/2/1824/files/2021/10/Aurora-Configuration.png). +::: +::: + +--- + +![](images/01_flowFrameDetectors.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And finally, at the bottom we reach a line that tells us that for this .fcs files, 599 keyword can be found in a description slot. +::: +::: + +--- + +![](images/02_KeywordsFiveNineNine.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +So let's get our bearings, we have loaded in an .fcs file to R, but let's use some of the concepts we covered last week to try to understand a bit about what type or class of object we are working with. From the output, we saw the words flowFrame object, so let's read it back in again, but assign it to an variable/object called flowFrame so that we can use the type-discerning functions we worked with last week on. +::: +::: + +::: {.fragment} +```{r} +flowFrame <- read.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE) +``` +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As we create this variable, if we have the session tab selected on our right secondary side bar, we see it appear: +::: +::: + +--- + +![](images/03_SessionTab.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we were to use the type-determining functions we learned last week +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +#| include: FALSE +# This is the whole ball game +str(flowFrame) +``` + +```{r} +class(flowFrame) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +flowFrames are a class of object with a structure defined within the `flowCore` package. They are used to work with the data contained within individual .fcs files. Looking again at the right secondary side bar, we can see that it shows up as a ""S4 class flowFrame package flowCore""" with 3 slots, with the words flowFrame adjacent to it. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +A perfectly valid first reaction to first reading this is "well how should I know what any of this means?". Powering through this initial discomfort, let's go ahead and click on the dropdown arrow next to the variables name and see if we get any additional clarity on the issue. +::: +::: + +--- + +![](images/04_Slots.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When we do so, three additional drop-downs appear. Based on the previous line that mentioned 3 slots, we could infer that each line corresponds to one of those slots. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +What we are encountering with flowFrame is our first example of an S4 object type. These more-complicated object types are quite common for the various [Bioconductor](https://adv-r.hadley.nz/s4.html) affilitated R packages. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +These objects will usually appear with either S4 or S3 in their metadata, and are made up of various simpler object types that are cobbled together within the larger object, usually occupying individual slots. +::: +::: + + +::: {.fragment} +::: {.callout-tip title="."} +What advantage this bundling provides will be something we revisit throughout the course as you encounter more of these S4/S3 objects. +::: +::: + +--- + +### exprs + +::: {.fragment} +::: {.callout-tip title="."} +The first slot within the flowFrame object shows up with the name "exprs". For the exprs object, glancing at it's middle column, we can based on the 100 rows and 61 columns, that it is likely a matrix-style object. We might also recall we saw similar numbers in the printed output when we ran `read.FCS()`earlier. +::: +::: + +--- + +![](images/00_flowFrame.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Which likely means that "exprs" slot is where the MFI data for the individual acquired cells within our .fcs file is being stored. Within Positron, for a matrix object, we can click on the little grid symbol on the far right to open up the table within editor. +::: +::: + +--- + +![](images/05_OpenTable.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we utilize the scroll bars, we can see that the individual detectors (in the case of uploading a raw spectral fcs file, they would appear as fluorophores for unmixed spectral or conventional fcs files) occupy the individual columns, which are named. The rows are not named, but number 100, matching the number of cells present in the .fcs file. Additionally, on the far left there is a little summary table about the overall data. +::: +::: + +--- + +![](images/06_TableInEditor.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Let's go ahead and assign this matrix to a new variable/object so that we can explore it later. Since flowFrame is an S4 object, it's slots can be individually accessed by adding the @ symbol and the respective slot name. +::: +::: + +::: {.fragment} +```{r} +MFI_Matrix <- flowFrame@exprs +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, we can use the Bioconductor helper function `exprs()` to get data held in that slot +::: +::: + +::: {.fragment} +```{r} +MFI_Matrix_Alternate <- exprs(flowFrame) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In the case of the above, this displayed text output to the console would be unwiedly to display all at once. If we wanted to only see the first five rows, we could use the `head()` function, and provide a value of 5. +::: +::: + +::: {.fragment} +```{r} +head(MFI_Matrix, 5) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This is much more workable, especially on a small laptop screen. We can see that there are names for each column corresponding to detector/fluorophore/metal depending on the .fcs file we are accessing. Lets retrieve these column names using the `colnames()` function. +::: +::: + +::: {.fragment} + +```{r} +ColumnNames <- colnames(MFI_Matrix) +ColumnNames +``` + +::: + +::: {.fragment} +::: {.callout-tip title="."} +Something interesting occurred when this occurred, we can see in addition to the detector names directly above each a "$P#N" pattern appear, with # standing for increasing numbers. If we recall, we saw something similar in the first output column when we first ran `read.FCS()`. +::: +::: + +--- + +![](images/00_flowFrame.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Lets break out the `str()` and `class()` functions from last week and see what we can find out about why this is occuring. +::: +::: + +::: {.fragment} + +```{r} +str(ColumnNames) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this case we can see that we don't just have a vector (list) similar to what we saw with Fluorophores object last week, because instead of a chr [1:61] we get back a Named chr [1:61] designation. What we see is that in this case, each value has a corresponding index name as well. (ex. $P1N, $P2N, etc.) Let's double check with `class()` function. +::: +::: + +::: {.fragment} + +```{r} +class(ColumnNames) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can see that everything is character, but it doesn't inform us that each index was named. This is one of the reasons it is best when trying to see what type of an object something is, to use multiple functions, to avoid missing some important details. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +If we were trying to remove the names, being left with just the values (similar to what we saw with the vector-style list last week), we could use the `unname()` function: +::: +::: + +::: {.fragment} + +```{r} +unname(ColumnNames) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Let's return to the right sidebar to continue our exploration, by clicking on the dropdown arrow for exprs in the side-bar +::: +::: + +--- + +![](images/07_ExprsExpanded.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The output is less user-friendly than what we saw when clicking on the little grid. If we scroll down far enough, we get down as far as [,61], which corresponds to the total number of columns. +::: +::: + +--- + +![](images/08_LessFriendly.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In base R, column order can be defined by placing the corresponding column index number after a comma ",". So for this case, the first column would be designated would be [,1] while the last column would be designated [,61]. +::: +::: + +::: {.fragment} +```{r} +MFI_Matrix[,1] +``` + +::: + +--- + +::: {.fragment} +```{r} +MFI_Matrix[,61] +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +What would happen if used a column index number that didn't exist? Let's check. +::: +::: + +::: {.fragment} +```{r} +#| error: TRUE + +MFI_Matrix[,350] +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We get back an error message telling us the subscript is out of bounds. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +So if columns are specified by a number after the comma (ex. [,1]), how are rows specified? In R, rows would be specified by a number before the comma [1,] +::: +::: + +::: {.fragment} +```{r} +MFI_Matrix[1,] +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And while not the focus of today, we could retrieve individual values from a matrix by specifying both a row and a column index number. So for example, if we wanted the MFI value for the UV1-A detector for the first acquired cell (knowing that UV1-A is the 2nd column): +::: +::: + +::: {.fragment} +```{r} +MFI_Matrix[1,2] +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +From our exploration, this looks to be all the information contained within the "exprs" slot, so let's back up and check on the next slot. +::: +::: + +--- + +### parameters + +::: {.fragment} +::: {.callout-tip title="."} +As we look at the next slot in the flowFrame object, we can see that parameters looks like it is going to be another more complex object, as it is showing up as an AnnotatedDataFrame object (defined by the Biobase R package, and itself contains 4 slots). +::: +::: + +--- + +![](images/09_Parameters.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Having carved our way this far into the heart of an .fcs file, we are not about to call it quits now, so [CHARGE](https://youtu.be/92gP2J0CUjc?t=72) my fellow cytometrist!!! Click that drop-down arrow! +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Having survived our charge into the unknown, the four parameter slots appear to be "varMetadata", "data", "dimLabels" and "._classVersion_". +::: +::: + +--- + +![](images/10_ParameterSlots.png) + +--- + +#### varMetadata + +::: {.fragment} +::: {.callout-tip title="."} +Fortunately for us, both "varMetadata" and "data" at least appear to be table-like objects of a type known as a "data.frame", so lets click on the grid to open in our editor window. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In the case of varMetadata, we seem to have retrieved a column of metadata names. +::: +::: + +--- + +![](images/11_varMetadata.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +These look reminiscent of what we saw at the top of the `read.FCS()` column outputs previously +::: +::: + +--- + +![](images/12_varMetadata2.png) + +--- + +#### data + +::: {.fragment} +::: {.callout-tip title="."} +Clicking on the grid for parameters's data slot will end opening the actual content that was displayed. +::: +::: + +--- + +![](images/13_data.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Let's try to retrieve the data contained within this slot and save it as it's own variable/object within our R session. First, we need to open flowFrame object, then use @ to get inside its parameters slot. Since parameters is also a complex object (AnnotatedDataFrame specifically), we will need to use another @ to get inside its data slot: +::: +::: + +::: {.fragment} +```{r} +ParameterData <- flowFrame@parameters@data + +head(ParameterData, 10) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And similarly, we could access with the Bioconductor helper function `parameters()`, but we would need to specify the accessor for data outside the parenthesis. +::: +::: + +::: {.fragment} +```{r} +ParameterData_Alternate <- parameters(flowFrame)@data +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we ran the `str()` function, we get the following insight into ParameterData's object type +::: +::: + +::: {.fragment} +```{r} +str(ParameterData) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can see this class of object is a "data.frame". This is one of the more common object types in R, and we will be seeing these extensively throughout the course. We see that each of the columns appears to be designated by a $ followed by the column name, and then type of column (numeric, character, etc). +::: +::: + +--- + +![](images/15_dataframe.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we are trying to see these columns in R, we notice that data.frame is not like the previous S4 class objets we interacted with, as the @ symbol after doesn't bring up any suggestions +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE + +ParameterData@ +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +By contrast, adding the $ we saw when using the `str()` function does retrieve the underlying information +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +ParameterData$ +``` +::: + +--- + +![](images/15_Suggestions.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As you become more familiar with R, remembering to check what kind of object you are working with, and how to access the contents will with practice become more familiar to you. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Similar to what we saw with a matrix, we can subset a data.frame based on the column or row index using square brackets []. +::: +::: + +::: {.fragment} +```{r} +ParameterData[,1] +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The individual detectors or fluorophore appear under "name". For now, based on what we know, the $P# appears to be some sort of name being used as an internal consistent reference to the respective. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +"desc" is appearing empty for this raw spectral fcs file, but if you were to checked an unmixed file, this would be occupied the marker/ligand name assigned to it during the experiment setup. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +"range", "minRange" and "maxRange" are beyond the scope of today, but are used by both instrument manufacturers and software vendors when setting appropiate scaling for a plot. For the actual details, see the [Flow Cytometry Standard](https://web.archive.org/web/20150209122542/http://www.isac-net.org/images/stories/documents/Standards/fcs3.1_normativespecification_20090813.pdf) documentation. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +Having exhausted our options under parameters "varMetadata" and "data" slots, let's continue to the next slot. +::: +::: + +--- + +#### dimLabels + +![](images/16_DimLabels.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this case, not much is returned. Yey! +::: +::: + +::: {.fragment} +```{r} +flowFrame@parameters@dimLabels +``` + +::: + +--- + +#### classVersion + +::: {.fragment} +::: {.callout-tip title="."} +Continuing on to the last slot ".__classVersion__" +::: +::: + +::: {.fragment} +```{r} +flowFrame@parameters@.__classVersion__ +``` +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Also mercifully short, both of these seem to be more involved in defining the S4 class object, and don't contain anything we need to retrieve today. +::: +::: + +--- + +### Description + +::: {.fragment} +::: {.callout-tip title="."} +At this point, we have explored both "exprs" and "parameter" slots for the flowFrame object we created. Let's tackle the final slot, named description. +::: +::: + +::: {.fragment} +![](images/17_Description.png) +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When doing so, a very large list is opened within the Positron variables window. While we could scroll through it, it might be easier to retrieve certain number of rows via the console to make interpreting this more structured. +::: +::: + +--- + +![](images/18_List.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To retrieve the list itself, we would need to access the description slot of the flowFrame object. Since it is a slot, we will need to use the @ accessor. +::: +::: + + + + +::: {.fragment} +```{r} +DescriptionList <- flowFrame@description +``` +::: + +--- + +::: {.fragment} +```{r} +#| class-output: "scroll-output" +DescriptionList +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The returned list is a little too large to reasonably explore. We can attempt to subset using the `head()` function as shown below +::: +::: + +::: {.fragment} +```{r} +head(DescriptionList, 5) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, it might be better to subset based on position index +::: +::: + +::: {.fragment} +```{r} +DescriptionList[1:10] +``` +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And just as we saw for exprs and parameters, there is also a Bioconductor helper `keyword()` function to access this same information directly from the flowFrame. +::: +::: + +::: {.fragment} +```{r} +DescriptionList_Alternate <- keyword(flowFrame) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we run the `class()` function, we can see that DescriptionList is an actual "list". +::: +::: + +::: {.fragment} +```{r} +class(DescriptionList) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This is in contrast to the vectors we have previously generated. While these are also list like, they are what are known as as atomic list, which contain values that are all either characters, numerics or logicals. +::: +::: + +::: {.fragment} +```{r} +Fluorophores <- c("BV421", "FITC", "PE", "APC") +class(Fluorophores) +``` + +::: + +::: {.fragment} +```{r} +PanelAntibodyCounts <- c(5, 12, 19, 26, 34, 46, 51) +class(PanelAntibodyCounts) +``` + +::: + +::: {.fragment} +```{r} +SpecimenIndexToKeep <- c(TRUE, TRUE, FALSE, TRUE) +class(SpecimenIndexToKeep) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +A list on the other hand is not restricted to contain objects composed entirely of a certain atomic type. For example, I could include the three previous vectors into a list using the `list()` function. +::: +::: + +::: {.fragment} +```{r} +MyListofVectors <- list(Fluorophores, PanelAntibodyCounts, SpecimenIndexToKeep) +str(MyListofVectors) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can see that with the Description/Keyword list we retrieved from our flowFrame shares a somewhat similar format. +::: +::: + +::: {.fragment} +```{r} +str(DescriptionList[1:10]) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +But in this case, there are also names present ($BEGINANALYSIS, $BEGINDATA, etc). What if we had tried to provide names to our List of Vectors? Would the format match? +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When we assigned a name to each of the vectors (by providing an equal to = ), we get the same kind of structure format to what we see in Description. +::: +::: + +::: {.fragment} +```{r} +MyNamedListofVectors <- list(FluorophoresNamed=Fluorophores, + PanelAntibodyCountsNamed=PanelAntibodyCounts, + SpecimenIndexToKeepNamed=SpecimenIndexToKeep) + +str(MyNamedListofVectors) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We could then subsequently be able to isolate items from that list using the $ operator. +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +MyNamedListofVectors$ +``` + +::: + +::: {.fragment} +![](images/20_ListAccess.png) +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, we could also access by list index position +::: +::: + +::: {.fragment} +```{r} +MyNamedListofVectors[1] +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Remembering back to the original output from `read.FCS()` we remember that it mentioned 599 keywords being in the description slot, so now we know that this is what was being referenced. +::: +::: + +--- + +![](images/00_flowFrame.png) + +--- + +# Keyword Madness + +::: {.fragment} +::: {.callout-tip title="."} +Rather than go through the keywords individually (in which case we would be here through tomorrow), let's take a birds eye view of the contents of this list. +::: +::: + +::: {.fragment} +```{r} +#| class-output: "scroll-output" +Subset <- DescriptionList[1:18] +Subset +``` + +::: + +--- + +## Early Metadata + +::: {.fragment} +::: {.callout-tip title="."} +Within the initial portion, we are getting back metadata keywords related to where and how the particular file was acquired. Keywords of potential interest include: +::: +::: + +::: {.fragment} +:::{.callout-tip title="Start Time"} +What time was the .fcs file acquired +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$BTIM` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="Cytometer"} +What type of cytometer was the .fcs file acquired on +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$CYT` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="Cytometer Serial Number"} +Manufacturer Serial Number of the Cytometer +::: +::: + +::: {.fragment} +```{r} +DescriptionList$`$CYTSN` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="FCS File Acquisition Date"} +What was the date of acquisition +::: +::: + +::: {.fragment} +```{r} +DescriptionList$`$DATE` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="Acquisition End Time"} +What time was acquisition stopped +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$ETIM` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="File Name"} +Name of the .fcs file +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$FIL` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="Operator"} +Who acquired the .fcs file +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$OP` +``` + +::: + +--- + +## Detector Values + +::: {.fragment} +::: {.callout-tip title="."} +The next major stretch of keywords encode parameter values associated with the individual detectors for at the time of acquisition. +::: +::: + +::: {.fragment} +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[20:384] +Detectors +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Fortunately for all involved, there is a consistently repeating pattern for the keywords corresponding to each detector. We can see that here for $P7B, $P7E, $P7N, $P7R, $P7TYPE, $P7V +::: +::: + +--- + +![](images/21_DetectorIteration.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When referencing to the [Flow Cytometry Standard](https://web.archive.org/web/20150209122542/http://www.isac-net.org/images/stories/documents/Standards/fcs3.1_normativespecification_20090813.pdf) documentation, here are what the particular keyword letters mean: +::: +::: + +--- + +::: {.fragment} +:::{.callout-tip title="B"} +Number of bits reserved for parameter number n +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7B` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="E"} +Amplification type for parameter n. +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7E` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="N"} +Short Name for parameter n. +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7N` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="R"} +Range for parameter number n. +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7R` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="TYPE"} +Detector type for parameter n. +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7TYPE` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="V"} +Detector voltage for parameter n. +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$P7V` +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +While not immediately obvious, understanding what these keywords encoded has proven useful for our core. In our case, we have built an automated [InstrumentQC dashboard](https://umgccfcss.github.io/InstrumentQC/Aurora3L.html) for all the instruments at our core. +::: +::: + +--- + +![](images/InstrumentQC.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +By extracting out from our daily QC bead .fcs files the stored **N (Detector Name)** and **V (Gain/Voltage)** values for all the individual detectors, it allows us to plot Levey-Jennings Plots for our individual instruments, giving us usually around a months warning before an individual laser begins to fail. This helps with scheduling the Field-Service Engineer visit before it starts impacting the actual data. +::: +::: + +--- + +![](images/LeveyJennings.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +While most of the detectors keywords are similar (only changing there individual name and voltage) there are a couple exceptions. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For the FSC/SSC parameters, instead of Raw_Fluorescence value for Type, we see the corresponding Scatter value get return. This in term is what is used by various commercial softwares to show those axis as linear instead of biexponential when selected. +::: +::: + +--- + +![](images/22_FSC.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This is similarly the case for the Time parameter, where in addition to Type being set to Time, the range also appears different to Raw/Scatters value. +::: +::: + +--- + +![](images/23_Time.png) + +--- + +## Middle Metadata + +::: {.fragment} +::: {.callout-tip title="."} +Once we are out of the detector keywords, we find the last of the $Metadata associated keywords. +::: +::: + +::: {.fragment} +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[385:398] +Detectors +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Among those of potential interest +::: +::: + +::: {.fragment} +:::{.callout-tip title="Proj"} +Often corresponding to the experiment file name +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$PROJ` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="Spillover"} +Where the internal spillover matrix is stored (we will revisit during compensation) +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$SPILLOVER` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="TOT"} +Total events (in this case my downsampled 100 cells) +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$TOT` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="Volume"} +Volume amount acquired during acquisition. +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$`$VOL` +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="Software"} +Software used and version +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$CREATOR +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will notice at this point, the keyword names including a "$" symbol have stopped, so tick marks are no longer required (except when there is a space in the name). The only $ remaining is being used as a selector for a particular item in the list. +::: +::: + +::: {.fragment} +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[390:398] +Detectors +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="FILENAME"} +Basically the full file.path to the .fcs file of interest. +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$FILENAME +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="GROUPNAME"} +The Name assigned to the acquisition Group. +::: +::: + +::: {.fragment} + +```{r} +DescriptionList$GROUPNAME +``` + +::: + +--- + +## Laser Metadata + +::: {.fragment} +::: {.callout-tip title="."} +Next up, there is a small stretch of keywords containing the values associated with the individual lasers as far as delays and area scaling factors for a particular day (also useful when [plotted](https://umgccfcss.github.io/InstrumentQC/Aurora5L.html)). +::: +::: + +::: {.fragment} +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[399:410] +Detectors +``` + +::: + +--- + +## Display + +::: {.fragment} +::: {.callout-tip title="."} +Then there is a stretch matching whether a particular detector needs to be displayed as linear (in the case of time and scatter) or as log (for individual detectors). +::: +::: + +::: {.fragment} +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[412:472] +Detectors +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And a few final keywords with threshold, window scaling and other user selected settings. +::: +::: + +::: {.fragment} +```{r} +#| class-output: "scroll-output" +Detectors <- DescriptionList[473:476] +Detectors +``` + +::: + +--- + +## flowCore Parameters + +::: {.fragment} +::: {.callout-tip title="."} +Depending on the arguments selected during `read.FCS()`, we might also encounter additional keywords that are added in by flowCore. For example, we do not see these keywords when "transformation" is set to FALSE. +::: +::: + +::: {.fragment} +```{r} +flowCoreCheck <- read.FCS(filename=firstfile, + transformation = FALSE, truncate_max_range = FALSE) + +flowCoreCheck +``` + +::: + +--- + +::: {.fragment} +```{r} +#| class-output: "scroll-output" +NoChange <- keyword(flowCoreCheck) +Detectors <- NoChange [476:500] +Detectors +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +By contrast, if we had set "transformation" to TRUE: +::: +::: + +::: {.fragment} +```{r} +flowCoreCheck <- read.FCS(filename=firstfile, + transformation = TRUE, truncate_max_range = FALSE) + +flowCoreCheck +``` + +::: + +--- + +::: {.fragment} +```{r} +#| class-output: "scroll-output" +YesChange <- keyword(flowCoreCheck) +Detectors <- YesChange [476:500] +Detectors +``` + +::: +--- + +::: {.fragment} +::: {.callout-tip title="."} +For some flow cytometry R packages, you will notice when opening their exported .fcs outputs in commercial software that these flowCore keywords have ended up integrated. It is likely somewhere in the package code the author forgot to add set transformation to FALSE, which is why we are seeing these flowCore keywords after the fact. +::: +::: + +--- + +# Take Away + +::: {.fragment} +::: {.callout-tip title="."} +Today we broke open an .fcs file and explored how the underlying data is organized and stored once it is brought into R. In the process, we continued to build familiarity with some of the basic R knowledge, going from smaller simpler objects we encountered in week 2 to matrices and data.frames, to complex objects with multiple slots typical of what we encounter in the Bioconductor packages. We will build on these initial observations on the weeks to come. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In context of our continuing analogy, with each function being a tool, and an R package a toolbox, each tool in the toolbox works on different types of objects. A hammer needs nails, screwdrivers need screws, a paintbrush needs paint and a wall, etc. Object types help define these requirements, so when we use a function, knowing what type can help determine what we provide to it in order for it to work properly and not error out. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next week, we will dive into the world of [tidyverse](https://tidyverse.org/), working specifically with these intermediate object types matrices and data.frames. The basic premise is to think of all data as rows and columns, the reasoning behind this approach which can be found [here](https://vita.had.co.nz/papers/tidy-data.html). +::: +::: + +--- + +![](images/TakeAway.jpg) + +--- + +# Additional Resources + +[Data File Standard for Flow Cytometry, Version FCS 3.1](https://pmc.ncbi.nlm.nih.gov/articles/PMC2892967/) + +[R Programming - R Data Types: Vectors and Lists](https://youtu.be/p01ckVx-678?si=BQp6SFTWfZzz2-wI) + +[Base Types vs. Object-Oriented Objects](https://adv-r.hadley.nz/base-types.html) + +--- + +# Take-home Problems + +:::{.callout-tip title="Problem 1"} +Today's walkthrough focused on a raw spectral flow cytometry file. Within a subfolder in data you will also find an unmixed .fcs file (2025_07_26...). Using what learned to day, investigate it, and see if you can catalog the main differences that occured to the keyword, parameters and exprs. Did any keywords get added, changed, deleted entirely? etc. +::: + +--- + +:::{.callout-tip title="Problem 2"} +Today's files were for spectral .fcs files from a Cytek Aurora within a subfolder in data you will also find a conventional flow cytometry file (2025-10_22...). Similarly, explore and see if you find any major differences (beyond the different detector or fluorophore names which will vary based on antibody panel used, etc) +::: + +--- + +:::{.callout-tip title="Problem 3"} +If you have access to commercial software, take one of the .fcs files and try to see if you can see similar internal information from within the software. For those without commercial access, try the equivalent process using [Floreada.io](/course/00_Floreada/index.qmd). +::: + +--- + +![](images/TakeAway.jpg) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) ::: \ No newline at end of file diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/BonusContent.qmd b/course/04_IntroToTidyverse/homeworks/claude-chew/BonusContent.qmd new file mode 100644 index 0000000..2459223 --- /dev/null +++ b/course/04_IntroToTidyverse/homeworks/claude-chew/BonusContent.qmd @@ -0,0 +1,88 @@ +--- +title: "Bonus Content" +author: "David Rach" +date: 02-23-2026 +format: html +toc: true +toc-depth: 5 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +```{r} +thefilepath <- file.path("data", "Dataset.csv") + +thefilepath +``` + +```{r} +Data <- read.csv(file=thefilepath, check.names=FALSE) +colnames(Data) +``` + +## Pull + +## Case-When + +Case-when is an useful function, but may be a bit much to try to teach in the main segment. Basically, when the condition on the left side of the ~ is fulfilled, it will execute what is being specified on the right hand side. + +In turn, we can combine these together by adding a ",". I tend to use this mutate str_detect case_when combination when encountering messy data out in the while where I need to selectively change particular cell values in a consistent reproducible manner + +# Quasiquosure + +```{r} +library(dplyr) +DateColumn <- select(Data, Date) +DateColumn +``` + + +## Selecting Columns (Base R) + +As we saw [last week](/course/03_InsideFCSFile/index.qmd), there are multiple ways to select values from particular columns in base R. If we had wanted to retrieve the "Date" column, why not first identify its index position, and use [,] to extract the underlying data? + +```{r} +colnames(Data) +``` + +```{r} +colnames(Data)[4] +``` + +```{r} +DataColumn <- Data[,4] # Column specified after the , +DataColumn +``` + +However, looking at the output, we see this looks like the values, not a column. Our suspicions are confirmed when running DataColumn + +```{r} +str(DataColumn) +``` + +This is similarly the case when we use the $ accessor. + +```{r} +DataColumn <- Data$Date +str(DataColumn) +``` + +```{r} +head(DataColumn, 3) +``` + +By contrast, when selecting two columns, the structure is maintained. + +```{r} +TwoColumns <- Data[,4:5] +``` + +Why is the data.frame column structure lost in base R when isolating a single data.frame column? And who thought to make it that convoluted? If we were an R course in early 2010s, we might go into an explanation, but fortunately, we don't need to understand why, we have the `dplyr` R package to rescue us. + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +::: \ No newline at end of file diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/Week4_Classwork.qmd b/course/04_IntroToTidyverse/homeworks/claude-chew/Week4_Classwork.qmd new file mode 100644 index 0000000..712b8ec --- /dev/null +++ b/course/04_IntroToTidyverse/homeworks/claude-chew/Week4_Classwork.qmd @@ -0,0 +1,101 @@ +# Week 4 Classwork + +# read.csv +```{r} +library(tidyverse) +thefilepath <- file.path("data","Dataset.csv") +thefilepath + +Data <- read.csv(file=thefilepath, check.names=FALSE) +colnames(Data) + +Data_Alternative <- read.csv(thefilepath, check.names=TRUE) +colnames(Data_Alternative) + +head(Data,3) +view(Data) +class(Data) + +library(dplyr) +glimpse(Data) + +dim(Data) + +is.character(Data$bid) +is.numeric(Data$bid) +is.character(Data$Tcells_count) +is.numeric(Data$`CD8-`) + +DateColumn <- select(Data,"Date") +DateColumn + +Data |> select("Date") +Data |> select("Date") |> nrow() +Data |> select(Date) |> head(5) + +Subset <- Data |> select(bid, timepoint, Condition, Tcells, `CD8+`, `CD4+`, timepoint, Condition) +head(Subset, 5) + +Data |> relocate(Tcells, .after=bid) |> head(5) +Data |> relocate(Tcells, Monocytes, .after=bid) |> head(5) +Data |> relocate(Tcells, .before=bid) |> head(5) +Data |> relocate(Tcells, .before=1) |> head(5) + +colnames(Subset) +colnames(Subset)[3] +colnames(Subset)[3] <- "CD8Positive" +colnames(Subset) + +Renamed <- Subset |> rename(CD4_Positive = `CD4+`) +colnames (Renamed) + +Renamed <- Subset |> rename(specimen = `bid`, CD4_Positive=`CD4+`) +colnames(Renamed) + +Data |> pull(Date) |> head(10) +Data |> pull(Date) |> unique() + +Data |> pull(Condition) |> unique() + +Data |> pull(Condition) |> unique() + +PPDOnly <- Data |> filter(Condition == "PPD") +head(PPDOnly,5) + +Data |> filter(Condition %in% "PPD") |> head(10) + +Data |> filter(Condition %in% c("PPD", "SEB")) |> head(10) + +TheseConditions <- c("PPD", "SEB") +Data |> filter(Condition %in% TheseConditions) |> head(10) + +IsThisASpectralInstrument <- TRUE +!IsThisASpectralInstrument + +Subset <- Data |> filter(!Condition %in% "SEB") +Subset |> pull(Condition) |> unique() + +Subset <- Data |> select(!timepoint) +Subset[1:3] + +TidyData <- Data |> filter(Condition %in% "Ctrl") |> filter(timepoint %in% "0") |> select(bid, timepoint, Condition, Date, Tcells_count, CD45_count) |> rename(specimen=bid, condition=Condition) |> relocate(Date, .after=specimen) +TidyData + +TidyData <- TidyData |> mutate(Tcells_ProportionCD45 = Tcells_count / CD45_count) +TidyData + +TidyData <- TidyData |> mutate(Tcells_rounded = round(Tcells_ProportionCD45,2)) +TidyData + +# arrange +TidyData <- TidyData |> arrange(desc(Tcells_rounded)) +TidyData + +TidyData |> filter(Tcells_rounded >0.3) +TidyData |> filter(Tcells_rounded >0.3) |> pull(specimen) + +NewName <- paste0("MyNewDataset", ".csv") +StorageLocation <- file.path("data", NewName) +StorageLocation +NewName +``` \ No newline at end of file diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/Week4_Homework.qmd b/course/04_IntroToTidyverse/homeworks/claude-chew/Week4_Homework.qmd new file mode 100644 index 0000000..4b5094d --- /dev/null +++ b/course/04_IntroToTidyverse/homeworks/claude-chew/Week4_Homework.qmd @@ -0,0 +1,70 @@ +# Problem 1 +Taking a dataset (either todays or one of your own), work through the column-operating functions (select(), rename(), and relocate()). Once this is done, filter() by conditions from two separate columns, arrange in an order that makes sense, and export this “tidy” data as a .csv file. + +```{r} +library(tidyverse) +thefilepath <- file.path("data","Dataset.csv") +thefilepath + +Data <- read.csv(file=thefilepath, check.names=FALSE) +colnames(Data) + +Data |> select(ptype) +Data + +Data |> relocate(ptype, .before=bid) |> head(5) +Renamed <- Subset |> rename(phenotype = `ptype`) +colnames (Renamed) + +Renamed <- Subset |> rename(specimen = `bid`, CD4_Positive=`CD4+`) +colnames(Renamed) + +Renamed |> filter(phenotype %in% "HEU-hi") |> head(10) + +TidyData <- Renamed |> filter(phenotype %in% "HEU-hi") |> filter(infant_sex %in% "Male") +TidyData + +# arrange +TidyData <- TidyData |> arrange(desc(CD45_count)) +TidyData + +tidy <- paste0("tidy", ".csv") +StorageLocation <- file.path("data", tidy) +StorageLocation +tidy +write.csv(TidyData, StorageLocation) +``` + +# Problem 2 +We used the mutate() function to create new columns, but it can also be used to modify existing ones. Various numeric columns are showing way to many significant digits. As was shown, use round() to round all these proportion columns, but use mutate to overwrite the existing column. Export this as it’s own .csv file. + +```{r} +colnames(Data) +Rounded <- Data |> mutate(CD45 = round(CD45,2)) |> mutate(NotMonocytes = round(NotMonocytes,2)) |> mutate(nonDebris = round(nonDebris,2)) |> mutate(lymphocytes = round(lymphocytes,2)) |> mutate(live = round(live,2)) |> mutate(`Dump+` = round(`Dump+`,2)) |> mutate(`Dump-` = round(`Dump-`,2)) |> mutate(Tcells = round(Tcells,2)) |> mutate(`Vd2+` = round(`Vd2+`,2)) |> mutate(`Vd2-`= round(`Vd2-`,2)) |> mutate(`Va7.2+` = round(`Va7.2+`,2)) |> mutate(`Va7.2-` = round(`Va7.2-`,2)) |> mutate(`CD4+`= round(`CD4+`,2)) |> mutate(`CD4-` = round(`CD4-`,2)) |> mutate(`CD8+`= round(`CD8+`,2)) |> mutate(`CD8-` = round(`CD8-`,2)) |> mutate(Monocytes = round(Monocytes,2)) |> mutate(Debris = round(Debris, 2)) + +Rounded + +rounded <- paste0("rounded", ".csv") +StorageLocation <- file.path("data", rounded) +StorageLocation +rounded +write.csv(Rounded, StorageLocation) +``` + +# Problem 3 +We can also use mutate() to combine columns. For our dataset, “bid”, “timepoint”, “Condition” are separate columns that originally were all part of the filename for the individual .fcs file. Try to figure out a way to combine them back together using paste0(), and save the new column as “filename”. Once this is done, pull() the contents of this column, and using try to determine whether there were any duplicates (think innovative ways of using !, length() and unique()) + +```{r} +combined <- Data |> mutate(filename = paste(bid, timepoint, Condition)) +combined + +unique_filenames <- combined |> + dplyr::pull(filename) |> + unique() +unique_filenames + +length(unique(unique_filenames)) < length(unique_filenames) +any(duplicated(unique_filenames)) +unique_filenames[duplicated(unique_filenames)] + +``` \ No newline at end of file diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/data/Dataset.csv b/course/04_IntroToTidyverse/homeworks/claude-chew/data/Dataset.csv new file mode 100644 index 0000000..a7ac736 --- /dev/null +++ b/course/04_IntroToTidyverse/homeworks/claude-chew/data/Dataset.csv @@ -0,0 +1,197 @@ +bid,timepoint,Condition,Date,infant_sex,ptype,root,singletsFSC,singletsSSC,singletsSSCB,CD45,NotMonocytes,nonDebris,lymphocytes,live,Dump+,Dump-,Tcells,Vd2+,Vd2-,Va7.2+,Va7.2-,CD4+,CD4-,CD8+,CD8-,Tcells_count,lymphocytes_count,Monocytes,Debris,CD45_count +INF0052,0,Ctrl,2025-07-26,Male,HEU-hi,2098368,1894070,1666179,1537396,0.595294250798103,0.882034914658278,0.862764872929831,0.642013848293767,0.902058127245466,0.210909963527936,0.69114816371753,0.280426432119924,0.00812036098585309,0.991879639014147,0.0144807035218576,0.977398935492289,0.63411644039303,0.343282495099259,0.273482590989919,0.0697999041093396,164771,587573,0.117965085341722,0.137235127070169,915203 +INF0100,0,Ctrl,2025-07-26,Male,HEU-lo,2020184,1791890,1697083,1579098,0.91067622148847,0.905225628925897,0.860266041374169,0.214584780608701,0.890898072803751,0.06252774780205,0.828370325001701,0.6748297864756,0.00726562012283844,0.992734379877162,0.0157749914762223,0.976959388400939,0.611911199043416,0.365048189357523,0.335769613092523,0.0292785762650006,208241,308583,0.0947743710741026,0.139733958625831,1438047 +INF0100,4,Ctrl,2025-07-26,Male,HEU-lo,1155040,1033320,875465,845446,0.970576476794497,0.984540014867714,0.957879279037742,0.740311003326956,0.875766489924721,0.200238033703334,0.675528456221388,0.611912879006119,0.00465131294001178,0.995348687059988,0.0157940186644356,0.979554668395553,0.663962143854429,0.315592524541123,0.286210430885364,0.0293820936557598,371723,607477,0.0154599851322861,0.0421207209622579,820570 +INF0100,9,Ctrl,2025-07-26,Male,HEU-lo,358624,328624,289327,276289,0.981957298336163,0.985507032701324,0.941261463155722,0.651158847639548,0.915324178374523,0.21469246357451,0.700631714800014,0.631443094723257,0.0113489672977625,0.988651032702238,0.0170234509466437,0.971627581755594,0.437894434882387,0.533733146873207,0.486123063683305,0.0476100831899025,111552,176662,0.014492967298676,0.058738536844278,271304 +INF0179,0,Ctrl,2025-07-26,Male,HU,1362216,1206309,1032946,982736,0.957259121473112,0.955627154569894,0.840783729283442,0.705478600197931,0.895214015462574,0.338318765284397,0.556895250178177,0.439643676723417,0.00475363034097958,0.99524636965902,0.0133218176895369,0.981924551969484,0.739256349883644,0.24266820208584,0.195063353177255,0.0476048489085843,291777,663667,0.0443728454301061,0.159216270716558,940733 +INF0179,4,Ctrl,2025-07-26,Male,HU,1044808,917398,735579,685592,0.985800592772378,0.962289360027343,0.949924318309938,0.755677606357558,0.967305621365496,0.369473107121179,0.597832514244317,0.532316488164001,0.00516055467686762,0.994839445323132,0.0124618383786368,0.982377606944495,0.587626439106926,0.394751167837569,0.357137602530621,0.0376135653069482,271870,510730,0.0377106399726569,0.0500756816900616,675857 +INF0179,9,Ctrl,2025-07-26,Male,HU,1434840,1265022,988445,940454,0.98001603480872,0.980521016426882,0.965775882646529,0.7879673632359,0.929742040488104,0.238631137450808,0.691110903037296,0.671869277013871,0.00263148726167518,0.997368512738325,0.0135632264001295,0.983805286338195,0.699414063700847,0.284391222637349,0.258078399465505,0.0263128231718439,487937,726238,0.0194789835731181,0.0342241173534709,921660 +INF0186,4,Ctrl,2025-07-26,Female,HEU-hi,972056,875707,767323,718000,0.977238161559889,0.949066281673239,0.9189703801145,0.642831183897545,0.875651539639993,0.325167887160318,0.550483652479675,0.489159666287549,0.00930047046239474,0.990699529537605,0.0387700898320295,0.951929439705576,0.572472964275678,0.379456475429897,0.355552634680058,0.0239038407498391,220634,451047,0.0509337183267607,0.0810296198854996,701657 +INF0186,9,Ctrl,2025-07-26,Female,HEU-hi,1521928,1359574,1175755,1097478,0.972123359192622,0.95816977290877,0.918676257212593,0.666392972431867,0.874952880877231,0.228757011606776,0.646195869270455,0.584933976966485,0.0179408320448605,0.982059167955139,0.0367713716164062,0.945287796338733,0.511920878550113,0.43336691778862,0.413879918339277,0.0194869994493432,415867,710964,0.0418302270912302,0.0813237427874071,1066884 +INF0052,0,PPD,2025-07-26,Male,HEU-hi,2363512,2136616,1875394,1732620,0.587383846429107,0.86198368302262,0.84296849897761,0.640804431111718,0.900925393503078,0.207432282202851,0.693493111300228,0.28356755679248,0.00740820851132861,0.992591791488671,0.015070567241659,0.977521224247012,0.634034499540367,0.343486724706646,0.274411939652842,0.0690747850538041,184930,652155,0.13801631697738,0.15703150102239,1017713 +INF0100,0,PPD,2025-07-26,Male,HEU-lo,2049112,1821676,1717636,1597085,0.906308054987681,0.925196086085125,0.877188934202263,0.217428431083332,0.892967332555915,0.0618142648792407,0.831153067676675,0.67357975578059,0.00713723011316732,0.992862769886833,0.0167180062928387,0.976144763593994,0.61457070480737,0.361574058786624,0.331227858312066,0.0303462004745574,211987,314717,0.0748039139148752,0.122811065797737,1447451 +INF0100,4,PPD,2025-07-26,Male,HEU-lo,1063496,946587,796056,767297,0.970989069421619,0.984871892268438,0.955604889421599,0.731350255088002,0.878230739443147,0.207272019864815,0.670958719578332,0.598987305531646,0.00525464338895391,0.994745356611046,0.0160978987554308,0.978647457855615,0.655948011201735,0.32269944665388,0.291208353504219,0.0314910931496608,326378,544883,0.0151281077315624,0.0443951105784008,745037 +INF0100,9,PPD,2025-07-26,Male,HEU-lo,788368,714198,626387,600011,0.982280324860711,0.98421389292798,0.812304137066302,0.622322817745458,0.95666386756238,0.231645873320537,0.725017994241843,0.648940520851509,0.0119359216203612,0.988064078379639,0.0185529848206671,0.969511093558972,0.430688888795526,0.538822204763445,0.490855848853673,0.0479663559097727,238021,366784,0.0157861070720199,0.187695862933698,589379 +INF0179,0,PPD,2025-07-26,Male,HU,1380336,1242311,1047081,1000877,0.947027456920281,0.957568538747365,0.913443785883539,0.699650158568056,0.885689771385574,0.331861109309995,0.55382866207558,0.444153752663348,0.00438297193336253,0.995617028066637,0.0129723747152426,0.982644653351395,0.749919368254518,0.232725285096877,0.185089747376498,0.0476355377203793,294549,663169,0.0424314612526349,0.0865562141164605,947858 +INF0179,4,PPD,2025-07-26,Male,HU,1240984,1089933,868877,814909,0.985594710575046,0.954141713460413,0.940082423397288,0.730307406900158,0.960259887718413,0.343572109294685,0.616687778423727,0.565465484408271,0.00432042932947419,0.995679570670526,0.012668837433671,0.983010733236855,0.631877110467921,0.351133622768934,0.317746020260492,0.0333876025084419,331680,586561,0.0458582865395869,0.0599175766027118,803170 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+INF0186,9,PPD,2025-07-26,Female,HEU-hi,1425416,1259825,1089955,1014266,0.977148992473375,0.955257297780522,0.913761528984783,0.633243835821001,0.879303888935805,0.238632506959039,0.640671381976766,0.581861724248368,0.0182240393014894,0.981775960698511,0.0373818723523113,0.944394088346199,0.503380552444431,0.441013535901768,0.42133814561158,0.019675390290188,365177,627601,0.0447427022194777,0.0862384710152166,991089 +INF0052,0,SEB,2025-07-26,Male,HEU-hi,2523776,2282292,2041563,1889418,0.578359050247219,0.887807226093147,0.867014958426446,0.67185626879412,0.911565163264,0.233447156619843,0.678118006644156,0.274166109354803,0.00922563305131479,0.990774366948685,0.00842081207430187,0.982353554874383,0.608325425884434,0.37402812898995,0.281175634790126,0.0928524941998241,201287,734179,0.112192773906853,0.132985041573554,1092762 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+INF0179,0,SEB,2025-07-26,Male,HU,783096,710001,604070,579147,0.966198564440462,0.97132088689371,0.892646330849883,0.779109353415384,0.925393435741696,0.34958379877376,0.575809636967936,0.480378102012308,0.00410640360217544,0.995893596397825,0.00684718926223207,0.989046407135592,0.725620616056038,0.263425791079554,0.185747914567706,0.0776778765118489,209429,435967,0.0286791131062903,0.107353669150117,559571 +INF0179,4,SEB,2025-07-26,Male,HU,985280,860127,686367,640888,0.984159478723271,0.951545496055402,0.933428565992745,0.757827363587935,0.925535943295766,0.332859124373155,0.592676818922611,0.519413626673417,0.00457156206449326,0.995428437935507,0.00662171632953914,0.988806721605968,0.56142407179165,0.427382649814318,0.377611026527143,0.0497716232871747,248274,477989,0.048454503944598,0.0665714340072551,630736 +INF0179,9,SEB,2025-07-26,Male,HU,1111728,981610,783127,748455,0.984322370750413,0.984891159611305,0.974006442058798,0.818738708412004,0.935493764734359,0.263124562735625,0.672369201998733,0.651935899943964,0.00303888758913223,0.996961112410868,0.00824949902857317,0.988711613382295,0.696706303593771,0.292005309788524,0.256265957338596,0.0357393524499283,393236,603182,0.0151088403886953,0.0259935579412016,736721 +INF0186,4,SEB,2025-07-26,Female,HEU-hi,492984,443892,386199,365672,0.980110590912074,0.977871032006228,0.943936785537906,0.6789695283748,0.860509077758874,0.334175769082197,0.526333308676677,0.470724330366316,0.00879115123049927,0.991208848769501,0.0126410992867557,0.978567749482745,0.504692397007342,0.473875352475403,0.445432879080203,0.0284424733952002,114547,243342,0.0221289679937723,0.0560632144620939,358399 +INF0186,9,SEB,2025-07-26,Female,HEU-hi,1226128,1088491,957607,891839,0.9712649928967,0.956045402280273,0.910587708320827,0.60486116562689,0.868179059354351,0.229586325099535,0.638592734254816,0.574161446583374,0.0188780852655198,0.98112191473448,0.00923128064489321,0.971890634089587,0.483639990027425,0.488250644062162,0.460942408376963,0.027308235685199,300825,523938,0.0439545977197268,0.0894122916791732,866212 +INF0134,0,Ctrl,2025-07-29,Female,HEU-lo,1205504,1088093,965389,876164,0.787154003131834,0.798904123095483,0.783886926614816,0.577284116019696,0.882294876914846,0.15782427745084,0.724470599464006,0.321159193146112,0.00979932116434392,0.990200678835656,0.0251826130480347,0.965018065787621,0.698582891464502,0.26643517432312,0.225141945474168,0.0412932288489512,127866,398139,0.201095876904517,0.216113073385184,689676 +INF0134,4,Ctrl,2025-07-29,Female,HEU-lo,1277824,1143114,940824,904464,0.981203231969432,0.979719717892464,0.962388291117489,0.775382184947429,0.939878481027374,0.321119916061518,0.618758564965856,0.511173147823863,0.00979673063255153,0.990203269367449,0.0261066098081023,0.964096659559346,0.636952380952381,0.327144278606965,0.275565031982942,0.0515792466240227,351750,688123,0.0202802821075357,0.0376117088825112,887463 +INF0134,9,Ctrl,2025-07-29,Female,HEU-lo,424520,386914,358089,331672,0.95725897875009,0.970383878852017,0.900017638017487,0.427759719807494,0.822040762230142,0.119105822754985,0.702934939475157,0.535733219450417,0.029535864978903,0.970464135021097,0.0286699927156778,0.941794142305419,0.461001388144422,0.480792754160997,0.420387855797908,0.0604048983630891,72759,135812,0.029616121147983,0.0999823619825132,317496 +INF0148,0,Ctrl,2025-07-29,Female,HU,2034128,1833204,1602246,1509990,0.671517692170147,0.91727885520989,0.899144464661706,0.647882365123744,0.876630088150722,0.220344839658844,0.656285248491878,0.356705224045313,0.00385772505174216,0.996142274948258,0.0201335694625216,0.976008705485736,0.668798941686048,0.307209763799689,0.267719290758956,0.0394904730407323,234335,656943,0.0827211447901103,0.100855535338294,1013985 +INF0148,9,Ctrl,2025-07-29,Female,HU,872400,793908,670148,623296,0.982887745148373,0.981657770595629,0.948915332256011,0.610627948353819,0.969135686962194,0.210789411075974,0.75834627588622,0.728201043067291,0.0133988223719954,0.986601177628005,0.0208287446955347,0.96577243293247,0.550636535835426,0.415135897097044,0.362616184309061,0.0525197127879829,272412,374089,0.0183422294043714,0.051084667743989,612630 +INF0191,0,Ctrl,2025-07-29,Female,HEU-hi,1997680,1808121,1593734,1482293,0.482659636117826,0.866839147213684,0.851001407519537,0.578498916056206,0.822556133013436,0.201008497570569,0.621547635442867,0.134772387365512,0.035317318035138,0.964682681964862,0.0205091430620294,0.944173538902833,0.455557547508067,0.488615991394765,0.379221943348871,0.109394048045895,55780,413883,0.133160852786316,0.148998592480463,715443 +INF0191,4,Ctrl,2025-07-29,Female,HEU-hi,644496,572957,458792,438631,0.974322380315117,0.97583347372756,0.953489732502199,0.793023810860897,0.964819880028208,0.240123571536058,0.72469630849215,0.672588540421878,0.00767715585503775,0.992322844144962,0.0165168524538384,0.975805991691124,0.665047883517804,0.310758108173319,0.223865864732901,0.0868922434404187,227949,338913,0.0241665262724396,0.0465102674978005,427368 +INF0191,9,Ctrl,2025-07-29,Female,HEU-hi,1504536,1353339,1109880,1047290,0.954451011658662,0.972429613430347,0.953109634278957,0.693557439222399,0.937200604092772,0.393165154751894,0.544035449340878,0.415256083119011,0.0211785956197787,0.978821404380221,0.0144085311843271,0.964412873195894,0.570575056011949,0.393837817183945,0.260659638397277,0.133178178786668,287885,693271,0.0275703865696533,0.0468903657210428,999587 +INF0134,0,PPD,2025-07-29,Female,HEU-lo,1245024,1126248,993895,896183,0.791566008281791,0.804229843188777,0.789978121986839,0.592486763238172,0.900348082216877,0.154857329117327,0.74549075309955,0.331456116182849,0.00945360055128058,0.990546399448719,0.0258771677960262,0.964669231652693,0.69642241874354,0.268246812909154,0.226039393591363,0.0422074193177903,139312,420303,0.195770156811223,0.210021878013161,709388 +INF0134,4,PPD,2025-07-29,Female,HEU-lo,1340280,1201488,986763,947027,0.983254965275541,0.983444466042147,0.964371666152975,0.763760391507879,0.947150550485805,0.320176042970233,0.626974507515572,0.513328365134493,0.010466371201455,0.989533628798545,0.0256112459391795,0.963922382859365,0.628647890564653,0.335274492294713,0.281901751425738,0.0533727408689745,365074,711190,0.016555533957853,0.0356283338470246,931169 +INF0134,9,PPD,2025-07-29,Female,HEU-lo,929672,828324,752940,697560,0.958546935030678,0.966002835589641,0.899239356069897,0.431271349178337,0.776881543311128,0.129113248048494,0.647768295262634,0.490593583870554,0.0258639579843219,0.974136042015678,0.0275392129835797,0.946596829032098,0.444189975330633,0.502406853701465,0.440365870036969,0.0620409836644966,141471,288367,0.0339971644103588,0.100760643930103,668644 +INF0148,0,PPD,2025-07-29,Female,HU,1862952,1676887,1450059,1372237,0.674659697996775,0.911606590242095,0.896064238982148,0.658815739587575,0.888040699952617,0.226900924208963,0.661139775743655,0.360931718058063,0.00422000345231714,0.995779996547683,0.0193193484205649,0.976460648127118,0.664716410316977,0.311744237810141,0.271842719699103,0.0399015181110374,220142,609927,0.0883934097579049,0.103935761017852,925793 +INF0148,4,PPD,2025-07-29,Female,HU,632312,562703,496868,467363,0.972633691584486,0.986906393472556,0.950157620448201,0.512846121525036,0.914050770827793,0.240886902361813,0.67316386846598,0.639881437505898,0.00312388971194519,0.996876110288055,0.0167054359703163,0.980170674317738,0.619850777285434,0.360319897032305,0.305376978407621,0.0549429186246841,149173,233126,0.0130936065274444,0.0498423795517992,454573 +INF0148,9,PPD,2025-07-29,Female,HU,1110656,997595,827243,774214,0.980991043819926,0.975244141846512,0.945795704262163,0.654739913390046,0.956100572522538,0.196441391348414,0.759659181174124,0.730733420073079,0.012606845839273,0.987393154160727,0.0212756003456494,0.966117553815078,0.556118489490167,0.40999906432491,0.358245223929065,0.0517538403958456,363374,497273,0.0247558581534885,0.054204295737837,759497 +INF0191,0,PPD,2025-07-29,Female,HEU-hi,1968064,1782256,1568308,1456260,0.489216898081387,0.876586653790494,0.861205428766737,0.584636741729328,0.802235715263222,0.199096782557964,0.603138932705259,0.12735317914773,0.0365357062061685,0.963464293793832,0.0206055350275243,0.942858758766307,0.450814418218837,0.49204434054747,0.378968403589473,0.113075936957997,53044,416511,0.123413346209506,0.138794571233263,712427 +INF0191,4,PPD,2025-07-29,Female,HEU-hi,1066672,941050,756678,723688,0.979242435966881,0.966806647983676,0.947546516976968,0.794993692374123,0.960648579568146,0.289526700213886,0.67112187935426,0.608381479805107,0.00961333671769467,0.990386663282305,0.0165308545804121,0.973855808701893,0.631869013546198,0.341986795155695,0.243043824561711,0.0989429705939846,342753,563385,0.0331933520163237,0.052453483023032,708666 +INF0191,9,PPD,2025-07-29,Female,HEU-hi,2415400,2151222,1768089,1652532,0.93912916663641,0.928039145818043,0.910939268954168,0.649623922558912,0.888403635072378,0.410601104170097,0.477802530902281,0.346151175685246,0.0267177103690162,0.973282289630984,0.0146425890160524,0.958639700614931,0.53798476712266,0.420654933492272,0.276607389492868,0.144047543999404,348982,1008178,0.0719608541819566,0.0890607310458322,1551941 +INF0134,0,SEB,2025-07-29,Female,HEU-lo,1193160,1079791,959139,869331,0.782985997278367,0.805832160476234,0.791506653699128,0.566516423427368,0.876204899731078,0.163671867909018,0.71253303182206,0.346036051689129,0.00822116969933151,0.991778830300668,0.0153107107527204,0.976468119547948,0.632348091969184,0.344120027578764,0.261855870979346,0.0822641565994185,133436,385613,0.194167839523766,0.208493346300872,680674 +INF0134,4,SEB,2025-07-29,Female,HEU-lo,1291352,1157622,964426,923312,0.982650501672241,0.977873740897373,0.956105690223555,0.740553492642399,0.941799288285888,0.339208720358268,0.60259056792762,0.501288140032951,0.00984813621721123,0.990151863782789,0.0180811424669329,0.972070721315856,0.600050472811484,0.372020248504372,0.304793432596529,0.0672268159078426,336815,671899,0.0221262591026272,0.0438943097764449,907293 +INF0148,0,SEB,2025-07-29,Female,HU,2042880,1841683,1602125,1513482,0.68014684020028,0.901883639825528,0.887045726109638,0.655521231020313,0.869403233909367,0.222301259508556,0.647101974400811,0.382685202886244,0.00371760168221476,0.996282398317785,0.0109359449485151,0.98534645336927,0.659413470884596,0.325932982484675,0.255453450592686,0.0704795318919882,258231,674787,0.0981163601744722,0.112954273890362,1029390 +INF0191,0,SEB,2025-07-29,Female,HEU-hi,1956304,1772838,1558215,1448120,0.500612518299588,0.874513585131051,0.858720706479232,0.584808268742405,0.813640598648442,0.205064216721114,0.608576381927327,0.153905485251973,0.0330426519946666,0.966957348005333,0.0149274318380358,0.952029916167298,0.46397645940934,0.488053456757958,0.365047740195252,0.123005716562706,65249,423955,0.125486414868949,0.141279293520768,724947 +INF0191,9,SEB,2025-07-29,Female,HEU-hi,1814944,1620273,1311159,1239312,0.955994132228204,0.953430820197928,0.93669852925661,0.694926040809436,0.916094499053236,0.411346105029447,0.504748394023789,0.378588927175097,0.0235030670122937,0.976496932987706,0.0090374201165208,0.967459512871185,0.549190899058081,0.418268613813105,0.271844442163078,0.146424171650027,311704,823331,0.0465691798020721,0.0633014707433901,1184775 +INF0124,0,Ctrl,2025-07-31,Male,HEU-hi,1229248,1096279,962417,891568,0.771360120596522,0.857697900308265,0.851096376432269,0.620287326237422,0.848707405809876,0.216735742550119,0.631971663259757,0.164790521913621,0.0142253581233908,0.985774641876609,0.00988662389575658,0.975888017980853,0.672020143107103,0.30386787487375,0.264805041466919,0.039062833406831,70297,426584,0.142302099691735,0.148903623567731,687720 +INF0124,4,Ctrl,2025-07-31,Male,HEU-hi,1105296,993220,820093,766344,0.899851763698809,0.947894129316295,0.938007181016131,0.699090481963352,0.91153726482607,0.258244311228194,0.653292953597876,0.479005994731274,0.00947930920995652,0.990520690790043,0.00774280715733315,0.98277788363271,0.509990299838908,0.472787583793802,0.423485648958099,0.0493019348357035,230924,482090,0.0521058706837046,0.0619928189838688,689596 +INF0124,9,Ctrl,2025-07-31,Male,HEU-hi,1017128,915840,757350,701114,0.745743202959861,0.954792091819658,0.946617678841582,0.744550550730514,0.902542840922811,0.341029415164569,0.561513425758241,0.534849430628659,0.00372698848763994,0.99627301151236,0.0102107957792816,0.986062215733079,0.662625893924913,0.323436321808166,0.290926031765853,0.0325102900423128,208211,389289,0.045207908180342,0.053382321158418,522851 +INF0149,0,Ctrl,2025-07-31,Female,HU,1327920,1192637,1046943,958252,0.895218585507779,0.886543606362455,0.868127692065583,0.541476607079368,0.836291692411029,0.157884879107347,0.678406813303682,0.232291287677367,0.017191844300278,0.982808155699722,0.0213438368860056,0.961464318813716,0.62177015755329,0.339694161260426,0.299629286376274,0.040064874884152,107900,464503,0.113456393637545,0.131872307934417,857845 +INF0149,4,Ctrl,2025-07-31,Female,HU,1026960,910155,731344,694429,0.945859115906738,0.979643196433791,0.947015370749294,0.669381211634025,0.91294172233329,0.292650641047511,0.62029108128578,0.545926385865795,0.00758244871431666,0.992417551285683,0.0194019031113037,0.97301564817438,0.672871498325195,0.300144149849184,0.263023480593931,0.0371206692552536,240028,439671,0.0203568035662087,0.0529846292507065,656832 +INF0149,9,Ctrl,2025-07-31,Female,HU,757368,665858,536020,502656,0.935176343264579,0.969391922939465,0.928508824180126,0.660841317925765,0.898426811484566,0.184607411079599,0.713819400404966,0.632452686846316,0.00949268833951758,0.990507311660482,0.0293433502827447,0.961163961377738,0.614535774455761,0.346628186921977,0.304509154209104,0.0421190327128729,196467,310643,0.0306080770605354,0.0714911758198744,470072 +INF0169,0,Ctrl,2025-07-31,Female,HEU-lo,1288912,1144653,1051293,973587,0.877778770669699,0.842549795575443,0.826082326812498,0.351936709127375,0.771953332025548,0.130222135036557,0.641731196988991,0.251161213314138,0.0128673550436855,0.987132644956315,0.0153958167858088,0.971736828170506,0.745724119671697,0.226012708498809,0.135041037860736,0.0909716706380725,75540,300763,0.157450204424557,0.173917673187502,854594 +INF0169,4,Ctrl,2025-07-31,Female,HEU-lo,1068232,944862,869444,785215,0.916182192138459,0.94555323881012,0.865148735056992,0.368202668890742,0.781063480378277,0.167733167223512,0.613330313154765,0.37912679087151,0.0106148867313916,0.989385113268608,0.0155240229026637,0.973861090365945,0.812735872541698,0.161125217824247,0.0949166044311675,0.0662086133930794,100425,264885,0.0544467611898805,0.134851264943008,719400 +INF0169,9,Ctrl,2025-07-31,Female,HEU-lo,778672,685649,594814,542125,0.951313811390362,0.975039313130295,0.922139642565601,0.573702181951444,0.867772310021766,0.302004893942057,0.565767416079709,0.461223620705971,0.0194995053676767,0.980500494632323,0.0165243835415674,0.963976111090756,0.829546037445499,0.134430073645257,0.0826072619352948,0.0518228117099623,136465,295876,0.0249606868697053,0.0778603574343989,515731 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+INF0169,9,PPD,2025-07-31,Female,HEU-lo,1054184,923351,814226,740463,0.941281333435972,0.956064988579365,0.903875842200108,0.518514054842005,0.787211258564013,0.264463358753279,0.522747899810734,0.416426855858947,0.0214824412771188,0.978517558722881,0.0152895445031396,0.963228014219741,0.829416259676401,0.13381175454334,0.0789527891292069,0.0548589654141334,150495,361396,0.0439350114206352,0.0961241577998921,696984 +INF0124,0,SEB,2025-07-31,Male,HEU-hi,1004008,900404,794342,737214,0.815346697159848,0.858233028606603,0.850839731485564,0.645535989086402,0.90635582518517,0.244872713402848,0.661483111782322,0.178788831561097,0.0139389396603915,0.986061060339608,0.00593882434341396,0.980122235996195,0.65523106639375,0.324891169602445,0.256133421743016,0.0687577478594286,69374,388022,0.141766971393397,0.149160268514436,601085 +INF0124,4,SEB,2025-07-31,Male,HEU-hi,1571248,1425147,1204162,1120656,0.879540197884096,0.899691780752428,0.891540913619476,0.636573186345826,0.779254310331088,0.235330211683555,0.543924098647533,0.407646235691996,0.00896878518703866,0.991031214812961,0.00402305141999249,0.987008163392969,0.48618713249093,0.500821030902039,0.445170774427624,0.0556502564744151,255776,627446,0.100308219247572,0.108459086380524,985662 +INF0124,9,SEB,2025-07-31,Male,HEU-hi,1109328,998592,812606,756059,0.904774627376964,0.966187324851658,0.954087562110507,0.656252421195124,0.903795347925456,0.368147412222277,0.53564793570318,0.510429521649834,0.00333419161127865,0.996665808388721,0.00606176982731157,0.99060403856141,0.663831440030374,0.326772598531035,0.289782273796483,0.0369903247345521,229141,448918,0.0338126751483416,0.0459124378894926,684063 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+INF0149,9,SEB,2025-07-31,Female,HU,531432,467288,379931,358096,0.92417396452348,0.969384455933499,0.925790846157798,0.651432421897426,0.89664497395483,0.255715789913121,0.640929184041709,0.552259644598236,0.0108684696791534,0.989131530320847,0.0216865445993617,0.967444985721485,0.571140601377457,0.396304384344028,0.34592642365194,0.050377960692088,119060,215587,0.0306155440665009,0.0742091538422024,330943 +INF0169,0,SEB,2025-07-31,Female,HEU-lo,1237144,1103284,1012883,939441,0.876379676850382,0.844672764837418,0.827158034609204,0.358358425228985,0.774778927531614,0.138666413592779,0.636112513938835,0.265283572680222,0.0129553207527885,0.987044679247212,0.00994007844740574,0.977104600799806,0.719211948536458,0.257892652263348,0.137052983940002,0.120839668323346,78269,295039,0.155327235162582,0.172841965390796,823307 +INF0169,4,SEB,2025-07-31,Female,HEU-lo,698912,617805,566286,511948,0.921683452225617,0.933040728699979,0.850002331229575,0.381090337265341,0.73006189557277,0.16779094533948,0.56227095023329,0.332923662126916,0.0121103798483279,0.987889620151672,0.0104566866000735,0.977432933551599,0.795125780910701,0.182307152640898,0.0982360605351953,0.0840710921057027,59866,179819,0.0669592713000208,0.149997668770425,471854 +INF0169,9,SEB,2025-07-31,Female,HEU-lo,887744,782828,694751,633595,0.93819869159321,0.95722682601045,0.905700846850302,0.520298163980096,0.774770842426888,0.261616308582699,0.513154533844189,0.40678662075432,0.0211186443372307,0.978881355662769,0.0102612607600169,0.968620094902752,0.834238115298101,0.134381979604651,0.0766693425957572,0.0577126370088942,125813,309285,0.0427731739895498,0.0942991531496977,594438 +INF0019,0,Ctrl,2025-08-05,Female,HEU-lo,1324344,1197859,1022143,939295,0.930082668384267,0.868875783805811,0.863010546895568,0.690163480315285,0.91948810996746,0.102868932666824,0.816619177300636,0.345066357958145,0.00882458965177477,0.991175410348225,0.0146163274134243,0.976559082934801,0.733344548316551,0.24321453461825,0.222489245632165,0.0207252889860854,208055,602942,0.131124216194189,0.136989453104432,873622 +INF0019,4,Ctrl,2025-08-05,Female,HEU-lo,1244280,1117290,891334,840761,0.905377390245266,0.955721578652822,0.935905654973818,0.704970796341595,0.886148318760855,0.352806786078997,0.533341532681858,0.451748697421678,0.00439318375883277,0.995606816241167,0.0133404284282302,0.982266387812937,0.652608478638402,0.329657909174535,0.293807054669356,0.035850854505179,242421,536628,0.0442784213471781,0.0640943450261822,761206 +INF0019,9,Ctrl,2025-08-05,Female,HEU-lo,1844096,1632745,1274587,1217805,0.930321356867479,0.964861644379717,0.957356458802242,0.793717286729335,0.940427604582526,0.21288596395631,0.727541640626216,0.703361275385269,0.00365696325012807,0.996343036749872,0.0164096937194463,0.979933343030426,0.699705292715165,0.280228050315261,0.26313218190902,0.0170958684062407,632492,899242,0.0351383556202833,0.042643541197758,1132950 +INF0032,0,Ctrl,2025-08-05,Female,HU,1124480,1006880,824473,773851,0.973138239790347,0.93983645480331,0.936204625370486,0.81375420946958,0.977386102358157,0.189406487176265,0.787979615181892,0.589146047137036,0.00786906496341065,0.992130935036589,0.015089991524344,0.977040943512245,0.713304010148629,0.263736933363617,0.236961061839051,0.0267758715245656,361034,612809,0.0601635451966898,0.0637953746295136,753064 +INF0032,4,Ctrl,2025-08-05,Female,HU,711784,637561,497456,468981,0.969265279403643,0.940503820118926,0.934273715425889,0.812375293411092,0.942385025955985,0.363519181973521,0.578865843982463,0.431871295145405,0.0113430439989717,0.988656956001028,0.0133871746477637,0.975269781353265,0.678833215241941,0.296436566111324,0.218145108194707,0.078291457916617,159481,369279,0.0594961798810736,0.0657262845741112,454567 +INF0032,9,Ctrl,2025-08-05,Female,HU,1248456,1118033,911093,872062,0.984879515447296,0.972946036447636,0.965117199688896,0.784273864911815,0.958258238642268,0.255593131767801,0.702665106874467,0.660764496120809,0.0196613246399019,0.980338675360098,0.0175763390078794,0.962762336352219,0.707335869167152,0.255426467185067,0.221487035118977,0.0339394320660905,445087,673594,0.0270539635523638,0.0348828003111042,858876 +INF0180,0,Ctrl,2025-08-05,Male,HEU-hi,1614504,1435508,1209469,1117422,0.939361315599657,0.867784231701032,0.861666077588712,0.699933216660966,0.927674650943114,0.107572676515665,0.820101974427449,0.387859435356761,0.0045269829237993,0.995473017076201,0.0201398100772745,0.975333206998926,0.66050084573867,0.314832361260256,0.295819032980299,0.019013328279957,284958,734694,0.132215768298968,0.138333922411288,1049663 +INF0180,4,Ctrl,2025-08-05,Male,HEU-hi,528392,465660,387783,356166,0.986118832229915,0.924284355763591,0.897517809248851,0.643003570391376,0.977466048521721,0.210988456275987,0.766477592245735,0.5716158114038,0.012913271155455,0.987086728844545,0.0140674867536331,0.973019242090912,0.521325876119357,0.451693365971555,0.374554581228891,0.0771387847426641,129092,225837,0.0757156442364089,0.102482190751149,351222 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+INF0019,9,PPD,2025-08-05,Female,HEU-lo,1725968,1521365,1188395,1141230,0.939210325701217,0.973696068964552,0.966078434116555,0.812773182939857,0.963162395615118,0.221661549057308,0.74150084655781,0.717317416133383,0.00372374217686095,0.996276257823139,0.0165176049632827,0.979758652859856,0.698383284606239,0.281375368253618,0.263582377594178,0.01779299065944,624909,871175,0.0263039310354479,0.0339215658834451,1071855 +INF0032,0,PPD,2025-08-05,Female,HU,1240368,1107613,907113,859658,0.976240551475121,0.915239272049598,0.912261553108612,0.6988631285948,0.983314834043467,0.168643618426998,0.81467121561647,0.671650392406596,0.00751404440901787,0.992485955590982,0.0149722411906714,0.977513714400311,0.721688426086934,0.255825288313376,0.229117429790648,0.0267078585227287,393929,586509,0.0847607279504023,0.0877384468913878,839233 +INF0032,4,PPD,2025-08-05,Female,HU,774384,688988,533872,502702,0.962799034020155,0.938179879793637,0.931460885411394,0.810487994859515,0.962080366679668,0.362208337475814,0.599872029203853,0.450324643045603,0.0114179290356181,0.988582070964382,0.0143332654031655,0.974248805561216,0.680716889704051,0.293531915857165,0.216431175418337,0.0771007404388289,176652,392277,0.0618201202063632,0.0685391145886062,484001 +INF0032,9,PPD,2025-08-05,Female,HU,1335992,1193171,967189,926155,0.985408489939589,0.971373190553569,0.9628320445827,0.777570808236755,0.954451745455109,0.258002967689387,0.696448777765722,0.653293275632959,0.0199027189094164,0.980097281090584,0.0174696131404968,0.962627667950087,0.705177899289266,0.257449768660821,0.222760755384433,0.0346890132763883,463605,709643,0.0286268094464307,0.0371679554172999,912641 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+INF0180,9,PPD,2025-08-05,Male,HEU-hi,1516936,1391367,1205249,1116976,0.580700032946097,0.859905832002319,0.852679810307295,0.619310298044488,0.699471249831965,0.106603900403782,0.592867349428183,0.434677945342567,0.018629983219843,0.981370016780157,0.0152624977807813,0.966107518999376,0.298383263368287,0.667724255631089,0.591028056651643,0.0766961989794457,174611,401702,0.140094167997681,0.147320189692705,648628 +INF0019,0,SEB,2025-08-05,Female,HEU-lo,1353632,1227164,1049849,966363,0.931358092145498,0.874083086119352,0.868618823816984,0.700898858926925,0.923351774646101,0.104785758445223,0.818566016200878,0.359317090182775,0.00802054105564085,0.991979458944359,0.00897788836536256,0.983001570578997,0.701554696737078,0.281446873841919,0.234563326098082,0.0468835477438368,226668,630830,0.125916913880648,0.131381176183016,900030 +INF0019,4,SEB,2025-08-05,Female,HEU-lo,1170048,1047919,832442,792400,0.917228672387683,0.96310875439591,0.942818775694402,0.723126475622307,0.904638140557901,0.344459517825171,0.56017862273273,0.484003295425789,0.00425346232619575,0.995746537673804,0.00847547576273385,0.98727106191107,0.625577381958558,0.361693679952512,0.323259205679669,0.0384344742728427,254381,525577,0.0368912456040902,0.0571812243055976,726812 +INF0019,9,SEB,2025-08-05,Female,HEU-lo,1710322,1517501,1200599,1151235,0.925440939512784,0.969865778111507,0.962381265252487,0.80652900319129,0.946442121041435,0.211284849105526,0.735157271935909,0.711653764331833,0.00369415231550906,0.996305847684491,0.0108077258314296,0.985498121853061,0.692474493341859,0.293023628511203,0.272495654178938,0.0205279743322644,611507,859276,0.0301342218884926,0.0376187347475126,1065400 +INF0032,0,SEB,2025-08-05,Female,HU,1027392,922706,754901,711686,0.97571541382014,0.955185965498421,0.951156605026188,0.835023754217652,0.990864768566664,0.225678330168684,0.76518643839798,0.575916239395836,0.00765404667291528,0.992345953327085,0.0082170203718621,0.984128932955223,0.68755858070737,0.296570352247852,0.251981637474883,0.0445887147729689,333941,579843,0.0448140345015791,0.0488433949738121,694403 +INF0032,9,SEB,2025-08-05,Female,HU,1155456,1036243,850931,814746,0.98729910917022,0.970027275055383,0.962124470722205,0.785860979266482,0.962943628439678,0.261944648775202,0.700998979664476,0.658102175924827,0.0194511749548094,0.980548825045191,0.0122952001846083,0.968253624860582,0.710602476827814,0.257651148032768,0.222056363216799,0.0355947848159686,416016,632145,0.029972724944617,0.0378755292777954,804398 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+INF0155,4,Ctrl,2025-08-07,Female,HEU-lo,1215184,1083687,851644,825005,0.98352979678911,0.985920925985036,0.98077190889518,0.854323978915897,0.967996849453198,0.341870391928599,0.626126457524599,0.59517060412889,0.00328178777449222,0.996718212225508,0.011180861893451,0.985537350332057,0.721515827233506,0.264021523098551,0.223845072470794,0.040176450627757,412580,693213,0.014079074014964,0.0192280911048204,811417 +INF0155,9,Ctrl,2025-08-07,Female,HEU-lo,1123680,1000603,815357,761574,0.980901396318677,0.959184984786401,0.928468640441,0.618258461184238,0.931716960011432,0.317645938028437,0.614071021982995,0.495439064472337,0.0109735951962661,0.989026404803734,0.011511130922726,0.977515273881008,0.501966594121195,0.475548679759813,0.399603185008435,0.0759454947513788,228822,461857,0.0408150152135994,0.0715313595589997,747029 +INF0158,0,Ctrl,2025-08-07,Male,HU,1974064,1742021,1484261,1352364,0.92381784785753,0.802042361634722,0.793962082318796,0.613198349846078,0.932262704740423,0.332249912543141,0.600012792197282,0.366683113777458,0.00460996821079836,0.995390031789202,0.0221207277698077,0.973269304019394,0.590346477379117,0.382922826640277,0.359495644558992,0.023427182081285,280913,766092,0.197957638365278,0.206037917681204,1249338 +INF0158,4,Ctrl,2025-08-07,Male,HU,1017536,914368,805877,754118,0.947414065172824,0.973280594349315,0.924193309091316,0.565141323121454,0.828913347136503,0.594199201529576,0.234714145606927,0.196596098788425,0.0103426555807508,0.989657344419249,0.0161375661375661,0.973519778281683,0.573066263542454,0.400453514739229,0.368808264046359,0.0316452506928697,79380,403772,0.0267194056506854,0.0758066909086837,714462 +INF0158,9,Ctrl,2025-08-07,Male,HU,1148432,1020361,904910,847242,0.957195228754004,0.964520528351024,0.91473730418656,0.565784930750108,0.797826248043972,0.320764627166887,0.477061620877085,0.433948365218225,0.00991904053999759,0.990080959460002,0.0223090521917313,0.967771907268271,0.505695287074611,0.46207662019366,0.431159347502913,0.0309172726907469,199112,458838,0.035479471648976,0.0852626958134396,810976 +INF0159,0,Ctrl,2025-08-07,Male,HEU-hi,2024024,1786795,1447822,1277260,0.931853342310884,0.818567843396887,0.811916966541452,0.651424653782203,0.946597483936038,0.162708392984737,0.783889090951301,0.583682213434657,0.00516847824886035,0.99483152175114,0.0213721768375277,0.973459344913612,0.724433268294623,0.249026076618989,0.217864947818036,0.0311611288009528,452551,775338,0.181432156603113,0.188083033458548,1190219 +INF0159,4,Ctrl,2025-08-07,Male,HEU-hi,1487344,1333646,1131385,1067284,0.940156509420173,0.982565521310247,0.942089705744588,0.646537720223158,0.759423194013056,0.264593946774156,0.4948292472389,0.42502524104232,0.0127949864542873,0.987205013545713,0.0225689344402012,0.964636079105512,0.490235118756188,0.474400960349323,0.394639016729953,0.0797619436193709,275733,648745,0.0174344786897532,0.0579102942554121,1003414 +INF0159,9,Ctrl,2025-08-07,Male,HEU-hi,1167840,1028158,742821,709883,0.982519654647315,0.986670470870599,0.965210172708947,0.813984463937007,0.923115267211876,0.0548056921123134,0.868309575099563,0.858577887845167,0.00239002303859118,0.997609976961409,0.0274596209197793,0.970150356041629,0.627872387130393,0.342277968911237,0.327390074326639,0.0148878945845976,487443,567733,0.0133295291294012,0.0347898272910532,697474 +INF0155,0,PPD,2025-08-07,Female,HEU-lo,2221632,2004398,1728584,1609792,0.784455383055699,0.904280137154441,0.884300092650517,0.762086141224729,0.92752060018496,0.266291551066638,0.661229049118322,0.42905223562663,0.0100119397346134,0.989988060265387,0.0111574761386947,0.978830584126692,0.693289287902603,0.285541296224089,0.231345072861443,0.0541962233626458,412907,962370,0.0957198628455587,0.115699907349483,1262810 +INF0155,4,PPD,2025-08-07,Female,HEU-lo,1393256,1237743,976719,947853,0.987092935296929,0.986962641844597,0.982248115953182,0.856480041555377,0.963070560649114,0.341770461689747,0.621300098959367,0.590333179840242,0.00351120478081922,0.996488795219181,0.0112248629657737,0.985263932253407,0.718674493771364,0.266589438482043,0.226748573639117,0.0398408648429259,473057,801339,0.013037358155403,0.0177518840468182,935619 +INF0155,9,PPD,2025-08-07,Female,HEU-lo,1302344,1145745,915824,856281,0.980871933395696,0.959576236275185,0.932713578488919,0.651871289745708,0.966500946104897,0.340636118558998,0.625864827545899,0.500440176216603,0.0116133506085877,0.988386649391412,0.0115622547856713,0.976824394605741,0.496768189200533,0.480056205405208,0.406102301136882,0.0739539042683261,273995,547508,0.0404237637248155,0.0672864215110811,839902 +INF0158,0,PPD,2025-08-07,Male,HU,1897704,1691391,1435638,1304624,0.922783116054894,0.848499649052858,0.840498884860265,0.656822703165169,0.897703287684052,0.29528959618787,0.602413691496183,0.380556669141145,0.00439650273659864,0.995603497263401,0.022052299440717,0.973551197822684,0.60114116329535,0.372410034527334,0.349540244781853,0.0228697897454814,300921,790739,0.151500350947142,0.159501115139735,1203885 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+INF0159,0,PPD,2025-08-07,Male,HEU-hi,1898040,1677926,1357904,1200314,0.92715656069995,0.836210405623612,0.830270856040953,0.664310315856441,0.953162260904616,0.171448010745343,0.781714250159273,0.588793137264185,0.00438555180074111,0.995614448199259,0.021238568044972,0.974375880154287,0.719421171486792,0.254954708667495,0.223869899125417,0.0310848095420786,435293,739297,0.163789594376388,0.169729143959047,1112879 +INF0159,4,PPD,2025-08-07,Male,HEU-hi,1468272,1314327,1118313,1054808,0.946339997421332,0.981112134056363,0.940226826700274,0.633504874239511,0.820599997786103,0.307417030246581,0.513182967539522,0.438671092352724,0.0131866388850837,0.986813361114916,0.0228152644898018,0.963998096625114,0.479992934441713,0.484005162183402,0.403468612338772,0.0805365498446298,277402,632369,0.0188878659436369,0.0597731732997264,998207 +INF0159,9,PPD,2025-08-07,Male,HEU-hi,1124616,979389,693430,664229,0.986489599219546,0.987891736804755,0.970960923609892,0.834537699063723,0.953283897336491,0.0770854096756791,0.876198487660812,0.865529821609809,0.00256495852542351,0.997435041474577,0.0272806791435489,0.970154362331028,0.626557673536135,0.343596688794892,0.328836556786153,0.0147601320087386,473302,546835,0.0121082631952446,0.0290390763901077,655255 +INF0155,0,SEB,2025-08-07,Female,HEU-lo,2378848,2136279,1866817,1735030,0.768161357440505,0.871291875721704,0.849967324012986,0.725989902332188,0.917141300988955,0.265460366871403,0.651680934117552,0.427269072445165,0.00920371535000726,0.990796284649993,0.00827487784819312,0.9825214068018,0.683459919694258,0.299061487107542,0.234429877606308,0.0646316095012336,413420,967587,0.128708124278296,0.150032675987014,1332783 +INF0155,4,SEB,2025-08-07,Female,HEU-lo,995464,892094,720248,700245,0.986965990474762,0.988068607676258,0.983642446007773,0.852773332484467,0.955501410835693,0.343553337733534,0.611948073102159,0.563346777135469,0.00340041804962382,0.996599581950376,0.00690324018577306,0.989696341764603,0.704103391984772,0.285592949779831,0.238706937575674,0.0468860122041576,332018,589367,0.0119313923237421,0.016357553992227,691118 +INF0158,0,SEB,2025-08-07,Male,HU,1995888,1767501,1513529,1376026,0.927221578662031,0.808748621540724,0.801494026480526,0.617858562044579,0.886202706028309,0.318907186730161,0.567295519298148,0.350209434311708,0.00469075432400616,0.995309245675994,0.0136267318663407,0.981682513809653,0.587833016390474,0.39384949741918,0.357326813365933,0.0365226840532464,276075,788314,0.191251378459276,0.198505973519474,1275881 +INF0158,4,SEB,2025-08-07,Male,HU,1006016,899118,788056,735913,0.950509095504496,0.970617247945652,0.921042699559109,0.55347309190098,0.810776184941237,0.568911274699729,0.241864910241508,0.201115846571096,0.0105699827900645,0.989430017209936,0.00946546453982687,0.979964552670109,0.538285684929747,0.441678867740361,0.406193008142611,0.0354858595977499,77862,387150,0.029382752054348,0.0789573004408914,699492 +INF0158,9,SEB,2025-08-07,Male,HU,1120552,994396,877895,829211,0.951199393158074,0.969440059841901,0.923015676803023,0.590119747193326,0.769334885939319,0.291835498244724,0.477499387694595,0.4362257065145,0.00997818196145644,0.990021818038544,0.0136030299000704,0.976418788138473,0.498879547682018,0.477539240456455,0.442625453721625,0.0349137867348296,203043,465454,0.0305599401580993,0.0769843231969775,788745 +INF0159,0,SEB,2025-08-07,Male,HEU-hi,2086792,1847605,1507051,1327409,0.929341295712173,0.817877686411331,0.811086269957588,0.63500068092502,0.933116486052797,0.168540889286612,0.764575596766184,0.573310423094746,0.00499887553133928,0.995001124468661,0.0134001037628507,0.98160102070581,0.708139149100091,0.273461871605719,0.229282499927633,0.0441793716780858,449101,783347,0.182122313588669,0.188913730042412,1233616 +INF0159,4,SEB,2025-08-07,Male,HEU-hi,1459280,1303303,1109557,1042434,0.940995784865037,0.978019748686445,0.936432513767603,0.633759325372148,0.809547172057246,0.292138446219946,0.5174087258373,0.446210294512692,0.0123001052646758,0.987699894735324,0.0150975500728201,0.972602344662504,0.473806399515494,0.49879594514701,0.416260508442804,0.0825354367042063,277396,621671,0.0219802513135547,0.0635674862323967,980926 +INF0159,9,SEB,2025-08-07,Male,HEU-hi,527136,464846,340607,329303,0.989851291971224,0.990468184844199,0.978966808912723,0.810075438472701,0.908817547992259,0.101222103138385,0.807595444853874,0.791356280746668,0.00333078101071976,0.99666921898928,0.0168501148545176,0.979819104134763,0.607656967840735,0.372162136294028,0.351852029096478,0.0203101071975498,208960,264053,0.00953181515580082,0.0210331910872773,325961 +INF0013,0,Ctrl,2025-08-22,Male,HEU-lo,1284824,1149119,931095,865836,0.966202606498228,0.932750638617311,0.92304556804965,0.750423453781081,0.949825099078664,0.0932661552381074,0.856558943840557,0.291104902323092,0.00844865417973089,0.991551345820269,0.00902320643936285,0.982528139380906,0.850868121104672,0.131660018276234,0.12322777987535,0.00843223840088426,182751,627784,0.0672493613826887,0.0769544319503498,836573 +INF0013,4,Ctrl,2025-08-22,Male,HEU-lo,1212080,1066572,933636,828526,0.95181563402959,0.847583831682315,0.831272730039411,0.60063606068445,0.925172696257263,0.148377330766113,0.77679536549115,0.594396027563843,0.0112913079305544,0.988708692069446,0.0117814622226011,0.976927229846845,0.529906515500241,0.447020714346603,0.122662887506038,0.324357826840565,281544,473664,0.152416168317685,0.168727269960589,788604 +INF0013,9,Ctrl,2025-08-22,Male,HEU-lo,591208,513249,411678,387329,0.98218826888769,0.981357937071209,0.957161632889099,0.743813579370712,0.979025971042764,0.223218797818842,0.755807173223922,0.739819556205803,0.00397428181097322,0.996025718189027,0.00966820479015601,0.986357513398871,0.631418799499393,0.354938713899477,0.330366952318172,0.0245717615813056,209346,282969,0.0186420629287911,0.0428383671109008,380430 +INF0023,0,Ctrl,2025-08-22,Female,HEU-hi,1428512,1282467,1103378,1007499,0.960829737796266,0.84605411994401,0.843164761604694,0.703389856771708,0.877314930401553,0.283347481150115,0.593967449251439,0.320800521657909,0.00813056515668277,0.991869434843317,0.0207613248792547,0.971108109964062,0.74064138073111,0.230466729232953,0.199926751665255,0.0305399775676975,218435,680906,0.15394588005599,0.156835238395306,968035 +INF0023,4,Ctrl,2025-08-22,Female,HEU-hi,1945688,1737383,1389603,1347134,0.970804686096558,0.973963988487571,0.967753577753241,0.82823955271585,0.91921157707665,0.46567267523715,0.4535389018395,0.425440025849932,0.00191178449132644,0.998088215508674,0.0244929756567555,0.973595239851918,0.711776245263939,0.261818994587979,0.236718414325581,0.0251005802623984,460826,1083175,0.0260360115124285,0.0322464222467587,1307804 +INF0023,9,Ctrl,2025-08-22,Female,HEU-hi,987800,871641,686162,661242,0.967712274779884,0.980770192469979,0.97006369824908,0.82072599751208,0.977877892363703,0.332214343382028,0.645663548981675,0.598146145292245,0.00485146371589014,0.99514853628411,0.0375956604230069,0.957552875861103,0.581545337628767,0.376007538232335,0.327330548941209,0.048676989291126,314132,525176,0.0192298075300207,0.0299363017509204,639892 +INF0030,0,Ctrl,2025-08-22,Male,HU,1055672,939062,820166,756891,0.967538258481076,0.956857716766282,0.935349389134,0.547854014837756,0.885988459764958,0.214057651325382,0.671930808439576,0.213160354432273,0.00440827399118345,0.995591726008817,0.0174693934823026,0.978122332526514,0.649021877667473,0.32910045485904,0.304334607874089,0.0247658469849511,85521,401205,0.0431422832337185,0.064650610866,732321 +INF0030,4,Ctrl,2025-08-22,Male,HU,887272,774792,587687,558971,0.959545307359416,0.973952099157652,0.963873010190955,0.820582521375648,0.966016549806192,0.344733099157968,0.621283450648223,0.586763790369122,0.00488673765730881,0.995113262342691,0.0210029041626331,0.974110358180058,0.605254598257502,0.368855759922556,0.302152952565344,0.066702807357212,258250,440126,0.0260479008423479,0.0361269898090455,536358 +INF0030,9,Ctrl,2025-08-22,Male,HU,1059640,929289,780683,761469,0.997026799515148,0.989099123425162,0.984053055498844,0.880723915148083,0.981709414491887,0.19381141105212,0.787898003439767,0.731571076048755,0.00457105475657498,0.995428945243425,0.0326617807897131,0.962767164453712,0.52534420900923,0.437422955444482,0.392945120767021,0.0444778346774606,489165,668650,0.0109008765748382,0.0159469445011559,759205 +INF0013,0,PPD,2025-08-22,Male,HEU-lo,1309848,1169793,941515,876615,0.962326677047507,0.941158619708626,0.932124610296471,0.759162626394339,0.937937797264928,0.0886665355031526,0.849271261761776,0.284356252595945,0.00974147209348299,0.990258527906517,0.00882443385243921,0.981434094054078,0.848205460495969,0.133228633558108,0.124788586992334,0.00844004656577416,182108,640422,0.0588413802913738,0.0678753897035289,843590 +INF0013,4,PPD,2025-08-22,Male,HEU-lo,1021264,890816,775431,680459,0.904611446097414,0.847437499086185,0.828137717264695,0.527857155621549,0.906420905876161,0.1306524930522,0.775768412823961,0.582688821659285,0.00979247764473483,0.990207522355265,0.012153447173967,0.978054075181298,0.563225918903073,0.414828156278225,0.36157693750033,0.0532512187778946,189329,324923,0.152562500913815,0.171862282735305,615551 +INF0013,9,PPD,2025-08-22,Male,HEU-lo,739216,639880,503620,472587,0.982966099363715,0.979256765338391,0.957546976882358,0.746838249698086,0.975531369078845,0.202663907256135,0.77286746182271,0.752431298171987,0.00539755749988508,0.994602442500115,0.00971866811725226,0.984883774382863,0.620462450774582,0.364421323608281,0.338517644535021,0.0259036790732597,261044,346934,0.0207432346616093,0.0424530231176419,464537 +INF0023,0,PPD,2025-08-22,Female,HEU-hi,1572088,1406726,1193232,1088074,0.963874699698734,0.860464717139269,0.857511725674053,0.722300568191028,0.866451932279463,0.280125408402363,0.5863265238771,0.293390977195472,0.00882785679254536,0.991172143207455,0.0203418657283882,0.970830277479066,0.733432020553338,0.237398256925728,0.203517644465042,0.0338806124606863,222251,757525,0.139535282860731,0.142488274325947,1048767 +INF0023,4,PPD,2025-08-22,Female,HEU-hi,1960856,1733414,1389954,1349503,0.97374070305883,0.974950268860164,0.969395753333546,0.816614994985031,0.920252430839653,0.478423910105993,0.44182852073366,0.41255500491107,0.00191097046127574,0.998089029538724,0.0242485436191431,0.973840485919581,0.713799420384137,0.260041065535444,0.234965790014615,0.0250752755208298,442707,1073086,0.0250497311398362,0.0306042466664536,1314066 +INF0023,9,PPD,2025-08-22,Female,HEU-hi,942384,831282,659209,636544,0.965433654232857,0.981319391220439,0.969826260574966,0.819434342053663,0.976605318760227,0.343987799259695,0.632617519500532,0.588131682208842,0.00467976054212291,0.995320239457877,0.0367965587215407,0.958523680736336,0.586502976341211,0.372020704395126,0.324355351167745,0.0476653532273803,296169,503576,0.0186806087795607,0.0301737394250343,614541 +INF0030,0,PPD,2025-08-22,Male,HU,972560,864436,748225,696152,0.967973948218205,0.94563980191643,0.924446878195225,0.564357126215206,0.915665691987294,0.220120642867661,0.695545049119633,0.217351747060185,0.00416172663263084,0.995838273367369,0.0178930049118053,0.977945268455564,0.648612354521038,0.329332913934525,0.304435142393961,0.0248977715405647,82658,380296,0.0543601980835696,0.0755531218047746,673857 +INF0030,4,PPD,2025-08-22,Male,HU,983584,844256,638719,608344,0.973238825401418,0.972557020862609,0.963926197167874,0.819625918819587,0.948748225218486,0.355848587696359,0.592899637522127,0.555135171893643,0.0058947774795743,0.994105222520426,0.0206465694845039,0.973458653035922,0.598208551881837,0.375250101154085,0.307887048936304,0.0673630522177801,269391,485271,0.0274429791373906,0.0360738028321262,592064 +INF0030,9,PPD,2025-08-22,Male,HU,1369512,1205519,999002,973830,0.996570243266279,0.990564560170635,0.984433636616554,0.888463559645128,0.979156736194469,0.202834461203022,0.776322274991447,0.725544363840904,0.00440699044272911,0.995593009557271,0.0321021360396549,0.963490873517616,0.543279459460324,0.420211414057292,0.376963124823169,0.0432482892341236,625597,862245,0.00943543982936457,0.0155663633834455,970490 +INF0013,0,SEB,2025-08-22,Male,HEU-lo,1304808,1167431,967694,900086,0.963833455914213,0.930778425719828,0.919863567149607,0.731671302417314,0.937149960062954,0.10830737819201,0.828842581870944,0.296109170711573,0.00917240828921816,0.990827591710782,0.00503844005214014,0.985789151658642,0.773584102577745,0.212205049080897,0.17543028916496,0.0367747599159373,187955,634749,0.0692215742801715,0.080136432850393,867533 +INF0013,4,SEB,2025-08-22,Male,HEU-lo,1108496,975841,843244,746237,0.875108042083145,0.883216596890227,0.866020047837951,0.519903895332278,0.895616419796358,0.120630189357234,0.774986230439124,0.60606979915586,0.00892739987656181,0.991072600123438,0.00634200154540727,0.984730598578031,0.529000685227753,0.455729913350278,0.401436548396032,0.0542933649542453,205771,339517,0.116783403109773,0.133979952162049,653038 +INF0013,9,SEB,2025-08-22,Male,HEU-lo,338400,296428,235954,224609,0.973162250844801,0.98512679510113,0.96496035794511,0.781618713428889,0.98204826540706,0.217726972086136,0.764321293320925,0.748031864767892,0.00402976549112278,0.995970234508877,0.00665106925719294,0.989319165251684,0.625662172630459,0.363656992621226,0.337897792627485,0.0257591999937402,127799,170847,0.0148732048988705,0.0350396420548904,218581 +INF0023,0,SEB,2025-08-22,Female,HEU-hi,1553624,1392141,1200738,1097477,0.961156361363382,0.842094635525342,0.839047748156842,0.695863949937763,0.866243886489653,0.296521940520142,0.569721945969511,0.334008146805989,0.00759466823291404,0.992405331767086,0.010641508818299,0.981763822948787,0.657619956601896,0.324143866346891,0.233648214314848,0.0904956520320428,245172,734030,0.157905364474658,0.160952251843158,1054847 +INF0023,4,SEB,2025-08-22,Female,HEU-hi,1938960,1727707,1390235,1352003,0.974983043676678,0.973879895006752,0.968768301749382,0.812414086088395,0.935776929484139,0.488083943718788,0.447692985765351,0.423472417798728,0.00190297684674752,0.998097023153252,0.0136758544652701,0.984421168687982,0.703230429988975,0.281190738699008,0.245587651598677,0.0356030871003308,453500,1070908,0.0261201049932482,0.0312316982506182,1318180 +INF0023,9,SEB,2025-08-22,Female,HEU-hi,904872,793595,633506,611464,0.957374432509518,0.979145883156816,0.968143149982918,0.821083020157158,0.971231343438841,0.380720755957409,0.590510587481432,0.543729273377134,0.00462215419934953,0.99537784580065,0.0153969772335948,0.979980868567056,0.561159364836426,0.418821503730629,0.359801033097379,0.0590204706332504,261350,480662,0.0208541168431842,0.0318568500170824,585400 +INF0030,0,SEB,2025-08-22,Male,HU,1039944,924772,816017,756973,0.967017317658622,0.960038578918752,0.938458154714579,0.543828875719598,0.88617032500515,0.227832679370789,0.65833764563436,0.221035153208101,0.00398904433407962,0.99601095566592,0.0100464820265709,0.985964473639349,0.606050618813288,0.379913854826062,0.328624518416656,0.0512893364094055,87991,398086,0.039961421081248,0.0615418452854212,732006 +INF0030,4,SEB,2025-08-22,Male,HU,776400,671086,524037,503966,0.974065710782077,0.979785942439947,0.9725400084743,0.853854991688667,0.979747300514847,0.400874141723567,0.57887315879128,0.548695706112789,0.00444805815955615,0.995551941840444,0.0138442005669861,0.981707741273458,0.59258309129172,0.389124649981738,0.320364540758648,0.0687601092230899,229988,419154,0.0202140575600535,0.0274599915256999,490896 +INF0030,9,SEB,2025-08-22,Male,HU,1288944,1140767,954830,930021,0.996728030872421,0.988507817877015,0.982723430329522,0.876881651991741,0.981596850587439,0.215690471796764,0.765906378790675,0.717375899612475,0.00418782444063733,0.995812175559363,0.0166741265504983,0.979138049008864,0.543307626745141,0.435830422263723,0.388106029815526,0.0477243924481967,583119,812850,0.0114921821229845,0.0172765696704776,926978 +INF0166,0,Ctrl,2025-08-28,Female,HU,1142328,1017218,889137,819646,0.902212662539682,0.902008803304958,0.89485256830675,0.618988634135457,0.762528427772158,0.0749357166420165,0.687592711130142,0.492966515852921,0.00387325504099269,0.996126744959007,0.00858852204741857,0.987538222911589,0.842814092621316,0.144724130290273,0.135945047640151,0.00877908265012187,225650,457739,0.0979911966950419,0.10514743169325,739495 +INF0166,4,Ctrl,2025-08-28,Female,HU,910864,805652,630109,604513,0.989270702201607,0.977171599275618,0.961137206179654,0.796360365000242,0.943407279866455,0.410589087549476,0.53281819231698,0.485300633077513,0.0113749448343299,0.98862505516567,0.00761502583051375,0.981010029335156,0.667746904232397,0.31326312510276,0.263912565657964,0.0493505594447954,231122,476245,0.022828400724382,0.0388627938203459,598027 +INF0166,9,Ctrl,2025-08-28,Female,HU,1053896,933222,740554,713494,0.978962682236991,0.979133380292176,0.963402168124109,0.803150823784081,0.935201822498877,0.276155639692828,0.659046182806049,0.631649874863633,0.00772968945782113,0.992270310542179,0.00842956641493673,0.983840744127242,0.701231557677763,0.282609186449479,0.242981475837312,0.0396277106121666,354348,560988,0.0208666197078243,0.0365978318758912,698484 +INF0199,0,Ctrl,2025-08-28,Male,HEU-hi,1729240,1545717,1379096,1282394,0.867265442601884,0.896476816618952,0.873258369178979,0.717055573937938,0.28363795498889,0.0213393990159149,0.262298555972975,0.21283724476233,0.00818329641325352,0.991816703586746,0.0199721921101004,0.971844511476646,0.552840882311354,0.419003629165292,0.373862940095207,0.0451406890700853,169736,797492,0.103523183381048,0.126741630821021,1112176 +INF0199,4,Ctrl,2025-08-28,Male,HEU-hi,955672,847071,733820,687490,0.930010618336267,0.934141729475596,0.901921100828468,0.565672932701256,0.826955617735211,0.233648348245391,0.59330726948982,0.521875933155642,0.0159364238410596,0.98406357615894,0.0125139072847682,0.971549668874172,0.286638410596027,0.684911258278146,0.529997350993378,0.154913907284768,188750,361676,0.0658582705244044,0.0980788991715321,639373 +INF0199,9,Ctrl,2025-08-28,Male,HEU-hi,1090984,980857,815737,784725,0.987602026187518,0.97428760922637,0.950512002642594,0.742637381354226,0.926212033547567,0.20359800604996,0.722614027497607,0.674732121603848,0.00524803263153558,0.994751967368464,0.0140136376745911,0.980738329693873,0.336626014585308,0.644112315108566,0.534534526801533,0.109577788307033,388336,575541,0.0257123907736297,0.0494879973574057,774996 +INF0207,0,Ctrl,2025-08-28,Male,HEU-lo,1373960,1231782,1089637,986621,0.917642134112288,0.63901299475902,0.63159830565573,0.394152634572797,0.91575499086456,0.337731048165626,0.578023942698934,0.109443130485467,0.0260914095506337,0.973908590449366,0.015567789015491,0.958340801433875,0.651952374855972,0.306388426577903,0.247727563692229,0.058660862885674,39055,356852,0.36098700524098,0.36840169434427,905365 +INF0207,4,Ctrl,2025-08-28,Male,HEU-lo,864640,768455,603156,581744,0.986143389532165,0.971151315273418,0.956406238288393,0.818066772067501,0.970326712989894,0.492044720878053,0.478281992111841,0.372480082503926,0.00918716999696812,0.990812830003032,0.0178766539480233,0.972936176055009,0.451521374757593,0.521414801297416,0.454879325435189,0.0665354758622268,174809,469311,0.0288486847265824,0.0435937617116072,573683 +INF0207,9,Ctrl,2025-08-28,Male,HEU-lo,1155280,1020738,803205,743244,0.981793327628612,0.965042372881356,0.952004352402044,0.778534545135615,0.96670867760594,0.315897033300124,0.650811644305816,0.601995050219501,0.00591233256432074,0.994087667435679,0.0177428456974769,0.976344821738202,0.702509086337015,0.273835735401188,0.238192147884338,0.0356435875168496,341997,568106,0.034957627118644,0.0479956475979565,729712 +INF0166,0,PPD,2025-08-28,Female,HU,1421024,1265409,1081320,999289,0.913050178677039,0.909845561326654,0.902988927017835,0.662145262883316,0.743515597326456,0.0731665734214804,0.670349023904976,0.475618314899477,0.00287811346100974,0.99712188653899,0.009069363578466,0.988052522960524,0.838769963214439,0.149282559746086,0.140460289342628,0.00882227040345791,287341,604142,0.0901544386733465,0.0970110729821646,912401 +INF0166,4,PPD,2025-08-28,Female,HU,895072,775403,609274,585499,0.990645586072735,0.976435376589164,0.957963663447249,0.793280254886884,0.965443797270277,0.420251238807268,0.54519255846301,0.498737285925411,0.00980917643880268,0.990190823561197,0.00757367776572148,0.982617145795476,0.681099359854279,0.301517785941197,0.251665729761765,0.0498520561794325,229479,460120,0.0235646234108361,0.0420363365527514,580022 +INF0166,9,PPD,2025-08-28,Female,HU,996616,876933,700861,676818,0.985086094045962,0.980557172083201,0.964765030207402,0.808679453566993,0.94496500150232,0.279680098522533,0.665284902979787,0.638831083562391,0.0074672798429897,0.99253272015701,0.00825697662265268,0.984275743534358,0.704746309909533,0.279529433624824,0.239013924212336,0.0405155094124888,344436,539166,0.0194428279167992,0.0352349697925979,666724 +INF0199,0,PPD,2025-08-28,Male,HEU-hi,1516328,1353418,1204623,1122951,0.855110329836297,0.90664797703091,0.883277948277891,0.726175661053875,0.292509192494565,0.020824370292611,0.271684822201954,0.22272797673338,0.00813212285107205,0.991867877148928,0.019490052153757,0.972377824995171,0.554053183954671,0.4183246410405,0.370826089755972,0.0474985512845277,155310,697308,0.0933520229690903,0.116722051722109,960247 +INF0199,4,PPD,2025-08-28,Male,HEU-hi,897696,790855,670560,632602,0.937085244751044,0.939225913542802,0.909882220370377,0.599200070175202,0.859586100499146,0.233278060398584,0.626308040100561,0.548494258277568,0.0174050064415462,0.982594993558454,0.0131551257769634,0.96943986778149,0.267480713856767,0.701959153924724,0.548701681987794,0.153257471936929,194829,355207,0.0607740864571982,0.0901177796296234,592802 +INF0199,9,PPD,2025-08-28,Male,HEU-hi,858968,768197,633815,610401,0.98810617938044,0.973886703109223,0.953236473726707,0.773676470344414,0.952894761655766,0.188153078630881,0.764741683024885,0.707733651068499,0.00545943425363508,0.994540565746365,0.0140497919782955,0.980490773768069,0.311602584677248,0.668888189090821,0.558709357040339,0.110178832050482,330254,466636,0.0261132968907768,0.0467635262732926,603141 +INF0207,0,PPD,2025-08-28,Male,HEU-lo,1232224,1105088,964965,866432,0.912570172846802,0.669899327161431,0.662423483583751,0.437218596650984,0.927630893838588,0.339022273647671,0.588608620190917,0.112016199016488,0.0265210205557277,0.973478979444272,0.0136607788451606,0.959818200599112,0.65434872430534,0.305469476293771,0.245945666769962,0.0595238095238095,38724,345700,0.330100672838569,0.337576516416249,790680 +INF0207,4,PPD,2025-08-28,Male,HEU-lo,964456,862394,674289,650158,0.985832674519117,0.971358006200201,0.957436418299797,0.726423557642052,0.962862892746763,0.463789655905618,0.499073236841144,0.370627943788539,0.0095095153102617,0.990490484689738,0.0172283906260866,0.973262094063652,0.403937090007186,0.569325004056466,0.502746806981757,0.0665781970747085,172564,465599,0.0286419937997994,0.042563581700203,640947 +INF0207,9,PPD,2025-08-28,Male,HEU-lo,1131528,982637,762643,713953,0.983508718361013,0.955307692198143,0.941492126651466,0.919422255578706,0.941057839308921,0.299647304286407,0.641410535022514,0.565919401981726,0.00585728479268223,0.994142715207318,0.0182533795712139,0.975889335636104,0.679510725126383,0.296378610509721,0.256338321148904,0.040040289360817,365357,645599,0.0446923078018568,0.0585078733485337,702179 +INF0166,0,SEB,2025-08-28,Female,HU,1550664,1380306,1200328,1097863,0.91635112942143,0.876639616392387,0.869641799234216,0.617185605172023,0.785068915423591,0.0850933957797154,0.699975519643875,0.529613178162234,0.00253922880428172,0.997460771195718,0.00601508332319669,0.991445687872522,0.822019827271621,0.1694258606009,0.142005230507238,0.0274206300936626,328840,620906,0.123360383607613,0.130358200765784,1006028 +INF0166,4,SEB,2025-08-28,Female,HU,775352,679787,538754,516822,0.988949773809938,0.976631299267674,0.959359121599809,0.795521912069981,0.960580423020167,0.423162813575996,0.537417609444171,0.494367929168716,0.0101387990647231,0.989861200935277,0.0036664842545147,0.986194716680762,0.640256703646585,0.345938013034177,0.290030346748918,0.0559076662852594,201010,406600,0.0233687007323262,0.0406408784001909,511111 +INF0166,9,SEB,2025-08-28,Female,HU,1043248,923970,742880,716921,0.981115074045815,0.982730578831986,0.967342070169552,0.814757841400548,0.945940050882416,0.303301773206814,0.642638277675602,0.6141730909497,0.00777898367493053,0.992221016325069,0.0048838834686653,0.987337132856404,0.680834379812145,0.306502753044259,0.259226533778063,0.0472762192661958,351974,573086,0.017269421168014,0.0326579298304478,703382 +INF0199,0,SEB,2025-08-28,Male,HEU-hi,1582712,1412403,1263938,1177939,0.869944029359755,0.866133979220115,0.843422874658084,0.708885464717426,0.282640716716408,0.0414248427915377,0.24121587392487,0.187879255090691,0.0113936107854631,0.988606389214537,0.0120896834701055,0.976516705744431,0.533514067995311,0.443002637749121,0.377667057444314,0.0653355803048066,136480,726424,0.133866020779885,0.156577125341916,1024741 +INF0199,4,SEB,2025-08-28,Male,HEU-hi,915104,813472,701070,665961,0.932535088391062,0.95633880379755,0.926079493488258,0.603382756444112,0.84911133646456,0.242567783945346,0.606543552519214,0.533737190435525,0.017189828101719,0.982810171898281,0.0044249557504425,0.978385216147839,0.242657573424266,0.735727642723573,0.579969200307997,0.155758442415576,200002,374720,0.0436611962024501,0.0739205065117418,621032 +INF0199,9,SEB,2025-08-28,Male,HEU-hi,333800,301408,254051,245249,0.982495341469282,0.988259267252112,0.96349125981507,0.795941997709125,0.948302022556273,0.205358027394975,0.742943995161299,0.688774525906344,0.00454208239337462,0.995457917606625,0.00611667095641115,0.989341246650214,0.31760511135672,0.671736135293494,0.553104513315872,0.118631621977623,132098,191787,0.0117407327478876,0.03650874018493,240956 +INF0207,0,SEB,2025-08-28,Male,HEU-lo,1196056,1073884,953274,871433,0.919260574249541,0.604085265531025,0.597713819197727,0.39015496695686,0.891970064919067,0.385367773394381,0.506602291524686,0.11529933481153,0.022005772005772,0.977994227994228,0.0057997557997558,0.972194472194472,0.417637917637918,0.554556554556555,0.39005439005439,0.164502164502165,36036,312543,0.395914734468975,0.402286180802273,801074 +INF0207,4,SEB,2025-08-28,Male,HEU-lo,766016,680078,547528,530330,0.987837761393849,0.981113995571505,0.966207910208445,0.830596701534703,0.969487490031783,0.511599901639269,0.457887588392514,0.360494377581107,0.00866361092163225,0.991336389078368,0.00758623767236378,0.983750151406004,0.409236084991362,0.574514066414642,0.498772814494176,0.0757412519204656,156863,435133,0.0188860044284951,0.0337920897915553,523880 +INF0207,9,SEB,2025-08-28,Male,HEU-lo,677136,599173,485830,453507,0.985559208567894,0.957409868488762,0.946164964045839,0.899464826672752,0.94905764098074,0.329227432261338,0.619830208719402,0.550475967792887,0.00663340924700864,0.993366590752991,0.00992752051476702,0.983439070238224,0.675970610562846,0.307468459675379,0.258983118244587,0.048485341430792,221304,402023,0.0425901315112381,0.0538350359541613,446958 +INF0614,0,Ctrl,2025-08-30,Female,HU,2502056,2240583,1939275,1791189,0.875958371785445,0.859828541236591,0.858035050194167,0.720463324892751,0.868600121017824,0.205269406198802,0.663330714819022,0.198508154548961,0.00489313535000624,0.995106864649994,0.0189308187311717,0.976176045918822,0.539608549172,0.436567496746823,0.383946237900854,0.0526212588459687,224396,1130412,0.140171458763409,0.141964949805833,1569007 +INF0614,4,Ctrl,2025-08-30,Female,HU,1391096,1344752,1105255,990319,0.672744842823373,0.908350244359322,0.897685791135821,0.636089230178076,0.813475292779559,0.300045070236418,0.513430222543141,0.384902178709387,0.00855224841369586,0.991447751586304,0.0171044968273917,0.974343254758912,0.342206418784293,0.632136835974619,0.525016092940563,0.107120743034056,163115,423783,0.0916497556406777,0.102314208864179,666232 +INF0614,9,Ctrl,2025-08-30,Female,HU,985816,886942,751813,687188,0.944112819199404,0.96687644404986,0.93044823924178,0.507858559795802,0.823181280160248,0.305544933078394,0.517636347081854,0.383501775471183,0.0226970560303894,0.977302943969611,0.0197293447293447,0.957573599240266,0.266927825261159,0.690645773979107,0.576155428933207,0.114490345045901,126360,329490,0.0331235559501405,0.0695517607582197,648783 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+"39","INF0148",4,"PPD","2025-07-29","Female","HU",632312,562703,496868,467363,0.97,0.99,0.95,0.51,0.91,0.24,0.67,0.64,0,1,0.02,0.98,0.62,0.36,0.31,0.05,149173,233126,0.01,0.05,454573 +"40","INF0148",9,"PPD","2025-07-29","Female","HU",1110656,997595,827243,774214,0.98,0.98,0.95,0.65,0.96,0.2,0.76,0.73,0.01,0.99,0.02,0.97,0.56,0.41,0.36,0.05,363374,497273,0.02,0.05,759497 +"41","INF0191",0,"PPD","2025-07-29","Female","HEU-hi",1968064,1782256,1568308,1456260,0.49,0.88,0.86,0.58,0.8,0.2,0.6,0.13,0.04,0.96,0.02,0.94,0.45,0.49,0.38,0.11,53044,416511,0.12,0.14,712427 +"42","INF0191",4,"PPD","2025-07-29","Female","HEU-hi",1066672,941050,756678,723688,0.98,0.97,0.95,0.79,0.96,0.29,0.67,0.61,0.01,0.99,0.02,0.97,0.63,0.34,0.24,0.1,342753,563385,0.03,0.05,708666 +"43","INF0191",9,"PPD","2025-07-29","Female","HEU-hi",2415400,2151222,1768089,1652532,0.94,0.93,0.91,0.65,0.89,0.41,0.48,0.35,0.03,0.97,0.01,0.96,0.54,0.42,0.28,0.14,348982,1008178,0.07,0.09,1551941 +"44","INF0134",0,"SEB","2025-07-29","Female","HEU-lo",1193160,1079791,959139,869331,0.78,0.81,0.79,0.57,0.88,0.16,0.71,0.35,0.01,0.99,0.02,0.98,0.63,0.34,0.26,0.08,133436,385613,0.19,0.21,680674 +"45","INF0134",4,"SEB","2025-07-29","Female","HEU-lo",1291352,1157622,964426,923312,0.98,0.98,0.96,0.74,0.94,0.34,0.6,0.5,0.01,0.99,0.02,0.97,0.6,0.37,0.3,0.07,336815,671899,0.02,0.04,907293 +"46","INF0148",0,"SEB","2025-07-29","Female","HU",2042880,1841683,1602125,1513482,0.68,0.9,0.89,0.66,0.87,0.22,0.65,0.38,0,1,0.01,0.99,0.66,0.33,0.26,0.07,258231,674787,0.1,0.11,1029390 +"47","INF0191",0,"SEB","2025-07-29","Female","HEU-hi",1956304,1772838,1558215,1448120,0.5,0.87,0.86,0.58,0.81,0.21,0.61,0.15,0.03,0.97,0.01,0.95,0.46,0.49,0.37,0.12,65249,423955,0.13,0.14,724947 +"48","INF0191",9,"SEB","2025-07-29","Female","HEU-hi",1814944,1620273,1311159,1239312,0.96,0.95,0.94,0.69,0.92,0.41,0.5,0.38,0.02,0.98,0.01,0.97,0.55,0.42,0.27,0.15,311704,823331,0.05,0.06,1184775 +"49","INF0124",0,"Ctrl","2025-07-31","Male","HEU-hi",1229248,1096279,962417,891568,0.77,0.86,0.85,0.62,0.85,0.22,0.63,0.16,0.01,0.99,0.01,0.98,0.67,0.3,0.26,0.04,70297,426584,0.14,0.15,687720 +"50","INF0124",4,"Ctrl","2025-07-31","Male","HEU-hi",1105296,993220,820093,766344,0.9,0.95,0.94,0.7,0.91,0.26,0.65,0.48,0.01,0.99,0.01,0.98,0.51,0.47,0.42,0.05,230924,482090,0.05,0.06,689596 +"51","INF0124",9,"Ctrl","2025-07-31","Male","HEU-hi",1017128,915840,757350,701114,0.75,0.95,0.95,0.74,0.9,0.34,0.56,0.53,0,1,0.01,0.99,0.66,0.32,0.29,0.03,208211,389289,0.05,0.05,522851 +"52","INF0149",0,"Ctrl","2025-07-31","Female","HU",1327920,1192637,1046943,958252,0.9,0.89,0.87,0.54,0.84,0.16,0.68,0.23,0.02,0.98,0.02,0.96,0.62,0.34,0.3,0.04,107900,464503,0.11,0.13,857845 +"53","INF0149",4,"Ctrl","2025-07-31","Female","HU",1026960,910155,731344,694429,0.95,0.98,0.95,0.67,0.91,0.29,0.62,0.55,0.01,0.99,0.02,0.97,0.67,0.3,0.26,0.04,240028,439671,0.02,0.05,656832 +"54","INF0149",9,"Ctrl","2025-07-31","Female","HU",757368,665858,536020,502656,0.94,0.97,0.93,0.66,0.9,0.18,0.71,0.63,0.01,0.99,0.03,0.96,0.61,0.35,0.3,0.04,196467,310643,0.03,0.07,470072 +"55","INF0169",0,"Ctrl","2025-07-31","Female","HEU-lo",1288912,1144653,1051293,973587,0.88,0.84,0.83,0.35,0.77,0.13,0.64,0.25,0.01,0.99,0.02,0.97,0.75,0.23,0.14,0.09,75540,300763,0.16,0.17,854594 +"56","INF0169",4,"Ctrl","2025-07-31","Female","HEU-lo",1068232,944862,869444,785215,0.92,0.95,0.87,0.37,0.78,0.17,0.61,0.38,0.01,0.99,0.02,0.97,0.81,0.16,0.09,0.07,100425,264885,0.05,0.13,719400 +"57","INF0169",9,"Ctrl","2025-07-31","Female","HEU-lo",778672,685649,594814,542125,0.95,0.98,0.92,0.57,0.87,0.3,0.57,0.46,0.02,0.98,0.02,0.96,0.83,0.13,0.08,0.05,136465,295876,0.02,0.08,515731 +"58","INF0124",0,"PPD","2025-07-31","Male","HEU-hi",1246824,1108772,973652,900843,0.78,0.86,0.86,0.64,0.81,0.21,0.6,0.15,0.01,0.99,0.01,0.98,0.67,0.31,0.27,0.04,68997,452525,0.14,0.14,703680 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+"64","INF0169",0,"PPD","2025-07-31","Female","HEU-lo",1218624,1082765,987457,903485,0.86,0.84,0.83,0.38,0.76,0.12,0.64,0.25,0.01,0.99,0.01,0.97,0.74,0.23,0.13,0.1,74296,297323,0.16,0.17,773674 +"65","INF0169",4,"PPD","2025-07-31","Female","HEU-lo",940776,820971,737842,662123,0.93,0.93,0.85,0.38,0.74,0.16,0.58,0.34,0.01,0.99,0.02,0.97,0.81,0.16,0.09,0.07,80159,234002,0.07,0.15,613226 +"66","INF0169",9,"PPD","2025-07-31","Female","HEU-lo",1054184,923351,814226,740463,0.94,0.96,0.9,0.52,0.79,0.26,0.52,0.42,0.02,0.98,0.02,0.96,0.83,0.13,0.08,0.05,150495,361396,0.04,0.1,696984 +"67","INF0124",0,"SEB","2025-07-31","Male","HEU-hi",1004008,900404,794342,737214,0.82,0.86,0.85,0.65,0.91,0.24,0.66,0.18,0.01,0.99,0.01,0.98,0.66,0.32,0.26,0.07,69374,388022,0.14,0.15,601085 +"68","INF0124",4,"SEB","2025-07-31","Male","HEU-hi",1571248,1425147,1204162,1120656,0.88,0.9,0.89,0.64,0.78,0.24,0.54,0.41,0.01,0.99,0,0.99,0.49,0.5,0.45,0.06,255776,627446,0.1,0.11,985662 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+"84","INF0019",0,"PPD","2025-08-05","Female","HEU-lo",1271392,1149523,966376,895883,0.93,0.91,0.91,0.72,0.94,0.1,0.84,0.36,0.01,0.99,0.01,0.98,0.74,0.24,0.22,0.02,216135,602680,0.09,0.09,834677 +"85","INF0019",4,"PPD","2025-08-05","Female","HEU-lo",1374576,1213048,954728,905952,0.93,0.96,0.94,0.72,0.89,0.36,0.53,0.45,0,1,0.01,0.98,0.66,0.32,0.29,0.03,270713,602258,0.04,0.06,841834 +"86","INF0019",9,"PPD","2025-08-05","Female","HEU-lo",1725968,1521365,1188395,1141230,0.94,0.97,0.97,0.81,0.96,0.22,0.74,0.72,0,1,0.02,0.98,0.7,0.28,0.26,0.02,624909,871175,0.03,0.03,1071855 +"87","INF0032",0,"PPD","2025-08-05","Female","HU",1240368,1107613,907113,859658,0.98,0.92,0.91,0.7,0.98,0.17,0.81,0.67,0.01,0.99,0.01,0.98,0.72,0.26,0.23,0.03,393929,586509,0.08,0.09,839233 +"88","INF0032",4,"PPD","2025-08-05","Female","HU",774384,688988,533872,502702,0.96,0.94,0.93,0.81,0.96,0.36,0.6,0.45,0.01,0.99,0.01,0.97,0.68,0.29,0.22,0.08,176652,392277,0.06,0.07,484001 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+"99","INF0155",0,"Ctrl","2025-08-07","Female","HEU-lo",1956872,1761294,1560508,1450803,0.73,0.86,0.85,0.71,0.83,0.24,0.58,0.38,0.01,0.99,0.01,0.98,0.7,0.28,0.23,0.05,281626,750862,0.14,0.15,1065048 +"100","INF0155",4,"Ctrl","2025-08-07","Female","HEU-lo",1215184,1083687,851644,825005,0.98,0.99,0.98,0.85,0.97,0.34,0.63,0.6,0,1,0.01,0.99,0.72,0.26,0.22,0.04,412580,693213,0.01,0.02,811417 +"101","INF0155",9,"Ctrl","2025-08-07","Female","HEU-lo",1123680,1000603,815357,761574,0.98,0.96,0.93,0.62,0.93,0.32,0.61,0.5,0.01,0.99,0.01,0.98,0.5,0.48,0.4,0.08,228822,461857,0.04,0.07,747029 +"102","INF0158",0,"Ctrl","2025-08-07","Male","HU",1974064,1742021,1484261,1352364,0.92,0.8,0.79,0.61,0.93,0.33,0.6,0.37,0,1,0.02,0.97,0.59,0.38,0.36,0.02,280913,766092,0.2,0.21,1249338 +"103","INF0158",4,"Ctrl","2025-08-07","Male","HU",1017536,914368,805877,754118,0.95,0.97,0.92,0.57,0.83,0.59,0.23,0.2,0.01,0.99,0.02,0.97,0.57,0.4,0.37,0.03,79380,403772,0.03,0.08,714462 +"104","INF0158",9,"Ctrl","2025-08-07","Male","HU",1148432,1020361,904910,847242,0.96,0.96,0.91,0.57,0.8,0.32,0.48,0.43,0.01,0.99,0.02,0.97,0.51,0.46,0.43,0.03,199112,458838,0.04,0.09,810976 +"105","INF0159",0,"Ctrl","2025-08-07","Male","HEU-hi",2024024,1786795,1447822,1277260,0.93,0.82,0.81,0.65,0.95,0.16,0.78,0.58,0.01,0.99,0.02,0.97,0.72,0.25,0.22,0.03,452551,775338,0.18,0.19,1190219 +"106","INF0159",4,"Ctrl","2025-08-07","Male","HEU-hi",1487344,1333646,1131385,1067284,0.94,0.98,0.94,0.65,0.76,0.26,0.49,0.43,0.01,0.99,0.02,0.96,0.49,0.47,0.39,0.08,275733,648745,0.02,0.06,1003414 +"107","INF0159",9,"Ctrl","2025-08-07","Male","HEU-hi",1167840,1028158,742821,709883,0.98,0.99,0.97,0.81,0.92,0.05,0.87,0.86,0,1,0.03,0.97,0.63,0.34,0.33,0.01,487443,567733,0.01,0.03,697474 +"108","INF0155",0,"PPD","2025-08-07","Female","HEU-lo",2221632,2004398,1728584,1609792,0.78,0.9,0.88,0.76,0.93,0.27,0.66,0.43,0.01,0.99,0.01,0.98,0.69,0.29,0.23,0.05,412907,962370,0.1,0.12,1262810 +"109","INF0155",4,"PPD","2025-08-07","Female","HEU-lo",1393256,1237743,976719,947853,0.99,0.99,0.98,0.86,0.96,0.34,0.62,0.59,0,1,0.01,0.99,0.72,0.27,0.23,0.04,473057,801339,0.01,0.02,935619 +"110","INF0155",9,"PPD","2025-08-07","Female","HEU-lo",1302344,1145745,915824,856281,0.98,0.96,0.93,0.65,0.97,0.34,0.63,0.5,0.01,0.99,0.01,0.98,0.5,0.48,0.41,0.07,273995,547508,0.04,0.07,839902 +"111","INF0158",0,"PPD","2025-08-07","Male","HU",1897704,1691391,1435638,1304624,0.92,0.85,0.84,0.66,0.9,0.3,0.6,0.38,0,1,0.02,0.97,0.6,0.37,0.35,0.02,300921,790739,0.15,0.16,1203885 +"112","INF0158",4,"PPD","2025-08-07","Male","HU",1229864,1101656,968001,903455,0.94,0.97,0.92,0.53,0.85,0.6,0.25,0.21,0.01,0.99,0.01,0.97,0.56,0.41,0.38,0.03,92726,450635,0.03,0.08,853125 +"113","INF0158",9,"PPD","2025-08-07","Male","HU",1371136,1216419,1068812,1005622,0.95,0.97,0.92,0.59,0.84,0.35,0.5,0.45,0.01,0.99,0.02,0.97,0.51,0.46,0.43,0.03,257109,566004,0.03,0.08,954296 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+"129","INF0023",4,"Ctrl","2025-08-22","Female","HEU-hi",1945688,1737383,1389603,1347134,0.97,0.97,0.97,0.83,0.92,0.47,0.45,0.43,0,1,0.02,0.97,0.71,0.26,0.24,0.03,460826,1083175,0.03,0.03,1307804 +"130","INF0023",9,"Ctrl","2025-08-22","Female","HEU-hi",987800,871641,686162,661242,0.97,0.98,0.97,0.82,0.98,0.33,0.65,0.6,0,1,0.04,0.96,0.58,0.38,0.33,0.05,314132,525176,0.02,0.03,639892 +"131","INF0030",0,"Ctrl","2025-08-22","Male","HU",1055672,939062,820166,756891,0.97,0.96,0.94,0.55,0.89,0.21,0.67,0.21,0,1,0.02,0.98,0.65,0.33,0.3,0.02,85521,401205,0.04,0.06,732321 +"132","INF0030",4,"Ctrl","2025-08-22","Male","HU",887272,774792,587687,558971,0.96,0.97,0.96,0.82,0.97,0.34,0.62,0.59,0,1,0.02,0.97,0.61,0.37,0.3,0.07,258250,440126,0.03,0.04,536358 +"133","INF0030",9,"Ctrl","2025-08-22","Male","HU",1059640,929289,780683,761469,1,0.99,0.98,0.88,0.98,0.19,0.79,0.73,0,1,0.03,0.96,0.53,0.44,0.39,0.04,489165,668650,0.01,0.02,759205 +"134","INF0013",0,"PPD","2025-08-22","Male","HEU-lo",1309848,1169793,941515,876615,0.96,0.94,0.93,0.76,0.94,0.09,0.85,0.28,0.01,0.99,0.01,0.98,0.85,0.13,0.12,0.01,182108,640422,0.06,0.07,843590 +"135","INF0013",4,"PPD","2025-08-22","Male","HEU-lo",1021264,890816,775431,680459,0.9,0.85,0.83,0.53,0.91,0.13,0.78,0.58,0.01,0.99,0.01,0.98,0.56,0.41,0.36,0.05,189329,324923,0.15,0.17,615551 +"136","INF0013",9,"PPD","2025-08-22","Male","HEU-lo",739216,639880,503620,472587,0.98,0.98,0.96,0.75,0.98,0.2,0.77,0.75,0.01,0.99,0.01,0.98,0.62,0.36,0.34,0.03,261044,346934,0.02,0.04,464537 +"137","INF0023",0,"PPD","2025-08-22","Female","HEU-hi",1572088,1406726,1193232,1088074,0.96,0.86,0.86,0.72,0.87,0.28,0.59,0.29,0.01,0.99,0.02,0.97,0.73,0.24,0.2,0.03,222251,757525,0.14,0.14,1048767 +"138","INF0023",4,"PPD","2025-08-22","Female","HEU-hi",1960856,1733414,1389954,1349503,0.97,0.97,0.97,0.82,0.92,0.48,0.44,0.41,0,1,0.02,0.97,0.71,0.26,0.23,0.03,442707,1073086,0.03,0.03,1314066 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Please see [Getting Help](/course/00_Homeworks/index.qmd) walkthrough for more detailed instructions. + +Within your branch, inside this "homeworks" folder, create a new folder (name it with your GitHub username). Then copy all files you will be submitting within your folder. Then commit the change to git, and push to GitHub. See [Getting Help](/course/00_Homeworks/index.qmd)for details on submitting the pull request to the UMGCCCFCSR/CytometryInR homework branch. \ No newline at end of file diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/images/00_CheckNamesTRUE.png b/course/04_IntroToTidyverse/homeworks/claude-chew/images/00_CheckNamesTRUE.png new file mode 100644 index 0000000..cb71c41 Binary files /dev/null and b/course/04_IntroToTidyverse/homeworks/claude-chew/images/00_CheckNamesTRUE.png differ diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/images/01_DataView.png b/course/04_IntroToTidyverse/homeworks/claude-chew/images/01_DataView.png new file mode 100644 index 0000000..10c6e7f Binary files /dev/null and b/course/04_IntroToTidyverse/homeworks/claude-chew/images/01_DataView.png differ diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/images/02_Glimpse.png b/course/04_IntroToTidyverse/homeworks/claude-chew/images/02_Glimpse.png new file mode 100644 index 0000000..13644d3 Binary files /dev/null and b/course/04_IntroToTidyverse/homeworks/claude-chew/images/02_Glimpse.png differ diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/images/03_ColumnClass.png b/course/04_IntroToTidyverse/homeworks/claude-chew/images/03_ColumnClass.png new file mode 100644 index 0000000..f2fff2a Binary files /dev/null and b/course/04_IntroToTidyverse/homeworks/claude-chew/images/03_ColumnClass.png differ diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/images/TakeAway.jpg b/course/04_IntroToTidyverse/homeworks/claude-chew/images/TakeAway.jpg new file mode 100644 index 0000000..4d60a0e Binary files /dev/null and b/course/04_IntroToTidyverse/homeworks/claude-chew/images/TakeAway.jpg differ diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/images/WebsiteBanner.png b/course/04_IntroToTidyverse/homeworks/claude-chew/images/WebsiteBanner.png new file mode 100644 index 0000000..71d5502 Binary files /dev/null and b/course/04_IntroToTidyverse/homeworks/claude-chew/images/WebsiteBanner.png differ diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/index.qmd b/course/04_IntroToTidyverse/homeworks/claude-chew/index.qmd new file mode 100644 index 0000000..dc71ad5 --- /dev/null +++ b/course/04_IntroToTidyverse/homeworks/claude-chew/index.qmd @@ -0,0 +1,582 @@ +--- +title: "04 - Introduction to Tidyverse" +author: "David Rach" +date: 02-23-2026 +format: html +toc: true +toc-depth: 5 +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +For the YouTube livestream schedule, see [here](https://www.youtube.com/@cytometryinr) + +For screen-shot slides, click [here](/course/04_IntroToTidyverse/slides.qmd) + + +# Background + +Within our daily workflows as cytometrist, after acquiring data on our respective instruments, we begin analyzing the resulting datasets. After implementing various workflows, we then export data for downstream statistical analysis. + +When I first started my Ph.D program, a substantial amount of my day was spent renaming column names of the exported data so that they would fit nicely in a Microsoft Excel sheet column; setting up formulas to combine proportion of positive cells across positive quadrants, etc. Once this was done, additional hours would go by as I copied and pasted contents of those columns over to a GraphPad Prism worksheet for statistical analysis. + +This of course was in an ideal scenario. Often times, the data was less organized, and instead of time spent copying and pasting over columns, it would first be spent rearranging values from individual cells in the worksheet that were separated by spaces, all the while trying to remember what various color codes and bold font stood for. + +Today, we will explore what makes data ["tidy"](https://vita.had.co.nz/papers/tidy-data.pdf), and how to use the toolsets implemented in the various [tidyverse](https://cran.r-project.org/web/packages/tidyverse/vignettes/paper.html) R packages. At it's simplest, if we think of and organize all our data in terms of rows and columns, we need fewer tools (ie. functions) to reshape and extract useful information that we are interested in. Additionally, this approach aligns more closely with how computers work, allowing us to carry out tasks that would otherwise have taken hours in mere seconds. + +The dataset we will be using today is a manually-gated spectral flow cytometry dataset (similar to ones we would see exported by commercial software), and has been intentionally left slightly messy. You could however just as easily use a "matrix" or "data.frame" object exported from inside an [fcs file](/course/03_InsideFCSFile/), or swap in your own dataset. You would just need to make sure to switch out the input data by providing an alternate [file path](/course/02_FilePaths/), etc. + +--- + +# Walk Through + +:::{.callout-important title="Housekeeping"} +As we do [every week](/course/02_FilePaths/index.qmd), on GitHub, sync your forked version of the CytometryInR course to bring in the most recent updates. Then within Positron, pull in those changes to your local computer. + +After creating a "Week04" project folder, copy over the contents of "course/04_IntroToTidyverse" to that folder. This will hopefully prevent any merge issues when you attempt to bring in new data to your local Cytometry in R folder next week. Please remember once you have set up your project folder to stage, commit and pus your changes to "Week04" to GitHub so that they are backed up remotely. + +If you are having issues syncing due to the Take-Home Problem merge conflict, see this [walkthrough](https://umgcccfcsr.github.io/CytometryInR/course/00_BonusContent/PullConflicts/) +::: + +--- + +## read.csv + +We will start by first loading in our copied over dataset (Dataset.csv) from it's location in the project folder. If you are following the organization scheme we have been using throughout the course, your file path will look something like this: + +```{r} +#| eval: FALSE +#| include: FALSE + +# For use only when building the website, otherwise keep eval to FALSE +thefilepath <- file.path(getwd(), "course", "04_IntroToTidyverse", "data", "Dataset.csv") + +thefilepath +``` +```{r} +#| eval: TRUE +thefilepath <- file.path("data", "Dataset.csv") + +thefilepath +``` + + +:::{.callout-tip title="Reminder"} +We encourage using the `file.path` function to build our file paths, as this keeps our code reproducible and replicable when a project folder is copied to other people's computers that differ on whether the operating system uses forward or backward slash separation between folders. +::: + +Above, we directly specified the name (Dataset) and filetype (.csv) of the file we wanted in the last argument of the file.path ("Dataset.csv"). This allows us to skip the `list.files()` step we used last week as we have provided the full file path. While this approach can be faster, if we accidentally mistype the file name, we could end up with an error at the next step due to no files being found with the mistyped name. + +Since our dataset is stored as a .csv file, we will be using the `read.csv()` function from the `utils` package (included in our base R software installation) to read it into R. We will also use the `colnames()` function from last week to get a read-out of the column names. + +```{r} +Data <- read.csv(file=thefilepath, check.names=FALSE) +colnames(Data) +``` + +As we look at the line of code, we now have enough context to decipher that the "file" argument is where we provide a file path to an individual file, but what does the "check.names" argument do? + +Let's see what happens to the column names when we set "check.names" argument to TRUE: + +```{r} +Data_Alternative <- read.csv(thefilepath, check.names=TRUE) +colnames(Data_Alternative) +``` + +As we can see, any column name that contained a special character or a space was automatically converted over to [R-approved syntax](https://ssojet.com/escaping/regex-escaping-in-r#understanding-the-need-for-escaping-special-characters). However, this resulted in the loss of both +" and "-", leaving us unable to determine whether we are looking at cells within or outside a particular gate. + +![](images/00_CheckNamesTRUE.png) + +Because of this, it is often better to rename columns individually after import, which we will learn how to do later today. + +Following up with what we practiced last week, lets use the `head()` function to visualize the first few rows of data. + +```{r} +head(Data, 3) +``` + +When working in Positron, we could have alternatively clicked on the little grid icon next to our created variable "Data" in the right secondary sidebar, which would have opened the data in our Editor window. From this same window, we can see it is stored as a "data.frame" object type. + +![](images/01_DataView.png) + +We could also achieve the same window to open using the `View()` function: + +```{r} +#| eval: FALSE +View(Data) +``` + +Wrapping up our brief recap of [last week](/course/03_InsideFCSFile/index.qmd) functions, we can check an objects type using both the `class()` and `str()` functions. + +```{r} +class(Data) +``` + +```{r} +str(Data) +``` + +## data.frame + +Or alternatively using the new-to-us `glimpse()` function + +```{r} +#| error: TRUE +glimpse(Data) +``` + +:::{.callout-tip title="Checkpoint 1"} +This however returns an error. Any idea why this might be occuring? +::: + +```{r} +#| code-fold: TRUE + +# We haven't attached/loaded the package in which the function glimpse is within +``` + +:::{.callout-tip title="Checkpoint 2"} +How would we locate a package a not-yet-loaded function is within? +::: + +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# We can use double ? to search all installed packages for a function, regardless +# if the package is attached to the environment or not + +??glimpse +``` + +![](images/02_Glimpse.png) + +From the list of search matches (in the right secondary sidebar), it looks likely that the `glimpse()` function in the `dplyr` package was the one we were looking for. This is one the main tidyverse packages we will be using throughout the course. Let's attach it to our environment via the `library()` call first and try running `glimpse()` again. + +```{r} +#| message: FALSE +#| warning: FALSE +library(dplyr) +glimpse(Data) +``` + +We notice that while similar to the `str()` output, `glimpse()` handles spacing a little differently, and includes the dimensions at the top. However, we can also retrieve the dimensions directly using the `dim()` function (which maintains the row followed by column position convention of base R (ex. [196,31])) + +```{r} +dim(Data) +``` + +## Column value type + +As we saw last week, functions often need values that match a certain type (the paintbrush needing paint analogy). As we inspect the columns of Data, we can notice some of the columns contain values within that are character (ie. "char") values. Others appear to contain numeric values (which are [subtyped](https://www.r-bloggers.com/2023/09/understanding-data-types-in-r/) as either double ("ie. dbl") or integer (ie. "int")). At first glance, we do not appear to have any logical (ie. TRUE or FALSE) columns in this dataset. + +![](images/03_ColumnClass.png) + +If we were trying to verify type of values contained within a data.frame column, we could employ several similarly-named functions (`is.character()`, `is.numeric()` or `is.logical()`) to check + +```{r} +# colnames(Data) # To recheck the column names + +is.character(Data$bid) +``` + +```{r} +is.numeric(Data$bid) +``` + +```{r} +# colnames(Data) # To recheck the column names + +is.character(Data$Tcells_count) +``` + +For numeric columns using the `is.numeric()` function, we can also be [subtype](https://www.r-bloggers.com/2023/09/understanding-data-types-in-r/) specific using either `is.integer()` or `is.double()`. + +```{r} +# colnames(Data) # To recheck the column names + +is.numeric(Data$Tcells_count) +is.integer(Data$Tcells_count) +is.double(Data$Tcells_count) +``` + +:::{.callout-tip title="Reminder"} +As we observed last week with keywords, column names that contain [special characters](https://ssojet.com/escaping/regex-escaping-in-r#understanding-the-need-for-escaping-special-characters) like $ or spaces will need to be surrounded with tick marks in order for the function to be able to run. +::: + +```{r} +#| error: TRUE + +# colnames(Data) # To recheck the column names +is.numeric(Data$CD8-) +``` + +```{r} +# colnames(Data) # To recheck the column names +is.numeric(Data$`CD8-`) +``` + +## select (Columns) + +Now that we have read in our data, and have a general picture of the structure and contents, lets start learning the main `dplyr` functions we will be using throughout the course. To do this, lets go ahead and attach `dplyr` to our local environment via the `library()` call. + +```{r} +library(dplyr) +``` + +We will start with the `select()` function. It is used to "select" a column from a data.frame type object. In the simplest usage, we provide the name of our data.frame variable/object as the first argument after the opening parenthesis. This is then followed by the name of the column we want to select as the second argument (let's place around the "" around the column name for now) + +```{r} +DateColumn <- select(Data, "Date") +DateColumn[1:10,] +``` + +This results in the column being selected, resulting in the new object containing only that subsetted out column from the original Data object. + +### Pipe Operators + +While the above line of code works to select a column, when you encounter `select()` out in the wild, it will more often be in a line of code that looks like this: + +```{r} +DateColumn <- Data |> select("Date") +DateColumn[1:10,] +``` + +... **"What in the world is that thing |> ?"** ... + +Glad you asked! An useful feature of the tidyverse packages is their use of [pipes](https://r4ds.had.co.nz/pipes.html) (either the original `magrittr` package's "%>%" or `base R version >4.1.0's` "|>""), usually appearing like this: + +```{r} +# magrittr %>% pipe + +DateColumn <- Data %>% select("Date") + +# base R |> pipe +DateColumn <- Data |> select("Date") +``` + +... **"How do we interpret/read that line of code?"** ... + +Let's break it down, starting off just to the right of the assignment arrow (<-) with our data.frame "Data". + +```{r} +#| eval: false + +Data +``` + +We then proceed to read to the right, adding in our pipe operator. The pipe essentially serves as an intermediate passing the contents of data onward to the subsequent function. + +```{r} +#| eval: FALSE +Data |> +``` + +In our case, this subsequent function is the `select()` function, which will select a particular column from the available data. When using the pipe, the first argument slot we saw for "select(Data, "Date")" is occupied by the contents Data that are being passed by the pipe. + +```{r} +#| eval: FALSE +Data |> select() +``` + +To complete the transfer, we provide the desired column name to `select()` to act on ("Date" in this case) + + +```{r} +#| eval: FALSE +Data |> select("Date") +``` + +In summary, contents of Data are passed to the pipe, and select runs on those contents to select the Date column + +```{r} +#| eval: FALSE +Data |> select("Date") +``` + +One of the main advantages for using pipes, is they can be linked together, passing resulting objects of one operation on to the next pipe and subsequent function. We can see this in operation in the example below where we hand off the isolated "Date" column to the `nrow()` function to determine number of rows. We will use pipes throughout the course, so you will gradually gain familiarity as you encounter them. + +```{r} +Data |> select("Date") |> nrow() +``` + +For those with prior R experience, you will be more familiar with the older magrittr %>% pipe. The base R |> pipe operator was introduced starting with R version 4.1.0. While mostly interchangeable, they have a [few nuances](https://tidyverse.org/blog/2023/04/base-vs-magrittr-pipe/) that come into play for more advance use cases. You are welcome to use whichever you prefer (my current preference is |> as it's one less key to press). + +### R Quirks + +:::{.callout-note title="Odd R Behavior # 1"} +While we used "" around the column name in our previous example, unlike what we encountered with `install.packages()` when we forget to include quotation marks, `select()` still retrieves the correct column despite Date not being an environment variable: +::: + +```{r} +Data |> select(Date) |> head(3) +``` + +:::{.callout-note title="."} +The reasons for this Odd R behaviour are nuanced and for [another day](https://adv-r.hadley.nz/evaluation.html). For now, think of it as `dplyr` R package is picking up the slack, and using context to infer it's a column name and not an environmental variable/object. +::: + +### Selecting multiple columns + +Since we are able to select one column, can we select multiple (similar to a [Data[,2:5]] approach in base R)? We can, and they can be positioned anywhere within the data.frame: + +```{r} +Subset <- Data |> select(bid, timepoint, Condition, Tcells, `CD8+`, `CD4+`) + +head(Subset, 3) +``` + +You will notice that the order in which we selected the columns will dictate their position in the subsetted data.frame object: + +```{r} +Subset <- Data |> select(bid, Tcells, `CD8+`, `CD4+`, timepoint, Condition, ) + +head(Subset, 3) +``` + +## relocate + +Alternatively, we occasionally want to move one column. While we could respecify the location using `select()`, specifying the names of all the other columns out in a line of code to just to rearrange one does not sound like a good use of time. For this reason, the second `dplyr` function we will be learning is the `relocate()` function. + +Looking at our Data object, let's say we wanted to move the Tcells column from its current location to the second column position (right after the bid column). The line of code to do so would look like: + +```{r} +Data |> relocate(Tcells, .after=bid) |> head(3) + +# |> head(3) is used only to make the website output visualization manageable :D +``` + +Similar to what we saw with `select()`, this approach can also be used for more than 1 column: + +```{r} +Data |> relocate(Tcells, Monocytes, .after=bid) |> head(3) + +# |> head(3) is used only to make the website output visualization manageable :D +``` + +We can also modify the argument so that columns are placed before a certain column + +```{r} +Data |> relocate(Tcells, .before=Date) |> head(3) + +# |> head(3) is used only to make the website output visualization manageable :D +``` + +And as we might suspect, we could specify a column index location rather than using a column name. + +```{r} +Data |> relocate(Date, .before=1) |> head(3) + +# |> head(3) is used only to make the website output visualization manageable :D +``` + +## rename + +At this point, we are able to both move and select particular columns, allowing us to rearrange and subset a larger data.frame object however we want it to appear. However, as we encountered, some of the names contain special characters and spaces, requiring use of tick marks (``) to avoid issues. How can we change a column name? + +In base R, we could change individual column names by assigning a new value with the assignment arrow to the corresponding column name index. For example, looking at our Subset object, wen could rename CD8+ as follows: + +```{r} +colnames(Subset) +colnames(Subset)[3] +``` + +```{r} +colnames(Subset)[3] <- "CD8Positive" +colnames(Subset) +``` + +With the tidyverse, we can use the `rename()` function which removes the need to look up the column index number. The way we write the argument is placing within the parenthesis the old name to the right of the equals sign, with the new name to the left + +```{r} +Renamed <- Subset |> rename(CD4_Positive = `CD4+`) +colnames(Renamed) +``` + +If we wanted to rename multiple column names at once, we would just need to include a comma between the individual rename arguments within the parenthesis. + +```{r} +Renamed_Multiple <- Subset |> rename(specimen = bid, timepoint_months = timepoint, stimulation = Condition, CD4Positive=`CD4+`) +colnames(Renamed_Multiple) +``` + +## pull + +Sometimes, we may want to retrieve individual values present in a column, to use within either a vector or a list. We can do this using the `pull()` function, which will retrieve the column contents and strip the column formatting + +```{r} +Data |> pull(Date) |> head(5) +``` + +This can be useful when we are doing data exploration, and trying to determine how many unique variants might be present. For example, if we wanted to see what days individual samples were acquired, we could `pull()` the data and pass it to the `unique()` function: + +```{r} +Data |> pull(Date) |> unique() +``` + + +## filter (Rows) + +So far, we have been working with `dplyr` functions primarily used when working with and subsetting columns (including `select()`, `pull()`, `rename()` and `relocate()`). What if we wanted to work with rows of a data.frame? This is where the `filter()` function is used. + +The Condition column in this Dataset appears to be indicating whether the samples were stimulated. Let's see how many unique values are contained within that column + +```{r} +Data |> pull(Condition) |> unique() +``` + +In the case of this dataset, looks like the .fcs files where treated with either left alone, treated with [PPD (Purified Protein Derrivative)](https://en.wikipedia.org/wiki/Tuberculin) or [SEB](https://en.wikipedia.org/wiki/Enterotoxin_type_B). What if we wanted to subset only those treated with PPD? + +Within `filter()`, we would specify the column name as the first argument, and ask that only values equal to (==) "PPD" be returned. Notice in this case, "" are needed, as we are asking for a matching character value. + +```{r} +PPDOnly <- Data |> filter(Condition == "PPD") +head(PPDOnly, 5) +``` + +While this works, using "==" to match can glitch, especially with character values. Using the %in% operator is a better way of identifying and extracting only the rows whose Condition column contains "PPD" + +```{r} +Data |> filter(Condition %in% "PPD") |> head(5) +``` + +Similar to what we saw for `select()`, we can grab rows that contain various values at once. We would just need to modify the second part of the argument. If we wanted to grab rows whose Condition column contained either PPD or SEB, we would need to provide that argument as a vector, placing both within `c()`/ + +```{r} +Data |> filter(Condition %in% c("PPD", "SEB")) |> head(5) +``` + +Alternatively, we could have set up the vector externally, and then provided it to `filter()` + +```{r} +TheseConditions <- c("PPD", "SEB") +Data |> filter(Condition %in% TheseConditions) |> head(5) +``` + +While this works when we have a limited number of variant condition values, what if had many more but only wanted to exclude one value? +As we saw when learning about [Conditionals](/course/02_FilePaths/index.qmd), when we add a ! in front of a logical value, we get the opposite logical value returned + +```{r} +IsThisASpectralInstrument <- TRUE + +!IsThisASpectralInstrument +``` + +In the context of the `dplyr` package, we can use ! within the `filter()` to remove rows that contain a certain value + +```{r} +Subset <- Data |> filter(!Condition %in% "SEB") +Subset |> pull(Condition) |> unique() +``` + +Likewise, we can also use it with the `select()` to exclude columns we don't want to include +```{r} +Subset <- Data |> select(!timepoint) +Subset[1:3,] +``` + + +## mutate + +As we can see, with just these handful of functions, we have the building blocks to rearrange and subset a larger data.frame into a format that we prefer. But what if we wanted to alter the content of a column, or add new columns to an existing data.frame? This is where the `mutate()` function can be used. + +Let's start by slimming down our current Data to a smaller workable example, highlighting the functions and pipes we learned about today + +```{r} +TidyData <- Data |> filter(Condition %in% "Ctrl") |> filter(timepoint %in% "0") |> + select(bid, timepoint, Condition, Date, Tcells_count, CD45_count) |> + rename(specimen=bid, condition=Condition) |> relocate(Date, .after=specimen) +``` + +```{r} +TidyData +``` + +The `mutate()` function can be used to modify existing columns, as well as to create new ones. For example, let's derrive the proportion of T cells from the overall CD45 gate. To do so, within the parenthesis, we would specify a new column name, and then divide the original columns: + +```{r} +TidyData <- TidyData |> mutate(Tcells_ProportionCD45 = Tcells_count / CD45_count) +TidyData +``` + +We can see that we have many significant digits being returned. Let's round this new column to 2 significant digits by applying the `round()` function + +```{r} +TidyData <- TidyData |> mutate(TcellsRounded = round(Tcells_ProportionCD45, 2)) +TidyData +``` + + +## arrange + +And while we are here, let's rearrange the rows so that they are descending based on the Tcell proportion. We can use this by using the `desc()` and `arrange()` functions from `dplyr`: + +```{r} +TidyData <- TidyData |> arrange(desc(TcellsRounded)) +``` + +And let's go ahead and `filter()` and identify the specimens that had more than 30% T cells as part of the overall CD45 gate (context, these samples were Cord Blood): + +```{r} +TidyData |> filter(TcellsRounded > 0.3) +``` + +Which is we had wanted to just retrieve the specimen IDs, we could add `pull()` after a new pipe argument. + +```{r} +TidyData |> filter(TcellsRounded > 0.3) |> pull(specimen) +``` + +And finally, since I may want to send the data to a supervisor, let's go ahead and export this "tidyed" version of our data.frame out to it's own .fcs file. Working within our project folder, this would look like this: + +```{r} +NewName <- paste0("MyNewDataset", ".csv") +StorageLocation <- file.path("data", NewName) +StorageLocation +``` +```{r} +#| eval: FALSE +write.csv(TidyData, StorageLocation, row.names=FALSE) +``` + +# Take Away + +In this session, we explored the main functions within the `dplyr` package used in context of "tidying" data, including selecting columns, filtering for rows, as well as additional functions used to create or modify existing values. We will continue to build on these throughout the course, introducing a few additional tidyverse functions we don't have time to cover today as appropiate. As we saw, knowing how to use these functions can allow us to extensively and quickly modify our existing exported data files. + +On important goal as we move through the course (in terms of both reproducibility and replicability) is to attempt to only modify files within R, not go back to the original csv or excel file and hand-modify individual values. This approach is not reproducible or replicable. Once set up, an R script can quickly re-carry out these same cleanup steps, and leave a documented process of how the data has changed (even more so if you are maintaining version control). If you do want to save the changes you have made, it is best to save it out as a new .csv file with which you work later. + +Next week, we will be using these skills when setting up metadata for our .fcs files. We will additionally take a look at the main format source of controversy within Bioconductor Flow Cytometry packages, ie. whether to use a flowframe or a cytoframe. Exciting stuff, but important information to know as the functions needed to import them are slightly different. We will also look at how to import existing manually gated .wsp from FlowJo/Diva/Floreada in via the `CytoML` package. + +![](images/TakeAway.jpg) + +# Additional Resources + +[Data Organization in Spreadsheets for Ecologists](https://datacarpentry.github.io/spreadsheet-ecology-lesson/) This Carpentry self-study course was one of my "Aha" moments early on when learning R, and reinforced the need to try to keep my own Excel/CSV files in a tidy manner. It is worth the time going through in its entirety (even for non-Ecologist). + +[Data Analysis and Visualization in R for Ecologists](https://datacarpentry.github.io/R-ecology-lesson/) Continuation of the above, and a good way to continue building on the tidyverse functions we learned today. + +[Simplistics: Introduction to Tidyverse in R](https://youtu.be/Bg4qxVNaDck?si=QPQq8TzOZ1w6XSy4) The YouTube channel is mainly focused on statistics for Psych classes, but at the end of the day, we are all working with similar objects with rows and columns, just the values contained within differ. + +[Riffomonas Project Playlist: Data Manipulation with R's Tidyverse](https://youtube.com/playlist?list=PLmNrK_nkqBpKf7j_ewpUm-w33R6PJYtD9&si=BVmDZPIXjRuHjERP) Riffomonas has a playlist that delves into both the tidyverse functions we used today, as well as other ones we will encounter later on in the course. + +# Take-home Problems + +:::{.callout-tip title="Problem 1"} +Taking a dataset (either todays or one of your own), work through the column-operating functions (`select()`, `rename()`, and `relocate()`). Once this is done, `filter()` by conditions from two separate columns, arrange in an order that makes sense, and export this "tidy" data as a .csv file. +::: + +:::{.callout-tip title="Problem 2"} +We used the `mutate()` function to create new columns, but it can also be used to modify existing ones. Various numeric columns are showing way to many significant digits. As was shown, use `round()` to round all these proportion columns, but use mutate to overwrite the existing column. Export this as it's own .csv file. +::: + +:::{.callout-tip title="Problem 3"} +We can also use `mutate()` to combine columns. For our dataset, "bid", "timepoint", "Condition" are separate columns that originally were all part of the filename for the individual .fcs file. Try to figure out a way to combine them back together using `paste0()`, and save the new column as "filename". Once this is done, `pull()` the contents of this column, and using try to determine whether there were any duplicates (think innovative ways of using !, `length()` and `unique()`) +::: + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +::: \ No newline at end of file diff --git a/course/04_IntroToTidyverse/homeworks/claude-chew/slides.qmd b/course/04_IntroToTidyverse/homeworks/claude-chew/slides.qmd new file mode 100644 index 0000000..97a8b8f --- /dev/null +++ b/course/04_IntroToTidyverse/homeworks/claude-chew/slides.qmd @@ -0,0 +1,1199 @@ +--- +title: "04 - Introduction to Tidyverse" +author: "David Rach" +date: 02-24-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + + +---- + +# Background + +::: {.fragment} +::: {.callout-tip title="."} +Within our daily workflows as cytometrist, after acquiring data on our respective instruments, we begin analyzing the resulting datasets. After implementing various workflows, we then export data for downstream statistical analysis. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +When I first started my Ph.D program, a substantial amount of my day was spent renaming column names of the exported data so that they would fit nicely in a Microsoft Excel sheet column; setting up formulas to combine proportion of positive cells across positive quadrants, etc. Once this was done, additional hours would go by as I copied and pasted contents of those columns over to a GraphPad Prism worksheet for statistical analysis. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This of course was in an ideal scenario. Often times, the data was less organized, and instead of time spent copying and pasting over columns, it would first be spent rearranging values from individual cells in the worksheet that were separated by spaces, all the while trying to remember what various color codes and bold font stood for. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +Today, we will explore what makes data ["tidy"](https://vita.had.co.nz/papers/tidy-data.pdf), and how to use the toolsets implemented in the various [tidyverse](https://cran.r-project.org/web/packages/tidyverse/vignettes/paper.html) R packages. At it's simplest, if we think of and organize all our data in terms of rows and columns, we need fewer tools (ie. functions) to reshape and extract useful information that we are interested in. Additionally, this approach aligns more closely with how computers work, allowing us to carry out tasks that would otherwise have taken hours in mere seconds. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The dataset we will be using today is a manually-gated spectral flow cytometry dataset (similar to ones we would see exported by commercial software), and has been intentionally left slightly messy. You could however just as easily use a "matrix" or "data.frame" object exported from inside an [fcs file](/course/03_InsideFCSFile/), or swap in your own dataset. You would just need to make sure to switch out the input data by providing an alternate [file path](/course/02_FilePaths/), etc. +::: +::: + +--- + +# Walk Through + +:::{.callout-important title="Housekeeping"} +As we do [every week](/course/02_FilePaths/index.qmd), on GitHub, sync your forked version of the CytometryInR course to bring in the most recent updates. Then within Positron, pull in those changes to your local computer. + +After creating a "Week04" project folder, copy over the contents of "course/04_IntroToTidyverse" to that folder. This will hopefully prevent any merge issues when you attempt to bring in new data to your local Cytometry in R folder next week. Please remember once you have set up your project folder to stage, commit and pus your changes to "Week04" to GitHub so that they are backed up remotely. + +If you are having issues syncing due to the Take-Home Problem merge conflict, see this [walkthrough](https://umgcccfcsr.github.io/CytometryInR/course/00_BonusContent/PullConflicts/) +::: + +--- + +## read.csv + +::: {.fragment} +::: {.callout-tip title="."} +We will start by first loading in our copied over dataset (Dataset.csv) from it's location in the project folder. If you are following the organization scheme we have been using throughout the course, your file path will look something like this: +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +#| include: FALSE + +# For use only when building the website, otherwise keep eval to FALSE +thefilepath <- file.path(getwd(), "course", "04_IntroToTidyverse", "data", "Dataset.csv") + +thefilepath +``` + +::: + +::: {.fragment} +```{r} +#| eval: TRUE +thefilepath <- file.path("data", "Dataset.csv") + +thefilepath +``` + +::: + +--- + +::: {.fragment} +:::{.callout-tip title="Reminder"} +We encourage using the `file.path` function to build our file paths, as this keeps our code reproducible and replicable when a project folder is copied to other people's computers that differ on whether the operating system uses forward or backward slash separation between folders. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Above, we directly specified the name (Dataset) and filetype (.csv) of the file we wanted in the last argument of the file.path ("Dataset.csv"). This allows us to skip the `list.files()` step we used last week as we have provided the full file path. While this approach can be faster, if we accidentally mistype the file name, we could end up with an error at the next step due to no files being found with the mistyped name. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Since our dataset is stored as a .csv file, we will be using the `read.csv()` function from the `utils` package (included in our base R software installation) to read it into R. We will also use the `colnames()` function from last week to get a read-out of the column names. +::: +::: + +::: {.fragment} +```{r} +Data <- read.csv(file=thefilepath, check.names=FALSE) +colnames(Data) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As we look at the line of code, we now have enough context to decipher that the "file" argument is where we provide a file path to an individual file, but what does the "check.names" argument do? + +Let's see what happens to the column names when we set "check.names" argument to TRUE: +::: +::: + + +::: {.fragment} +```{r} +Data_Alternative <- read.csv(thefilepath, check.names=TRUE) +colnames(Data_Alternative) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As we can see, any column name that contained a special character or a space was automatically converted over to [R-approved syntax](https://ssojet.com/escaping/regex-escaping-in-r#understanding-the-need-for-escaping-special-characters). However, this resulted in the loss of both +" and "-", leaving us unable to determine whether we are looking at cells within or outside a particular gate. +::: +::: + +::: {.fragment} +![](images/00_CheckNamesTRUE.png) +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Because of this, it is often better to rename columns individually after import, which we will learn how to do later today. + +Following up with what we practiced last week, lets use the `head()` function to visualize the first few rows of data. +::: +::: + +::: {.fragment} +```{r} +head(Data, 3) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +When working in Positron, we could have alternatively clicked on the little grid icon next to our created variable "Data" in the right secondary sidebar, which would have opened the data in our Editor window. From this same window, we can see it is stored as a "data.frame" object type. +::: +::: + +--- + +![](images/01_DataView.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We could also achieve the same window to open using the `View()` function: +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +View(Data) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Wrapping up our brief recap of [last week](/course/03_InsideFCSFile/index.qmd) functions, we can check an objects type using both the `class()` and `str()` functions. +::: +::: + +::: {.fragment} +```{r} +class(Data) +``` + +::: + +::: {.fragment} +```{r} +str(Data) +``` + +::: + +--- + +## data.frame + +::: {.fragment} +::: {.callout-tip title="."} +Or alternatively using the new-to-us `glimpse()` function +::: +::: + +::: {.fragment} +```{r} +#| error: TRUE +glimpse(Data) +``` + +::: + +--- + +:::{.callout-tip title="Checkpoint 1"} +This however returns an error. Any idea why this might be occuring? +::: + +::: {.fragment} +```{r} +#| code-fold: TRUE + +# We haven't attached/loaded the package in which the function glimpse is within +``` + +::: + +--- + +:::{.callout-tip title="Checkpoint 2"} +How would we locate a package a not-yet-loaded function is within? +::: + +::: {.fragment} +```{r} +#| code-fold: TRUE +#| eval: FALSE + +# We can use double ? to search all installed packages for a function, regardless +# if the package is attached to the environment or not + +??glimpse +``` + +::: + +--- + +![](images/02_Glimpse.png) + +::: {.fragment} +::: {.callout-tip title="."} +From the list of search matches (in the right secondary sidebar), it looks likely that the `glimpse()` function in the `dplyr` package was the one we were looking for. This is one the main tidyverse packages we will be using throughout the course. Let's attach it to our environment via the `library()` call first and try running `glimpse()` again. +::: +::: + +::: {.fragment} +```{r} +#| message: FALSE +#| warning: FALSE +library(dplyr) +glimpse(Data) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We notice that while similar to the `str()` output, `glimpse()` handles spacing a little differently, and includes the dimensions at the top. However, we can also retrieve the dimensions directly using the `dim()` function (which maintains the row followed by column position convention of base R (ex. [196,31])) +::: +::: + +::: {.fragment} +```{r} +dim(Data) +``` + +::: + +--- + +## Column value type + +::: {.fragment} +::: {.callout-tip title="."} +As we saw last week, functions often need values that match a certain type (the paintbrush needing paint analogy). As we inspect the columns of Data, we can notice some of the columns contain values within that are character (ie. "char") values. Others appear to contain numeric values (which are [subtyped](https://www.r-bloggers.com/2023/09/understanding-data-types-in-r/) as either double ("ie. dbl") or integer (ie. "int")). At first glance, we do not appear to have any logical (ie. TRUE or FALSE) columns in this dataset. +::: +::: + +--- + +![](images/03_ColumnClass.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we were trying to verify type of values contained within a data.frame column, we could employ several similarly-named functions (`is.character()`, `is.numeric()` or `is.logical()`) to check +::: +::: + +::: {.fragment} +```{r} +# colnames(Data) # To recheck the column names + +is.character(Data$bid) +``` + +::: + +::: {.fragment} +```{r} +is.numeric(Data$bid) +``` + +::: + +::: {.fragment} +```{r} +# colnames(Data) # To recheck the column names + +is.character(Data$Tcells_count) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For numeric columns using the `is.numeric()` function, we can also be [subtype](https://www.r-bloggers.com/2023/09/understanding-data-types-in-r/) specific using either `is.integer()` or `is.double()`. +::: +::: + +::: {.fragment} +```{r} +# colnames(Data) # To recheck the column names + +is.numeric(Data$Tcells_count) +is.integer(Data$Tcells_count) +is.double(Data$Tcells_count) +``` + +::: + +--- + +:::{.callout-tip title="Reminder"} +As we observed last week with keywords, column names that contain [special characters](https://ssojet.com/escaping/regex-escaping-in-r#understanding-the-need-for-escaping-special-characters) like $ or spaces will need to be surrounded with tick marks in order for the function to be able to run. +::: + +::: {.fragment} +```{r} +#| error: TRUE + +# colnames(Data) # To recheck the column names +is.numeric(Data$CD8-) +``` + +::: + +::: {.fragment} +```{r} +# colnames(Data) # To recheck the column names +is.numeric(Data$`CD8-`) +``` + +::: + +--- + +## select (Columns) + +::: {.fragment} +::: {.callout-tip title="."} +Now that we have read in our data, and have a general picture of the structure and contents, lets start learning the main `dplyr` functions we will be using throughout the course. To do this, lets go ahead and attach `dplyr` to our local environment via the `library()` call. +::: +::: + +::: {.fragment} +```{r} +library(dplyr) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We will start with the `select()` function. It is used to "select" a column from a data.frame type object. In the simplest usage, we provide the name of our data.frame variable/object as the first argument after the opening parenthesis. This is then followed by the name of the column we want to select as the second argument (let's place around the "" around the column name for now) +::: +::: + +::: {.fragment} +```{r} +DateColumn <- select(Data, "Date") +DateColumn +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This results in the column being selected, resulting in the new object containing only that subsetted out column from the original Data object. +::: +::: + +--- + +### Pipe Operators + +::: {.fragment} +::: {.callout-tip title="."} +While the above line of code works to select a column, when you encounter `select()` out in the wild, it will more often be in a line of code that looks like this: +::: +::: + +::: {.fragment} +```{r} +DateColumn <- Data |> select("Date") +DateColumn +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +... **"What in the world is that thing |> ?"** ... +::: +::: + + +::: {.fragment} +::: {.callout-tip title="."} +Glad you asked! An useful feature of the tidyverse packages is their use of [pipes](https://r4ds.had.co.nz/pipes.html) (either the original `magrittr` package's "%>%" or `base R version >4.1.0's` "|>""), usually appearing like this: +::: +::: + +::: {.fragment} +```{r} +# magrittr %>% pipe + +DateColumn <- Data %>% select("Date") + +# base R |> pipe +DateColumn <- Data |> select("Date") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +... **"How do we interpret/read that line of code?"** ... +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +Let's break it down, starting off just to the right of the assignment arrow (<-) with our data.frame "Data". +::: +::: + +::: {.fragment} +```{r} +#| eval: false + +Data +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We then proceed to read to the right, adding in our pipe operator. The pipe essentially serves as an intermediate passing the contents of data onward to the subsequent function. +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +Data |> +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In our case, this subsequent function is the `select()` function, which will select a particular column from the available data. When using the pipe, the first argument slot we saw for "select(Data, "Date")" is occupied by the contents Data that are being passed by the pipe. +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +Data |> select() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To complete the transfer, we provide the desired column name to `select()` to act on ("Date" in this case) +::: +::: + + +::: {.fragment} +```{r} +#| eval: FALSE +Data |> select("Date") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In summary, contents of Data are passed to the pipe, and select runs on those contents to select the Date column +::: +::: + +::: {.fragment} +```{r} +Data |> select("Date") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +One of the main advantages for using pipes, is they can be linked together, passing resulting objects of one operation on to the next pipe and subsequent function. We can see this in operation in the example below where we hand off the isolated "Date" column to the `nrow()` function to determine number of rows. We will use pipes throughout the course, so you will gradually gain familiarity as you encounter them. +::: +::: + +::: {.fragment} +```{r} +Data |> select("Date") |> nrow() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +For those with prior R experience, you will be more familiar with the older magrittr %>% pipe. The base R |> pipe operator was introduced starting with R version 4.1.0. While mostly interchangeable, they have a [few nuances](https://tidyverse.org/blog/2023/04/base-vs-magrittr-pipe/) that come into play for more advance use cases. You are welcome to use whichever you prefer (my current preference is |> as it's one less key to press). +::: +::: + +--- + +### R Quirks + +:::{.callout-note title="Odd R Behavior # 1"} +While we used "" around the column name in our previous example, unlike what we encountered with `install.packages()` when we forget to include quotation marks, `select()` still retrieves the correct column despite Date not being an environment variable: +::: + +::: {.fragment} +```{r} +Data |> select(Date) |> head(5) +``` + +::: + +--- + +:::{.callout-note title="."} +The reasons for this Odd R behaviour are nuanced and for [another day](https://adv-r.hadley.nz/evaluation.html). For now, think of it as `dplyr` R package is picking up the slack, and using context to infer it's a column name and not an environmental variable/object. +::: + +--- + +### Selecting multiple columns + +::: {.fragment} +::: {.callout-tip title="."} +Since we are able to select one column, can we select multiple (similar to a [Data[,2:5]] approach in base R)? We can, and they can be positioned anywhere within the data.frame: +::: +::: + +::: {.fragment} +```{r} +Subset <- Data |> select(bid, timepoint, Condition, Tcells, `CD8+`, `CD4+`) + +head(Subset, 5) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +You will notice that the order in which we selected the columns will dictate their position in the subsetted data.frame object: +::: +::: + +::: {.fragment} +```{r} +Subset <- Data |> select(bid, Tcells, `CD8+`, `CD4+`, timepoint, Condition, ) + +head(Subset, 5) +``` + +::: + +--- + +## relocate + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, we occasionally want to move one column. While we could respecify the location using `select()`, specifying the names of all the other columns out in a line of code to just to rearrange one does not sound like a good use of time. For this reason, the second `dplyr` function we will be learning is the `relocate()` function. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Looking at our Data object, let's say we wanted to move the Tcells column from its current location to the second column position (right after the bid column). The line of code to do so would look like: +::: +::: + +::: {.fragment} +```{r} +Data |> relocate(Tcells, .after=bid) |> head(5) + +# |> head(5) is used only to make the website output visualization manageable :D +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Similar to what we saw with `select()`, this approach can also be used for more than 1 column: +::: +::: + +::: {.fragment} +```{r} +Data |> relocate(Tcells, Monocytes, .after=bid) |> head(5) + +# |> head(5) is used only to make the website output visualization manageable :D +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can also modify the argument so that columns are placed before a certain column +::: +::: + +::: {.fragment} +```{r} +Data |> relocate(Tcells, .before=Date) |> head(5) + +# |> head(5) is used only to make the website output visualization manageable :D +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And as we might suspect, we could specify a column index location rather than using a column name. +::: +::: + +::: {.fragment} +```{r} +Data |> relocate(Date, .before=1) |> head(5) + +# |> head(5) is used only to make the website output visualization manageable :D +``` + +::: + +--- + +## rename + +::: {.fragment} +::: {.callout-tip title="."} +At this point, we are able to both move and select particular columns, allowing us to rearrange and subset a larger data.frame object however we want it to appear. However, as we encountered, some of the names contain special characters and spaces, requiring use of tick marks (``) to avoid issues. How can we change a column name? +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In base R, we could change individual column names by assigning a new value with the assignment arrow to the corresponding column name index. For example, looking at our Subset object, wen could rename CD8+ as follows: +::: +::: + + +::: {.fragment} +```{r} +colnames(Subset) +colnames(Subset)[3] +``` + +::: + + +::: {.fragment} +```{r} +colnames(Subset)[3] <- "CD8Positive" +colnames(Subset) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +With the tidyverse, we can use the `rename()` function which removes the need to look up the column index number. The way we write the argument is placing within the parenthesis the old name to the right of the equals sign, with the new name to the left +::: +::: + +::: {.fragment} +```{r} +Renamed <- Subset |> rename(CD4_Positive = `CD4+`) +colnames(Renamed) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we wanted to rename multiple column names at once, we would just need to include a comma between the individual rename arguments within the parenthesis. +::: +::: + +::: {.fragment} +```{r} +Renamed_Multiple <- Subset |> rename(specimen = bid, timepoint_months = timepoint, stimulation = Condition, CD4Positive=`CD4+`) +colnames(Renamed_Multiple) +``` + +::: + +--- + +## pull + +::: {.fragment} +::: {.callout-tip title="."} +Sometimes, we may want to retrieve individual values present in a column, to use within either a vector or a list. We can do this using the `pull()` function, which will retrieve the column contents and strip the column formatting +::: +::: + +::: {.fragment} +```{r} +Data |> pull(Date) |> head(10) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This can be useful when we are doing data exploration, and trying to determine how many unique variants might be present. For example, if we wanted to see what days individual samples were acquired, we could `pull()` the data and pass it to the `unique()` function: +::: +::: + +::: {.fragment} +```{r} +Data |> pull(Date) |> unique() +``` + +::: + +--- + + +## filter (Rows) + +::: {.fragment} +::: {.callout-tip title="."} +So far, we have been working with `dplyr` functions primarily used when working with and subsetting columns (including `select()`, `pull()`, `rename()` and `relocate()`). What if we wanted to work with rows of a data.frame? This is where the `filter()` function is used. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The Condition column in this Dataset appears to be indicating whether the samples were stimulated. Let's see how many unique values are contained within that column +::: +::: + +::: {.fragment} +```{r} +Data |> pull(Condition) |> unique() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In the case of this dataset, looks like the .fcs files where treated with either left alone, treated with [PPD (Purified Protein Derrivative)](https://en.wikipedia.org/wiki/Tuberculin) or [SEB](https://en.wikipedia.org/wiki/Enterotoxin_type_B). What if we wanted to subset only those treated with PPD? +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Within `filter()`, we would specify the column name as the first argument, and ask that only values equal to (==) "PPD" be returned. Notice in this case, "" are needed, as we are asking for a matching character value. +::: +::: + +::: {.fragment} +```{r} +PPDOnly <- Data |> filter(Condition == "PPD") +head(PPDOnly, 5) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +While this works, using "==" to match can glitch, especially with character values. Using the %in% operator is a better way of identifying and extracting only the rows whose Condition column contains "PPD" +::: +::: + +::: {.fragment} +```{r} +Data |> filter(Condition %in% "PPD") |> head(10) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Similar to what we saw for `select()`, we can grab rows that contain various values at once. We would just need to modify the second part of the argument. If we wanted to grab rows whose Condition column contained either PPD or SEB, we would need to provide that argument as a vector, placing both within `c()`/ +::: +::: + +::: {.fragment} +```{r} +Data |> filter(Condition %in% c("PPD", "SEB")) |> head(10) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, we could have set up the vector externally, and then provided it to `filter()` +::: +::: + +::: {.fragment} +```{r} +TheseConditions <- c("PPD", "SEB") +Data |> filter(Condition %in% TheseConditions) |> head(10) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +While this works when we have a limited number of variant condition values, what if had many more but only wanted to exclude one value? +As we saw when learning about [Conditionals](/course/02_FilePaths/index.qmd), when we add a ! in front of a logical value, we get the opposite logical value returned +::: +::: + +::: {.fragment} +```{r} +IsThisASpectralInstrument <- TRUE + +!IsThisASpectralInstrument +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In the context of the `dplyr` package, we can use ! within the `filter()` to remove rows that contain a certain value +::: +::: + +::: {.fragment} +```{r} +Subset <- Data |> filter(!Condition %in% "SEB") +Subset |> pull(Condition) |> unique() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Likewise, we can also use it with the `select()` to exclude columns we don't want to include +::: +::: + +::: {.fragment} +```{r} +Subset <- Data |> select(!timepoint) +Subset[1:3,] +``` + +::: + +--- + + +## mutate + +::: {.fragment} +::: {.callout-tip title="."} +As we can see, with just these handful of functions, we have the building blocks to rearrange and subset a larger data.frame into a format that we prefer. But what if we wanted to alter the content of a column, or add new columns to an existing data.frame? This is where the `mutate()` function can be used. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Let's start by slimming down our current Data to a smaller workable example, highlighting the functions and pipes we learned about today +::: +::: + +::: {.fragment} +```{r} +TidyData <- Data |> filter(Condition %in% "Ctrl") |> filter(timepoint %in% "0") |> + select(bid, timepoint, Condition, Date, Tcells_count, CD45_count) |> + rename(specimen=bid, condition=Condition) |> relocate(Date, .after=specimen) +``` + +::: + +--- + +::: {.fragment} +```{r} +TidyData +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The `mutate()` function can be used to modify existing columns, as well as to create new ones. For example, let's derrive the proportion of T cells from the overall CD45 gate. To do so, within the parenthesis, we would specify a new column name, and then divide the original columns: +::: +::: + +::: {.fragment} +```{r} +TidyData <- TidyData |> mutate(Tcells_ProportionCD45 = Tcells_count / CD45_count) +TidyData +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can see that we have many significant digits being returned. Let's round this new column to 2 significant digits by applying the `round()` function +::: +::: + +::: {.fragment} +```{r} +TidyData <- TidyData |> mutate(TcellsRounded = round(Tcells_ProportionCD45, 2)) +TidyData +``` + +::: + +--- + + +## arrange + +::: {.fragment} +::: {.callout-tip title="."} +And while we are here, let's rearrange the rows so that they are descending based on the Tcell proportion. We can use this by using the `desc()` and `arrange()` functions from `dplyr`: +::: +::: + +::: {.fragment} +```{r} +TidyData <- TidyData |> arrange(desc(TcellsRounded)) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And let's go ahead and `filter()` and identify the specimens that had more than 30% T cells as part of the overall CD45 gate (context, these samples were Cord Blood): +::: +::: + +::: {.fragment} +```{r} +TidyData |> filter(TcellsRounded > 0.3) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Which is we had wanted to just retrieve the specimen IDs, we could add `pull()` after a new pipe argument. +::: +::: + +::: {.fragment} +```{r} +TidyData |> filter(TcellsRounded > 0.3) |> pull(specimen) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And finally, since I may want to send the data to a supervisor, let's go ahead and export this "tidyed" version of our data.frame out to it's own .fcs file. Working within our project folder, this would look like this: +::: +::: + +::: {.fragment} +```{r} +NewName <- paste0("MyNewDataset", ".csv") +StorageLocation <- file.path("data", NewName) +StorageLocation +``` +::: + +::: {.fragment} +```{r} +#| eval: FALSE +write.csv(TidyData, StorageLocation, row.names=FALSE) +``` +::: + +--- + +# Take Away + +::: {.fragment} +::: {.callout-tip title="."} +In this session, we explored the main functions within the `dplyr` package used in context of "tidying" data, including selecting columns, filtering for rows, as well as additional functions used to create or modify existing values. We will continue to build on these throughout the course, introducing a few additional tidyverse functions we don't have time to cover today as appropiate. As we saw, knowing how to use these functions can allow us to extensively and quickly modify our existing exported data files. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +On important goal as we move through the course (in terms of both reproducibility and replicability) is to attempt to only modify files within R, not go back to the original csv or excel file and hand-modify individual values. This approach is not reproducible or replicable. Once set up, an R script can quickly re-carry out these same cleanup steps, and leave a documented process of how the data has changed (even more so if you are maintaining version control). If you do want to save the changes you have made, it is best to save it out as a new .csv file with which you work later. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next week, we will be using these skills when setting up metadata for our .fcs files. We will additionally take a look at the main format source of controversy within Bioconductor Flow Cytometry packages, ie. whether to use a flowframe or a cytoframe. Exciting stuff, but important information to know as the functions needed to import them are slightly different. We will also look at how to import existing manually gated .wsp from FlowJo/Diva/Floreada in via the `CytoML` package. +::: +::: + +--- + +![](images/TakeAway.jpg) + +--- + +# Additional Resources + +[Data Organization in Spreadsheets for Ecologists](https://datacarpentry.github.io/spreadsheet-ecology-lesson/) This Carpentry self-study course was one of my "Aha" moments early on when learning R, and reinforced the need to try to keep my own Excel/CSV files in a tidy manner. It is worth the time going through in its entirety (even for non-Ecologist). + +[Data Analysis and Visualization in R for Ecologists](https://datacarpentry.github.io/R-ecology-lesson/) Continuation of the above, and a good way to continue building on the tidyverse functions we learned today. + +--- + +[Simplistics: Introduction to Tidyverse in R](https://youtu.be/Bg4qxVNaDck?si=QPQq8TzOZ1w6XSy4) The YouTube channel is mainly focused on statistics for Psych classes, but at the end of the day, we are all working with similar objects with rows and columns, just the values contained within differ. + +[Riffomonas Project Playlist: Data Manipulation with R's Tidyverse](https://youtube.com/playlist?list=PLmNrK_nkqBpKf7j_ewpUm-w33R6PJYtD9&si=BVmDZPIXjRuHjERP) Riffomonas has a playlist that delves into both the tidyverse functions we used today, as well as other ones we will encounter later on in the course. + +--- + +# Take-home Problems + +:::{.callout-tip title="Problem 1"} +Taking a dataset (either todays or one of your own), work through the column-operating functions (`select()`, `rename()`, and `relocate()`). Once this is done, `filter()` by conditions from two separate columns, arrange in an order that makes sense, and export this "tidy" data as a .csv file. +::: + +--- + +:::{.callout-tip title="Problem 2"} +We used the `mutate()` function to create new columns, but it can also be used to modify existing ones. Various numeric columns are showing way to many significant digits. As was shown, use `round()` to round all these proportion columns, but use mutate to overwrite the existing column. Export this as it's own .csv file. +::: + +--- + +:::{.callout-tip title="Problem 3"} +We can also use `mutate()` to combine columns. For our dataset, "bid", "timepoint", "Condition" are separate columns that originally were all part of the filename for the individual .fcs file. Try to figure out a way to combine them back together using `paste0()`, and save the new column as "filename". Once this is done, `pull()` the contents of this column, and using try to determine whether there were any duplicates (think innovative ways of using !, `length()` and `unique()`) +::: + +--- + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +::: \ No newline at end of file diff --git a/course/05_GatingSets/index.qmd b/course/05_GatingSets/index.qmd index 42f682a..65b2823 100644 --- a/course/05_GatingSets/index.qmd +++ b/course/05_GatingSets/index.qmd @@ -13,9 +13,11 @@ toc-depth: 5 [![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) ::: -For the YouTube livestream schedule, see [here](https://www.youtube.com/@cytometryinr) +For the YouTube livestream recording, see [here](https://youtu.be/x0SbK6PZF6Y?t=262) -For screen-shot slides, click [here]() + + +For screen-shot slides, click [here](/course/05_GatingSets/slides.qmd)
@@ -75,7 +77,8 @@ library(flowCore) ``` ```{r} -flowFrame <- read.FCS(filename=fcs_files[1], truncate_max_range = FALSE, transformation = FALSE) +flowFrame <- read.FCS(filename=fcs_files[1], truncate_max_range = FALSE, + transformation = FALSE) flowFrame ``` @@ -107,14 +110,16 @@ str(fcs_files) Consequently, we will need to use another function if we want to read in multiple .fcs files at once. For `flowCore`, this function is the `read.flowSet()` function. ```{r} -flowSet <- read.flowSet(files=fcs_files, truncate_max_range = FALSE, transformation = FALSE) +flowSet <- read.flowSet(files=fcs_files, truncate_max_range = FALSE, + transformation = FALSE) flowSet ``` Alternatively, we can designate specific files within "fcs_files" we want to read in using the [] and c() notation style we have encountered previously. ```{r} -read.flowSet(files=fcs_files[c(1, 3:4)], truncate_max_range = FALSE, transformation = FALSE) +read.flowSet(files=fcs_files[c(1, 3:4)], + truncate_max_range = FALSE, transformation = FALSE) ``` On follow-up, we can see that `read.flowSet()` has created a "flowSet" class object. @@ -149,7 +154,7 @@ While not today's focus, remember we could access individual components inside t Both "flowFrame" and "flowSet" objects were implemented in the `flowCore` package, which is the [oldest](/course/03_InsideFCSFile/#flowcore) extant flow cytometry R package on [Bioconductor](https://www.bioconductor.org/packages/release/bioc/html/flowCore.html). Consequently, a large proportion of the other flow cytometry R packages read in .fcs files as "flowFrame" and "flowSet" objects. -One consideration of this method is the contents of your .fcs files are read into your computer's random access memory [(RAM)](https://en.wikipedia.org/wiki/Random-access_memory). While for individual .fcs files or small experiments this present a problem for most modern computers, when working with large spectral flow cytometry files containing millions of events (or trying to analyze many .fcs files at once), you may encounter situations where you can quickly exceed your computers available RAM. +One consideration of this method is the contents of your .fcs files are read into your computer's random access memory [(RAM)](https://en.wikipedia.org/wiki/Random-access_memory). While for individual .fcs files or small experiments this will not present a problem for most modern computers, when working with large spectral flow cytometry files containing millions of events (or trying to analyze many .fcs files at once), you may encounter situations where you can quickly exceed your computers available RAM. To build some contextual understanding of the problem, let's learn how to check how much memory is being used by our individual variables/objects within our R session. We will primarily use the `lobstr` R packages `obj_size()` function, as it better handles evaluating complicated objects than base R's `object.size()` function. @@ -176,16 +181,17 @@ If we were curious how much memory total we are using within R at the current mo mem_used() ``` -Ultimately, how many .fcs files you are able to read in and interact with before running out of available RAM memory space will be dictated by your individual computers hardware configuration. You can check programmatically how much RAM you have available, although the specific function you will need to use will depend on your computer's operating system. +Ultimately, how many .fcs files you are able to read in and interact with before running out of available RAM memory space will be dictated by your individual computers hardware configuration. There are various ways you can check programmatically how much RAM your computer has available, although the specific functions will vary depending on your computers operating system, since they often involve system-level code outside R. Using the `ps` R package's `ps_system_memory()` function is one of the easier ways for Windows users. To simplify the process, here is an additional example of where a [conditional](/course/02_FilePaths/index.qmd#conditionals) can prove useful, allowing us to check in an operating system specific manner. It takes the output of the `Sys.info()` function, namely the "sysname" argument and then retrieves the relavent function. ```{r} - OperatingSystem <- Sys.info()[["sysname"]] if (OperatingSystem == "Windows") { # Windows - memory.limit() + Memory <- ps::ps_system_memory() + message("Total GB ", round(Memory$total / 1024^3, 2)) + message("Free GB ", round(Memory$free / 1024^3, 2)) } else if (OperatingSystem == "Darwin") { # MacOS system("top -l 1 | grep PhysMem") @@ -196,8 +202,13 @@ if (OperatingSystem == "Windows") { # Windows } else {message("A wild FreeBSD-User appears")} ``` -When evaluating the returned outputs, primarily consider the total, used and free outputs. - +```{r} +# install.packages("ps") # CRAN +library(ps) +Memory <- ps::ps_system_memory() +message("Total GB ", round(Memory$total / 1024^3, 2)) +message("Free GB ", round(Memory$free / 1024^3, 2)) +``` ## cytoframe diff --git a/course/05_GatingSets/slides.qmd b/course/05_GatingSets/slides.qmd new file mode 100644 index 0000000..51f3032 --- /dev/null +++ b/course/05_GatingSets/slides.qmd @@ -0,0 +1,1413 @@ +--- +title: "05 - Gating Sets" +author: "David Rach" +date: 03-03-2026 +format: + revealjs: + theme: default + slide-number: true + incremental: true +page-layout: full +execute: + echo: true + warning: false + message: false +--- + +![](/images/WebsiteBanner.png) + +::: {style="text-align: right;"} +[![AGPL-3.0](https://img.shields.io/badge/license-AGPLv3-blue)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg)](http://creativecommons.org/licenses/by-sa/4.0/) +::: + +--- + +# Background + + +::: {.fragment} +::: {.callout-tip title="."} +Welcome to the fifth week of the Cytometry in R course!!! At this point, we are through a significant portion of the "Intro to R" material, and will start encountering more "Cytometry-focused" material moving forward. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +If we think of a typical flow cytometry experiment, there is more to the analysis than simply acquiring the .fcs file. While there is [substantial information](/course/03_InsideFCSFile/) present within an .fcs file, in the context of analyzing them with commercial software, we rely on additional infrastructural elements to organize the various files, transform (scale), compensate (for conventional flow), visualize, derrive statistics, etc. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This infrastructural requirement within the R context is primarily handled by the `flowCore` and `flowWorkspace` R packages from [Bioconductor](https://www.bioconductor.org/). Today, we will build on what we learned during [Week 03](/course/03_InsideFCSFile/index.qmd) but in the context of working and interacting with multiple .fcs files. This will provide a solid foundation to explore in greater depth how individual components of our typical workflow are represented within the R context. +::: +::: + +--- + +# Walk Through + +:::{.callout-important title="Housekeeping"} +As we do [every week](/course/02_FilePaths/index.qmd), on GitHub, [sync](/course/00_Homeworks/index.qmd#sync-your-fork) your forked version of the CytometryInR course to bring in the most recent updates. Then within Positron, [pull](/course/00_Homeworks/index.qmd#pull-to-local) in those changes to your local computer. + +After [setting up](/course/00_Git/index.qmd#new-folder-from-template) a "Week05" project folder, copy over the contents of "course/05_GatingSets/data" to that folder. This will hopefully prevent merge issues next week when attempting to pull in new course material. Once you have your new project folder organized, remember to [commit](/course/00_Git/index.qmd#push) and push your changes to GitHub to maintain remote version control. + +If you encounter issues syncing due to the Take-Home Problem merge conflict, see this [walkthrough](https://umgcccfcsr.github.io/CytometryInR/course/00_BonusContent/PullConflicts/). The updated homework submission protocol can be found [here](https://umgcccfcsr.github.io/CytometryInR/course/00_BonusContent/PullConflicts/UpdatedPullRequest) +::: + +
+ +--- + +## flowFrame + + +::: {.fragment} +::: {.callout-tip title="."} +Let's start off by recalling the approach we first saw during [Week 03](/course/03_InsideFCSFile/index.qmd), where using the `flowCore` package we loaded the contents of our .fcs file into R as a "flowFrame" object. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To do this, we first identified the .fcs files we were interested using `file.path()` to specify the folder, and `list.files()` to find contents containing ".fcs". +::: +::: + +::: {.fragment} +```{r} +# Folder <- file.path("course", "05_GatingSets", "data") # For Testing + + Folder <- file.path("data") # For Quarto Rendering + +fcs_files <- list.files(Folder, pattern=".fcs", full.names=TRUE) + +fcs_files +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We then identified an individual .fcs file of interest using the [] method of indexing. +::: +::: + +::: {.fragment} +```{r} +fcs_files[1] +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Then, after making sure flowCore was attached to our local environment (via the `library()` function), we could use `read.FCS()` to read in our .fcs files contents to R. +::: +::: + +::: {.fragment} +```{r} +# BiocManager::install("flowCore") #Bioconductor +library(flowCore) +``` + +::: + +::: {.fragment} +```{r} +flowFrame <- read.FCS(filename=fcs_files[1], truncate_max_range = FALSE, + transformation = FALSE) +flowFrame +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As we start to think about the wider infrastructural handling of our .fcs files, what would have occurred if we had provided multiple .fcs file paths to `read.FCS()`? Let's go ahead and check by not providing an index number. +::: +::: + +::: {.fragment} +```{r} +#| error: TRUE +read.FCS(filename=fcs_files, truncate_max_range = FALSE, transformation = FALSE) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As you can tell, this error message is not particularly interpretable. It however arises from type of object we are passing to the function, whereby an individual file.path (fcs_files[1]) appears as class "character" with a **single value** (ie. a [scalar](https://nathanieldphillips-yarrr.share.connect.posit.cloud/scalars.html)), but the combined vector (fcs_files) contains **multiple** values. +::: +::: + +::: {.fragment} +```{r} +fcs_files[1] + +str(fcs_files[1]) +``` + +::: + +::: {.fragment} +```{r} +fcs_files + +str(fcs_files) +``` + +::: + +--- + +## flowSet + +::: {.fragment} +::: {.callout-tip title="."} +Consequently, we will need to use another function if we want to read in multiple .fcs files at once. For `flowCore`, this function is the `read.flowSet()` function. +::: +::: + +::: {.fragment} +```{r} +flowSet <- read.flowSet(files=fcs_files, truncate_max_range = FALSE, + transformation = FALSE) +flowSet +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, we can designate specific files within "fcs_files" we want to read in using the [] and c() notation style we have encountered previously. +::: +::: + +::: {.fragment} +```{r} +read.flowSet(files=fcs_files[c(1, 3:4)], + truncate_max_range = FALSE, transformation = FALSE) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +On follow-up, we can see that `read.flowSet()` has created a "flowSet" class object. +::: +::: + +::: {.fragment} +```{r} +class(flowSet) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Which we can also confirm by glancing at the right secondary sidebar to see the created Variables within our environment. Applying our investigatory skills from [Week 3](/course/03_InsideFCSFile/index.qmd), we surmise that "flowSet" is another Bioconductor style S4-type object that within its frame slot contains individual "flowFrames". +::: +::: + +::: {.fragment} +![](images/00_FlowSet.png) +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If instead of `class()` we had used `str()`, we would have seen a similar output ton what we see in the Variables panel. +::: +::: + +::: {.fragment} +```{r} +str(flowSet) +``` + +::: + +--- + +:::{.callout-tip title="Reminder"} +While not today's focus, remember we could access individual components inside the flowSet using the @ accessors covered during [Week 3](/course/03_InsideFCSFile/index.qmd) +::: + +--- + +## Memory Usage + +::: {.fragment} +::: {.callout-tip title="."} +Both "flowFrame" and "flowSet" objects were implemented in the `flowCore` package, which is the [oldest](/course/03_InsideFCSFile/#flowcore) extant flow cytometry R package on [Bioconductor](https://www.bioconductor.org/packages/release/bioc/html/flowCore.html). Consequently, a large proportion of the other flow cytometry R packages read in .fcs files as "flowFrame" and "flowSet" objects. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +One consideration of this method is the contents of your .fcs files are read into your computer's random access memory [(RAM)](https://en.wikipedia.org/wiki/Random-access_memory). While for individual .fcs files or small experiments this will not present a problem for most modern computers, when working with large spectral flow cytometry files containing millions of events (or trying to analyze many .fcs files at once), you may encounter situations where you can quickly exceed your computers available RAM. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To build some contextual understanding of the problem, let's learn how to check how much memory is being used by our individual variables/objects within our R session. We will primarily use the `lobstr` R packages `obj_size()` function, as it better handles evaluating complicated objects than base R's `object.size()` function. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can check and see the memory usage by our flowFrame object +::: +::: + +::: {.fragment} +```{r} +# Base R +object.size(flowFrame) + +# install.packages("lobstr") # CRAN +library(lobstr) +obj_size(flowFrame) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And contrast to the greater ammount of space occupied by our flowSet object (which contains multiple flowFrames) +::: +::: + +::: {.fragment} +```{r} +obj_size(flowSet) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If we were curious how much memory total we are using within R at the current moment, we can check using the `mem_used()` function: +::: +::: + +::: {.fragment} +```{r} +mem_used() +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Ultimately, how many .fcs files you are able to read in and interact with before running out of available RAM memory space will be dictated by your individual computers hardware configuration. There are various ways you can check programmatically how much RAM your computer has available, although the specific functions will vary depending on your computers operating system, since they often involve system-level code outside R. Using the `ps` R package's `ps_system_memory()` function is one of the easier ways for Windows users. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To simplify the process, here is an additional example of where a [conditional](/course/02_FilePaths/index.qmd#conditionals) can prove useful, allowing us to check in an operating system specific manner. It takes the output of the `Sys.info()` function, namely the "sysname" argument and then retrieves the relavent function. +::: +::: + +::: {.fragment} +```{r} + +OperatingSystem <- Sys.info()[["sysname"]] + +if (OperatingSystem == "Windows") { # Windows + # install.packages("ps") # CRAN + Memory <- ps::ps_system_memory() + message("Total GB ", round(Memory$total / 1024^3, 2)) + message("Free GB ", round(Memory$free / 1024^3, 2)) + + } else if (OperatingSystem == "Darwin") { # MacOS + system("top -l 1 | grep PhysMem") + + } else if (OperatingSystem == "Linux") { # Linux + system("free -h") + + } else {message("A wild FreeBSD-User appears")} +``` + +::: + +--- + +::: {.fragment} +```{r} +# install.packages("ps") # CRAN +library(ps) +Memory <- ps::ps_system_memory() +message("Total GB ", round(Memory$total / 1024^3, 2)) +message("Free GB ", round(Memory$free / 1024^3, 2)) +``` + +::: + +--- + +## cytoframe + +::: {.fragment} +::: {.callout-tip title="."} +In addition to the `flowCore` R package, additional flow cytometry infrastructure support is provided by the `flowWorkspace` package. Instead of the reading all the .fcs files contents into active RAM, `flowWorkspace` reduces the memory overhead by using ["pointers"](https://www.geeksforgeeks.org/c/c-pointers/) to interact with the object in it's current storage location (either on your harddrive, SSD, etc.), only reading in components to RAM as needed. +::: +::: + +::: {.fragment} +```{r} +# BiocManager::install("flowWorkspace") #Bioconductor +library(flowWorkspace) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Because of these differences in how data is interracted with, we end up with parallel equivalents to the traditional flowFrame and flowSet type objects. These include "cytoframe" for single .fcs files +::: +::: + +::: {.fragment} +```{r} +cytoframe <- load_cytoframe_from_fcs(fcs_files[1], truncate_max_range = FALSE, transformation = FALSE) + +cytoframe +``` + +::: + +--- + +::: {.fragment} +```{r} +class(cytoframe) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Which also still errors out when not given a scalar object +::: +::: + +::: {.fragment} +```{r} +#| error: TRUE + +load_cytoframe_from_fcs(fcs_files, truncate_max_range = FALSE, transformation = FALSE) +``` + +::: + +--- + +## cytoset + +::: {.fragment} +::: {.callout-tip title="."} +As well as "cytoset" to handle multiple .fcs files. +::: +::: + +::: {.fragment} +```{r} +cytoset <- load_cytoset_from_fcs(fcs_files, truncate_max_range = FALSE, transformation = FALSE) + +cytoset +``` + +::: + +::: {.fragment} +```{r} +class(cytoset) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Unlike "flowFrame" and "flowSet", when we run `str()`, for "cytoframe" and "cytoset" objects we don't get back quite as much information. +::: +::: + +::: {.fragment} +```{r} +str(cytoframe) +``` + +::: + +--- + +::: {.fragment} +```{r} +str(cytoset) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This is similarly the case when glancing at the right secondary side bar, as the respective objects under variables appear to have empty matrices where normally we would have seen the MFI values. +::: +::: + +::: {.fragment} +![](images/01_LookMaNoData.png) +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Due to `flowWorkspace` use of pointers, the missing data remains stored on the drive, only being retrieved right before it is required. This reduces the overall RAM utilization. Let's double check the differences in memory utilization for flowFrame/cytoframe: +::: +::: + +::: {.fragment} +```{r} +obj_size(flowFrame) +``` + +::: + +::: {.fragment} +```{r} +obj_size(cytoframe) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +And similarly the case for flowSet and cytoset: +::: +::: + +::: {.fragment} +```{r} +obj_size(flowSet) +``` + +::: + +::: {.fragment} +```{r} +obj_size(cytoset) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Additionally, with computer hardware increasingly switching from spinning disk hard-drives to faster [solid state](https://unihost.com/help/nvme-vs-ssd-vs-hdd-overview-and-comparison/) drives, the performance penalty previously experienced when not running from RAM is not as large of a concern as in previous years. +::: +::: + +--- + +## Interconverting + +::: {.fragment} +::: {.callout-tip title="."} +Despite both R packages having been around for a while, many [Bioconductor](https://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry) and [GitHub](https://github.com/stars/DavidRach/lists/cytometry-r-packages) often only implement methods to handle either flowFrames or cytoframes (although newer R packages are now allowing for both). Consequently, as we move forward in the course, it helps to be aware of which ones we are working with, and have the ability to interconvert between them as needed. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To go from a flowFrame to a cytoframe, we can use the `flowFrame_to_cytoframe()` function +::: +::: + +::: {.fragment} +```{r} +ConvertedToCytoframe <- flowFrame_to_cytoframe(flowFrame) +ConvertedToCytoframe +``` + +::: + +--- + +::: {.fragment} +```{r} +obj_size(ConvertedToCytoframe) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To go from a cytoframe to a flowFrame, we can use the `cytoframe_to_flowFrame()` function +::: +::: + +::: {.fragment} +```{r} +ConvertedToFlowframe <- flowWorkspace::cytoframe_to_flowFrame(cytoframe) +ConvertedToFlowframe +``` + +::: + +--- + +::: {.fragment} +```{r} +obj_size(ConvertedToFlowframe) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To go from a flowSet to a cytoSet, we can use the `flowSet_to_cytoset()` funciton +::: +::: + +::: {.fragment} +```{r} +ConvertedToCytoset <- flowSet_to_cytoset(flowSet) +ConvertedToCytoset +``` + +::: + +::: {.fragment} +```{r} +obj_size(ConvertedToCytoset) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To go from a cytoSet to a flowSet, we can use the `cytoset_to_flowSet()` function. +::: +::: + +::: {.fragment} +```{r} +ConvertedToFlowset <- cytoset_to_flowSet(flowSet) +ConvertedToFlowset +``` + +::: + +::: {.fragment} +```{r} +obj_size(ConvertedToFlowset) +``` + +::: + +--- + +## Gating Sets + +::: {.fragment} +::: {.callout-tip title="."} +Fortunately, regardless of whether we are using flowFrame/flowSet (RAM) and cytoframe/cytoset (memory pointers), both routes end up converging at the next step, where the underlying .fcs files are passed off to the `GatingSet()` function. +::: +::: + +::: {.fragment} +```{r} +GatingSet1 <- GatingSet(flowSet) +GatingSet1 +``` + +::: + +::: {.fragment} +```{r} +class(GatingSet1) +``` + +::: + +--- + +::: {.fragment} +```{r} +GatingSet2 <- GatingSet(cytoset) +GatingSet2 +``` + +::: + +::: {.fragment} +```{r} +class(GatingSet1) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As we prefaced in the [background](/course/05_GatingSets/index.qmd#background), beyond the .fcs files themselves, we need infrastructural elements with which to interact with the underlying data, which allows us to organize the various files, transform (scale), compensate (for conventional flow), visualize, derrive statistics, etc. A GatingSet serves as the infrastructural framework that allows us to do this in R. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +If we investigate our current GatingSet objects, we won't see much +::: +::: + +::: {.fragment} +![](images/03_GatingSetConvergence.png) +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This will change as we start layering on additional elements. However, rather than try to cram everything into a single week, we will explore in greater depth the individual components over the next [three weeks](/Schedule.qmd#applying-transformations-and-compensation). Instead, for the rest of today, we will work backward, by exploring a GatingSet objecct and what it is capable of doing once fully assembled. +::: +::: + +--- + +## CytoML + +::: {.fragment} +::: {.callout-tip title="."} +The `CytoML` R package (also maintained by [Mike Jiang](https://github.com/mikejiang)) is a sister package to the `flowWorkspace`. It's main purpose is to permit bringing in existing FlowJo, Diva and Cytobank Workspaces, with all their gates, transformations, etc. into R as fully assembled GatingSet objects. For those who already use one of these commercial softwares, it can be quite useful tool. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +Since our goal is to examine a fully assembled GatingSet object, we will be using it today to bring in a [FlowJo](https://www.flowjo.com/flowjo10/overview) workspace to R. However, since this is a free Cytometry in R course, and not about to have everyone pay for a license for a one-off topic, in the [pre-course Floreada](/course/00_Floreada/index.qmd) walkthrough I documented how to convert a free [Floreada.io](https://floreada.io/) workspae into a FlowJo.wsp that can also be used (please note that as of early 2026, some scaling bugs may be present and require troubleshooting). +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +To get started, let's first attach `CytoML` to our local environment via the `library()` call. +::: +::: + +::: {.fragment} +```{r} +# BiocManager::install("CytoML") #Bioconductor +library(CytoML) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The .wsp files within this week's data where created via [Floreada.io](/course/00_Floreada/index.qmd). The main difference between the two files is one is a copy of the original that was opened within FlowJo, and subsequently swtiched from [logicle](https://pubmed.ncbi.nlm.nih.gov/16604519/) to [bi-exponential](https://docs.flowjo.com/flowjo/graphs-and-gating/gw-transform-overview/gw-transform-benefits/) transformation. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +We will need to provide the appropiate file path for our desired .wsp file. We can start by identifying which are present using `list.files()` +::: +::: + +::: {.fragment} +```{r} +Folder # Defined Above +FlowJoWsp <- list.files(path = Folder, pattern = ".wsp", full = TRUE) +FlowJoWsp +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In our case, we will proceed by using `str_detect()` to select the .wsp that contains the pattern "Opened" +::: +::: + +::: {.fragment} +```{r} +ThisWorkspace <- FlowJoWsp[stringr::str_detect(FlowJoWsp, "Opened")] +ThisWorkspace +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +With our single .wsp filepath now identified, we can now proceed to set up the intermediate object using `open_flowjo_xml()` +::: +::: + +::: {.fragment} +```{r} +ws <- open_flowjo_xml(ThisWorkspace) +ws +``` + +::: + +::: {.fragment} +```{r} +class(ws) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Having set up the intermediate flowjo_workspace object, we can attempt to read in the actual data from the .wsp into a GatingSet using the `flowjo_to_gatingset()` function. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +However, due to how I named the original .fcs files ("GROUPNAME" being individual specimens, "TUBENAME" being either Ctrl or SEB), and downsampled to the same number of cells, we will encounter the following error +::: +::: + +::: {.fragment} +```{r} +#| error: TRUE +gs <- flowjo_to_gatingset(ws=ws, name=1, path = Folder) +gs +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As with any error, my first move is to check the help documentation. In this case, my initial response is to see if I can identify an argument that will help differentiate between the names for each specimen. +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +?flowjo_to_gatingset +``` + +::: + +--- + +![](images/CytoMLArguments.png) + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +In this case, I find that the "additional.keys" argument would likely work for this troubleshooting +::: +::: + +--- + +![](images/AdditionalKeys.png) + +--- + +::: {.fragment} +```{r} +gs <- flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME") +gs +``` + +::: + +::: {.fragment} +```{r} +class(gs) +``` + +::: + +--- + +## System Time + +::: {.fragment} +::: {.callout-tip title="."} +Especially when working with CytoML, it is often good to have an idea of how long it will take a particular function to run (to better plan how to use our time while waiting, whether to go grab coffee, etc.). There are a couple ways to do so. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +One, using the `system.time()` function from base R, in which we surround whatever line of code we wish to evaluate in {} +::: +::: + +::: {.fragment} +```{r} +system.time({ + +flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME") + +}) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, if we install the `bench` package, we can use the `mark` function to evaluate how long it takes on average across numerous iterations. +::: +::: + +::: {.fragment} +```{r} +# install.packages("bench") # CRAN +library(bench) +``` + +::: + +::: {.fragment} +```{r} +mark( + Test <- flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME"), + iterations= 5 + ) +``` + +::: + +--- + +## Gates + +::: {.fragment} +::: {.callout-tip title="."} +Now that we have loaded the contents of the FlowJo/Floreada workspace, we can start exploring the various infrastructural capabilities of a GatingSet object. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Let's start by evaluating whether the manually-drawn gates I drew survived the journey. To do this, I can generate a visual gating treee using the `plot()` function. +::: +::: + +::: {.fragment} +```{r} +plot(gs) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +We can also retrieve the individual gates and their gaing paths using the `gs_get_pop_paths()` function. +::: +::: + +::: {.fragment} +```{r} +gs_get_pop_paths(gs) +``` + +::: + +--- + +## Counts + +::: {.fragment} +::: {.callout-tip title="."} +If we wanted to retrieve counts of cells found within the individual gates, we could do so with `gs_pop_get_count_fast()` +::: +::: + +::: {.fragment} +```{r} +Data <- gs_pop_get_count_fast(gs) +head(Data, 5) +``` + +::: + +--- + +## Metadata + +::: {.fragment} +::: {.callout-tip title="."} +Since GatingSets contain multiple .fcs files, we may want to be able to subset them based on metadata for a particular variable. We can check to see current metadata using the `pData()` function. +::: +::: + +::: {.fragment} +```{r} +pData(gs) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +It currently doesn't have much, but we will explore how to change this more over the next few weeks. For now, just know that we could add additional metadata via either a .csv file, or by retrieving additional description keywords from within the .fcs files themselves (as shown below) +::: +::: + +::: {.fragment} +```{r} +AlternateGS <- flowjo_to_gatingset(ws=ws, name=1, path = Folder, + additional.keys="GROUPNAME", + keywords=c("$DATE", "$CYT", "GROUPNAME")) +pData(AlternateGS) +``` + +::: + +--- + +## ggcyto + +::: {.fragment} +::: {.callout-tip title="."} +As you can surmise, a lot of the infrastructural style handling done by commercial softwares is being orchestrated/mediated through our GatingSet object. Since it's able to create and retain gating information, how would we go about visualizing the underlying data contained within each? +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Within R, most plots are generated using the `ggplot2` package from the tidyverse (which we will explore [next week](/Schedule.qmd#visualizing-with-ggplot2)), which builds of the ["Grammar of Graphics"](https://vita.had.co.nz/papers/layered-grammar.html) concept, combining [layers](https://friendly.github.io/6135/lectures/ggplot-intro.pdf) together to create the final plots. The Bioconductor `ggcyto` R package extends this concept to enable flow cytometry data contained within a GatingSet to be plotted. +::: +::: + +--- + +:::{.callout-important} + +As is the case with most free open-source software ([FOSS](https://en.wikipedia.org/wiki/Free_and_open-source_software)), R packages will change over time as their developers add new features, make improvements, or alter internal functions to speed things up. + +::: + + +:::{.callout-important} + +ggplot2 recently had a major [version](/course/01_InstallingRPackages/index.qmd#installing-specific-package-versions) change, with [significant](https://tidyverse.org/blog/2025/09/ggplot2-4-0-0/) internal changes occuring. As a consequence of these changes, `ggcyto` functions that relied on the old `ggplot2` functions [broke](https://github.com/RGLab/ggcyto/pull/103) and had to be [updated](https://github.com/RGLab/ggcyto/pull/110). + +::: + +--- + +:::{.callout-important} + +Any updates to CRAN packages are reflected immediately. By contrast, Bioconductor is on a twice yearly [release cycle](https://www.bioconductor.org/developers/release-schedule/), so to take advantage of the `ggcyto` "fixes" that allow it to interact with the new version of `ggplot2`, we will need to make sure we have the "developmental" version installed. + +::: + +--- + +### packageVersion + +::: {.fragment} +::: {.callout-tip title="."} +Let's start off by checking what version of both the `ggplot2` and `ggcyto` packages you currently have installed on your computer. +::: +::: + +::: {.fragment} +```{r} +packageVersion("ggplot2") +``` + +::: + +::: {.fragment} +```{r} +packageVersion("ggcyto") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If you were able to retrieve the following package versions (or greater") for `ggplot2` and `ggcyto`, you should be all set and can skip the subsequent reinstallation steps. +::: +::: + +--- + +![](images/20_PackageVersion.png) + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If you however found you have the older package versions (ex. ggplot2 3.5.2 or ggcyto 1.37.1) currently installed, you will likely encounter errors when trying to run the functions to plot your data below (since the changes are not fully [backward-compatible](https://en.wikipedia.org/wiki/Backward_compatibility) with older versions). +::: +::: + +--- + +### remove.packages + +::: {.fragment} +::: {.callout-tip title="."} +Since `ggcyto` has a hard-coded dependency on ggplot2, if you have the older versions, I would recommend uninstaling both first, using the `remove.packages()` function. +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +remove.packages("ggplot2") +remove.packages("ggcyto") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Once this is done, I recommend exiting and then reopening Positron. This will ensure all currently-loaded R packages are unattached from the environment. However, you will loose all your environmental variables, so will need to reload them to get back to this point. If you are working with code chunks inside a Quarto Markdown File (.qmd), you can quickly accomplish this by scrolling down to the point of the document where you left off, and selecting the "Run Above" option showin on the code chunk. +::: +::: + +--- + +![](images/RunAbove.png) + +--- + +### Installing correct versions + +::: {.fragment} +::: {.callout-tip title="."} +To reinstall `ggplot2`, you just need to install again from CRAN (as with it's [rolling-release](https://cran.r-project.org/web/packages/policies.html) model any changes the developers make become immediately available to everyone) +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +install.packages("ggplot2") +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +If you need to reinstall `ggcyto`, because of Bioconductor's twice yearly [release cycle](https://www.bioconductor.org/developers/release-schedule/), you will need to install the "developmental" version to take advantage of the fixes. Since this is for a one-off package, the easiest installation approach if to go via the [GitHub](/course/01_InstallingRPackages/index.qmd#install-from-github) using the `remotes` package's `install_github()` +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +remotes::install_github("RGLab/ggcyto") +``` + +::: + +--- + +## Plotting + +::: {.fragment} +::: {.callout-tip title="."} +Once you have the current versions of both `ggplot2` and `ggcyto`, we can proceed to attach them to your local environment via the `library()` function. +::: +::: + +::: {.fragment} +```{r} +library(ggplot2) +library(ggcyto) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +As was mentioned, `ggcyto` follows the `ggplot2` grammar of graphics syntax, which we will learn more extensively [next week](/Schedule.qmd#visualizing-with-ggplot2). For now, lets look at a simple example +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +ggcyto(gs[1], subset="root", aes(x="FSC-A", y="SSC-A")) + geom_hex(bins=100) +``` + +::: + +--- + + +::: {.fragment} +::: {.callout-tip title="."} +The function responsible for plotting is the `ggcyto()` function. The first argument ("gs[1]") is designating which .fcs file in our GatingSet we are trying to visualize. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +The second argument ("subset") corresponds to which gating node we want to visualize. In this case, when set to "root", we are seeing all cells present in the .fcs file. If we however wanted to visualize the cells within the CD4+ gate, we would swap the value provided to this argument. +::: +::: + +::: {.fragment} +```{r} +#| eval: FALSE +ggcyto(gs[1], subset="CD4+", aes(x="FSC-A", y="SSC-A")) + geom_hex(bins=100) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +The next argument "aes" stands for aesthetics (more on this [next week](/Schedule.qmd#visualizing-with-ggplot2)). You will notice it has its own set of parenthesis, in which we designate the markers/fluorophores we want to visualize on the x and y axis. +::: +::: + +::: {.fragment} +::: {.callout-tip title="."} +The final argument ("+ geom_hex(bins=100)") specifies we want to generate a flow cytometry style plot, with it's bin arguments value setting the resolution. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Now that we have walked through the arguments, let's visualize the data +::: +::: + +::: {.fragment} +```{r} +#| eval: TRUE +ggcyto(gs[1], subset="CD4+", aes(x="FSC-A", y="SSC-A")) + geom_hex(bins=100) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Alternatively, if we switched things around +::: +::: + +::: {.fragment} +```{r} +ggcyto(gs[1], subset="CD8+", aes(x="IFNg", y="TNFa")) + geom_hex(bins=100) +``` + +::: + + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Briefly, if we didn't remember the marker, we could specify the fluorophore +::: +::: + +::: {.fragment} +```{r} +ggcyto(gs[1], subset="CD8+", aes(x="BV750-A", y="PE-Dazzle594-A")) + geom_hex(bins=100) +``` + +::: + +--- + +::: {.fragment} +```{r} +ggcyto(gs[6], subset="Tcells", aes(x="CD4", y="CD8")) + geom_hex(bins=100) +``` + +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +This is all we will cover for `ggcyto` for now, we will circle back over the [next couple weeks](/Schedule.qmd#applying-transformations-and-compensation) as we gain more familiarity with how to build our own GatingSet objects. If you want to jump ahead, please see the additional resources section and happy exploring! +::: +::: + +--- + +# Take Away + +::: {.fragment} +::: {.callout-tip title="."} +Today, we looked at the two main representations of flow cytometry data in R, the older `flowCore` implemented flowFrame/flowSet objects that are stored in RAM, and the `flowWorkspace` cytoFrame/cytoSet objects that operate through memory pointers. We started our learning journey to understand GatingSet objects, and how to use them to mediate/orchestrate in R many of the infrastructural steps that would normally be performed by commercial software. And finally, we briefly covered how to use the `ggcyto` to visualize data contained within our GatingSets. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Similar to our utilization of [tidyverse](/course/04_IntroToTidyverse/) functions last week, we will be using GatingSets continously throughout the rest of the course. Over the next few weeks we will instead of retrieving already assembled GatingSets via `CytoML` assemble them from scratch within R. +::: +::: + +--- + +::: {.fragment} +::: {.callout-tip title="."} +Next week, we will dive further into the `ggplot2` package from the tidyverse and how it implements the ["Grammar of Graphics"](https://vita.had.co.nz/papers/layered-grammar.html) concept. In the process, we will see how by combining [layers](https://friendly.github.io/6135/lectures/ggplot-intro.pdf) and changing various elements being added on to the base layers of the plot, we can end up with many different plots we normally encounter as cytometrist. +::: +::: + +--- + +![](images/SunsetSatzi.jpg) + +--- + +# Additional Resources + +[flowWorkspace Bioconductor Vignette](https://www.bioconductor.org/packages/release/bioc/vignettes/flowWorkspace/inst/doc/flowWorkspace-Introduction.html) The Bioconductor vignettes are always a good place to start with any of the Cytoverse packages, the vignette for `flowWorkspace` is no exception. If you want to understand more about how to subset cytosets, or the various functions and arguments in a GatingSet, this should be your first stop. + +[CytoML Bioconductor Vignette](https://www.bioconductor.org/packages/release/bioc/vignettes/CytoML/inst/doc/flowjo_to_gatingset.html) If you use FlowJo, Diva, or CytoBank routinely, and want to understand more about how to bring in your own experiments to R, the `CytoML` vignettes should be your next stop. + +--- + +[ggcyto Bioconductor Vignette](https://www.bioconductor.org/packages/release/bioc/vignettes/ggcyto/inst/doc/Top_features_of_ggcyto.html). There are several vignettes that can be found on the `ggcyto` Bioconductor [website](https://www.bioconductor.org/packages/release/bioc/html/ggcyto.html) on how to plot your flow cytometry data, this one surmize many of the points we will be covering over the next few weeks. + +[Bioc2023 Workshop: Reproducible and programmatic analysis of flow cytometry experiments with the cytoverse](https://youtu.be/_8x-prIxJgw?si=MhVVUJJdYEDI4JzV) Ozette hosted a workshop covering many of the cytoverse R packages at the Bioconductor conference (BioC) back in 2023. Some of the contents we will cover in greater depth over the next few weeks. + +--- + +# Take-home Problems + +:::{.callout-tip title="Problem 1"} + +Using what you learned last week in [Introduction to Tidyverse](/course/04_IntroToTidyverse/), for the imported GatingSet, retrieve the data.frame from cell counts per gate and attempt to mutate a new column showing percent of the parent gate. Remember, this is intentionally tricky at this point, we will go over how to efficiently do this in a [few weeks](/Schedule.qmd#retrieving-data-for-statistics) + +::: + +--- + +:::{.callout-tip title="Problem 2"} + +As we saw, `CytoML` can be finicky when names are repeated, or .fcs files are not present. Try removing a couple of the .fcs files from the data folder, and re-run the code. Document what kind of errors result. + +::: + +--- + +:::{.callout-tip title="Problem 3"} + +For `ggcyto`, attempt to generate plots to visualize TNFa and IFNg for the various cell populations, across both Ctrl and SEB samples. In the process, change the bins argument until you end up with a resolution that you would be happy with for your own plots, and write it down. + +::: + +--- + +![](images/SunsetSatzi.jpg) + +--- + +::: {style="text-align: right;"} +[![AGPL-3.0](https://www.gnu.org/graphics/agplv3-with-text-162x68.png)](https://www.gnu.org/licenses/agpl-3.0.en.html) [![CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](http://creativecommons.org/licenses/by-sa/4.0/) +::: \ No newline at end of file diff --git a/course/index.qmd b/course/index.qmd index 535ef6f..4263b3a 100644 --- a/course/index.qmd +++ b/course/index.qmd @@ -1,3 +1,49 @@ +<<<<<<< HEAD +--- +title: "Cytometry in R" +format: html +--- + +![](/images/WebsiteBanner.png) + +Cytometry in R is a free virtual mini-course being organized by the [Flow Cytometry Shared Resource](https://www.medschool.umaryland.edu/cibr/core/umgccc_flow/) Core at the [University of Maryland's Greenebaum Comprehensive Cancer Center](https://www.umms.org/umgccc). This course is a passion project arising from our desire to contribute back to the community. + +We are excited that so many individuals worldwide have chosen to take part, and we look forward to helping you get started on your own learning journeys. + +![](/images/WorldwideSignups.png){width=100%} + +# Participating + +The course will start the first week of February, with Week #1 resources being released on Sunday, February 1st at 2200 EST (Monday 0300 GMT+0). See below for additional details. + +## Resources + +The pre-course learning materials are now [available](/course/00_GitHub/index.qmd), providing walkthroughs of how to set up your workstations with the required software, and exercises to help you become more familiar with the various teaching and coding resources we will be using throughout the course. + +Narrated versions of the walk through materials are now also available via [YouTube](https://www.youtube.com/@CytometryInR) + + +## In-Person (Baltimore) + +For those joining us in person, the class is being offered on Monday, Tuesday and Thursday from **4-5 pm EST** in Bressler Research Building Room 7-035. We invite you to make whichever session best fits your schedule. Monitors to plug your laptops in will be available on a first come, first served basis. These in-person sessions will not be recorded, but with the smaller class size you will have our undivided attention should you have any questions. + +## Virtual (Worldwide) + +For those joining us virtually, we will have three separate livestreams throughout the week on [YouTube](https://www.youtube.com/@CytometryInR). These will be offered on: + +- Tuesday 2200 EST (Wednesday 0300 GMT+0) +- Wednesday 1600 EST (Wednesday 2100 GMT+0) +- Thursday 1000 EST (Thursday 1500 GMT+0) + +All three livestreams will be recorded and available on YouTube immediately afterwards. + +## Discussion Forum + +We will be using the Cytometry in R [Discussions page](https://github.com/UMGCCCFCSR/CytometryInR/discussions) as a community forum, and a place to ask questions, celebrate wins, and provide feedback. After creating a a [GitHub](/course/00_GitHub/index.qmd) account, pleae go introduce yourself. + + + +======= --- title: "Cytometry in R" format: html @@ -40,3 +86,4 @@ We will be using the Cytometry in R [Discussions page](https://github.com/UMGCC +>>>>>>> 23a81a59a64966e782d820f6b60f087d577c3b25 diff --git a/docs/ExistingResources.html b/docs/ExistingResources.html index a22c58e..ed61160 100644 --- a/docs/ExistingResources.html +++ b/docs/ExistingResources.html @@ -1,800 +1,800 @@ - - - - - - - - - -Existing Resources – Cytometry in R - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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We are not the first “Cytometry in R” course, nor will we be the last. This page is linking to the already existant online Cytometry in R resources that we have encountered and benefited from during our own learning journey. May they prove useful to you as you progress your way through yours!

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Christopher Hall - Flow Cytometry Data Analysis in R

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Cytometry-R-Scripts: R scripts to help with your flow cytometry analysis

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Workshop: Reproducible and programmatic analysis of flow cytometry experiments with the cytoverse

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Pritam Kumar Panda - Flow Cytometry Data Analysis & Visualization in R using CytoExploreR

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Flow-Cytometry-analysis-in-R

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Flow Cytometry Data Analysis & Visualization in R using CytoExploreR: Complete Guide

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Bioinformatics DotCa - Introduction to Flow Cytometry in R

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Introduction to Flow Cytometry in R

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Introduction to Flow Cytometry in R

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Clustering and Additional FCM Tools

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Tulika Rai - Learn Innovatively With Me

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flowAI Flow Cytometry Data Cleaning using R

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flowAI Flow Cytometry Data Cleaning using R: A Step-by-step Tutorial

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tSNE UMAP TRIMAP colorization or Transformation using R script

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{tidytof}: Predicting Patient Outcomes from Single-cell Data using Tidy Data Principles

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Cytometry on Air: Analyzing Flow Cytometry Data in R Presentation by TJ Chen and Greg Finak,

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Guillaume Beyrend - Learn Cytometry

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Hong Qin - flow analysis in R

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Flow Analysis in R

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flow analysis in R, bio125, Spring 2015

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We are not the first “Cytometry in R” course, nor will we be the last. This page is linking to the already existant online Cytometry in R resources that we have encountered and benefited from during our own learning journey. May they prove useful to you as you progress your way through yours!

+


+
+
+

Christopher Hall - Flow Cytometry Data Analysis in R

+

Cytometry-R-Scripts: R scripts to help with your flow cytometry analysis

+

R_flowcytometry_course: The files and presentation from the Cytometry Core Facility flow cytometry data analysis course in R

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+

Installation and Loading Data

+

(1) Flow Cytometry Data Analysis in R - Installation and Loading Data

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Compensation, Cleaning, Transformation, Visualization

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(2) Flow Cytometry Data Analysis in R: compensation, cleaning, transformation, visualization

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Gating with flowWorkspace

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(4) Flow Cytometry Data Analysis in R: Visualisation

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Ozette Technologies - BioC 2023 Workshop

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Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew McDavid.

+

Workshop: Reproducible and programmatic analysis of flow cytometry experiments with the cytoverse

+ +


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Pritam Kumar Panda - Flow Cytometry Data Analysis & Visualization in R using CytoExploreR

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Flow-Cytometry-analysis-in-R

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CytoExploreR-Interactive-visualization

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Complete Guide

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Flow Cytometry Data Analysis & Visualization in R using CytoExploreR: Complete Guide

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Bioinformatics DotCa - Introduction to Flow Cytometry in R

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Introduction to Flow Cytometry in R

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Introduction to Flow Cytometry in R

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Exploring FCM Data in R

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Exploring FCM Data in R

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Processing and Quality Assurance of FCM Data

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Processing and Quality Assurance of FCM Data

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1D Dynamic Gating

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1D Dynamic Gating

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Clustering and Additional FCM Tools

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Clustering and Additional FCM Tools

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Tulika Rai - Learn Innovatively With Me

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+

flowAI Flow Cytometry Data Cleaning using R

+

flowAI Flow Cytometry Data Cleaning using R: A Step-by-step Tutorial

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tSNE UMAP TRIMAP colorization or Transformation using R script

+

tSNE UMAP TRIMAP colorization or Transformation using R script

+ +


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Givanna Putri - Introduction to Cytometry Data Analysis in R workshop

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ACS 2021 Workshops - Introduction to Cytometry Data Analysis in R workshop

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Timothy Keyes -

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{tidytof}: Predicting Patient Outcomes from Single-cell Data using Tidy Data Principles

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Ryan Duggan - Cytometry on Air

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Cytometry on Air: Analyzing Flow Cytometry Data in R Presentation by TJ Chen and Greg Finak,

+ +


+
+
+
+

Guillaume Beyrend - Learn Cytometry

+

Learn Cytometry Originally appeared to have been paywalled, doesn’t currently appear to be the case.

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Hong Qin - flow analysis in R

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Flow Analysis in R

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flow analysis in R, bio125, Spring 2015

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Flow Cytometer Data Analysis

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BIO233 demo, flow cytometer data analysis, simple example

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Swayam Prabha - Flow cytometry data analysis in R/Bioconductor

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Lecture 15 : Flow cytometry data analysis in R/Bioconductor

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AGPL-3.0 CC BY-SA 4.0

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+ + + + \ No newline at end of file diff --git a/docs/PackageWalkthroughs.html b/docs/PackageWalkthroughs.html index 211cf96..810c7af 100644 --- a/docs/PackageWalkthroughs.html +++ b/docs/PackageWalkthroughs.html @@ -1,905 +1,905 @@ - - - - - - - - - -Package Walkthroughs – Cytometry in R - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Background

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The purpose of this page is to host the Vignette writing challenge entries. There are a substantial number of R packages on both Bioconductor and GitHub that we will not be able to get to during the course. My goal for the off-weeks is to have the class assist in navigating through the existing vignettes/articles for each package, and write up a basic .qmd file to help anyone trying to use these packages have a simpler learning curve in doing so than they would have otherwise.

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Bioconductor

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flowCore

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cytolib

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flowWorkspace

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ncdfFlow

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flowViz

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FlowSOM

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ggcyto

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openCyto

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quantiseqr

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flowStats

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CytoML

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CATALYST

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flowAI

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diffcyt

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flowDensity

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PeacoQC

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flowFP

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flowClean

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COMPASS

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SamSPECTRAL

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cydar

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MAPFX

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tidyFlowCore

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tidytof

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GitHub

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autospill

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flowMagic

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AGPL-3.0 CC BY-SA 4.0

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Made with Quarto

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AGPL-3.0 CC-BY-SA

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- - - - + + + + + + + + + +Package Walkthroughs – Cytometry in R + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + +
+ +
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+

Package Walkthroughs

+
+ + + +
+ + + + +
+ + + +
+ + +

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+

AGPL-3.0 CC BY-SA 4.0

+
+
+

Background

+

The purpose of this page is to host the Vignette writing challenge entries. There are a substantial number of R packages on both Bioconductor and GitHub that we will not be able to get to during the course. My goal for the off-weeks is to have the class assist in navigating through the existing vignettes/articles for each package, and write up a basic .qmd file to help anyone trying to use these packages have a simpler learning curve in doing so than they would have otherwise.

+
+
+

Bioconductor

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+

flowCore

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cytolib

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+

flowWorkspace

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+
+

ncdfFlow

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+

flowViz

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FlowSOM

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ggcyto

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openCyto

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quantiseqr

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flowStats

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CytoML

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CATALYST

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flowAI

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diffcyt

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flowDensity

+
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flowMeans

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+

PeacoQC

+
+
+

flowFP

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+

flowClean

+
+
+

flowPeaks

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COMPASS

+
+
+

SamSPECTRAL

+
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+

flowVS

+
+
+

cydar

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+

flowMerge

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flowTrans

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distinct

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+

flowCut

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flowMatch

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flowBeads

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+

flowTime

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sccomp

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flowCHIC

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flowSpecs

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DepecheR

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treekoR

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flowBin

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MetaCyto

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immunoClust

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scDataviz

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cytoMEM

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flowPloidy

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plotGrouper

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CytoDx

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Sconify

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flowPlots

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GateFinder

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flowGate

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flowGraph

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infinityFlow

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cyanoFilter

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optimalFlow

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CytoGLMM

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scifer

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cytoKernel

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CytoPipeline

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censcyt

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flowCyBar

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reconsi

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MACSQuantifyR

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CytoMDS

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CytoPipelineGUI

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MAPFX

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spillR

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tidyFlowCore

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+

CyTOFpower

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tidytof

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SuperCellCyto

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GitHub

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autospill

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autospectral

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+
+

flowMagic

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+

AGPL-3.0 CC BY-SA 4.0

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+ + +
+
+ +
+ +
+
+
+
+

Made with Quarto

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+   +
+
+

AGPL-3.0 CC-BY-SA

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+
+
+ + + + \ No newline at end of file diff --git a/docs/course/00_BonusContent/Immport/images/index.html b/docs/course/00_BonusContent/Immport/images/index.html index 748afa5..0801bc5 100644 --- a/docs/course/00_BonusContent/Immport/images/index.html +++ b/docs/course/00_BonusContent/Immport/images/index.html @@ -212,7 +212,7 @@
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    - - Intro to R + + 01 - Installing R Packages
    diff --git a/docs/course/00_Floreada/slides.html b/docs/course/00_Floreada/slides.html index 9e2b8ea..80582e0 100644 --- a/docs/course/00_Floreada/slides.html +++ b/docs/course/00_Floreada/slides.html @@ -1,1525 +1,1525 @@ - - - - - - - - - - - - - - Cytometry in R – Using Floreada - - - - - - - - - - - - - - - - - -
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    Using Floreada

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    -David Rach -
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    2026-02-01

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    AGPL-3.0 CC BY-SA 4.0

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    Background

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    As a “Cytometry in R” course, we will primarily be working in R. However, within our daily workflows and projects here at our flow cytometry core, we often use various flow cytometry softwares (like FlowJo or FCS Express) for various tasks. Fortunately, R packages like CytoML can allow us to import our manually drawn gates from existing FlowJo workspaces so that we can work with them in R.

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    For this course, we are adamant about staying neutral in regards to both commercial software or instrument vendors as much as possible. If they have worked with the open-source community to make their files readable and accessible via R, we will showcase how to integrate those tools into your own workflows. At the same time, this being a free course, it doesn’t make sense to turn around and ask you to go and either free trial or buy an expensive software license just to see how a particular free R package works.

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    Fortunately, for showing how to use this CytoML functionality, we can use Floreada.io. It is a simple (but free) web-based analysis platform that can be used to draw manual gates for your .fcs files of interest. These can then be saved as Floreada workspaces for later use. We typically recommend it to users from labs that do flow experiments infrequently. Fortunately thanks to the hard work of its developers, it can also save the gated files as FlowJo v10 .wsp files, which with a small workaround become usable within the CytoML pipeline.

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    To facilitate this, we will provide a small walk-through of how to use it for those who want to create a .wsp with their own .fcs files for Week 5.

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    Walk-through

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    Floreada

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    Loading Dataset

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    First, open your web browser and navigate to the website

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    Click on Start to proceed to the next page.

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    Once that is done, select the File tab on the upper navigation bar. Then click on Open File(s).

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    From there, select your .fcs files of interest, and click Open.

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    The .fcs files will now load in, and you should see a view similar to the one below. On the left side-bar, you have your gating options (Rectangle, Polygon, Range, Elipse, Quad, etc). Next to these on the right you have the FCS files that are loaded into the workspace. Then on the right, you have the visual display for your selected specimen.

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    Switching Axis Markers

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    If you left click on the axis name (SSC-H or FSC-H in this case), you will be able to select other markers by which to gate your specimen. For the provided example, we were using a raw spectral flow cytometry .fcs file, so the names of the detectors are present.

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    For now, I plan to start off by gating for singlets. I switch the y-axis to FSC-H, and then proceed to switch the x-axis to FSC-A.

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    With this done, I can now select the Poly gate tab on the upper left.

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    Then manually click on the locations on the plot to add the individual gate nodes.

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    To complete the gate, I click back to the original node point. At this point, the popup will allow you to name the gate.

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    To adjust the polygon gate, you can click on a node and drag it to expand or contract in a particular direction

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    To move the entire gate, first click on a node to select the gate, then click in the center of the gate to adjust its location.

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    Additional Gates

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    Unfortunately for those with the force-of-habit from using other softwares, double-clicking within the gate doesn’t do anything. To continue gating on the selected cells, you will need to click on the newly created gate name on the left. This will result in visualizing the isolated cells.

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    Once this is done, you can repeat the previous steps to change the axis markers and create a second gate. For this example, we went with a “Cells” gate to exclude debris from this particular sample.

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    Having created the “Cells” gate, we will be switching gating based on FSC and SSC to using the detector parameters.

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    The samples in this example were acquired to derive the cell counts and concentration of various cell populations within cryopreserved cord and peripheral blood mononuclear cells (CBMC and PBMC) specimens after thawing.

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    They were stained with CD19 BV421, CD45 PE, and CD14 APC on a 5-Laser Cytek Aurora, before unmixing, this would correspond respectively to V1, YG1/B4, R1/YG4 peaks respectively.

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    To change the scaling/transformation, we need to click directly on the axis.

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    From there, when we click on the drop-down, we see the various transformation options. We will select Logicle, given we are working with spectral flow cytometry files.

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    This y-axis values are subsequently visualized with the logicle transformation applied, increasing our resolution between the positive and negative population.

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    We can then repeat this for the x-axis, adjusting the fine-tune options for the scaling as needed.

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    With this done, let’s first draw a rectangle gate for the CD45+ (B4-A) cells.

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    And then selecting that population by clicking on the gate name, let’s proceed and gate the CD19+ cells (V2-A).

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    As you can see, we now have the various gates present in the gating hierarchy for the respective .fcs file. To return to a previous gated population, we would click on the parent population above it.

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    We can subsequently add an additional gate at this gating level for the likely debris population (the threshold setting was suboptimal for this experimental run).

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    Copying Gates

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    This was the process for gating for a single specimen. To copy gates over to the other specimens, we have two options. First, holding down your Ctrl (or equivalent) button, you can click on the individual gate names.

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    From there, you can drag them down to the next specimen and apply them.

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    Alternatively, you can drag down the highlighted gated to the Pipelines Tab, and apply to All Files. This will result in the gates being copied to all specimens in the experiment.

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    Adjustments within Pipelines will carry over to all other respective unmodified specimens that share it’s gates.

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    Once this is done, I recommend cycling through the gates for each specimen, just to ensure that the gates were positioned correctly before saving the workspace.

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    Saving Workspace

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    With everyone now “correctly” gated, we can proceed to save the workspace so that we can reopen it later from another browser.

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    To do this we open the File tab from the upper navigation bar, and select Save Workspace.

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    From there we have a couple options, for now let’s select Floreada Workspace. Where it is saved at will depend on your individual browser settings, so watch for a popup.

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    Alternatively (and crucially for the CytoML pipeline) we can also choose to save it as a FlowJo v10 .wsp file.

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    In both cases, you will end up with Workspace files that can be used later to access your created gates

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    Reopening Workspace

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    To reopen the Floreada workspace within the browser, reopen the website, and select the Open File(s) option.

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    From there, select both the Floreada Workspace file as well as the .fcs files

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    At which point you will now be back to the point you last saved at.

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    CytoML

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    Due to a unknown formatting bug, the Floreada produced FlowJo v10 .wsp is not directly accessible by CytoML at the time of this course. However, the issue is resolved as soon as the file is opened the first time within FlowJo v10, regardless of whether you have a log in or not. Strange? Yes, but we will take the workaround.

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    So, for anyone on Windows or MacOS, download FlowJo v10. Once installed, open the software, and close the login popups. Once there, open the Floreada created FlowJo.wsp file. Since you haven’t logged in, it won’t show any events. But it will correct the formatting bug. Close the software, and return to R. Your Floreada sourced .WSP file should now be readable by CytoML.

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    Odd? For sure. Fixable? Likely, I will set a reminder to work with the Floreada and CytoML devs to see if we can cut out the need for this workaround.

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    Wrap-up

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    Additional Resources

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    Floreada Documentation

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    AGPL-3.0 CC BY-SA 4.0

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    - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + Cytometry in R – Using Floreada + + + + + + + + + + + + + + + + + +
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    Using Floreada

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    +David Rach +
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    2026-02-01

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    AGPL-3.0 CC BY-SA 4.0

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    Background

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    As a “Cytometry in R” course, we will primarily be working in R. However, within our daily workflows and projects here at our flow cytometry core, we often use various flow cytometry softwares (like FlowJo or FCS Express) for various tasks. Fortunately, R packages like CytoML can allow us to import our manually drawn gates from existing FlowJo workspaces so that we can work with them in R.

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    For this course, we are adamant about staying neutral in regards to both commercial software or instrument vendors as much as possible. If they have worked with the open-source community to make their files readable and accessible via R, we will showcase how to integrate those tools into your own workflows. At the same time, this being a free course, it doesn’t make sense to turn around and ask you to go and either free trial or buy an expensive software license just to see how a particular free R package works.

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    Fortunately, for showing how to use this CytoML functionality, we can use Floreada.io. It is a simple (but free) web-based analysis platform that can be used to draw manual gates for your .fcs files of interest. These can then be saved as Floreada workspaces for later use. We typically recommend it to users from labs that do flow experiments infrequently. Fortunately thanks to the hard work of its developers, it can also save the gated files as FlowJo v10 .wsp files, which with a small workaround become usable within the CytoML pipeline.

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    To facilitate this, we will provide a small walk-through of how to use it for those who want to create a .wsp with their own .fcs files for Week 5.

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    Walk-through

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    Floreada

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    Loading Dataset

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    First, open your web browser and navigate to the website

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    Click on Start to proceed to the next page.

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    Once that is done, select the File tab on the upper navigation bar. Then click on Open File(s).

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    From there, select your .fcs files of interest, and click Open.

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    The .fcs files will now load in, and you should see a view similar to the one below. On the left side-bar, you have your gating options (Rectangle, Polygon, Range, Elipse, Quad, etc). Next to these on the right you have the FCS files that are loaded into the workspace. Then on the right, you have the visual display for your selected specimen.

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    Switching Axis Markers

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    If you left click on the axis name (SSC-H or FSC-H in this case), you will be able to select other markers by which to gate your specimen. For the provided example, we were using a raw spectral flow cytometry .fcs file, so the names of the detectors are present.

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    For now, I plan to start off by gating for singlets. I switch the y-axis to FSC-H, and then proceed to switch the x-axis to FSC-A.

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    Creating Gates

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    With this done, I can now select the Poly gate tab on the upper left.

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    Then manually click on the locations on the plot to add the individual gate nodes.

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    To complete the gate, I click back to the original node point. At this point, the popup will allow you to name the gate.

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    To adjust the polygon gate, you can click on a node and drag it to expand or contract in a particular direction

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    To move the entire gate, first click on a node to select the gate, then click in the center of the gate to adjust its location.

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    Additional Gates

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    Unfortunately for those with the force-of-habit from using other softwares, double-clicking within the gate doesn’t do anything. To continue gating on the selected cells, you will need to click on the newly created gate name on the left. This will result in visualizing the isolated cells.

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    Once this is done, you can repeat the previous steps to change the axis markers and create a second gate. For this example, we went with a “Cells” gate to exclude debris from this particular sample.

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    Having created the “Cells” gate, we will be switching gating based on FSC and SSC to using the detector parameters.

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    The samples in this example were acquired to derive the cell counts and concentration of various cell populations within cryopreserved cord and peripheral blood mononuclear cells (CBMC and PBMC) specimens after thawing.

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    They were stained with CD19 BV421, CD45 PE, and CD14 APC on a 5-Laser Cytek Aurora, before unmixing, this would correspond respectively to V1, YG1/B4, R1/YG4 peaks respectively.

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    Scaling/Transformation

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    When we switch the axis, we can see that the scaling/transformation is not ideal, as the staining and not-staining populations are scrunched up together in the center of the plot.

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    To change the scaling/transformation, we need to click directly on the axis.

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    From there, when we click on the drop-down, we see the various transformation options. We will select Logicle, given we are working with spectral flow cytometry files.

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    This y-axis values are subsequently visualized with the logicle transformation applied, increasing our resolution between the positive and negative population.

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    We can then repeat this for the x-axis, adjusting the fine-tune options for the scaling as needed.

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    With this done, let’s first draw a rectangle gate for the CD45+ (B4-A) cells.

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    And then selecting that population by clicking on the gate name, let’s proceed and gate the CD19+ cells (V2-A).

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    As you can see, we now have the various gates present in the gating hierarchy for the respective .fcs file. To return to a previous gated population, we would click on the parent population above it.

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    We can subsequently add an additional gate at this gating level for the likely debris population (the threshold setting was suboptimal for this experimental run).

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    Copying Gates

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    This was the process for gating for a single specimen. To copy gates over to the other specimens, we have two options. First, holding down your Ctrl (or equivalent) button, you can click on the individual gate names.

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    From there, you can drag them down to the next specimen and apply them.

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    Alternatively, you can drag down the highlighted gated to the Pipelines Tab, and apply to All Files. This will result in the gates being copied to all specimens in the experiment.

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    Adjustments within Pipelines will carry over to all other respective unmodified specimens that share it’s gates.

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    Once this is done, I recommend cycling through the gates for each specimen, just to ensure that the gates were positioned correctly before saving the workspace.

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    Saving Workspace

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    With everyone now “correctly” gated, we can proceed to save the workspace so that we can reopen it later from another browser.

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    To do this we open the File tab from the upper navigation bar, and select Save Workspace.

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    From there we have a couple options, for now let’s select Floreada Workspace. Where it is saved at will depend on your individual browser settings, so watch for a popup.

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    Alternatively (and crucially for the CytoML pipeline) we can also choose to save it as a FlowJo v10 .wsp file.

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    In both cases, you will end up with Workspace files that can be used later to access your created gates

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    Reopening Workspace

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    To reopen the Floreada workspace within the browser, reopen the website, and select the Open File(s) option.

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    From there, select both the Floreada Workspace file as well as the .fcs files

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    At which point you will now be back to the point you last saved at.

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    CytoML

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    Due to a unknown formatting bug, the Floreada produced FlowJo v10 .wsp is not directly accessible by CytoML at the time of this course. However, the issue is resolved as soon as the file is opened the first time within FlowJo v10, regardless of whether you have a log in or not. Strange? Yes, but we will take the workaround.

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    So, for anyone on Windows or MacOS, download FlowJo v10. Once installed, open the software, and close the login popups. Once there, open the Floreada created FlowJo.wsp file. Since you haven’t logged in, it won’t show any events. But it will correct the formatting bug. Close the software, and return to R. Your Floreada sourced .WSP file should now be readable by CytoML.

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    Odd? For sure. Fixable? Likely, I will set a reminder to work with the Floreada and CytoML devs to see if we can cut out the need for this workaround.

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    Wrap-up

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    Additional Resources

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    Floreada Documentation

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    AGPL-3.0 CC BY-SA 4.0

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    AGPL-3.0 CC BY-SA 4.0

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    Background

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    Now that we have created a GitHub account, installed the required software and investigated Positron’s layout, we will start learning about version control software.

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    When working with code, it is important to stay organized. Ideally, everything needed for your code to successfully run should be present and accounted for within the local environment. Likewise, if you make changes, and your code stops working (no longer returning the expected output, ie. breaks), it would be most useful to have a track record of what has changed since your last working version in order to fix the issue. For beginners, this is often a typo in a function name or a misplaced comma somewhere within your document.

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    For this course, we will be using the version control software Git. It is widely used by software developers and bioinformaticians worldwide, and is a very useful tool to have in your coding toolbox.

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    Git works locally within your individual project folders to track changes to the documents within, allowing to save the current state of the folder along the way (ie. a commit). This allows you to compare to previous versions (other commits) and return the changes that have occured to the tracked files.

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    As we saw during the workstation setup section, when you have a linked GitHub account, you can backup folders as repositories online. By leveraging the ability to send and receive changes, this allows you to modify a file on one computer,

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    Individual repositories can be linked to a GitHub account, which permits them to be backed up online. Within our workflow, this allows to modify on one computer, back up (ie. push) the changes to GitHub, and then later on a different workstation, retrieve (ie. pull) these new changes and continue working.

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    In this walk-through, we will set up a New Project Folder from a template, create a few folders and files, and work through how to use the main set of Git commands needed for this course.

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    Getting Started

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    For this walkthrough, we are going to create a brand new project folder. To do this, we can open the folder tab on the upper right.

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    We will go ahead and select “New Folder from a Template” for this example.

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    New Folder from Template

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    Since Positron can use multiple programming languages, when we select “New Folder from Template” we will be asked what kind of folder template we want to use. Since we are working in R, we will select the “R Project” option.

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    We will next be asked to name the new project folder and a storage location.

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    One thing I would like to remind everyone who is just starting to code is that it is best to avoid using special characters (ex. @ $ # ^ ! ; : ,) in any folder or file name. This is because when coding, these can be misinterpreted as commands.

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    While spaces are generally okay, it is often to best stick to to stick to hyphens (-), underscores (_). We will explore naming conventions in more depth at a later time.

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    Another useful thing to know when getting started with version control, it is best to save your files within your local computer, avoid using OneDrive or other cloud storage options for the time reason. The reason behind is that permissions to write/save to the cloud locations can sometimes be quite finicky, and some autosave/indexing behaviors can cause issues. akes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder.

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    Having named our new Project Folder, and designated a storage location, go ahead and check the Initialize Git Repository option. This will indicate to version control to monitor content and changes to files within this folder.

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    The next setup screen will verify which version of R you wish to use. Since we are just getting started, your most recent version of R (usually system) should work. We will also leave the “renv” (reproducible environment setup) option unchecked for the time being (we will revisit the concept later in the course).

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    And if all goes well, we should see the “New Folder Created” popup.

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    Creating SubFolders

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    Once your new project folder has opened, you should be seeing the main layout elements that we briefly covered in the Positron walk-through.

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    For this section, we will primarily be focused on what is happening within the primary side bar on the left, where changes to the individual files within the folder since the last save/commit will be reflected by colored text.

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    For my own projects, there are some elements of organization that I go ahead and add for each new folder. These include both a data and an images subfolders to help keep things a little more organized.

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    To create these folders, we would click on the respective add folder (+) button on the side bar. Files and Folders can be clicked and dragged within the primary side bar to move things to new folder locations.

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    Creating Files

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    In context of this course, we will primarily be working with two types of files when coding:

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    • R Scripts: These files end in .R. These contain only code (with occasional # comment line). These are often used for self-contained code that once we get them working we rarely need to modify.

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    • Quarto Markdowns: These files end in .qmd. They contain a .yaml header, followed by a mix of regular written text (often explanations or other documentation), and sections (ie. chunks) that contain code. These are used when we are still getting the code to work, when we need to modify inputs frequently, or simply when we need to document what and why we are doing something to make life easier for our future-self two months from now.

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    In this example, I will go ahead and select the new file icon

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    Thenn I will name the file, and designate it as a Quarto Markdown file by adding the .qmd at the end of the name to denote the file type.

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    QMD Files

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    Once this is done, we can now see we have a new .qmd file (“Example.qmd” in this case).

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    YAML

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    What designates the location of the YAML block are three hyphens at the start, and three hyphens at the end. For this example, we will also provide a “title:” and “format:” field for the time being (see additional options here).

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    Text

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    With a basic YAML formatting block now in place, we can build out other elements of our Quarto Markdown document. Unless otherwise specified, everything else in the document is assumed to be text, so I will go ahead and provide an initial text description of what I am trying to do.

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    Code-Chunks

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    Having provided some initial text for documentation, we can then add code-block chunks to start writing some code.

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    The easiest way to do do this is to click the respective option on the upper-right of the Editor screen. Since Positron can handle multiple programming languages, so the chunk is inserted, we will need to select the language we use to be used within the code chunk (R in this case).

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    You will notice, that the inserted code block starts off with three backticks (`) and then “{r}”. The end of the code block is denoted by an additional three backticks.

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    We can also add new code blocks by simply typing these elements into the location we want to place a code chunk (as long as we are careful to add 3 backticks also at the end).

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    Running Code

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    Now that we have two code-chunks written, we can write lines of code within them. For this example, I will use two beginner friendly functions, print(“Hello”), which will print the contents contained between the ” ” to the console, and getwd() which will return the location of the folder you are working within (ie. the working directory).

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    To run/execute these lines of code, we have a couple options. We can click on the Run Cell option that appears on the upper-left side of the code chunk. Additionally, it has a companion option that will run all code chunks above it.

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    When a code block is successfully run, you will see within the console (lower bottom of the screen) the line of code be run, with any returned outputs appear directly after.

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    An alternative to clicking the Run Cell button is to click on the line of code you are interested in running, then press (Ctrl + Enter)/(Command + Enter). This will execute the line of code that you have clicked on. This can be useful in scenarios where you want to run a specific line, and not the entire code-chunk.

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    Using this approach, you can see the location (ie. file path) of the current working directory was returned to the Console.

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    Local Version Control

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    Having introduced the main elements of a Quarto Markdown file, let’s turn our attention to the tab within the editor showing our newly created .qmd file.

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    We can see there is a solid circle next to the file name, and it is appearing as green. The circle denotes unsaved changes, which we can correct by clicking on the Save Button to save the changes to our file.

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    Untracked

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    If we turn our attention to the left primary sidebar, we can see that within our GitPractie folder there are three files, our Example.qmd, and the default README.md and .gitignore files. These all show up in green text with U’s to the right of the file names.

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    This denotes that the version control tracking software Git is currently considering them as “Untracked” files. While saving the document via the Save button means we will still have our changes when we reopen Positron, we won’t have any history of changes that we can use to revert back to the way all the files appeared at this exact point in time should something go wrong.

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    We will next go the address bar on the very far left, and select the Git tab.

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    On the Git tab, we can see that each of the three files are shown underneath a “Changes” drop-down. This contains the files that have undergone changes since the last commit. In our case, since we haven’t updated the save-state yet, this last commit would be the initial creation of the project folder.

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    To have version control track these individual files going forward, we can do so in two separate ways. We can add them individually by clicking the + symbol next to the individual names.

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    Staged

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    This will result in the files being moved to the “Staged” dropdown. This denotes files being tracked with the intention of being recorded as the next save-state or waypoint (ie. a commit).

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    Commit

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    To create a new commit (save-state or waypoint), once we have the files we want to track staged, we will write a commit message, and then press commit.

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    A commit message is a brief description of the changes that have occurred to the files between this commit and the previous one. Make this short description informative enough that if you need to revert back in the future, you can quickly identify the commit you need to fall back to (more about this later).

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    If this your first time using version control, you will likely encounter the following pop-up asking that you provide a user.name and user.email. This is used to designate the author of the changes.If you get this popup, go ahead and select “Open Git Log”

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    UserName and UserEmail

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    The Output tab at the bottom of the screen will open, showing the messages that led to the popup.

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    The important part to note is the commands that will be needed to provide your user name and email to the computer for authoring the commit. Typically, your email will be the same one you used for your GitHub account.

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    “git config –global user.email”you@example.com””

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    Then click on the adjacent terminal tab. You will paste the command in, but do not hit enter just yet.

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    Windows users, please note, depending on your settings, if trying to paste from the keyboard into the terminal, you may need to press “Ctrl + Shift + V” instead of the usual “Ctrl + V”.

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    With the command now pasted (or typed), use your keyboard arrows to navigate to the email portion, and replace the generic email with your email address used for your GitHub account.

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    Make sure that the quotation marks (“) around the email address remain present, as they help the computer identify where your email address starts and ends. Once satisfied that your email address is correct, press enter.

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    Next up, repeat the process, this time copying over the command needed to set your user name to the terminal. Repeat the editing process to provide your name between the “” marks. Then press enter.

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    First Commit

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    Now that your user.name and email address have been provided, Git should be able to provide an author to the commit message. Reattempt to press commit button.

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    If this is successful, you will see your initial commit appear on the bottom half of the left primary side bar, under the Graph dropdown. Congrats! Your files are now being tracked by version control.

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    If you hover with your mouse arrow just over the commit, you can see the longer commit message and additional details appear.

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    If you click on the commit tab, a new display will open in the editor, displaying the changes that occured in that commit compared to the previous one. In this case, since we added everything since the previous commit, nothing appears on the left side, while the entire documents contents appear highlighted in green on the right.

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    Green highlighting is used to show additions, while red highlighting is used to show deletions.

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    Having completed this initial commit, for this example, let’s imitate a typical workflow and make some additional changes to the file before we make a second commit. Within text portions of the .qmd file, use of # denotes a section header in markdown, so let’s add a header for Introduction and click save.

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    Modified

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    Within the left primary sidebar, we can see that the Git tracking has updated. Examples.qmd is visible once again. However, becuase it is now a tracked file, instead of showing up with the “U/Untracked” green highlight, it now appears as a brownish-red with a “M/Modified”.

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    Let’s make an additional change to the .qmd file by adding another section (# Setup) and a code block with a commented out line (denoted by the # at the line start), before pressing Save.

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    If we were now to click on the Example.qmd file in the left primary sidebar, it will open the same kind of tracking display we saw previously. This time, we can see changes since our last commit. These appear as the green highlights along the scroll-bar, corresponding to the # Introduction and # Setup headers that we have added in since the last commit.

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    For a larger document, we can scroll down to see the various highlighted regions.

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    We could now repeat the steps showed above, staging the file, writing a commit message, and commiting again by clicking on the designated buttons.

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    An important question is how often should we commit, vs. just hit save? Well… it depends :D Let’s think about this in context of a video game. If you made commits at regular intervals throughout the day (or more frequently when doing something particularly risky), you are more likely to be close enough to a particular commit (waypoint/save-state) that you can quickly revert back to without loosing any progress. Alternatively, if your last commit was last week, you will not have any intermediate versions to fall back to.

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    Commit via Terminal

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    Having demonstrated how to commit changes to Git via the left primary side-bar, for this second commit, let’s do it the alternate way via the terminal (tab on the panel at the bottom of your screen).

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    After clicking on the terminal tab, click on blinking command line.

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    In this case, you would enter “git add Example.qmd” and press Enter.

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    You will see after pressing enter a new blank terminal line appear. If you glance at the left-sidebar, you can see that Example.qmd now appears under the Staged Changes dropdown.

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    Next up, let’s write the git commit via the terminal. In this case, the command would be “git commit -m” (-m denoting message). The commit text is then surrounded by “” marks.

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    For example: “git commit -m”Added section headers to my QMD file””

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    Press enter to save the commit.

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    And you should see your second commit now appear in the left primary sidebar underneath the graphs dropdown.

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    Remote Version Control

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    Copying Project Folder to GitHub

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    While having local version control in place is helpful when you need to revert back after encountering issues, where Git shines is the ability to pass your changes to your online GitHub repository.

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    Not only does this allow you to switch between computers, but should something disastrous happen to your main computer, you still have all your hard work backed up and readily assessible.

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    For this subsection, first, double check that Positron is still connected to your GitHub account by checking the user tab on the bottom-left. If not, repeat the connection setup.

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    Since our project was created using the “New Folder from Template” option, it currently only exist locally. What we want to do next is to copy it to our GitHub account, creating a new repository in the process.

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    To do this, we will first need to install the usethis R package. Within your console, you would run the following line of code:

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    Depending on what R packages you already have installed on your computer, you may get a prompt asking if you want to update/install additional dependencies. Go ahead and type the number corresponding to Update All, and press enter.

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    The package and all it’s dependencies should then install. If an error message appears, read through it, and follow provided instructions. Go to Discussions if need help.

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    Once the usethis package is installed, we need to activate it within R by calling it with the library command. This makes all the tools (ie. functions) within an R package available for use within Positron.

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    With library called, you now have access to the functions (tools) within the usethis R package. One of these is the use_github() function.

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    In Positron, if you hover over a function, it will pull up the associated help file which will provide you information about the arguments the function expects to receive, and what they do.

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    For use_github(), the main thing to remember for now is since this is a personal project being used for testing, we don’t necessarily want to share it with the entire world, so we should set the “private” argument equal to TRUE when creating a new repository.

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    Taking this information that we have now gathered, we can now within our Quarto Markdown create a code chunk, write out the line of code calling the function, and providing the Private=TRUE argument within the ().

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    Within a code chunk, adding a # in front of a line of code, will comment it out, resulting in that line of code not being run. Since we have already installed the usethis package, and we don’t want to reinstall it every single time, let’s go ahead and comment out that line. Go ahead and press Enter.

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    We will see a message pop-up in the console. In this case, we had not saved before pressing enter, so there are uncommitted changes within the folder. The pop-up is asking whether you want to save these as well before sending the Folder to GitHub.

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    In this case I will chose to ignore the uncommitted changes by entering 3 (for Definitely) in the console and hitting enter on my keyboard.

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    The usethis R package will then execute the series of git commands that are needed to set up a GitHub repository (ie. the messages being displayed in the console window), and when finished will open a pop-up asking whether you want to see your new repository in your default Web Browser. I will go ahead and select yes in this case.

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    After the browser opens, you can see that the elements I had staged and committed within Positron are now present within the GitHub repository. Since I had only staged Example.qmd, it is the only file that was backed up. We can also see the commit history online by clicking on the commit clock.

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    As we would expect, we only see our two commit messages. One important thing to note is the commit hash numbers, that denote a particular commit. If we decided to revert/fall back to a prior commit in the future, this would be the number we would need to provide to Git to return to that previous commit/save-state

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    Similarly, on GitHub, we have an option to Browse a Repository at a particular point in time. This will be quite useful later in the future when troubleshooting what major changes occurred between versions of an R package.

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    Code Chunk Arguments

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    Having successfully connected our local Project Folder to a remote GitHub repository, let’s return to Positron.

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    Before continuing, if we left the code chunk that created the GitHub repository as is, every time we ran all code chunks in the document, it would try to recreate the GitHub repository. We don’t want this to happen, as the setup was a one-time operation.

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    While we could add # in front of every line of code (or delete the code chunk entirely) it is often useful to have these set-up code chunks around to remind us what arguments we need to provide next time we need to a similar setup and are mind blanking on what to do.

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    Fortunately, Quarto allows us to set conditions on whether a chunk is run (ie. evaluated). We will discuss the conditiona arguments in more depth in the next section, but for now, we can modify the code chunk as follows.

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    On the next line after the {r}, we will add a hashtag (#), then a pipe (|), followed by a space. This is the setup for a code-chunk specific argument. We will then add “eval: FALSE”, which signals that the particular code-chunk should not be evaluated (ie, should not be run).

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    README

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    Now that we have connected our local Project Folder to GitHub, and have gotten a basic introduction to the “git add”, “git commit” arguments, let’s turn our focus to the other files currently listed as untracked by Git within our folder, the README.md and the .gitignore files.

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    When setting up our GitHub account, we encounted an example of a README.md file. This file often provides a brief description of the project, and an outline of what the other files in the folder are for. As you may have gathered, even software developers are forgetful/under-caffenaited, and having notes to catch back up to speed is important.

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    .gitignore

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    We additionally have a .gitignore file. Within a project, there are often some files that we will never want version control to track. These could be files that are too large for GitHub (ex. really large .fcs files), or files containing sensitive information (passwords, history, credentials, etc.).

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    When the names of these file (or the file type shothand) are added to the .gitignore file, they are ignored by version control, and no longer appear on the primary left side bar.

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    Let’s proceed and stage both the README.md and .gitignore file, so that changes to these files will be tracked. We can of course select both from the primary left side bar and write a short commit message.

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    Or alternatively, if we want to stage all uncommitted files present in a single step, we could in the terminal use the “git add .”

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    We can then write our git commit using “git commit -m”.

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    Both approaches work, and you may switch between them based on preferrence.

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    You will notice after having committed, that if you look at the Graph dropdown on the bottom half of the primary left side-bar that something has changed.

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    There are now separate icons denoted as main and origin/main. These correspond to the last commit present locally (main), and the last commit on remote (ie. GitHub, origin/main).

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    Local is ahead since you just made the commit with the changes inactivating the code-chunk, and you have not passed these changes up to GitHub yet.

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    Pull

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    Before sending (ie. pushing up) our updated commit to GitHub, especially if you are working on a project from multiple computers (or as part of a team) to bring in (ie. pull down) any changes that might be on GitHub that are not present locally.

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    This ensures that everything is up to date, and you don’t end up with mismatched commits that are incompatible with each other and trigger an error message.

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    To pull in changes from GitHub, at the top of the primary left side-bar, you can select the … button to open a drop-down menu of Git options. You would then select “Pull”.

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    Alternatively, you could do the same thing via the terminal by running the “git pull” command.

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    Push

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    In our case, there was no new material present on our GitHub repository that were not already present locally, so all that is returned is the “Already up to date” message.

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    We are now good to proceed to push (ie. send) the updated commit up to our GitHub repository.

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    We can do this by either pressing the Sync changes button, or via the terminal entering the “git push” command.

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    And now, if you glance down at left side-bar’s graph section, you will see that both the main and origin/main icons are now present for the most recent commit.

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    If we switch to our Web browser, we can see that this is also now the case for our GitHub repository that now also has the most recent changes.

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    Reverting to Prior Commit

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    For most daily-workflows, you will only need the git commands that we have introduced above (git add, commit, pull, push). The next two areas (reverting to a prior commit, and branches) are more specialized, and will be covered in greater depth later in the course. We are briefly covering them here. If you are at the point where your last remaining neuron has disconnected, and you feel you need to take a break from version control, feel free to skip to the next section and we will revisit these topics later in the course.

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    –

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    In most cases, if your code stops working, you can identify the issue and fix it in the existing version, never needing to resort to reverting to a previous commit (save-state). The times you would need to revert would be if you deleted important files, or the new files are hopeless mess that is not worth trying to sort through. In those cases, reverting back might be better approach.

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    To imitate a falling back scenario, lets create and additional file, stage and commit it to end up a commit ahead of where we are currently at within the Project Folder.

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    Now being one (or several) commits ahead, if we wanted to revert back, we would first need to identify the commit we want to revert back to and copy the commit hash number.

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    Then, opening the terminal, we can enter “git reset” and paste the hash afterwards. We can then press enter.

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    You will notice our additional commit has been removed, although the newer files we were working on subsequent last commit are still present.

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    If however, we had wanted to return to the exact same state as the previous commit (removing all subsequent created files), we could do so by adding in the –hard argument. Before starting, save any newer files you want to keep in a completely different folder, because they will be permanently removed.

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    Then, enter “git reset –hard thecommithashnumber” into the terminal, which would result in a “hard” return to the previous commits save-state. You may need to close and reopen Positron to see the changes reflected.

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    Branches

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    Branches are an useful Git feature that we will start using extensively later in the course. Branching allows you to create a parallel/carbon-copy of your existing repository, which you can then edit without affecting the main branch. This is particularly useful for projects that may get messy or drawn out. By isolating these edits to a parallel branch, if they don’t work, your main branch remains safe. Alternatively, if you like the changes that occurred in the branch, you can pull these changes from the branch back to main, bringing the timelines back together.

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    Within the terminal, entering “git branch” will show the existing branches. In this case, only main is present since we haven’t yet created a new branch.

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    We can create a new branch in the terminal by entering “git branch” followed by the name of our desired branch. In this case, we are creating a branch called Week1

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    Now, when we check “git branch” again in the terminal, which returns the two branches, Week1 and main. The * is located next to main, indicating that we are currently within the main branch.

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    Besides the terminal, we can also create a new branch via Positron. To do so, we first click on the Git tab in the Actions Bar.

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    Once the left-side bar displays the version control display, we can click on the … button (to the right of changes)to gain access to the Git options drop-down.

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    From here, we click on Branch, and then select Create Branch.

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    Using Git branch, we saw that we were still within the main branch. In the terminal, we can switch over to the Week1 branch by using the “git checkout” command, followed by the branch we wish to switch to.

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    This results in us switching over to the Week1 branch.

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    Having switched (ie. checkout) to the Week 1 branch, let’s create the file BranchTest.qmd, which will exist within this branch, but not yet in the main branch.

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    Having created the file, let’s stage and then commit it. This will put the Week1 branch ahead of the main branch by a single commit.

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    With our changes staged and committed, if we look at the left side-bar’s graph section, our Week1 branch is now ahead of the origin/main branch by one commit.

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    If we were to check on GitHub, we can see that no new files are present on the main branch, but can see the notification listing recent changes to Week1 branch.

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    Using the drop-down, we can switch from displaying the main branch to the Week1 branch, where we can see the new file.

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    If we click the green compare and pull request button, we end up on this screen. This compares how the two branches are different from each other.

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    We will delve into branches again at a later point. For now, remember that by creating and prunning parallel branches, you can develop knowing that even if something goes wrong, your main branch remains safe.

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    Wrap-Up

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    In this section, we saw how to create a New Project Folder, create files and back up the project folder to GitHub. We also started learning about git, covering the basic commands (git add, commit, pull, push). If you feel a bit overwhelmed, please know, that is normal. Understanding how to leverage git takes time and practice, but is an incredibly valuable skillset to have in the long run.

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    In the next section, we will look at how by changing various elements within our .qmd file produce a variety of files, and how to leverage code-chunk arguments to fine-tune whether a code-chunk is utilized.

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    Additional Resources

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    Git & GitHub Tutorial for Scientist: It’s Not Only for Programmers

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    Ten Simple Rules for Taking Advantage of Git and GitHub

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    A brief introduction to Git for beginers

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    AGPL-3.0 CC BY-SA 4.0

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    - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + Cytometry in R – Version Control with Git + + + + + + + + + + + + + + + + + +
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    Version Control with Git

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    +David Rach +
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    2026-02-01

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    AGPL-3.0 CC BY-SA 4.0

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    Background

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    Now that we have created a GitHub account, installed the required software and investigated Positron’s layout, we will start learning about version control software.

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    When working with code, it is important to stay organized. Ideally, everything needed for your code to successfully run should be present and accounted for within the local environment. Likewise, if you make changes, and your code stops working (no longer returning the expected output, ie. breaks), it would be most useful to have a track record of what has changed since your last working version in order to fix the issue. For beginners, this is often a typo in a function name or a misplaced comma somewhere within your document.

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    For this course, we will be using the version control software Git. It is widely used by software developers and bioinformaticians worldwide, and is a very useful tool to have in your coding toolbox.

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    Git works locally within your individual project folders to track changes to the documents within, allowing to save the current state of the folder along the way (ie. a commit). This allows you to compare to previous versions (other commits) and return the changes that have occured to the tracked files.

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    As we saw during the workstation setup section, when you have a linked GitHub account, you can backup folders as repositories online. By leveraging the ability to send and receive changes, this allows you to modify a file on one computer,

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    Individual repositories can be linked to a GitHub account, which permits them to be backed up online. Within our workflow, this allows to modify on one computer, back up (ie. push) the changes to GitHub, and then later on a different workstation, retrieve (ie. pull) these new changes and continue working.

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    In this walk-through, we will set up a New Project Folder from a template, create a few folders and files, and work through how to use the main set of Git commands needed for this course.

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    Getting Started

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    For this walkthrough, we are going to create a brand new project folder. To do this, we can open the folder tab on the upper right.

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    From here we can see we have two options, create a “New Folder from a Template”, and create a “New Folder from Git” (which was the option we used during workstation setup to bring in the forked CytometryInR and README repository folders locally).

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    We will go ahead and select “New Folder from a Template” for this example.

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    New Folder from Template

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    Since Positron can use multiple programming languages, when we select “New Folder from Template” we will be asked what kind of folder template we want to use. Since we are working in R, we will select the “R Project” option.

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    We will next be asked to name the new project folder and a storage location.

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    One thing I would like to remind everyone who is just starting to code is that it is best to avoid using special characters (ex. @ $ # ^ ! ; : ,) in any folder or file name. This is because when coding, these can be misinterpreted as commands.

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    While spaces are generally okay, it is often to best stick to to stick to hyphens (-), underscores (_). We will explore naming conventions in more depth at a later time.

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    Another useful thing to know when getting started with version control, it is best to save your files within your local computer, avoid using OneDrive or other cloud storage options for the time reason. The reason behind is that permissions to write/save to the cloud locations can sometimes be quite finicky, and some autosave/indexing behaviors can cause issues. akes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder.

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    Having named our new Project Folder, and designated a storage location, go ahead and check the Initialize Git Repository option. This will indicate to version control to monitor content and changes to files within this folder.

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    The next setup screen will verify which version of R you wish to use. Since we are just getting started, your most recent version of R (usually system) should work. We will also leave the “renv” (reproducible environment setup) option unchecked for the time being (we will revisit the concept later in the course).

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    And if all goes well, we should see the “New Folder Created” popup.

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    Creating SubFolders

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    Once your new project folder has opened, you should be seeing the main layout elements that we briefly covered in the Positron walk-through.

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    For this section, we will primarily be focused on what is happening within the primary side bar on the left, where changes to the individual files within the folder since the last save/commit will be reflected by colored text.

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    For my own projects, there are some elements of organization that I go ahead and add for each new folder. These include both a data and an images subfolders to help keep things a little more organized.

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    To create these folders, we would click on the respective add folder (+) button on the side bar. Files and Folders can be clicked and dragged within the primary side bar to move things to new folder locations.

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    Creating Files

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    In context of this course, we will primarily be working with two types of files when coding:

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    • R Scripts: These files end in .R. These contain only code (with occasional # comment line). These are often used for self-contained code that once we get them working we rarely need to modify.

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    • Quarto Markdowns: These files end in .qmd. They contain a .yaml header, followed by a mix of regular written text (often explanations or other documentation), and sections (ie. chunks) that contain code. These are used when we are still getting the code to work, when we need to modify inputs frequently, or simply when we need to document what and why we are doing something to make life easier for our future-self two months from now.

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    In this example, I will go ahead and select the new file icon

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    Thenn I will name the file, and designate it as a Quarto Markdown file by adding the .qmd at the end of the name to denote the file type.

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    QMD Files

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    Once this is done, we can now see we have a new .qmd file (“Example.qmd” in this case).

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    YAML

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    As previously mentioned, the start of a Quarto Markdown file containg a YAML code chunk that is used to set formatting choices (we will explore this in-depth during the next section)

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    What designates the location of the YAML block are three hyphens at the start, and three hyphens at the end. For this example, we will also provide a “title:” and “format:” field for the time being (see additional options here).

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    Text

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    With a basic YAML formatting block now in place, we can build out other elements of our Quarto Markdown document. Unless otherwise specified, everything else in the document is assumed to be text, so I will go ahead and provide an initial text description of what I am trying to do.

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    Code-Chunks

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    Having provided some initial text for documentation, we can then add code-block chunks to start writing some code.

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    The easiest way to do do this is to click the respective option on the upper-right of the Editor screen. Since Positron can handle multiple programming languages, so the chunk is inserted, we will need to select the language we use to be used within the code chunk (R in this case).

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    You will notice, that the inserted code block starts off with three backticks (`) and then “{r}”. The end of the code block is denoted by an additional three backticks.

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    We can also add new code blocks by simply typing these elements into the location we want to place a code chunk (as long as we are careful to add 3 backticks also at the end).

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    Running Code

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    Now that we have two code-chunks written, we can write lines of code within them. For this example, I will use two beginner friendly functions, print(“Hello”), which will print the contents contained between the ” ” to the console, and getwd() which will return the location of the folder you are working within (ie. the working directory).

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    To run/execute these lines of code, we have a couple options. We can click on the Run Cell option that appears on the upper-left side of the code chunk. Additionally, it has a companion option that will run all code chunks above it.

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    When a code block is successfully run, you will see within the console (lower bottom of the screen) the line of code be run, with any returned outputs appear directly after.

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    An alternative to clicking the Run Cell button is to click on the line of code you are interested in running, then press (Ctrl + Enter)/(Command + Enter). This will execute the line of code that you have clicked on. This can be useful in scenarios where you want to run a specific line, and not the entire code-chunk.

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    Using this approach, you can see the location (ie. file path) of the current working directory was returned to the Console.

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    Local Version Control

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    Having introduced the main elements of a Quarto Markdown file, let’s turn our attention to the tab within the editor showing our newly created .qmd file.

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    We can see there is a solid circle next to the file name, and it is appearing as green. The circle denotes unsaved changes, which we can correct by clicking on the Save Button to save the changes to our file.

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    Untracked

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    If we turn our attention to the left primary sidebar, we can see that within our GitPractie folder there are three files, our Example.qmd, and the default README.md and .gitignore files. These all show up in green text with U’s to the right of the file names.

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    This denotes that the version control tracking software Git is currently considering them as “Untracked” files. While saving the document via the Save button means we will still have our changes when we reopen Positron, we won’t have any history of changes that we can use to revert back to the way all the files appeared at this exact point in time should something go wrong.

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    We will next go the address bar on the very far left, and select the Git tab.

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    On the Git tab, we can see that each of the three files are shown underneath a “Changes” drop-down. This contains the files that have undergone changes since the last commit. In our case, since we haven’t updated the save-state yet, this last commit would be the initial creation of the project folder.

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    To have version control track these individual files going forward, we can do so in two separate ways. We can add them individually by clicking the + symbol next to the individual names.

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    Staged

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    This will result in the files being moved to the “Staged” dropdown. This denotes files being tracked with the intention of being recorded as the next save-state or waypoint (ie. a commit).

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    Commit

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    To create a new commit (save-state or waypoint), once we have the files we want to track staged, we will write a commit message, and then press commit.

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    A commit message is a brief description of the changes that have occurred to the files between this commit and the previous one. Make this short description informative enough that if you need to revert back in the future, you can quickly identify the commit you need to fall back to (more about this later).

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    If this your first time using version control, you will likely encounter the following pop-up asking that you provide a user.name and user.email. This is used to designate the author of the changes.If you get this popup, go ahead and select “Open Git Log”

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    UserName and UserEmail

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    The Output tab at the bottom of the screen will open, showing the messages that led to the popup.

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    The important part to note is the commands that will be needed to provide your user name and email to the computer for authoring the commit. Typically, your email will be the same one you used for your GitHub account.

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    From the displayed message, go ahead and copy

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    “git config –global user.email”you@example.com””

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    Then click on the adjacent terminal tab. You will paste the command in, but do not hit enter just yet.

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    Windows users, please note, depending on your settings, if trying to paste from the keyboard into the terminal, you may need to press “Ctrl + Shift + V” instead of the usual “Ctrl + V”.

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    With the command now pasted (or typed), use your keyboard arrows to navigate to the email portion, and replace the generic email with your email address used for your GitHub account.

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    Make sure that the quotation marks (“) around the email address remain present, as they help the computer identify where your email address starts and ends. Once satisfied that your email address is correct, press enter.

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    Next up, repeat the process, this time copying over the command needed to set your user name to the terminal. Repeat the editing process to provide your name between the “” marks. Then press enter.

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    First Commit

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    Now that your user.name and email address have been provided, Git should be able to provide an author to the commit message. Reattempt to press commit button.

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    If this is successful, you will see your initial commit appear on the bottom half of the left primary side bar, under the Graph dropdown. Congrats! Your files are now being tracked by version control.

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    If you hover with your mouse arrow just over the commit, you can see the longer commit message and additional details appear.

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    If you click on the commit tab, a new display will open in the editor, displaying the changes that occured in that commit compared to the previous one. In this case, since we added everything since the previous commit, nothing appears on the left side, while the entire documents contents appear highlighted in green on the right.

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    Green highlighting is used to show additions, while red highlighting is used to show deletions.

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    Having completed this initial commit, for this example, let’s imitate a typical workflow and make some additional changes to the file before we make a second commit. Within text portions of the .qmd file, use of # denotes a section header in markdown, so let’s add a header for Introduction and click save.

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    Modified

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    Within the left primary sidebar, we can see that the Git tracking has updated. Examples.qmd is visible once again. However, becuase it is now a tracked file, instead of showing up with the “U/Untracked” green highlight, it now appears as a brownish-red with a “M/Modified”.

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    Let’s make an additional change to the .qmd file by adding another section (# Setup) and a code block with a commented out line (denoted by the # at the line start), before pressing Save.

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    If we were now to click on the Example.qmd file in the left primary sidebar, it will open the same kind of tracking display we saw previously. This time, we can see changes since our last commit. These appear as the green highlights along the scroll-bar, corresponding to the # Introduction and # Setup headers that we have added in since the last commit.

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    For a larger document, we can scroll down to see the various highlighted regions.

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    We could now repeat the steps showed above, staging the file, writing a commit message, and commiting again by clicking on the designated buttons.

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    An important question is how often should we commit, vs. just hit save? Well… it depends :D Let’s think about this in context of a video game. If you made commits at regular intervals throughout the day (or more frequently when doing something particularly risky), you are more likely to be close enough to a particular commit (waypoint/save-state) that you can quickly revert back to without loosing any progress. Alternatively, if your last commit was last week, you will not have any intermediate versions to fall back to.

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    Commit via Terminal

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    Having demonstrated how to commit changes to Git via the left primary side-bar, for this second commit, let’s do it the alternate way via the terminal (tab on the panel at the bottom of your screen).

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    After clicking on the terminal tab, click on blinking command line.

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    The command to stage a file is “git add”, followed by the name of the file you want to stage.

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    In this case, you would enter “git add Example.qmd” and press Enter.

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    You will see after pressing enter a new blank terminal line appear. If you glance at the left-sidebar, you can see that Example.qmd now appears under the Staged Changes dropdown.

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    Next up, let’s write the git commit via the terminal. In this case, the command would be “git commit -m” (-m denoting message). The commit text is then surrounded by “” marks.

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    For example: “git commit -m”Added section headers to my QMD file””

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    Press enter to save the commit.

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    And you should see your second commit now appear in the left primary sidebar underneath the graphs dropdown.

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    Remote Version Control

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    Copying Project Folder to GitHub

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    While having local version control in place is helpful when you need to revert back after encountering issues, where Git shines is the ability to pass your changes to your online GitHub repository.

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    Not only does this allow you to switch between computers, but should something disastrous happen to your main computer, you still have all your hard work backed up and readily assessible.

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    For this subsection, first, double check that Positron is still connected to your GitHub account by checking the user tab on the bottom-left. If not, repeat the connection setup.

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    Since our project was created using the “New Folder from Template” option, it currently only exist locally. What we want to do next is to copy it to our GitHub account, creating a new repository in the process.

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    To do this, we will first need to install the usethis R package. Within your console, you would run the following line of code:

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    install.packages("usethis")
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    Depending on what R packages you already have installed on your computer, you may get a prompt asking if you want to update/install additional dependencies. Go ahead and type the number corresponding to Update All, and press enter.

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    The package and all it’s dependencies should then install. If an error message appears, read through it, and follow provided instructions. Go to Discussions if need help.

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    Once the usethis package is installed, we need to activate it within R by calling it with the library command. This makes all the tools (ie. functions) within an R package available for use within Positron.

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    In your console, you would type:

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    library(usethis)
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    With library called, you now have access to the functions (tools) within the usethis R package. One of these is the use_github() function.

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    In Positron, if you hover over a function, it will pull up the associated help file which will provide you information about the arguments the function expects to receive, and what they do.

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    For use_github(), the main thing to remember for now is since this is a personal project being used for testing, we don’t necessarily want to share it with the entire world, so we should set the “private” argument equal to TRUE when creating a new repository.

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    Taking this information that we have now gathered, we can now within our Quarto Markdown create a code chunk, write out the line of code calling the function, and providing the Private=TRUE argument within the ().

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    Within a code chunk, adding a # in front of a line of code, will comment it out, resulting in that line of code not being run. Since we have already installed the usethis package, and we don’t want to reinstall it every single time, let’s go ahead and comment out that line. Go ahead and press Enter.

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    We will see a message pop-up in the console. In this case, we had not saved before pressing enter, so there are uncommitted changes within the folder. The pop-up is asking whether you want to save these as well before sending the Folder to GitHub.

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    In this case I will chose to ignore the uncommitted changes by entering 3 (for Definitely) in the console and hitting enter on my keyboard.

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    The usethis R package will then execute the series of git commands that are needed to set up a GitHub repository (ie. the messages being displayed in the console window), and when finished will open a pop-up asking whether you want to see your new repository in your default Web Browser. I will go ahead and select yes in this case.

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    After the browser opens, you can see that the elements I had staged and committed within Positron are now present within the GitHub repository. Since I had only staged Example.qmd, it is the only file that was backed up. We can also see the commit history online by clicking on the commit clock.

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    As we would expect, we only see our two commit messages. One important thing to note is the commit hash numbers, that denote a particular commit. If we decided to revert/fall back to a prior commit in the future, this would be the number we would need to provide to Git to return to that previous commit/save-state

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    Similarly, on GitHub, we have an option to Browse a Repository at a particular point in time. This will be quite useful later in the future when troubleshooting what major changes occurred between versions of an R package.

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    Code Chunk Arguments

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    Having successfully connected our local Project Folder to a remote GitHub repository, let’s return to Positron.

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    Before continuing, if we left the code chunk that created the GitHub repository as is, every time we ran all code chunks in the document, it would try to recreate the GitHub repository. We don’t want this to happen, as the setup was a one-time operation.

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    While we could add # in front of every line of code (or delete the code chunk entirely) it is often useful to have these set-up code chunks around to remind us what arguments we need to provide next time we need to a similar setup and are mind blanking on what to do.

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    Fortunately, Quarto allows us to set conditions on whether a chunk is run (ie. evaluated). We will discuss the conditiona arguments in more depth in the next section, but for now, we can modify the code chunk as follows.

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    On the next line after the {r}, we will add a hashtag (#), then a pipe (|), followed by a space. This is the setup for a code-chunk specific argument. We will then add “eval: FALSE”, which signals that the particular code-chunk should not be evaluated (ie, should not be run).

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    README

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    .

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    Now that we have connected our local Project Folder to GitHub, and have gotten a basic introduction to the “git add”, “git commit” arguments, let’s turn our focus to the other files currently listed as untracked by Git within our folder, the README.md and the .gitignore files.

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    When setting up our GitHub account, we encounted an example of a README.md file. This file often provides a brief description of the project, and an outline of what the other files in the folder are for. As you may have gathered, even software developers are forgetful/under-caffenaited, and having notes to catch back up to speed is important.

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    .gitignore

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    We additionally have a .gitignore file. Within a project, there are often some files that we will never want version control to track. These could be files that are too large for GitHub (ex. really large .fcs files), or files containing sensitive information (passwords, history, credentials, etc.).

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    When the names of these file (or the file type shothand) are added to the .gitignore file, they are ignored by version control, and no longer appear on the primary left side bar.

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    Let’s proceed and stage both the README.md and .gitignore file, so that changes to these files will be tracked. We can of course select both from the primary left side bar and write a short commit message.

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    Or alternatively, if we want to stage all uncommitted files present in a single step, we could in the terminal use the “git add .”

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    We can then write our git commit using “git commit -m”.

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    Both approaches work, and you may switch between them based on preferrence.

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    You will notice after having committed, that if you look at the Graph dropdown on the bottom half of the primary left side-bar that something has changed.

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    There are now separate icons denoted as main and origin/main. These correspond to the last commit present locally (main), and the last commit on remote (ie. GitHub, origin/main).

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    Local is ahead since you just made the commit with the changes inactivating the code-chunk, and you have not passed these changes up to GitHub yet.

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    Pull

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    Before sending (ie. pushing up) our updated commit to GitHub, especially if you are working on a project from multiple computers (or as part of a team) to bring in (ie. pull down) any changes that might be on GitHub that are not present locally.

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    This ensures that everything is up to date, and you don’t end up with mismatched commits that are incompatible with each other and trigger an error message.

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    To pull in changes from GitHub, at the top of the primary left side-bar, you can select the … button to open a drop-down menu of Git options. You would then select “Pull”.

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    Alternatively, you could do the same thing via the terminal by running the “git pull” command.

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    Push

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    In our case, there was no new material present on our GitHub repository that were not already present locally, so all that is returned is the “Already up to date” message.

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    We are now good to proceed to push (ie. send) the updated commit up to our GitHub repository.

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    We can do this by either pressing the Sync changes button, or via the terminal entering the “git push” command.

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    And now, if you glance down at left side-bar’s graph section, you will see that both the main and origin/main icons are now present for the most recent commit.

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    If we switch to our Web browser, we can see that this is also now the case for our GitHub repository that now also has the most recent changes.

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    Reverting to Prior Commit

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    For most daily-workflows, you will only need the git commands that we have introduced above (git add, commit, pull, push). The next two areas (reverting to a prior commit, and branches) are more specialized, and will be covered in greater depth later in the course. We are briefly covering them here. If you are at the point where your last remaining neuron has disconnected, and you feel you need to take a break from version control, feel free to skip to the next section and we will revisit these topics later in the course.

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    –

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    In most cases, if your code stops working, you can identify the issue and fix it in the existing version, never needing to resort to reverting to a previous commit (save-state). The times you would need to revert would be if you deleted important files, or the new files are hopeless mess that is not worth trying to sort through. In those cases, reverting back might be better approach.

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    To imitate a falling back scenario, lets create and additional file, stage and commit it to end up a commit ahead of where we are currently at within the Project Folder.

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    Now being one (or several) commits ahead, if we wanted to revert back, we would first need to identify the commit we want to revert back to and copy the commit hash number.

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    Then, opening the terminal, we can enter “git reset” and paste the hash afterwards. We can then press enter.

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    You will notice our additional commit has been removed, although the newer files we were working on subsequent last commit are still present.

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    If however, we had wanted to return to the exact same state as the previous commit (removing all subsequent created files), we could do so by adding in the –hard argument. Before starting, save any newer files you want to keep in a completely different folder, because they will be permanently removed.

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    Then, enter “git reset –hard thecommithashnumber” into the terminal, which would result in a “hard” return to the previous commits save-state. You may need to close and reopen Positron to see the changes reflected.

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    Branches

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    Branches are an useful Git feature that we will start using extensively later in the course. Branching allows you to create a parallel/carbon-copy of your existing repository, which you can then edit without affecting the main branch. This is particularly useful for projects that may get messy or drawn out. By isolating these edits to a parallel branch, if they don’t work, your main branch remains safe. Alternatively, if you like the changes that occurred in the branch, you can pull these changes from the branch back to main, bringing the timelines back together.

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    Within the terminal, entering “git branch” will show the existing branches. In this case, only main is present since we haven’t yet created a new branch.

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    We can create a new branch in the terminal by entering “git branch” followed by the name of our desired branch. In this case, we are creating a branch called Week1

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    Now, when we check “git branch” again in the terminal, which returns the two branches, Week1 and main. The * is located next to main, indicating that we are currently within the main branch.

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    Besides the terminal, we can also create a new branch via Positron. To do so, we first click on the Git tab in the Actions Bar.

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    Once the left-side bar displays the version control display, we can click on the … button (to the right of changes)to gain access to the Git options drop-down.

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    From here, we click on Branch, and then select Create Branch.

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    Using Git branch, we saw that we were still within the main branch. In the terminal, we can switch over to the Week1 branch by using the “git checkout” command, followed by the branch we wish to switch to.

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    This results in us switching over to the Week1 branch.

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    Having switched (ie. checkout) to the Week 1 branch, let’s create the file BranchTest.qmd, which will exist within this branch, but not yet in the main branch.

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    Having created the file, let’s stage and then commit it. This will put the Week1 branch ahead of the main branch by a single commit.

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    With our changes staged and committed, if we look at the left side-bar’s graph section, our Week1 branch is now ahead of the origin/main branch by one commit.

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    If we were to check on GitHub, we can see that no new files are present on the main branch, but can see the notification listing recent changes to Week1 branch.

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    Using the drop-down, we can switch from displaying the main branch to the Week1 branch, where we can see the new file.

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    If we click the green compare and pull request button, we end up on this screen. This compares how the two branches are different from each other.

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    We will delve into branches again at a later point. For now, remember that by creating and prunning parallel branches, you can develop knowing that even if something goes wrong, your main branch remains safe.

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    Wrap-Up

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    In this section, we saw how to create a New Project Folder, create files and back up the project folder to GitHub. We also started learning about git, covering the basic commands (git add, commit, pull, push). If you feel a bit overwhelmed, please know, that is normal. Understanding how to leverage git takes time and practice, but is an incredibly valuable skillset to have in the long run.

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    In the next section, we will look at how by changing various elements within our .qmd file produce a variety of files, and how to leverage code-chunk arguments to fine-tune whether a code-chunk is utilized.

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    Additional Resources

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    Git & GitHub Tutorial for Scientist: It’s Not Only for Programmers

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    Ten Simple Rules for Taking Advantage of Git and GitHub

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    A brief introduction to Git for beginers

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    AGPL-3.0 CC BY-SA 4.0

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    AGPL-3.0 CC BY-SA 4.0

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    Background

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    When working with code, it is very important to stay organized. You ultimately want to avoid being in a scenario where you need some code you wrote the previous month, and then having to search through multiple .R files, scattered across multiple folders, external hard-drives, and computers to find it. Likewise, you want to avoid ending up having identified multiple similarly-named copies of your original file that have all since diverged slightly from each other in some way that you have long since forgotten.

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    Ideally, everything needed for your coding script to successfully run should be kept within a project-specific folder. This ensures, that should you transfer it to another computer (whether your own or a colleagues) that you would still be able to recreate the scripts output.

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    Likewise, if you make changes to your script, and your code stops working (no longer returns the expected output, ie. breaks), having a record of what changes were made since the last working version would be very helpful in pinpointing what went wrong. For beginners, this often ends up being a typo in a function name, or an accidentally misplaced comma somewhere in your document.

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    For these reasons, in this course, we will be extensively using the version control software Git from the very beginning. We will also have you create a GitHub account, which will allow you to back-up your coding projects online as private repositories. Not only is this useful in case something happens to your computer, but it allows you to switch between separate computers while still having ready access to all your code, avoiding ending up with divergent copies on each computer.

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    Additionally, since all the material for this course is being hosted on a public GitHub repository, once you have set up your GitHub account you will be able to retrieve all the new materials and changes by simply refreshing (ie. syncing) your version of the course folder (ie. fork) once a week. Your GitHub account will also be needed when posting or asking questions on the Discussion Forum.

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    In this walk-through, we will go through setting up a GitHub account, and make sure you are familiar with some of the elements and locations that we will be circling back to throughout the course.

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    Getting Started

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    Creating an Account

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    We will first navigate to the GitHub homepage. If you haven’t previously created an account, click on the button to sign up for an account.

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    On the sign-up page, you will fill in various details needed to create an account. Please remember that GitHub usernames are visible to others. Additionally, if you end up sharing code with others as part of a manuscript, or use GitHub to create a personal portfolio website in the future, your username will appear as part of the URL.

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    For example, in my case, my user name is DavidRach, so my GitHub profile ends up as: https://github.com/DavidRach. For our course, the core’s GitHub user name is UMGCCCFCSR, so the github profile ends up as https://github.com/UMGCCCFCSR, while the course website ends up as https://umgcccfcsr.github.io/CytometryInR/

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    Once you have entered your new account information, you will need your account creation by entering the code sent to the email address that you provided.

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    Once account creation has been confirmed, please proceed to login to GitHub for the first time.

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    GitHub Profile

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    Upon creating a brand new account, your GitHub homepage will initially look rather empty, and can be intimidating to navigate for the first time.

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    For now, on the upper right, go ahead and click on the default profile picture icon…

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    And then select Profile…

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    You are now on your public GitHub profile page. For a newly created account, it will look something like this:

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    For a more established account, this page will look a little different, and can be customized to highlight various projects that you are working on.

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    For this course, we will have you set up a basic GitHub profile page for now, although you are free to customize and personalize it as much as you may want to in the future!

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    To start, first select the edit profile button on the left below the default profile icon.

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    You can then proceed to fill in any details that you feel are relevant and are comfortable sharing.

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    With the quick access details filled in, it is now time to navigate to the Settings tab. You will return to the previous menu dropdown on the upper right, and instead of selecting Profile, click on the Settings option.

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    You should now end up within your Public Profile Settings page.

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    Feel free to edit the default profile picture, and any other fields that you feel are relevant. Once done, continue to scroll down the page past ORCID ID.

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    When you reach Contributions and Activity, go ahead and select the option to include private repositories in the activity summary graphic. Then scroll down and click save. You will now be returned to your GitHub profile page.

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    At the top of the profile, you will see a “Your contributions” calendar graph. For a new account, it will look like this:

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    If you are just starting out, this chart will be mostly empty, but will fill in as you work on projects, see here as an example.

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    Every time you save your code (ie. make a commit), the activity will be reflected in this chart. By clicking the option in settings, code made within a private repository will remain private, but will count toward your contribution chart. As you progress through the course, this will provide a nice visual reminder of the progress you have made, and the obstacles that you have overcome.

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    GitHub ReadMe

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    With this done, we modify your GitHub profile by adding one customized element, a ReadMe page. This will be used for a couple projects during the course, and can be personalized further in the future.

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    To create a ReadMe page for your profile, we will navigate to the upper right of the screen and click on the + sign.

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    We will then select the Create New Repository option.

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    You will next create a repository (folder), naming it exactly the same as your username. This will be recognized by GitHub as being a special type of repository corresponding to the ReadMe section of your profile.

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    For options, leave the visibility as Public, and Add README set to On. And proceed to Create Repository.

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    Having created the repository (folder), you will see it has been populated by a few default files. For now, you will be editing the README.md file. On a new repository, the easiest way to access it is by clicking the green option on the right side of your screen.

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    With the README.md file now opened, you will be able to see generic filler text that is suggested by GitHub.

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    For this course, I will ask you to add a couple elements for now. You are free to return and further personalize it later if you wish to do so.

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    The type of file that we are working with is a Markdown file, which can allow for a bunch of customizations which we will cover throughout the course.

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    For now, please add and customize the following questions:

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    Cytometry In R

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    Location: Baltimore, Maryland, USA

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    My Favorite Fluorophore/Metal-Isotope: Spark Blue 550

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    Previous Coding Experience: Repeatedly Calling IT

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    What I Hope to Get From This Course: A faster way to match FlowSOM clusters to their likely cell type.

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    Next, to save you will select the green “Commit changes” button. We will cover the meaning of “Commit” more in-depth during the Git section.

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    For now, write a short summary of the change you made to the file in the “Commit message”, and any additional details within the “Extended description” field. When ready, click the green “Commit changes” button.

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    You will now be able to see the updated README.md file, as you can see in our example below. To make additional edits, you would select the pencil icon on the right-center side of the screen.

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    Next, navigate back to your profile page (by clicking on either your username or the Overview option on the tabs).

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    You will see that the README file contents are now displayed on the upper portion of your GitHub profile. Feel free to circle back and customize this further to your liking.

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    In this last example, we created your first repository (folder). Since this is public, it is now shown below the README section of the profile under your repositories. You can also see that your commits made in the process of making the changes are now shown both in the Contributions graph, and under the Contributor Activity summary at the bottom of the page.

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    GitHub Repository

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    Having set up your GitHub profile, it now is time to make sure you have access to our course materials. We will have you navigate to our course’s GitHub profile

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    On the profile page, you will be able to see our version of the README, our repositories, and the Contributions graph and Contribution activity sections.

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    Please click on the CytometryInR to navigate to its repository (folder)

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    On this page, you will see several elements that you will be circling back to throughout the course.

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    For our course, we will be extentsively ussing the Discussions page as a community forum. If you have any questions, are looking for feedback, or want to show off something that you worked on, this is the place for it. This will also help make sure

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    The Issues tab is where you will need to go to open an Issue if you encounter a bug (or major documentation typo), so that I can cicle back and correct them when I have the chance.

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    To submit the optional take-home problems, you would turn in these problems by going to the Pull Request tab, and initiating a pull request between your forked version of the project and our “homework” branch (more details on this later).

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    Optionally, you can “Star” a repository. This is basically the GitHub equivalent of liking a project. In our case, we will often star a repository since it will be saved under the Stars tab of our profile, which makes finding it again significantly easier a few weeks later after forgetting the repository name.

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    To see projects that you have starred, you can select the Stars option from the same dropdown you used to get to Settings.

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    Or from your GitHub profile, you can see these under Stars tab.

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    Forking CytometryInR

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    Before we go further, we will need you to make your own copy of the course repository (ie. fork it). This will allow you to quickly retrieve all the new materials and code corrections by simply rereshing (ie. syncing) your forked version with our upstream parent branch once a week.

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    To fork the course repository, you will select the “Fork repository” option on the upper-center portion of your screen.

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    By “Fork-ing” a repository, you are basically copying the contents from that repository to a newly created repository on your own GitHub. Forked projects are still linked to the original (parent) fork, and can retrieve any updates via syncing, as well as return changes via a pull request.

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    For this course, when you create the fork, keep the existing repository name (“CytometryInR”). Importantly, select the copy main branch option. This will ensure you only get the code and data needed for the course copied over, and don’t end up with your entire hard-drive filled will website elements, or other people’s solutions to the take-home problems.

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    Once you have created the fork, you will see your copy of the forked repository under your own username. Seeing as you have just now forked the project, you will see the notification that you are up to date with the existing version of the CytometryInR course repository.

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    As we go through the course, and new material is released each week on Sunday at 2200 EST (Monday 0300 GMT+0), you will see this changed to behind the main branch by a number of commits, and have the option to sync in the changes to your fork to gain access to that week’s material.

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    If you remember, previously under your GitHub profile, the Repositories tab only contained the repository corresponding to your ReadMe section.

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    You should however now be able to see your fork of the CytometryInR repository. As you add project specific repositories throughout the course, they will also appear here.

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    Wrap-Up

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    We have now completed our walk-through of setting up a GitHub account. At this point, you should have modified your GitHub profile, added a README section, and most importantly, forked the CytometryInR repository so that you can easily retrieve the new course materials each week.

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    Next up, we will have you proceed to installing the required software to your computer that will be needed throughout the course. Installation instructions will vary depending on your computer’s operating system, so please follow the appropiate walkthrough.

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    Additional Resources

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    Git & GitHub Tutorial for Scientist: It’s Not Only for Programmers

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    Ten Simple Rules for Taking Advantage of Git and GitHub

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    A brief introduction to Git for beginers

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    How to Use GitHub for Beginners

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    AGPL-3.0 CC BY-SA 4.0

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    Using GitHub

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    +David Rach +
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    2026-02-01

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    AGPL-3.0 CC BY-SA 4.0

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    Background

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    When working with code, it is very important to stay organized. You ultimately want to avoid being in a scenario where you need some code you wrote the previous month, and then having to search through multiple .R files, scattered across multiple folders, external hard-drives, and computers to find it. Likewise, you want to avoid ending up having identified multiple similarly-named copies of your original file that have all since diverged slightly from each other in some way that you have long since forgotten.

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    Ideally, everything needed for your coding script to successfully run should be kept within a project-specific folder. This ensures, that should you transfer it to another computer (whether your own or a colleagues) that you would still be able to recreate the scripts output.

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    Likewise, if you make changes to your script, and your code stops working (no longer returns the expected output, ie. breaks), having a record of what changes were made since the last working version would be very helpful in pinpointing what went wrong. For beginners, this often ends up being a typo in a function name, or an accidentally misplaced comma somewhere in your document.

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    For these reasons, in this course, we will be extensively using the version control software Git from the very beginning. We will also have you create a GitHub account, which will allow you to back-up your coding projects online as private repositories. Not only is this useful in case something happens to your computer, but it allows you to switch between separate computers while still having ready access to all your code, avoiding ending up with divergent copies on each computer.

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    Additionally, since all the material for this course is being hosted on a public GitHub repository, once you have set up your GitHub account you will be able to retrieve all the new materials and changes by simply refreshing (ie. syncing) your version of the course folder (ie. fork) once a week. Your GitHub account will also be needed when posting or asking questions on the Discussion Forum.

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    In this walk-through, we will go through setting up a GitHub account, and make sure you are familiar with some of the elements and locations that we will be circling back to throughout the course.

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    Getting Started

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    Creating an Account

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    We will first navigate to the GitHub homepage. If you haven’t previously created an account, click on the button to sign up for an account.

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    On the sign-up page, you will fill in various details needed to create an account. Please remember that GitHub usernames are visible to others. Additionally, if you end up sharing code with others as part of a manuscript, or use GitHub to create a personal portfolio website in the future, your username will appear as part of the URL.

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    For example, in my case, my user name is DavidRach, so my GitHub profile ends up as: https://github.com/DavidRach. For our course, the core’s GitHub user name is UMGCCCFCSR, so the github profile ends up as https://github.com/UMGCCCFCSR, while the course website ends up as https://umgcccfcsr.github.io/CytometryInR/

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    Once you have entered your new account information, you will need your account creation by entering the code sent to the email address that you provided.

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    Once account creation has been confirmed, please proceed to login to GitHub for the first time.

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    GitHub Profile

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    Upon creating a brand new account, your GitHub homepage will initially look rather empty, and can be intimidating to navigate for the first time.

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    For now, on the upper right, go ahead and click on the default profile picture icon…

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    And then select Profile…

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    You are now on your public GitHub profile page. For a newly created account, it will look something like this:

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    For a more established account, this page will look a little different, and can be customized to highlight various projects that you are working on.

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    For this course, we will have you set up a basic GitHub profile page for now, although you are free to customize and personalize it as much as you may want to in the future!

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    To start, first select the edit profile button on the left below the default profile icon.

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    You can then proceed to fill in any details that you feel are relevant and are comfortable sharing.

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    With the quick access details filled in, it is now time to navigate to the Settings tab. You will return to the previous menu dropdown on the upper right, and instead of selecting Profile, click on the Settings option.

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    You should now end up within your Public Profile Settings page.

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    Feel free to edit the default profile picture, and any other fields that you feel are relevant. Once done, continue to scroll down the page past ORCID ID.

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    When you reach Contributions and Activity, go ahead and select the option to include private repositories in the activity summary graphic. Then scroll down and click save. You will now be returned to your GitHub profile page.

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    At the top of the profile, you will see a “Your contributions” calendar graph. For a new account, it will look like this:

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    If you are just starting out, this chart will be mostly empty, but will fill in as you work on projects, see here as an example.

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    Every time you save your code (ie. make a commit), the activity will be reflected in this chart. By clicking the option in settings, code made within a private repository will remain private, but will count toward your contribution chart. As you progress through the course, this will provide a nice visual reminder of the progress you have made, and the obstacles that you have overcome.

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    GitHub ReadMe

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    With this done, we modify your GitHub profile by adding one customized element, a ReadMe page. This will be used for a couple projects during the course, and can be personalized further in the future.

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    To create a ReadMe page for your profile, we will navigate to the upper right of the screen and click on the + sign.

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    We will then select the Create New Repository option.

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    You will next create a repository (folder), naming it exactly the same as your username. This will be recognized by GitHub as being a special type of repository corresponding to the ReadMe section of your profile.

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    For options, leave the visibility as Public, and Add README set to On. And proceed to Create Repository.

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    Having created the repository (folder), you will see it has been populated by a few default files. For now, you will be editing the README.md file. On a new repository, the easiest way to access it is by clicking the green option on the right side of your screen.

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    With the README.md file now opened, you will be able to see generic filler text that is suggested by GitHub.

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    For this course, I will ask you to add a couple elements for now. You are free to return and further personalize it later if you wish to do so.

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    The type of file that we are working with is a Markdown file, which can allow for a bunch of customizations which we will cover throughout the course.

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    For now, please add and customize the following questions:

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    Cytometry In R

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    Location: Baltimore, Maryland, USA

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    My Favorite Fluorophore/Metal-Isotope: Spark Blue 550

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    Previous Coding Experience: Repeatedly Calling IT

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    What I Hope to Get From This Course: A faster way to match FlowSOM clusters to their likely cell type.

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    Next, to save you will select the green “Commit changes” button. We will cover the meaning of “Commit” more in-depth during the Git section.

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    For now, write a short summary of the change you made to the file in the “Commit message”, and any additional details within the “Extended description” field. When ready, click the green “Commit changes” button.

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    You will now be able to see the updated README.md file, as you can see in our example below. To make additional edits, you would select the pencil icon on the right-center side of the screen.

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    Next, navigate back to your profile page (by clicking on either your username or the Overview option on the tabs).

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    You will see that the README file contents are now displayed on the upper portion of your GitHub profile. Feel free to circle back and customize this further to your liking.

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    In this last example, we created your first repository (folder). Since this is public, it is now shown below the README section of the profile under your repositories. You can also see that your commits made in the process of making the changes are now shown both in the Contributions graph, and under the Contributor Activity summary at the bottom of the page.

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    GitHub Repository

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    Having set up your GitHub profile, it now is time to make sure you have access to our course materials. We will have you navigate to our course’s GitHub profile

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    On the profile page, you will be able to see our version of the README, our repositories, and the Contributions graph and Contribution activity sections.

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    Please click on the CytometryInR to navigate to its repository (folder)

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    On this page, you will see several elements that you will be circling back to throughout the course.

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    For our course, we will be extentsively ussing the Discussions page as a community forum. If you have any questions, are looking for feedback, or want to show off something that you worked on, this is the place for it. This will also help make sure

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    The Issues tab is where you will need to go to open an Issue if you encounter a bug (or major documentation typo), so that I can cicle back and correct them when I have the chance.

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    To submit the optional take-home problems, you would turn in these problems by going to the Pull Request tab, and initiating a pull request between your forked version of the project and our “homework” branch (more details on this later).

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    Optionally, you can “Star” a repository. This is basically the GitHub equivalent of liking a project. In our case, we will often star a repository since it will be saved under the Stars tab of our profile, which makes finding it again significantly easier a few weeks later after forgetting the repository name.

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    To see projects that you have starred, you can select the Stars option from the same dropdown you used to get to Settings.

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    Or from your GitHub profile, you can see these under Stars tab.

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    Forking CytometryInR

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    Before we go further, we will need you to make your own copy of the course repository (ie. fork it). This will allow you to quickly retrieve all the new materials and code corrections by simply rereshing (ie. syncing) your forked version with our upstream parent branch once a week.

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    To fork the course repository, you will select the “Fork repository” option on the upper-center portion of your screen.

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    By “Fork-ing” a repository, you are basically copying the contents from that repository to a newly created repository on your own GitHub. Forked projects are still linked to the original (parent) fork, and can retrieve any updates via syncing, as well as return changes via a pull request.

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    For this course, when you create the fork, keep the existing repository name (“CytometryInR”). Importantly, select the copy main branch option. This will ensure you only get the code and data needed for the course copied over, and don’t end up with your entire hard-drive filled will website elements, or other people’s solutions to the take-home problems.

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    Once you have created the fork, you will see your copy of the forked repository under your own username. Seeing as you have just now forked the project, you will see the notification that you are up to date with the existing version of the CytometryInR course repository.

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    As we go through the course, and new material is released each week on Sunday at 2200 EST (Monday 0300 GMT+0), you will see this changed to behind the main branch by a number of commits, and have the option to sync in the changes to your fork to gain access to that week’s material.

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    If you remember, previously under your GitHub profile, the Repositories tab only contained the repository corresponding to your ReadMe section.

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    You should however now be able to see your fork of the CytometryInR repository. As you add project specific repositories throughout the course, they will also appear here.

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    Wrap-Up

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    We have now completed our walk-through of setting up a GitHub account. At this point, you should have modified your GitHub profile, added a README section, and most importantly, forked the CytometryInR repository so that you can easily retrieve the new course materials each week.

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    Next up, we will have you proceed to installing the required software to your computer that will be needed throughout the course. Installation instructions will vary depending on your computer’s operating system, so please follow the appropiate walkthrough.

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    Additional Resources

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    Git & GitHub Tutorial for Scientist: It’s Not Only for Programmers

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    Ten Simple Rules for Taking Advantage of Git and GitHub

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    A brief introduction to Git for beginers

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    How to Use GitHub for Beginners

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    AGPL-3.0 CC BY-SA 4.0

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    AGPL-3.0 CC BY-SA 4.0

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    Background

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    In the previous sections, we set up our GitHub account, installed the required software, and further explored various elements of Positron, Git and Quarto that we will be using throughout the course.

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    This is our first year offering the course. Although we can and will answer questions during the livestreams, given the number of people signed up that might have a question, we want to make sure to provide multiple avenues by which you can get help and feedback throughout. These include the Discussions Forum, where you can ask questions, discuss topics, get feedback and celebrate wins; and 2) turning in optional take-home problems via a pull request, in which the course instructors will take a look and provide additional feedback.

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    In this walk-through, we go over how to use these resources.

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    Getting Started

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    Discussions Forum

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    On the course’s GitHub repository, we have opened up a Discussions page that we plan to use as a community forum. We hope that it will serve multiple functions, from providing a better sense of community for the online participants, to facilitating asking and receiving help on something that is not clear, provide feedback about something that it not working out, as well as a place to celebrate and show off your coding wins.

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    To keep the Discussions forum semi-organized, we have set up several categories, please select the appropiate category when opening a new discussion!

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    Code of Conduct

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    We ask that all course participants read and adhere to the spirit of our Code of Conduct. We are all human, at different points in our learning journeys, so what may be obvious to you at your point of your learning journey may have necessarily be obvious to someone just getting started. This course is our giving back to those in the community, but is on a voluntary basis in addition to our regular workload. While we try to reply quickly, sometimes our cell sorters fully melt down sending everything into chaos. We will reply when we can.

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    Announcements

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    When we send out an email to all participants, we will also repost it as an announcement. This ensures that even if you are not on our mailing list, you will still be able to have access to important information and course updates.

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    General

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    This section category can be used for any discussions that you think are worth having, that don’t fall under any of the other category. Good examples are continuing a discussion that was held during one of the livestreams; wanting to discuss and dive further into a given week’s topic; or bringing in additional resources that you found useful to understandingn something that didn’t click initially. This space is for the community to shape as they see best.

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    Ideas

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    Have an idea for a new topic or a way to improve the course? We would love to hear them. Provide as many details, and ideally, an example, and if it is doable, we will try to implement them.

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    Introductions

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    Online courses can be odd in terms of replicating in-person dynamics. Fortunately, we have gathered the largest cohort of “cytometrist with no-to-little flow experience trying to learn R at the same time” that the world has ever seen, so best to take advantage of this while we can. Treat this section as if we had just met at a conference, tell us about yourself, what brings you here, and what you want to hopefully be able to do after the course ends.

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    Polls

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    Occasionally, we will need to gather community feedback on what is working and what is not working. We will sporadically post Polls for this purpose.

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    Q&A

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    The Questions and Answers (Q&A) section is where you go if something is not clear, not working, and you are trying to troubleshoot your way through it. First thing before posting, search! to see if someone has already asked the question. If you don’t find anything, go ahead and open a new discussion.

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    Since we are not at your computer, and don’t have your dataset, when troubleshooting it is best to include a minimal reproducible example of the issuen you are encountering, slimming down the number of files needed to be transferred, and generalizing down the code so that other course participants and instructors can follow along. If this is not doable, or if the problem requires added context (and larger files), create a new repository on your GitHub, make it public, and share the links to it in your post. The goal would be to download the folder and be able to replicate the issue that you are encountering.

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    Show and Tell

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    Where Q&A section is for getting help on code that is frustratingly not working, Show and Tell is where to go and celebrate when you finally get things to work. Share your wins, show us the extra pretty graphs, bizarre autofluorescence signatures, or odd outputs that just make you laugh.

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    Issues

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    Most of the time, if you are having trouble getting you code to run, you should first stop after some initial troubleshooting should be to open a new Discussion under the Q&A category. Here you will be able to get both community and instructor help and suggestions to hopefully resolve whatever is going on.

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    The Issues page is primarily meant for course-specific problems that require the course instructor intervention to fix. For example, we release a new week of material, and while it runs fine for both Windows and Linux, the code fails to run for all MacOS users. While you may be able to find workarounds on your own, it’s ultimately our responsibility to help provide a solution so that everyone can move forward. This is the situation where opening an Issue is appropiate.

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    Similarly, if our code contains a wrong argument, is returning a deprecation warning, etc. open an issue to let us know. While we may not be able to fix something that is not directly related to our code, we can redirect it to the package maintainers so that they can fix the issue.

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    And likewise, if you find multiple typos in the documentation, you can open an issue and propose carrying out a pull-request to fix them.

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    Submitting Take-Home Problems

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    Each week, during the course, we introduce and cover the main concepts for the particular concept. Our goal is to provide you with the necessary code and enough code to be able to get the jist. However, to become comfortable and be able to apply what you have learned, you will need to explore beyond our examples, try it with your own datasets, encounter things that don’t work, and troubleshoot your way through them. It’s this cycle of venturing into the unknown that develops strong coding skills that are needed to overcome any barrier you encounter. The goal of the take-home questions is to provide some less curated problems that will take a little longer to answer to help get you started on your own exploration of the topic.

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    As previously mentioned, these take-home problems are completely optional. If you are in the middle of solving them and want to seek feedback from then community and course instructors, open a Discussion under the general category is the way to go.

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    However, if you have completed them, and want course instructor feedback, you can submit them to us in the form of a pull-request to the CytometryInR repo’s homework branch. We will take a look, offer constructive suggestions, and when ready merge the solution. This will also result in GitHub listing you as a contributor to the course.

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    We will outline the basic steps of how to set up and open a pull-request, to help simplify the process.

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    Sync your Fork

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    First off, make sure to Sync your fork of the Cytometry in R project. That makes sure that all the commits present are up-to-date and simplifies the process of having the pull-request being merged.

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    Pull to Local

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    Having Synced your branch on GitHub, return to your computer, open the CytometryInR repository and pull in the changes locally.

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    Create own Folder under Homeworks

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    Under the course folder, you will find folders for each week. Within these folders find the homework folder. This will appear empty except for a README file with ionstructions. It is within this folder you will need to create your own folder.

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    To ensure there are no conflicts on the pull-request merge, please use your GitHub username as the folder name.

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    Once you have your folder inside homework, go ahead and copy anything you are turning in from their respective working project folders. Remember, the goal is minimal reproducible example is the goal. Rendered Quarto Documents are preferred, but we will also accept scripts and small data files and images. a README.MD file with anything you want me to know,

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    Sign off Commit

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    Now that everything is present, Sign Off and Commit the change.

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    Push Branch to GitHub.

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    Proceed to push the branch to GitHub.

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    Re-sync if necessary

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    If additional changes have occured to the parent CytometryInR repository, go ahead and update your branch. As long as your edits occurred within your folder inside homework folders, they should still be able to merge.

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    Open a pull-request

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    To start a pull request, click to see how your commit is ahead by

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    Next, switch from the parent CytometryInR main branch (used for the website and course) to the homework branch for that respective week (used for the take-home problems).

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    Once this is done, select Pull request

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    Make sure to triple check it’s bound for the homeworks branch. If you see that it is not capable of merging, verify that your commit only contains files within your respective homework username folder. Fill in the required fields of the pull request.

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    And when ready, create the pull request.

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    Wait for Feedback

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    On our end, once you have created a pull request, we will review your work, offer constructive suggestions, etc. If I ask for revisions, all you would need to do is update your files, commit again on your side of the local forked repository.

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    If all is good, we will merge the pull request and your solution to the take-home problems will now be available on the homework branch.

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    After course

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    After the course completes, we will merge homework branch with the main branch, making the community solutions to the take-home problems additional coding examples that can be used by others following along after the course concludes.

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    Wrap-up

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    In this walk-through, we covered the Discussions Forum, mentioned appropiate use cases for the Issues page and provided the logistics of how to submit take-home problems as a pull request to the homework branch. We have now covered all the major elements that you will be using throughout the course.

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    The next couple sections cover our thoughts on AI use in a course for coding beginners, and an optional walkthrough of how to use Floreada in preparation for some topics starting around Week 5.

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    Additional Resources

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    Five tips for Reviewing a GitHub pull request

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    Getting Help

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    Background

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    In the previous sections, we set up our GitHub account, installed the required software, and further explored various elements of Positron, Git and Quarto that we will be using throughout the course.

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    This is our first year offering the course. Although we can and will answer questions during the livestreams, given the number of people signed up that might have a question, we want to make sure to provide multiple avenues by which you can get help and feedback throughout. These include the Discussions Forum, where you can ask questions, discuss topics, get feedback and celebrate wins; and 2) turning in optional take-home problems via a pull request, in which the course instructors will take a look and provide additional feedback.

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    In this walk-through, we go over how to use these resources.

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    Getting Started

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    Discussions Forum

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    On the course’s GitHub repository, we have opened up a Discussions page that we plan to use as a community forum. We hope that it will serve multiple functions, from providing a better sense of community for the online participants, to facilitating asking and receiving help on something that is not clear, provide feedback about something that it not working out, as well as a place to celebrate and show off your coding wins.

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    To keep the Discussions forum semi-organized, we have set up several categories, please select the appropiate category when opening a new discussion!

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    We ask that all course participants read and adhere to the spirit of our Code of Conduct. We are all human, at different points in our learning journeys, so what may be obvious to you at your point of your learning journey may have necessarily be obvious to someone just getting started. This course is our giving back to those in the community, but is on a voluntary basis in addition to our regular workload. While we try to reply quickly, sometimes our cell sorters fully melt down sending everything into chaos. We will reply when we can.

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    When we send out an email to all participants, we will also repost it as an announcement. This ensures that even if you are not on our mailing list, you will still be able to have access to important information and course updates.

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    General

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    This section category can be used for any discussions that you think are worth having, that don’t fall under any of the other category. Good examples are continuing a discussion that was held during one of the livestreams; wanting to discuss and dive further into a given week’s topic; or bringing in additional resources that you found useful to understandingn something that didn’t click initially. This space is for the community to shape as they see best.

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    Have an idea for a new topic or a way to improve the course? We would love to hear them. Provide as many details, and ideally, an example, and if it is doable, we will try to implement them.

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    Online courses can be odd in terms of replicating in-person dynamics. Fortunately, we have gathered the largest cohort of “cytometrist with no-to-little flow experience trying to learn R at the same time” that the world has ever seen, so best to take advantage of this while we can. Treat this section as if we had just met at a conference, tell us about yourself, what brings you here, and what you want to hopefully be able to do after the course ends.

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    Occasionally, we will need to gather community feedback on what is working and what is not working. We will sporadically post Polls for this purpose.

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    The Questions and Answers (Q&A) section is where you go if something is not clear, not working, and you are trying to troubleshoot your way through it. First thing before posting, search! to see if someone has already asked the question. If you don’t find anything, go ahead and open a new discussion.

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    Since we are not at your computer, and don’t have your dataset, when troubleshooting it is best to include a minimal reproducible example of the issuen you are encountering, slimming down the number of files needed to be transferred, and generalizing down the code so that other course participants and instructors can follow along. If this is not doable, or if the problem requires added context (and larger files), create a new repository on your GitHub, make it public, and share the links to it in your post. The goal would be to download the folder and be able to replicate the issue that you are encountering.

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    Where Q&A section is for getting help on code that is frustratingly not working, Show and Tell is where to go and celebrate when you finally get things to work. Share your wins, show us the extra pretty graphs, bizarre autofluorescence signatures, or odd outputs that just make you laugh.

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    Most of the time, if you are having trouble getting you code to run, you should first stop after some initial troubleshooting should be to open a new Discussion under the Q&A category. Here you will be able to get both community and instructor help and suggestions to hopefully resolve whatever is going on.

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    The Issues page is primarily meant for course-specific problems that require the course instructor intervention to fix. For example, we release a new week of material, and while it runs fine for both Windows and Linux, the code fails to run for all MacOS users. While you may be able to find workarounds on your own, it’s ultimately our responsibility to help provide a solution so that everyone can move forward. This is the situation where opening an Issue is appropiate.

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    Similarly, if our code contains a wrong argument, is returning a deprecation warning, etc. open an issue to let us know. While we may not be able to fix something that is not directly related to our code, we can redirect it to the package maintainers so that they can fix the issue.

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    And likewise, if you find multiple typos in the documentation, you can open an issue and propose carrying out a pull-request to fix them.

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    Each week, during the course, we introduce and cover the main concepts for the particular concept. Our goal is to provide you with the necessary code and enough code to be able to get the jist. However, to become comfortable and be able to apply what you have learned, you will need to explore beyond our examples, try it with your own datasets, encounter things that don’t work, and troubleshoot your way through them. It’s this cycle of venturing into the unknown that develops strong coding skills that are needed to overcome any barrier you encounter. The goal of the take-home questions is to provide some less curated problems that will take a little longer to answer to help get you started on your own exploration of the topic.

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    As previously mentioned, these take-home problems are completely optional. If you are in the middle of solving them and want to seek feedback from then community and course instructors, open a Discussion under the general category is the way to go.

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    However, if you have completed them, and want course instructor feedback, you can submit them to us in the form of a pull-request to the CytometryInR repo’s homework branch. We will take a look, offer constructive suggestions, and when ready merge the solution. This will also result in GitHub listing you as a contributor to the course.

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    We will outline the basic steps of how to set up and open a pull-request, to help simplify the process.

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    First off, make sure to Sync your fork of the Cytometry in R project. That makes sure that all the commits present are up-to-date and simplifies the process of having the pull-request being merged.

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    Having Synced your branch on GitHub, return to your computer, open the CytometryInR repository and pull in the changes locally.

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    Under the course folder, you will find folders for each week. Within these folders find the homework folder. This will appear empty except for a README file with ionstructions. It is within this folder you will need to create your own folder.

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    To ensure there are no conflicts on the pull-request merge, please use your GitHub username as the folder name.

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    Once you have your folder inside homework, go ahead and copy anything you are turning in from their respective working project folders. Remember, the goal is minimal reproducible example is the goal. Rendered Quarto Documents are preferred, but we will also accept scripts and small data files and images. a README.MD file with anything you want me to know,

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    Now that everything is present, Sign Off and Commit the change.

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    Push Branch to GitHub.

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    Proceed to push the branch to GitHub.

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    If additional changes have occured to the parent CytometryInR repository, go ahead and update your branch. As long as your edits occurred within your folder inside homework folders, they should still be able to merge.

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    To start a pull request, click to see how your commit is ahead by

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    Next, switch from the parent CytometryInR main branch (used for the website and course) to the homework branch for that respective week (used for the take-home problems).

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    Once this is done, select Pull request

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    Make sure to triple check it’s bound for the homeworks branch. If you see that it is not capable of merging, verify that your commit only contains files within your respective homework username folder. Fill in the required fields of the pull request.

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    And when ready, create the pull request.

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    On our end, once you have created a pull request, we will review your work, offer constructive suggestions, etc. If I ask for revisions, all you would need to do is update your files, commit again on your side of the local forked repository.

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    Final Review and Merge

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    If all is good, we will merge the pull request and your solution to the take-home problems will now be available on the homework branch.

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    After course

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    After the course completes, we will merge homework branch with the main branch, making the community solutions to the take-home problems additional coding examples that can be used by others following along after the course concludes.

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    Wrap-up

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    In this walk-through, we covered the Discussions Forum, mentioned appropiate use cases for the Issues page and provided the logistics of how to submit take-home problems as a pull request to the homework branch. We have now covered all the major elements that you will be using throughout the course.

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    The next couple sections cover our thoughts on AI use in a course for coding beginners, and an optional walkthrough of how to use Floreada in preparation for some topics starting around Week 5.

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    Additional Resources

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    Create a Home for Your Community With GitHub Discussions

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    GitHub for Beginners: How to create a pull request in 4 minutes

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    Five tips for Reviewing a GitHub pull request

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    Background

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    In this course, we are creating and working with code from the programming language R. However, in practice, we are not running the code directly using just the base R software. Typically, we are running an integrated development environment (IDE), which is an additional software running on top of base R.

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    An IDE has the responsibility to help organize and manage the projects folders, pass along lines of code being executed (run) to the underlying R software, and then return and visualize the outputs in a manner that leads to increased producitivity. Examples of IDEs include Positron, Visual Studio Code and Rstudio.

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    For this course, we will be using Positron as our primary IDE. For those of you who have previous R experience, you are likely more familiar with Rstudio which is also made by Posit, and is the older of the two IDEs. Why use Positron for this course then?

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    There are several reasons. First, Positron combines the best elements of both Rstudio (which preceeded it) and VS code (from which it’s base infrastructure was forked). In a course aimed at coding beginners, this combination is immensely helpful in bringing important elements that had been previously hidden behind several menus in Rstudio out into the open where they are immediately available, reducing complicated workarounds. In my recent experience, it has been easier to teach beginners to code well with Positron than it was previously with Rstudio.

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    Second, Data Science (and Bioinformatics) is increasingly moving in a multi-lingual programming direction. Flow Cytometry is not immune to this trend, Python, Julia and Rust are appearing more in Cyto posters each year. Positron is built to handle this, allowing us to bring in and use cool packages regardless of what language they are written, avoiding additional complicated workarounds to get them to work in Rstudio.

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    And finally, having placed so much effort into making these resources available to the wider community, I don’t want to provide all my examples using Rstudio only to find out two years from now that maintenance has been discontinued by Posit and everything needs to be remade.

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    Consequently, I decided to use Positron for the course. This walk-through will cover some of the main layout elements to help start build some initial familiarity with the IDE, which we will continue to build on throughout the course.

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    Getting Started

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    When opening Positron for the first time, you will see something like this. Let’s work our way around the screen, covering the major items in turn.

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    Interpreter

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    On the upper right, above Session/Variables tab, you have the option to select the coding language (interpreter) being used by the project folder. For most of this course, you will likely see this set to R 4.5.2 (or your current R version). If your computer has Python installed, you may also see these versions appear within the interpreter drop-down menu.

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    As briefly covered at the end of WorkStation walkthrough, the folders button to the right of the interpretor button allows us to open and work with Project Folders. From the drop-down, we can also Create New Folder from a template (which we will cover in the next section), or bring them in from existing GitHub repositories (as we did last section). You will also find the option to open other project folders that have been opened recently.

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    Panel

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    At the bottom-center of the screen you will find the Panel region. This contains several tabs (Console, Terminal, etc).

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    Console

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    At the bottom of the sceen, you will first see the Console Tab. This is the tab where your lines of code when executed (run) will appear, as well as any messages, warnings or errors that get returned. On the right side of the console, you can find several buttons, among them restart R and delete session (for when you need a fresh start), and clear console (which keeps all previously run outputs and objects, but clears away the displayed text within the console).

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    Terminal

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    Right next to the Console tab is your Terminal tab. While the console tab is primarily used to run R code within Positron, the terminal is the interface where code containing system commands directed at at your computer is entered. We will use this less frequently, primarily in two context: 1) rendering Quarto documents, and 2) commiting changes to version control. Among the buttons on the right-side of the terminal to make note of are the + button to add a new terminal, and the trash/garbage can button to kill (stop) the terminal.

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    The other tabs (Problems, Output, Ports, Debug Console) are used less frequently. I usually will Problems and Debug when something goes wrong with the code, as various warning and error messages will end up being displayed there.

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    Editor

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    Located above the panel section (ie, just above the console window) is the main area known as the Editor. It is typically where you end up writing your code. It displays any and all the files that you open.

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    For example, when I open a .png for one of my projects, the image will appear within the editor area in the middle of my screen.

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    When the file I open is an .R script, I will be able to see and edit the code contained within that same area.

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    Should I open a Quarto markdown file (.qmd), I can see and edit both the written as well as the code chunks contained within.

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    Looking below the tabs of the opened files, I can see the file.path (location) for the file I currently have open and am working on. This is denoted by the > > > interspersed with the parent folder names.

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    Just above the file path, and below the tabs, we find a couple buttons. Preview is used to render a Quarto document into various types of documents (including .html, .pdf or .docx) as long as no errors are encountered.

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    Source tab will normally be the active view, which will show everything as code/markdown

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    However, we can also switch to Visual mode (by right clicking and selecting Edit Visual Mode) which will visualize it in a similar manner as if we had rendered the document as an .html webpage.

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    As more files are opened, they will appear as individual tabs. These can be opened and closed as need be. The color of the text also displays their saved status.

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    Help

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    When trying to evaluate how a particular function is working in R, you can hover over it and positron will open up the documentation for that particular function if available, alternatively, you can enter ?theParticularFunctionsName in the console and hit enter to similarly view what is occuring.

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    Primary Side Bar

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    To open a file, several options exist. If they are present within your Project folder, you can click on the pages tab on the activity bar (far upper left) and then click on the file of interest shown within the primary side bar (between the activity bar and the editor). Alternatively, the Open Folder icon on the upper-left or entering “Ctrl + O”/“Command + O” will open a pop-up to allow you to navigate and select a folder elsewhere on your computer.

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    Unsaved changes to an open file are reflected by on the tab the change in color of the text, and the appearance of a dot. We can click the Save changes button to change this.

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    Secondary Side Bar

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    On the upper-portion of the Secondary Side Bar, we can find the Session window, containing the Variables tab. As you run (execute) lines of code, and different variables, objects and functions are created, these become visible under the variables tab on the upper right.

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    For some types of objects (generally data.frames and other matrix-like objects), you can click on their listing under variables to expand to see additional details about the object (column names, etc.) as well as view a larger version which will appear within the Editor window.

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    Plots

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    Similarly, any generated Plots or Documents will appear within the Secondary Side Bar, either under Plots (bottom) or Viewer (top) tabs.

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    On the upper bar multiple tabs can be found, which we will explore in due time. Most useful to point out is the View tab. If you accidentally close your console, session or plots window, and are trying to get them to reapper, you would need to reselect them from this tab.

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    At the far-left side of the screen, you will find the activity bar, which contains several tabs. Depending on which one you have opened, the contents will be displayed on the primary side bar next to it.

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    The pages tab and the left-side bar show you everything that is currently within your project folder, including all the folders, and files. Once version control with Git is initiated, new files are relected showing up as green text and a dot, while modified tracked files are reflected by light brown text and a dot.

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    The dropdown arrows can be used to open and close specific folders to allow for better organization. There is also a scrollbar on the right-side of the side-bar to scroll through the entire folders contents.

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    It can help locate code that you had been working on, but have since forgotten where it is at. Here is an example of finding the files where I had used a function that needed modifying within a local project folder’s files.

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    Similarly, if you need to replace a particular character string with another, the replace with field below can help simplify the task without having to track down and change 20 lines across 5 files.

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    Extensions

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    On the far-left side we can find the Activity bar, which contains several tabs. Which tab you have selected will then dictate the contents of your left side-bar.

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    Occupying the left side bar are several tabs. One of these is Extensions, which shows “Plugins” (or the VScode equivalent) that extend the functionality of Positron further. The ones you have installed may vary, but the main ones in context of this course are Air (provides color and highlights syntax for R code to make interpretation easier) as well as Quarto (for rendering the various document types).

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    Git

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    The Git tab on the left side bar is where once version control is initiated for the project folder, we can see changes that have occurred to the individual files since the last commit. These changes can be added to a new commit by clicking on the + sign. This will be covered more extensively in the next section

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    Similarly, if you want to discard a change that has occured, the circular arrow will revert to the last commited version. Selecting and pressing the delete button will similarly work.

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    Selecting the … options will highlight all the various git functions, some of which we will cover more extensively in the next section and throughout the course.

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    Wrap-up

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    In this walk-through, we looked at some of the elements within Positron. Don’t worry, you don’t need to remember them all or what they do at this point of time, these will come with practice over the first few weeks of the course.

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    In the next section, we will take a closer look at using the version control software Git that we have previewed here.

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    Additional Resources

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    A brief tour of Positron

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    A brief tour of Positron (YouTube)

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    Welcome to Positron

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    AGPL-3.0 CC BY-SA 4.0

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    Using Positron

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    +David Rach +
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    2026-02-01

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    AGPL-3.0 CC BY-SA 4.0

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    Background

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    In this course, we are creating and working with code from the programming language R. However, in practice, we are not running the code directly using just the base R software. Typically, we are running an integrated development environment (IDE), which is an additional software running on top of base R.

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    An IDE has the responsibility to help organize and manage the projects folders, pass along lines of code being executed (run) to the underlying R software, and then return and visualize the outputs in a manner that leads to increased producitivity. Examples of IDEs include Positron, Visual Studio Code and Rstudio.

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    For this course, we will be using Positron as our primary IDE. For those of you who have previous R experience, you are likely more familiar with Rstudio which is also made by Posit, and is the older of the two IDEs. Why use Positron for this course then?

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    There are several reasons. First, Positron combines the best elements of both Rstudio (which preceeded it) and VS code (from which it’s base infrastructure was forked). In a course aimed at coding beginners, this combination is immensely helpful in bringing important elements that had been previously hidden behind several menus in Rstudio out into the open where they are immediately available, reducing complicated workarounds. In my recent experience, it has been easier to teach beginners to code well with Positron than it was previously with Rstudio.

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    Second, Data Science (and Bioinformatics) is increasingly moving in a multi-lingual programming direction. Flow Cytometry is not immune to this trend, Python, Julia and Rust are appearing more in Cyto posters each year. Positron is built to handle this, allowing us to bring in and use cool packages regardless of what language they are written, avoiding additional complicated workarounds to get them to work in Rstudio.

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    And finally, having placed so much effort into making these resources available to the wider community, I don’t want to provide all my examples using Rstudio only to find out two years from now that maintenance has been discontinued by Posit and everything needs to be remade.

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    Consequently, I decided to use Positron for the course. This walk-through will cover some of the main layout elements to help start build some initial familiarity with the IDE, which we will continue to build on throughout the course.

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    Getting Started

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    When opening Positron for the first time, you will see something like this. Let’s work our way around the screen, covering the major items in turn.

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    Interpreter

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    On the upper right, above Session/Variables tab, you have the option to select the coding language (interpreter) being used by the project folder. For most of this course, you will likely see this set to R 4.5.2 (or your current R version). If your computer has Python installed, you may also see these versions appear within the interpreter drop-down menu.

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    Folders

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    As briefly covered at the end of WorkStation walkthrough, the folders button to the right of the interpretor button allows us to open and work with Project Folders. From the drop-down, we can also Create New Folder from a template (which we will cover in the next section), or bring them in from existing GitHub repositories (as we did last section). You will also find the option to open other project folders that have been opened recently.

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    Panel

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    At the bottom-center of the screen you will find the Panel region. This contains several tabs (Console, Terminal, etc).

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    Console

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    At the bottom of the sceen, you will first see the Console Tab. This is the tab where your lines of code when executed (run) will appear, as well as any messages, warnings or errors that get returned. On the right side of the console, you can find several buttons, among them restart R and delete session (for when you need a fresh start), and clear console (which keeps all previously run outputs and objects, but clears away the displayed text within the console).

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    Terminal

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    Right next to the Console tab is your Terminal tab. While the console tab is primarily used to run R code within Positron, the terminal is the interface where code containing system commands directed at at your computer is entered. We will use this less frequently, primarily in two context: 1) rendering Quarto documents, and 2) commiting changes to version control. Among the buttons on the right-side of the terminal to make note of are the + button to add a new terminal, and the trash/garbage can button to kill (stop) the terminal.

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    The other tabs (Problems, Output, Ports, Debug Console) are used less frequently. I usually will Problems and Debug when something goes wrong with the code, as various warning and error messages will end up being displayed there.

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    Editor

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    Located above the panel section (ie, just above the console window) is the main area known as the Editor. It is typically where you end up writing your code. It displays any and all the files that you open.

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    For example, when I open a .png for one of my projects, the image will appear within the editor area in the middle of my screen.

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    When the file I open is an .R script, I will be able to see and edit the code contained within that same area.

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    Should I open a Quarto markdown file (.qmd), I can see and edit both the written as well as the code chunks contained within.

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    Looking below the tabs of the opened files, I can see the file.path (location) for the file I currently have open and am working on. This is denoted by the > > > interspersed with the parent folder names.

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    Just above the file path, and below the tabs, we find a couple buttons. Preview is used to render a Quarto document into various types of documents (including .html, .pdf or .docx) as long as no errors are encountered.

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    Source tab will normally be the active view, which will show everything as code/markdown

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    However, we can also switch to Visual mode (by right clicking and selecting Edit Visual Mode) which will visualize it in a similar manner as if we had rendered the document as an .html webpage.

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    As more files are opened, they will appear as individual tabs. These can be opened and closed as need be. The color of the text also displays their saved status.

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    Help

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    When trying to evaluate how a particular function is working in R, you can hover over it and positron will open up the documentation for that particular function if available, alternatively, you can enter ?theParticularFunctionsName in the console and hit enter to similarly view what is occuring.

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    Primary Side Bar

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    To open a file, several options exist. If they are present within your Project folder, you can click on the pages tab on the activity bar (far upper left) and then click on the file of interest shown within the primary side bar (between the activity bar and the editor). Alternatively, the Open Folder icon on the upper-left or entering “Ctrl + O”/“Command + O” will open a pop-up to allow you to navigate and select a folder elsewhere on your computer.

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    Unsaved changes to an open file are reflected by on the tab the change in color of the text, and the appearance of a dot. We can click the Save changes button to change this.

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    Secondary Side Bar

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    The secondary side bar is found on the right-side of the screen, to the right of the Editor and Panel windows. It is divided between an upper, and a lower portion.

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    Variables

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    On the upper-portion of the Secondary Side Bar, we can find the Session window, containing the Variables tab. As you run (execute) lines of code, and different variables, objects and functions are created, these become visible under the variables tab on the upper right.

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    For some types of objects (generally data.frames and other matrix-like objects), you can click on their listing under variables to expand to see additional details about the object (column names, etc.) as well as view a larger version which will appear within the Editor window.

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    Plots

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    Similarly, any generated Plots or Documents will appear within the Secondary Side Bar, either under Plots (bottom) or Viewer (top) tabs.

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    View

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    On the upper bar multiple tabs can be found, which we will explore in due time. Most useful to point out is the View tab. If you accidentally close your console, session or plots window, and are trying to get them to reapper, you would need to reselect them from this tab.

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    Activity Bar

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    At the far-left side of the screen, you will find the activity bar, which contains several tabs. Depending on which one you have opened, the contents will be displayed on the primary side bar next to it.

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    Pages

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    The pages tab and the left-side bar show you everything that is currently within your project folder, including all the folders, and files. Once version control with Git is initiated, new files are relected showing up as green text and a dot, while modified tracked files are reflected by light brown text and a dot.

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    The dropdown arrows can be used to open and close specific folders to allow for better organization. There is also a scrollbar on the right-side of the side-bar to scroll through the entire folders contents.

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    It can help locate code that you had been working on, but have since forgotten where it is at. Here is an example of finding the files where I had used a function that needed modifying within a local project folder’s files.

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    Similarly, if you need to replace a particular character string with another, the replace with field below can help simplify the task without having to track down and change 20 lines across 5 files.

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    Extensions

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    On the far-left side we can find the Activity bar, which contains several tabs. Which tab you have selected will then dictate the contents of your left side-bar.

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    Occupying the left side bar are several tabs. One of these is Extensions, which shows “Plugins” (or the VScode equivalent) that extend the functionality of Positron further. The ones you have installed may vary, but the main ones in context of this course are Air (provides color and highlights syntax for R code to make interpretation easier) as well as Quarto (for rendering the various document types).

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    Git

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    The Git tab on the left side bar is where once version control is initiated for the project folder, we can see changes that have occurred to the individual files since the last commit. These changes can be added to a new commit by clicking on the + sign. This will be covered more extensively in the next section

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    Similarly, if you want to discard a change that has occured, the circular arrow will revert to the last commited version. Selecting and pressing the delete button will similarly work.

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    Selecting the … options will highlight all the various git functions, some of which we will cover more extensively in the next section and throughout the course.

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    Wrap-up

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    In this walk-through, we looked at some of the elements within Positron. Don’t worry, you don’t need to remember them all or what they do at this point of time, these will come with practice over the first few weeks of the course.

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    In the next section, we will take a closer look at using the version control software Git that we have previewed here.

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    Additional Resources

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    A brief tour of Positron

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    A brief tour of Positron (YouTube)

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    Welcome to Positron

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    AGPL-3.0 CC BY-SA 4.0

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    AGPL-3.0 CC BY-SA 4.0

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    Background

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    In the previous section, we briefly introduced Quarto Markdown Documents (.qmd) while working our way through version control concepts. Since we will be using .qmd files extensively throughout this course, this section will explore how we can build on these concepts to modify these files to create a variety of outputs (ranging from Word documents, pdfs, html webpages). We will also take a look at how to use code-chunk arguments to control what code is run or displayed within.

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    Getting Started

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    We will start off by creating a a new .QMD document within our GitPractice repository. As we saw in the previous section, the basic elements include:

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    Render/Preview

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    The preview button, at the upper-left end of the Editor, is used to render/knit a quarto document. This triggers the process by which code-chunks are run, and then the outputs are cobbled together into the file format type designated by the YAML header.

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    HTML

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    In this case, the YAML header’s format argument is set to html. After clicking preview, we can see the various rendering steps appear in the console below. Since no errors occured, the html document was formed succesfully and appears as a file in the left side-bar. Additional, a preview of the document appears in the View tab of the right side-bar, allowing for quick visual inspection.

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    Alternatively, we can render a document via the terminal, by entering “quarto render”, followed by the name of the document.

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    This results similar process as what we saw with the preview button

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    We can also open the .html document via our File Explorer, which will open it within our web browser.

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    Quarto documents can be rendered (previewed) in other formats besides html. These include pdf, Word documents (docx), and slides (revealjs). This is set by the format argument within the YAML header.

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    PDF

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    By switching the format argument from html to pdf, we can render the document as a pdf

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    We can see the pdf is now listed in the list of files, with a preview shown on the right side-bar.

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    Docx

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    We can also generate Word documents (.docx) as well.

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    In this case, we can see that a Word document file was created, but nothing appears in the View tab. This is because the format is not yet supported for the View tab. We can however open and view the Word document via our File explorer.

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    Which shows a Word Document style output.

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    YAML

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    We can additionally provide additional custom inputs to the YAML header. A couple examples include providing the document author and date.

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    Which we can see are updated after we preview/render.

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    Table of Contents

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    In the previous section, we saw that we could provide headings and subheadings to our .qmd file by placing a # at the start of a line in the text portion of the document. A subheading was designated by a ##, with additional hierarchy being designated by appending an additional #.

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    We can use the heading information to generate a table of contents for our document. To do this, we add a toc argument to the yaml header, and set it to TRUE. After rendering, it appears on the upper-right side of the document.

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    Notice, that the subheaders do not appear currently within the TOC.

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    We can fix this by setting a toc-expand argument in the YAML to true.

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    Code Chunk Arguments

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    As we briefly touched on in the last section, code-chunks can be modified by including arguments, which affect whether a particular code chunk gets evaluated. In that example, we included a “#| eval: FALSE” to the install commands since we did not want them to be re-run subsequently. We will take a closer look at the other arguments in this section.

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    Eval

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    The code-chunk argument, “Eval”, is used to determine when a code-chunk get’s evaluated. When set to true (or by default if no eval argument is included), the code-chunks contents will be run/executed, and the output will appear. We can see this in the html output, as below the code block, we get back the address of my working directory.

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    When we switch the Eval argument to FALSE, and then render the document, we can see that the code block remains, but we do not get any output for the code contained within.

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    In every-day practice, we will “use eval: FALSE” arguments when we want to keep the code for later use, but want to manually run the code contained within ourselves.

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    Echo

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    The code-block argument “echo” dictates whether the code within the code-block is displayed within the document. So in the case when “echo: true”, we get both the code displayed, as well as the output that gets returned by the code.

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    By contrast, when “echo: FALSE”, we do not have the code displayed, but do get the output of that code being run.

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    Include

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    The next code-chunk argument is include. Unlike echo, which focuses on whether the code is displayed, but still returns the output, include dictates behavior of both the code-block and it’s output. Unlike eval however, it will still run the code, which allows it to be available for the next code-chunk that might need it. When we set “include: false”, no trace of that code-chunk is present in the document. This is useful when making reports where we do not want to include the code used to generate a particular figure.

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    By contrast, when we set “include: true”, the code block and it’s output is once again included within the rendered document.

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    Code-Fold

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    One of my favorites is “code-fold”. When we set it as “code-fold: show”, it displays the code, but provides a drop-down arrow that can be closed to compress the code.

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    In contrast, if we want to make the code-available for those that are interested, but not directly visible, we can set as “code-fold: true”

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    Warnings

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    Within R, when code is executed, in addition to returning the output, R is capable of returning warnings (when something is not as expected, but not sufficient to elicit an error with a complete stop) or a message (text output that gets displayed, often telling about progress). While these are useful when running code yourself, it can be annoying when generating a report and the 2nd page is a bunch of warning text being displayed.

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    For example, when the R package ggcyto is loaded via the library call, it will automatically load several other packages, which typically results in these messages being outputted:

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    We can therefore set that code-chunk’s warning/message arguments to FALSE, therefore silencing the message outputs that would otherwise clutter up our report.

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    Text Styles

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    Quarto primarily uses Markdown for text styling. Consequently, markdown arguments can be used within the text to change how various text appears.

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    For a regular text, This single asterisk on each side of a word will italicize.

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    When the number of asterisk is doubled, This word is bolded.

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    When three asterisk are used, both are applied.

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    You can place images by adding the following, as long as the file.path to the image is correctly formatted. In my case, this is why I include images folders within my folders to simplify the copy and paste.

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    Wrap-up

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    We have now briefly looked at various common customizations within a Quarto Markdown Document that can allow us to better document what we are doing, and control whether various code chunk outputs are displayed in the final rendered document.

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    In the next section, we will cover some course logistics by investigate using the Discussions Forums to get community feedback throughout the course, when to use the Issues page, as well as how to open a pull request to submit any completed optional Take-Home problems to get course instructor feedback.

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    Additional Resources

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    Quarto Markdown

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    YAML

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    AGPL-3.0 CC BY-SA 4.0

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    - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + Cytometry in R – Introduction to Quarto + + + + + + + + + + + + + + + + + +
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    +

    Introduction to Quarto

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    +David Rach +
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    2026-02-01

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    AGPL-3.0 CC BY-SA 4.0

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    Background

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    .

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    In the previous section, we briefly introduced Quarto Markdown Documents (.qmd) while working our way through version control concepts. Since we will be using .qmd files extensively throughout this course, this section will explore how we can build on these concepts to modify these files to create a variety of outputs (ranging from Word documents, pdfs, html webpages). We will also take a look at how to use code-chunk arguments to control what code is run or displayed within.

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    Getting Started

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    We will start off by creating a a new .QMD document within our GitPractice repository. As we saw in the previous section, the basic elements include:

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    1. A YAML header, that dictates formatting
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    2. The text body, where we can include documentation
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    3. Code-block chunks, in which we can write code that can be executed, as well as # comments
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    Render/Preview

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    The preview button, at the upper-left end of the Editor, is used to render/knit a quarto document. This triggers the process by which code-chunks are run, and then the outputs are cobbled together into the file format type designated by the YAML header.

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    HTML

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    In this case, the YAML header’s format argument is set to html. After clicking preview, we can see the various rendering steps appear in the console below. Since no errors occured, the html document was formed succesfully and appears as a file in the left side-bar. Additional, a preview of the document appears in the View tab of the right side-bar, allowing for quick visual inspection.

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    Alternatively, we can render a document via the terminal, by entering “quarto render”, followed by the name of the document.

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    This results similar process as what we saw with the preview button

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    We can also open the .html document via our File Explorer, which will open it within our web browser.

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    Quarto documents can be rendered (previewed) in other formats besides html. These include pdf, Word documents (docx), and slides (revealjs). This is set by the format argument within the YAML header.

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    PDF

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    By switching the format argument from html to pdf, we can render the document as a pdf

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    We can see the pdf is now listed in the list of files, with a preview shown on the right side-bar.

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    Docx

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    We can also generate Word documents (.docx) as well.

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    In this case, we can see that a Word document file was created, but nothing appears in the View tab. This is because the format is not yet supported for the View tab. We can however open and view the Word document via our File explorer.

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    Which shows a Word Document style output.

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    YAML

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    We can additionally provide additional custom inputs to the YAML header. A couple examples include providing the document author and date.

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    Which we can see are updated after we preview/render.

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    Table of Contents

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    In the previous section, we saw that we could provide headings and subheadings to our .qmd file by placing a # at the start of a line in the text portion of the document. A subheading was designated by a ##, with additional hierarchy being designated by appending an additional #.

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    We can use the heading information to generate a table of contents for our document. To do this, we add a toc argument to the yaml header, and set it to TRUE. After rendering, it appears on the upper-right side of the document.

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    Notice, that the subheaders do not appear currently within the TOC.

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    We can fix this by setting a toc-expand argument in the YAML to true.

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    Code Chunk Arguments

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    As we briefly touched on in the last section, code-chunks can be modified by including arguments, which affect whether a particular code chunk gets evaluated. In that example, we included a “#| eval: FALSE” to the install commands since we did not want them to be re-run subsequently. We will take a closer look at the other arguments in this section.

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    Eval

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    The code-chunk argument, “Eval”, is used to determine when a code-chunk get’s evaluated. When set to true (or by default if no eval argument is included), the code-chunks contents will be run/executed, and the output will appear. We can see this in the html output, as below the code block, we get back the address of my working directory.

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    When we switch the Eval argument to FALSE, and then render the document, we can see that the code block remains, but we do not get any output for the code contained within.

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    In every-day practice, we will “use eval: FALSE” arguments when we want to keep the code for later use, but want to manually run the code contained within ourselves.

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    Echo

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    The code-block argument “echo” dictates whether the code within the code-block is displayed within the document. So in the case when “echo: true”, we get both the code displayed, as well as the output that gets returned by the code.

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    By contrast, when “echo: FALSE”, we do not have the code displayed, but do get the output of that code being run.

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    In daily-practice, “echo: FALSE” gets often used when generating plots that we want to include in the report, without the code that generated them being displayed.

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    Include

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    The next code-chunk argument is include. Unlike echo, which focuses on whether the code is displayed, but still returns the output, include dictates behavior of both the code-block and it’s output. Unlike eval however, it will still run the code, which allows it to be available for the next code-chunk that might need it. When we set “include: false”, no trace of that code-chunk is present in the document. This is useful when making reports where we do not want to include the code used to generate a particular figure.

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    By contrast, when we set “include: true”, the code block and it’s output is once again included within the rendered document.

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    Code-Fold

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    One of my favorites is “code-fold”. When we set it as “code-fold: show”, it displays the code, but provides a drop-down arrow that can be closed to compress the code.

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    In contrast, if we want to make the code-available for those that are interested, but not directly visible, we can set as “code-fold: true”

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    Warnings

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    Within R, when code is executed, in addition to returning the output, R is capable of returning warnings (when something is not as expected, but not sufficient to elicit an error with a complete stop) or a message (text output that gets displayed, often telling about progress). While these are useful when running code yourself, it can be annoying when generating a report and the 2nd page is a bunch of warning text being displayed.

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    For example, when the R package ggcyto is loaded via the library call, it will automatically load several other packages, which typically results in these messages being outputted:

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    We can therefore set that code-chunk’s warning/message arguments to FALSE, therefore silencing the message outputs that would otherwise clutter up our report.

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    Text Styles

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    Quarto primarily uses Markdown for text styling. Consequently, markdown arguments can be used within the text to change how various text appears.

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    For a regular text, This single asterisk on each side of a word will italicize.

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    When the number of asterisk is doubled, This word is bolded.

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    When three asterisk are used, both are applied.

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    For an underscore, the word of interest is surrounded by square brackets “[]”, with “{.underline}” adjacent.

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    Images

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    You can place images by adding the following, as long as the file.path to the image is correctly formatted. In my case, this is why I include images folders within my folders to simplify the copy and paste.

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    Wrap-up

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    .

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    We have now briefly looked at various common customizations within a Quarto Markdown Document that can allow us to better document what we are doing, and control whether various code chunk outputs are displayed in the final rendered document.

    +

    In the next section, we will cover some course logistics by investigate using the Discussions Forums to get community feedback throughout the course, when to use the Issues page, as well as how to open a pull request to submit any completed optional Take-Home problems to get course instructor feedback.

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    Additional Resources

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    Quarto Markdown

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    AGPL-3.0 CC BY-SA 4.0

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    here

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    This is the software installation walkthrough for those whose computers are running Linux. First off, welcome! Based on our pre-course interest form, there was a suprising number of you daily-drivers out there! However, a CytometryInR interest form is unlikely to be representative of the general population, so please stash all Year of the Linux desktop banners until further notice.

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    Background

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    If you are daily-driving Linux, you are likely not a stranger to the process of getting software installed on your particular distribution.

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    When it comes to installing R website, the R project supports packaging formats for both Debian (including Ubuntu, Linux Mint, etc) and RHEL (including Fedora) based-distributions. The supported branch for SUSE has not been active since 2012. This is similarly the case when installing Positron. Depending on your distribution, you might also need to install Git via your package manager.

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    I daily-drive Debian stable (Trixie), so this walk-through documents the installation process for the Debian branch. I plan to circle back with a Fedora version, but if that doesn’t occur by the publishing time, I refer you to the R for Linux documentation to help get you started.

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    Getting Started

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    Debian-based Distros

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    Installing R

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    To get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.

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    On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.

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    Once this is done, select your Linux Distro (or one that shares your package managers format).

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    On the landing page, you will find a bunch of relevant installation information, which is worthwhile giving a read-through when you have time.

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    The process to successfully install R can be summarized as follows:

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    Update apt/sources.list to include the CRAN repository (allowing access to R packages)

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    Since we are running on Debian stable (Trixie), we would add the following line to sources.list

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    So in practice, open sources.list:

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    Paste the line, and “Ctrl + O”; “Enter”; “Ctrl + X” to save the changes.

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    Next, we will need to retrieve the keyID used to sign. This can be fetched from Ubuntu via the terminal.

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    Then we need to export and write it

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    Which if successful, will display the public key.

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    With the above set up, we can proceed via our apt package manager to install both r-base and r-base-dev (which contains the equivalent of Rtools for Windows, or Xcode Command Line Tools for macOS).

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    And if all goes well, R should now be installed.

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    Installing Git

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    # sudo apt install git
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    Installing Positron

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    .

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    Finally, you will need to install Positron. It will be the integrated development environment (IDE) we will be using for the course.

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    First, navigate to their homepage, and select the blue Download option button on the upper-right.

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    You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).

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    With the license accepted, you will be able to select distribution and architecture.

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    Once the Download completes, proceed to install the .deb package as you would nornally. GUI example via Discover below.

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    Depending on your configurations, you may be asked to exert your sudo powers.

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    Once this completes, you should now be able to launch the software for the first time.

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    Connecting GitHub and Positron

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    .

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    Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected.

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    When opening Positron for the first time, you will encounter the following view:

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    We will go over the various aspects of using Positron in the next section. For now select the “Start Session” button on the upper right.

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    Then select the most recent/up-to-date R version.

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    R will proceed to activate, and you will see a message appear in the bottom center window (ie. console)

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    Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your GitHub account from your preferred web browser.

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    Once this is done, return to Positron, and click on the profile Icon and select “Sign with GitHub” option.

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    Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the “Copy & Continue to GitHub” button.

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    If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account.

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    You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue.

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    And select “Authorize posit-dev” to authorize Positron to interact with your GitHub Account.

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    And if all works out, you should see the following succes page

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    Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed.

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    New Folder from Git

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    With GitHub and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer.

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    To this, first navigate to the Folder icon on the upper-right, and select the “New Folder from Git” option

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    Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in “https://github.com/UMGCCCFCSR/CytometryInR”

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    You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder.

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    You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven’t had time to properly vet.

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    And with that done, you should now see the forked Cytometry in R course contents appear within Positron.

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    We will now repeat the process to bring in youir GitHub profile’s ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: “https://github.com/UMGCCCFCSR/UMGCCCFCSR”

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    After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK.

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    And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer.

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    Wrap-up

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    In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course.

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    In the next section, we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send changes from your local repositories back to GitHub.

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    Additional Resources

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    How to Download and Install Software on Linux

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    Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)

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    A brief tour of Positron

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    A brief introduction to Git for beginners

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    AGPL-3.0 CC BY-SA 4.0

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    - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + Cytometry in R – Installing Software on Linux + + + + + + + + + + + + + + + + + +
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    Installing Software on Linux

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    +David Rach +
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    2026-02-01

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    For screen-shot slide format, click here

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    AGPL-3.0 CC BY-SA 4.0

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    .

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    This is the software installation walkthrough for those whose computers are running Linux. First off, welcome! Based on our pre-course interest form, there was a suprising number of you daily-drivers out there! However, a CytometryInR interest form is unlikely to be representative of the general population, so please stash all Year of the Linux desktop banners until further notice.

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    Background

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    .

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    If you are daily-driving Linux, you are likely not a stranger to the process of getting software installed on your particular distribution.

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    When it comes to installing R website, the R project supports packaging formats for both Debian (including Ubuntu, Linux Mint, etc) and RHEL (including Fedora) based-distributions. The supported branch for SUSE has not been active since 2012. This is similarly the case when installing Positron. Depending on your distribution, you might also need to install Git via your package manager.

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    I daily-drive Debian stable (Trixie), so this walk-through documents the installation process for the Debian branch. I plan to circle back with a Fedora version, but if that doesn’t occur by the publishing time, I refer you to the R for Linux documentation to help get you started.

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    Getting Started

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    Debian-based Distros

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    Installing R

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    .

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    To get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.

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    On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.

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    Once this is done, select your Linux Distro (or one that shares your package managers format).

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    On the landing page, you will find a bunch of relevant installation information, which is worthwhile giving a read-through when you have time.

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    The process to successfully install R can be summarized as follows:

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    Update apt/sources.list to include the CRAN repository (allowing access to R packages)

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    Since we are running on Debian stable (Trixie), we would add the following line to sources.list

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    So in practice, open sources.list:

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    Paste the line, and “Ctrl + O”; “Enter”; “Ctrl + X” to save the changes.

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    Next, we will need to retrieve the keyID used to sign. This can be fetched from Ubuntu via the terminal.

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    Then we need to export and write it

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    Which if successful, will display the public key.

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    With the above set up, we can proceed via our apt package manager to install both r-base and r-base-dev (which contains the equivalent of Rtools for Windows, or Xcode Command Line Tools for macOS).

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    And if all goes well, R should now be installed.

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    Installing Git

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    # sudo apt install git
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    Installing Positron

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    .

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    Finally, you will need to install Positron. It will be the integrated development environment (IDE) we will be using for the course.

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    First, navigate to their homepage, and select the blue Download option button on the upper-right.

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    You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).

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    With the license accepted, you will be able to select distribution and architecture.

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    Once the Download completes, proceed to install the .deb package as you would nornally. GUI example via Discover below.

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    Depending on your configurations, you may be asked to exert your sudo powers.

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    Once this completes, you should now be able to launch the software for the first time.

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    Connecting GitHub and Positron

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    .

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    Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected.

    +

    When opening Positron for the first time, you will encounter the following view:

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    .

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    We will go over the various aspects of using Positron in the next section. For now select the “Start Session” button on the upper right.

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    Then select the most recent/up-to-date R version.

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    R will proceed to activate, and you will see a message appear in the bottom center window (ie. console)

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    .

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    Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your GitHub account from your preferred web browser.

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    Once this is done, return to Positron, and click on the profile Icon and select “Sign with GitHub” option.

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    Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the “Copy & Continue to GitHub” button.

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    If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account.

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    You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue.

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    And select “Authorize posit-dev” to authorize Positron to interact with your GitHub Account.

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    And if all works out, you should see the following succes page

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    .

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    Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed.

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    New Folder from Git

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    With GitHub and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer.

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    To this, first navigate to the Folder icon on the upper-right, and select the “New Folder from Git” option

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    Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in “https://github.com/UMGCCCFCSR/CytometryInR”

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    .

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    You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder.

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    .

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    You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven’t had time to properly vet.

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    And with that done, you should now see the forked Cytometry in R course contents appear within Positron.

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    We will now repeat the process to bring in youir GitHub profile’s ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: “https://github.com/UMGCCCFCSR/UMGCCCFCSR”

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    After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK.

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    And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer.

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    Wrap-up

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    .

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    In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course.

    +

    In the next section, we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send changes from your local repositories back to GitHub.

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    Additional Resources

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    How to Download and Install Software on Linux

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    Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)

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    A brief tour of Positron

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    A brief introduction to Git for beginners

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    AGPL-3.0 CC BY-SA 4.0

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    + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/course/00_WorkstationSetup/MacOS.html b/docs/course/00_WorkstationSetup/MacOS.html index c4326f7..154d92f 100644 --- a/docs/course/00_WorkstationSetup/MacOS.html +++ b/docs/course/00_WorkstationSetup/MacOS.html @@ -247,7 +247,7 @@
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    AGPL-3.0 CC BY-SA 4.0

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    This is the software installation walkthrough for those whose computers are running MacOS. Based on our pre-course interest form, you make up a solid proportion of the course participants.

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    Background

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    In this walkthrough, we will have you install the following pieces of software:

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    R website : The programming language we will be using throughout the course.

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    Positron : The integrated development environment (IDE) in which we will open, modify and run our code.

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    Git : The version control software that will allow us to track changes to our files. You may or may not already it on your computer depending on whether Xcode Command Line Tools is installed.

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    Please note, the installation steps detailed below were carried out on a Mac with the older older pre-2020 x86 Intel chips, if you are running a Mac with the newer ARM (M1 or greater) chips, the installation instructions will differ some of the options you selecct during the download. If you encounter major differences in installation, please take screenshots and open an issue so that we can update the documentation for your architecture.

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    Getting Started

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    Installing R

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    To get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.

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    On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.

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    You will then select your Operating System, in this case, macOS

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    Next, you will need to select the appropiate download based on your computers architecture. On newer Macs (containing M1+ chips) this would the arm64 option on the center left of the screen. For the older Intel (pre-2020) Macs, you would select the x86_64 option. If you are unsure, check your About This Mac tab

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    After the download has completed, launch the installer

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    Proceed through the Read Me

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    You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course).

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    Next, you will need to navigate through several pages, keeping the defaults.

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    And with any luck, you should see that the installation was successful.

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    Xcode Command Line Tools

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    Depending on your version of macOS, you may or may not already have Git installed on your computer. The reason is that it comes bundled within the Xcode Command Line Tools.

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    If this is not your first foray into coding, you may have previously seen an installation pop-up along the lines of “XYZ requires command line developer tools. Would you like to install the tools now?” when installing an IDE (like Positron, Rstudio or Visual Studio Code).

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    Since these command line developer tools contain both Git, and also the equivalent of Rtools for Windows, we will need to install them for this course. To get started, first open your terminal.

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    Next run the following code:

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    You will then have the pop-up asking whether you want to install the command line tools (which contain Git). Select Install.

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    You will then be asked to accept the license

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    Your installation will then proceed

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    And if all goes well, the software will finish installing.

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    After you complete Positron installation (next section), if you check the version control tab on the action bar on the far left side of the screen, you should see the following if Git was installed correctly.

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    Alternatively, if you see this, you will need to reattempt the installation.

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    Install Positron

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    Finally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.

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    You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).

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    With the license accepted, you will be able to select your operating system and the relevant installer depending on whether you are on an M1+ (ARM) or older Intel (x86) Mac.

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    Once the Download completes, proceed to install the package as you normally would for any other program.

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    Connecting GitHub and Positron

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    Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected.

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    We will go over the various aspects of using Positron in the next section. For now select the “Start Session” button on the upper right, and then select the most recent/up-to-date R version.

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    R will proceed to activate, and you will see a message appear in the bottom center window (ie. console)

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    Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your GitHub account from your preferred web browser.

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    Once this is done, return to Positron, and click on the profile Icon and select “Sign with GitHub” option.

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    Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the “Copy & Continue to GitHub” button.

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    If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account.

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    You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue.

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    And select “Authorize posit-dev” to authorize Positron to interact with your GitHub Account.

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    And if all works out, you should see the following succes page

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    Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed.

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    New Folder from Git

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    With GitHub and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer.

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    To this, first navigate to the Folder icon on the upper-right, and select the “New Folder from Git” option

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    Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in “https://github.com/UMGCCCFCSR/CytometryInR”

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    You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder.

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    You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven’t had time to properly vet.

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    And with that done, you should now see the forked Cytometry in R course contents appear within Positron.

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    We will now repeat the process to bring in youir GitHub profile’s ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: “https://github.com/UMGCCCFCSR/UMGCCCFCSR”

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    After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK.

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    And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer.

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    Wrap-up

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    In this walkthrough, we installed R, Positron, and ensured that Git/Command Line Tools were active. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course.

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    In the next section, we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send changes from your local repositories back to GitHub.

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    Additional Resources

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    How to Install Software on a Mac

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    Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)

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    A brief tour of Positron

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    A brief introduction to Git for beginners

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    AGPL-3.0 CC BY-SA 4.0

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    - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + Cytometry in R – Installing Software on MacOS + + + + + + + + + + + + + + + + + +
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    Installing Software on MacOS

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    +David Rach +
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    2026-02-01

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    AGPL-3.0 CC BY-SA 4.0

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    This is the software installation walkthrough for those whose computers are running MacOS. Based on our pre-course interest form, you make up a solid proportion of the course participants.

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    Background

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    In this walkthrough, we will have you install the following pieces of software:

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    R website : The programming language we will be using throughout the course.

    +

    Positron : The integrated development environment (IDE) in which we will open, modify and run our code.

    +

    Git : The version control software that will allow us to track changes to our files. You may or may not already it on your computer depending on whether Xcode Command Line Tools is installed.

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    Please note, the installation steps detailed below were carried out on a Mac with the older older pre-2020 x86 Intel chips, if you are running a Mac with the newer ARM (M1 or greater) chips, the installation instructions will differ some of the options you selecct during the download. If you encounter major differences in installation, please take screenshots and open an issue so that we can update the documentation for your architecture.

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    Getting Started

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    Installing R

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    .

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    To get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.

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    On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.

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    You will then select your Operating System, in this case, macOS

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    Next, you will need to select the appropiate download based on your computers architecture. On newer Macs (containing M1+ chips) this would the arm64 option on the center left of the screen. For the older Intel (pre-2020) Macs, you would select the x86_64 option. If you are unsure, check your About This Mac tab

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    After the download has completed, launch the installer

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    Proceed through the Read Me

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    You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course).

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    Next, you will need to navigate through several pages, keeping the defaults.

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    And with any luck, you should see that the installation was successful.

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    Xcode Command Line Tools

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    Depending on your version of macOS, you may or may not already have Git installed on your computer. The reason is that it comes bundled within the Xcode Command Line Tools.

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    If this is not your first foray into coding, you may have previously seen an installation pop-up along the lines of “XYZ requires command line developer tools. Would you like to install the tools now?” when installing an IDE (like Positron, Rstudio or Visual Studio Code).

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    Since these command line developer tools contain both Git, and also the equivalent of Rtools for Windows, we will need to install them for this course. To get started, first open your terminal.

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    Next run the following code:

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    xcode-select --install
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    You will then have the pop-up asking whether you want to install the command line tools (which contain Git). Select Install.

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    You will then be asked to accept the license

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    Your installation will then proceed

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    And if all goes well, the software will finish installing.

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    After you complete Positron installation (next section), if you check the version control tab on the action bar on the far left side of the screen, you should see the following if Git was installed correctly.

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    Alternatively, if you see this, you will need to reattempt the installation.

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    Install Positron

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    Finally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.

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    First, navigate to their homepage, and select the blue Download option button on the upper-right.

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    You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).

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    With the license accepted, you will be able to select your operating system and the relevant installer depending on whether you are on an M1+ (ARM) or older Intel (x86) Mac.

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    Once the Download completes, proceed to install the package as you normally would for any other program.

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    Connecting GitHub and Positron

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    Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected.

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    When opening Positron for the first time, you will encounter the following view:

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    We will go over the various aspects of using Positron in the next section. For now select the “Start Session” button on the upper right, and then select the most recent/up-to-date R version.

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    R will proceed to activate, and you will see a message appear in the bottom center window (ie. console)

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    Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your GitHub account from your preferred web browser.

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    Once this is done, return to Positron, and click on the profile Icon and select “Sign with GitHub” option.

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    Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the “Copy & Continue to GitHub” button.

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    If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account.

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    You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue.

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    And select “Authorize posit-dev” to authorize Positron to interact with your GitHub Account.

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    And if all works out, you should see the following succes page

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    Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed.

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    New Folder from Git

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    With GitHub and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer.

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    To this, first navigate to the Folder icon on the upper-right, and select the “New Folder from Git” option

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    Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in “https://github.com/UMGCCCFCSR/CytometryInR”

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    You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder.

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    You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven’t had time to properly vet.

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    And with that done, you should now see the forked Cytometry in R course contents appear within Positron.

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    We will now repeat the process to bring in youir GitHub profile’s ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: “https://github.com/UMGCCCFCSR/UMGCCCFCSR”

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    After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK.

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    And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer.

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    Wrap-up

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    .

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    In this walkthrough, we installed R, Positron, and ensured that Git/Command Line Tools were active. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course.

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    In the next section, we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send changes from your local repositories back to GitHub.

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    Additional Resources

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    How to Install Software on a Mac

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    Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)

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    A brief tour of Positron

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    A brief introduction to Git for beginners

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    AGPL-3.0 CC BY-SA 4.0

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    AGPL-3.0 CC BY-SA 4.0

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    This is the software installation walkthrough for those whose computers are running Windows. Based on our pre-course interest form, you make up the majority of course participants.

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    Background

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    In this walkthrough, we will have you install the following pieces of software:

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    Positron : The integrated development environment (IDE) in which we will open, modify and run our code.

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    Git : The version control software that will allow us to track changes to our files.

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    Additionally, Windows users will need to install:

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    RTools : Used to build R packages from source code.

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    Getting Started

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    Installing R

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    To get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.

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    On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.

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    You will then select your Operating System, in this case, Windows.

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    And go ahead and select the Install R for the first time link.

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    Next, you will select the download the current version option at the top of the page.

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    The popup window will then ask where you want to save the installer (.exe) file. We generally save this to either Downloads or Desktop to make finding it easier.

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    After the download is complete, double click on the installer’s .exe file. This will open a popup asking you to select your preferred language.

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    You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course).

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    On Windows, R will normally save it’s software folder under Program Files.

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    Next, please accept the defaults.

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    With the defaults accepted, the installation will commence. Feel free to go have a coffee/tea/beverage-of-your choice break while you wait.

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    And if all goes well, the installation will complete without any issues.

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    Installing RTools

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    We will now work on installing Rtools. This software is needed when building R packages from source, which we will need throughout the course for R packages hosted on GitHub.

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    To get started, we will return to the R installation page we visited previously and instead click on the Rtools option.

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    Next, select the most recent version of Rtools to Download.

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    You will then select for your architecture. For the vast majority of Windows users, your computer will likely be be using a x86 chip architecture, so you would select the Rtools45 installer option.

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    If your computer however uses the ARM chip architecture, you would select the 64-bit ARM Rtools45 installer instead. If you are unsure, see the following.

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    Next, you will select the location to save the Rtools installer to. We generally save this to either Downloads or Desktop to make finding it easier.

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    Once downloaded, double click on the .exe to launch the Rtools installer.

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    Similar to what we did when installing R, go ahead and keep the defaults.

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    And click install to proceed with the installation.

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    And wait while the installation wraps up.

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    If all goes well, you should see the following installation success page.

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    Installing Git

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    Git is a version control software widely used among software developers and bioinformaticians. We will use it extensively throughout the course, both locally on our computers (to keep track of changes to our files), as well as in combination with GitHub(to maintain online backups of our files).

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    We will first navigate to the website and select the download from Windows option.

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    We will then proceed and select install 64-bit Git for Windows Setup option

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    As was the case with our installation of R and Rtools, a pop-up will appear asking for a location to save the installer to.

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    Once downloaded, double-click and proceed with the installation.

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    You will be asked to accept the Git License (which is the free copyleft GPL2 license, which we will learn about later in the course).

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    Then you will be asked to select the folder to save to software to (usually your Programs folder)

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    At this point, the Git installer will ask a series of increasingly niche questions. It is best to just accept all the default options, to avoid wandering too far down a “What is Vim?!?” rabbit-hole.

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    Having made it through all the niche customization screens, we finally reach the install button.

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    We then can wait for the install to complete.

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    And success, we have now installed Git.

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    Installing Positron

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    Finally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.

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    First, navigate to their homepage, and select the blue Download option button on the upper-right.

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    You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).

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    With the license accepted, you will be able to select your operating system. In this case, we will select Windows, specifally the user level install.

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    Please note, if you are using a Windows computer with an ARM based chip (like is the case with Snapdragons), you will need to download the installed from the Positron’s GitHub Release Page, as they are still testing some features.

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    You will then be prompted to select the location you want to save the installer to. We will generally save this to either Downloads or Desktop to make finding it easier.

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    Once the download is complete, double click on the installer, and again accept the license agreement.

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    Generally, Positron will be store its software folder under Program Files.

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    Next up, accept the default options for the following screens

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    And finally, click Install.

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    If all goes well, you should then see the installation success page.

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    Connecting GitHub and Positron

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    Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected.

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    When opening Positron for the first time, you will encounter the following view:

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    We will go over the various aspects of using Positron in the next section. For now select the “Start Session” button on the upper right, and then select the most recent/up-to-date R version.

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    R will proceed to activate, and you will see a message appear in the bottom center window (ie. console)

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    Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your GitHub account from your preferred web browser.

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    Once this is done, return to Positron, and click on the profile Icon and select “Sign with GitHub” option.

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    Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the “Copy & Continue to GitHub” button.

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    If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account.

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    You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue.

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    And select “Authorize posit-dev” to authorize Positron to interact with your GitHub Account.

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    Depending on your computer settings, you may be asked for your two-factor authorization passkey. If so, complete this step.

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    And if all works out, you should see the following succes page

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    Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed.

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    New Folder from Git

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    With GitHub and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer.

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    To this, first navigate to the Folder icon on the upper-right, and select the “New Folder from Git” option

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    Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in “https://github.com/UMGCCCFCSR/CytometryInR”

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    You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder.

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    You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven’t had time to properly vet.

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    And with that done, you should now see the forked Cytometry in R course contents appear within Positron.

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    We will now repeat the process to bring in youir GitHub profile’s ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: “https://github.com/UMGCCCFCSR/UMGCCCFCSR”

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    After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK.

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    And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer.

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    Wrap-up

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    In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course.

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    In the next section, we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send changes from your local repositories back to GitHub.

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    Additional Resources

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    How to Download and Install Software on Windows 11

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    Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)

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    A brief tour of Positron

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    A brief introduction to Git for beginners

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    AGPL-3.0 CC BY-SA 4.0

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    - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + Cytometry in R – Installing Software on Windows + + + + + + + + + + + + + + + + + +
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    Installing Software on Windows

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    +David Rach +
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    2026-02-01

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    AGPL-3.0 CC BY-SA 4.0

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    This is the software installation walkthrough for those whose computers are running Windows. Based on our pre-course interest form, you make up the majority of course participants.

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    Background

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    In this walkthrough, we will have you install the following pieces of software:

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    R website : The programming language we will be using throughout the course.

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    Positron : The integrated development environment (IDE) in which we will open, modify and run our code.

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    Git : The version control software that will allow us to track changes to our files.

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    Additionally, Windows users will need to install:

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    RTools : Used to build R packages from source code.

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    Getting Started

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    Installing R

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    To get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.

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    On the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.

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    You will then select your Operating System, in this case, Windows.

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    And go ahead and select the Install R for the first time link.

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    Next, you will select the download the current version option at the top of the page.

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    The popup window will then ask where you want to save the installer (.exe) file. We generally save this to either Downloads or Desktop to make finding it easier.

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    After the download is complete, double click on the installer’s .exe file. This will open a popup asking you to select your preferred language.

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    You will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course).

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    On Windows, R will normally save it’s software folder under Program Files.

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    Next, please accept the defaults.

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    With the defaults accepted, the installation will commence. Feel free to go have a coffee/tea/beverage-of-your choice break while you wait.

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    And if all goes well, the installation will complete without any issues.

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    Installing RTools

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    We will now work on installing Rtools. This software is needed when building R packages from source, which we will need throughout the course for R packages hosted on GitHub.

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    To get started, we will return to the R installation page we visited previously and instead click on the Rtools option.

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    Next, select the most recent version of Rtools to Download.

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    You will then select for your architecture. For the vast majority of Windows users, your computer will likely be be using a x86 chip architecture, so you would select the Rtools45 installer option.

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    If your computer however uses the ARM chip architecture, you would select the 64-bit ARM Rtools45 installer instead. If you are unsure, see the following.

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    Next, you will select the location to save the Rtools installer to. We generally save this to either Downloads or Desktop to make finding it easier.

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    Once downloaded, double click on the .exe to launch the Rtools installer.

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    Similar to what we did when installing R, go ahead and keep the defaults.

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    And click install to proceed with the installation.

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    And wait while the installation wraps up.

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    If all goes well, you should see the following installation success page.

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    Installing Git

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    Git is a version control software widely used among software developers and bioinformaticians. We will use it extensively throughout the course, both locally on our computers (to keep track of changes to our files), as well as in combination with GitHub(to maintain online backups of our files).

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    We will first navigate to the website and select the download from Windows option.

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    We will then proceed and select install 64-bit Git for Windows Setup option

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    As was the case with our installation of R and Rtools, a pop-up will appear asking for a location to save the installer to.

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    Once downloaded, double-click and proceed with the installation.

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    You will be asked to accept the Git License (which is the free copyleft GPL2 license, which we will learn about later in the course).

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    Then you will be asked to select the folder to save to software to (usually your Programs folder)

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    At this point, the Git installer will ask a series of increasingly niche questions. It is best to just accept all the default options, to avoid wandering too far down a “What is Vim?!?” rabbit-hole.

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    Having made it through all the niche customization screens, we finally reach the install button.

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    We then can wait for the install to complete.

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    And success, we have now installed Git.

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    Installing Positron

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    Finally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.

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    First, navigate to their homepage, and select the blue Download option button on the upper-right.

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    You will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).

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    With the license accepted, you will be able to select your operating system. In this case, we will select Windows, specifally the user level install.

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    Please note, if you are using a Windows computer with an ARM based chip (like is the case with Snapdragons), you will need to download the installed from the Positron’s GitHub Release Page, as they are still testing some features.

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    You will then be prompted to select the location you want to save the installer to. We will generally save this to either Downloads or Desktop to make finding it easier.

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    Once the download is complete, double click on the installer, and again accept the license agreement.

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    Generally, Positron will be store its software folder under Program Files.

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    Next up, accept the default options for the following screens

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    And finally, click Install.

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    If all goes well, you should then see the installation success page.

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    Connecting GitHub and Positron

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    Now that you have all the software installed, we need to make sure that everything is communicating properly with each other. To do this, we will start by making sure your GitHub account and Positron are connected.

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    When opening Positron for the first time, you will encounter the following view:

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    We will go over the various aspects of using Positron in the next section. For now select the “Start Session” button on the upper right, and then select the most recent/up-to-date R version.

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    R will proceed to activate, and you will see a message appear in the bottom center window (ie. console)

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    Congratulations, we now know R is working correctly. Next up, connecting your GitHub account to Positron. To make this process easier, first log into your GitHub account from your preferred web browser.

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    Once this is done, return to Positron, and click on the profile Icon and select “Sign with GitHub” option.

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    Positron will provide a popup containing a code you will need to give to GitHub to set up authentication. Proceed to click on the “Copy & Continue to GitHub” button.

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    If you are already signed in, it will ask which account you want to connect Positron with. Select your GitHub account.

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    You will then be prompted to paste the one-time code provided by Positron. Once pasted, click on Continue.

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    And select “Authorize posit-dev” to authorize Positron to interact with your GitHub Account.

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    Depending on your computer settings, you may be asked for your two-factor authorization passkey. If so, complete this step.

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    And if all works out, you should see the following succes page

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    Returning to Positron, check the profile tab on the lower left and verify that it now shows your GitHub account. If it does, congrats! If not, close Positron, check the tab again, and repeat the above one-time code steps if needed.

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    New Folder from Git

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    With GitHub and Positron now connected, we will bring your two repositories (the README and the fork of CytometryInR) from GitHub to your local computer.

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    To this, first navigate to the Folder icon on the upper-right, and select the “New Folder from Git” option

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    Lets first bring in your forked version of the Cytometry in R repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username in place of UMGCCCFCSR in “https://github.com/UMGCCCFCSR/CytometryInR”

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    You will also be asked for a location to store your project folder. It is best to save the folder locally (avoid using OneDrive or other cloud locations for now), as it makes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder.

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    You may encounter a pop-up asking whether you trust the authors for that particular folder. For your own projects, you are the author, so go ahead and select Yes. Selecting No is a good precaution when bringing in a random GitHub project that you haven’t had time to properly vet.

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    And with that done, you should now see the forked Cytometry in R course contents appear within Positron.

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    We will now repeat the process to bring in youir GitHub profile’s ReadMe repository. Depending on your GitHub username, you would either need to copy the URL from your browser, or swap in your username twice in place for each UMGCCCFCSR: “https://github.com/UMGCCCFCSR/UMGCCCFCSR”

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    After pasting the URL, and selecting the folder to save your project folder to (Documents in our case), select OK.

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    And after a quick import you should now see your ReadMe repository files available and ready to be modified on your local computer.

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    Wrap-up

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    In this walkthrough, we installed R, Rtools, Git and Positron. We also made sure to connect Positron and your GitHub account, and brought copies of your repositories into local project folders. With this, you now have on your workstation the major pieces of software needed for the course.

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    In the next section, we will delve into how to use Positron, and explore more how to use the connection you set up with GitHub to send changes from your local repositories back to GitHub.

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    Additional Resources

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    How to Download and Install Software on Windows 11

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    Riffomonas Project: Installing R, RStudio, and packages for Windows and Mac OS X (CC077)

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    A brief tour of Positron

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    A brief introduction to Git for beginners

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    AGPL-3.0 CC BY-SA 4.0

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    On this page

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    01 - Installing R Packages

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    01 - Installing R Packages

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    Welcome to the first week of Cytometry in R! This week we will be diving into how R packages work, and the how to go about installing them.

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    Important

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    Before getting started, please make sure you have completed the creating a GitHub and Workstation Setup walk-throughs, since we will begin where they left off once the required software was successfully installed.

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    Important

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    Please make sure to sync your forked version of the CytometryInR repository, and pull any changes to your local computer’s CytometryInR project folder so that you have the most recent version of the code and data available.

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    Background

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    During Workstation Setup, you installed the R software to your local computer. R as a programming language that started up in the 1990s. While its original focus was on statistics, it is now widely used in various fields thanks to contributions of many open-source developers over the years.

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    This expanded reach is in part due to the ability to create R packages, that encapsulate additional functions, that can do new things beyond what the original software (ie. base R) was capable of doing.

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    Currently, there are thousands of R packages available. Furthermore, there is a vibrant community of individuals that help maintain and document how to use these packages, which has helped sustain and grow the R ecosystem over the last couple decades.

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    Regardless if you are working with flow cytometry, or in ecology, or in econometrics, or political science, a lot of the analysis and visualizations that you see in publications often involve R.

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    Tip

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    R packages can also just be made for fun! Among my favorite examples of this, there is an R package that lets you add the snake game to your recalculating screen, as well as R packages that provide the color-palette schemes needed to make your plots with Studio Ghibli, Wes Anderson, or Bluey colors.

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    These R packages start off as source code (which is what we will be learning to write during this course). When you install a R package to your computer, this human-readable source code gets converted into a binary format with which your computer can interact directly.

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    Expanding on this concept, a new R package can be made up of new code (primarily in the form of tools (ie. functions) that do a particular useful things) that is entirely self-contained, or reuse functions present in existing R packages to help make something new. When an R package relies on a function from another R package, it needs the other R package to be installed in order for everything to work properly. This is known as a package dependency.

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    To make distributing the thousands of R packages and their associated package dependencies easier, R packages are collected (ie. hosted) within repositories, which function as an intermediate distributor.

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    The three main locations for R packages from are CRAN (containing 23069 packages), Bioconductor (containing 2361 packages), and individual R packages hosted by their developers via GitHub.

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    The process of installing R packages will vary a bit depending on which repository the respective R package is in. For beginners, this often prooves to be a pain-point, as they will attempt to install an R package using one set of installation commands, only to get an error (because the R package is not in that repository).

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    In this session, we will work on installing the various R packages we will need through the course. While doing so, we will explore how to figure out which repository the individual package is in; what installation commands to use to download it; and how to look up the help documentation. We will also touch on how the functions within an R package are made available for our computer to use (via the library() call), and how to troubleshoot the more commonly encountered installation errors.

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    Getting Started

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    Set Up

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    Alright, with the background out of the way, let’s get started!

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    Important

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    Please make sure to sync your forked version of the CytometryInR repository, and pull any changes to your local computer’s CytometryInR project folder so that you have the most recent version of the code and data available.

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    Warning

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    Please remember to always copy over the new material from your local CytometryInR folder to a separate Project Folder that you created and named (ex. “Week_01” or “MyLearningFolder”, etc.). This will ensure any edits you make to the files do not affect your ability to bring in next week’s materials to the CytometryInR folder

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    Warning

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    After pulling the new data and code locally, open CytometryInR, open the course folder, and open the 01_InstallingRPackages folder. From here, copy the index.qmd file to your own working Project Folder (ex. Week_01) where you can work on it without causing any conflicts. Then return to Positron and open up your working project folder (ex. Week_01).

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    Next up, within Positron, let’s make sure to select R as the coding language being used for this session.

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    Now that R is running within Positron, the console (lower portion of the screenn) is now able to run (ie. execute) any R code that is sent to it.

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    Checking for Loaded Packages

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    For the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active.

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    Accessing Help Documentation

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    Within your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following sessionInfo() function

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    sessionInfo()
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    If you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over.

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    In this case, we can see the help documentation corresponding for sessionInfo(). Beyond hovering over the function, this can also be accessed by adding a ? directly in front of the function, and then running that line of code.

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    When executed, the function’s help file documentation will open up within the Help tab in the secondary side bar on the right-side of the screen. Glancing at the top of the page we can see the name of the package that contains the sessionInfo() function ({utils}). Scrolling down the help page past all the documentation, we can see a link to the index page.

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    After clicking, the Help tab switches from viewing the documentation for the sessionInfo() function, to showing all the functions within the utils package. Most R packages contain help documentation, so this process can be adapted to find out additional information about what a function does, and what arguments are needed to produce customized outputs.

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    sessionInfo()

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    Within your .qmd file, let’s go ahead and run the following code-block:

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    sessionInfo()
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    R version 4.5.2 (2025-10-31)
-Platform: x86_64-pc-linux-gnu
-Running under: Debian GNU/Linux 13 (trixie)
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-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
-
-locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
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-time zone: America/New_York
-tzcode source: system (glibc)
-
-attached base packages:
-[1] stats     graphics  grDevices utils     datasets  methods   base     
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-loaded via a namespace (and not attached):
- [1] compiler_4.5.2  fastmap_1.2.0   cli_3.6.5       tools_4.5.2    
- [5] htmltools_0.5.9 otel_0.2.0      yaml_2.3.12     rmarkdown_2.30 
- [9] knitr_1.51      jsonlite_2.0.0  xfun_0.56       digest_0.6.39  
-[13] rlang_1.1.7     evaluate_1.0.5
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    The outputs that get returned by sessionInfo() will vary a bit depending on your computer’s operating system, and the version of R you have installed.

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    For today, let’s focus on the last two elements of the output:

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    The R software itself is made up of several base R packages, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages.

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    As we install additional R packages and load them using the library() function throughout this session, sporadically re-run sessionInfo() to see how this list of R packages changes.

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    Installing from CRAN

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    We will start by installing R packages that are part of the CRAN repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository.

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    These include the tidyverse packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today.

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    dplyr

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    Our first R package we will install during this session is the dplyr package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function install.packages().

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    For the install.packages() function, we place within the () the name of the R package from CRAN that we wish to install.

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    Tip

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    A usual struggle point for beginners is that install.packages() requires ” ” to be placed around the package name. Forgetting them results in the error that we see below.

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    Error:
-! object 'dplyr' not found
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    install.packages("dplyr")
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    Go ahead and click on “Run Cell” next to your code-block, to install the dplyr R package.

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    When a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system).

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    Within this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN.

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    If the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder.

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    The final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the “Done” line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder).

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    Attaching packages via library()

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    If an R package has been installed successfully, we are now able to load it (ie. make it’s functions available) to our local environment using the library() function.

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    Unlike install.packages(), where we needed “” around the package name, the library() function does not require “” around the package name. Let’s go ahead and load in dplyr, making its respective functions to our local environment.

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    From the output, we can see that dplyr has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages.

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    With dplyr now loaded via the library() call, let’s check sessionInfo() to see what has changed.

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    R version 4.5.2 (2025-10-31)
-Platform: x86_64-pc-linux-gnu
-Running under: Debian GNU/Linux 13 (trixie)
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-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
-
-locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
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-time zone: America/New_York
-tzcode source: system (glibc)
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-attached base packages:
-[1] stats     graphics  grDevices utils     datasets  methods   base     
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-other attached packages:
-[1] dplyr_1.2.0
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-loaded via a namespace (and not attached):
- [1] digest_0.6.39    R6_2.6.1         fastmap_1.2.0    tidyselect_1.2.1
- [5] xfun_0.56        magrittr_2.0.4   glue_1.8.0       tibble_3.3.1    
- [9] knitr_1.51       pkgconfig_2.0.3  htmltools_0.5.9  generics_0.1.4  
-[13] rmarkdown_2.30   lifecycle_1.0.5  cli_3.6.5        vctrs_0.7.1     
-[17] compiler_4.5.2   tools_4.5.2      evaluate_1.0.5   pillar_1.11.1   
-[21] yaml_2.3.12      otel_0.2.0       rlang_1.1.7      jsonlite_2.0.0
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    Similar to what was seen for the base R packages, dplyr is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the dplyr packages select() function and it’s respective help page.

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    Since its parent package has been attached to our local environment (via the library() call), we can see dplyr functions appear as suggestions as we begin to type.

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    By contrast, is we check for the ggplot() function from the ggplot2 package (which we haven’t yet installed or attached via library()), no suggestions will pop up.

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    Beyond individual functions, some R packages also have help landing pages, that can be similarly accessed by adding a ? in front of the package name:

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    Unattaching

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    So far, we have installed an R package, and then attached it (via library()). How would we reverse these steps?

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    Well, to unload it from the local environment, there are a couple options. You could of course simply shut down Positron. The local environment only exist in context of when you open and close the session, which closing the program will do. All previously loaded R packages will be unattached, which is why when you start a new session you will need to load in all packages you plan on using via library().

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    Alternatively, although less used, you could detach() it via your console:

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    R version 4.5.2 (2025-10-31)
-Platform: x86_64-pc-linux-gnu
-Running under: Debian GNU/Linux 13 (trixie)
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-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
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-locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
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-time zone: America/New_York
-tzcode source: system (glibc)
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-attached base packages:
-[1] stats     graphics  grDevices utils     datasets  methods   base     
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-loaded via a namespace (and not attached):
- [1] digest_0.6.39    R6_2.6.1         fastmap_1.2.0    tidyselect_1.2.1
- [5] xfun_0.56        magrittr_2.0.4   glue_1.8.0       tibble_3.3.1    
- [9] knitr_1.51       pkgconfig_2.0.3  htmltools_0.5.9  generics_0.1.4  
-[13] rmarkdown_2.30   lifecycle_1.0.5  cli_3.6.5        vctrs_0.7.1     
-[17] compiler_4.5.2   tools_4.5.2      evaluate_1.0.5   pillar_1.11.1   
-[21] yaml_2.3.12      otel_0.2.0       rlang_1.1.7      jsonlite_2.0.0
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    Looking at the sessionInfo() output, dplyr is no longer attached to the local environment. Consequently, if we try to once again look for the documentation, no information will be retrieved.

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    There is a workaround however, if we want to access functions from an unloaded R package. We can specify the R package’s name, followed by two :, and then the function name. The :: conveys the context to your computer that the package is present, but may not be attached.

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    This particular use case can be useful if we want to run a particular function, but not load in all a packages functions (which may have identical function names to other R packages we are using and cause some conflicts).

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    Removing Packages

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    Just as we can install an R package, we can also uninstall an R package (although doing so is rare, most often when encountering package dependency conflict). To do so, we would use the remove.packages() function.

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    This results in the package being removed entirely from our computer. We would then need to reinstall it if needed in the future.

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    Common Issues

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    As previously mentioned, CRAN is the main repository for R packages. But what if we tried to install an R package that is only found on Bioconductor or via GitHub using the install.packages() function?

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    To see what occurs, let’s try installing the PeacoQC package (which is found on Bioconductor).

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    As you can see, the initial warning message suggest that PeacoQC is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn’t figure out what was going on.

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    This is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN.

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    Installing from Bioconductor

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    Bioconductor is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this link you can find it’s current flow and mass cytometry R packages.

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    Bioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different standards for acceptance than CRAN. They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems.

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    To install an R package that is located on Bioconductor, we first need to install the BiocManager package from CRAN. This package will allow us to install Bioconductor packages from their respective repository.

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    Once BiocManager is installed, we can attach it to our local environment using the library() function

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    When loaded, you will see an output showing the current Bioconductor and R versions.

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    We can then use BiocManager’s install() function to go back and install PeacoQC().

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    Tip

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    We see a similar opening sequence of installation steps as what we saw when installing the dplyr package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation.

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    Note

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    Behind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process

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    Within the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with dplyr, with a “Done (packagename)” being printed upon successful installation.

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    This process continues for each dependency being installed.

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    And finally, once all the dependencies are installed, PeacoQC starts to install.

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    Occasionally, during installation, you will see a pop-up windown like this one in the console. This let’s you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n].

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    Alternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter.

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    Generally, it’s okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn’t cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option.

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    With PeacoQC has been installed, we can load it via the library() call

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    Remeber, library() doesn’t require ” ”

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    And we can check to see if it has been attached to the local environment

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    R version 4.5.2 (2025-10-31)
-Platform: x86_64-pc-linux-gnu
-Running under: Debian GNU/Linux 13 (trixie)
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-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
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-locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
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-tzcode source: system (glibc)
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-attached base packages:
-[1] stats     graphics  grDevices utils     datasets  methods   base     
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-other attached packages:
-[1] PeacoQC_1.20.0      BiocManager_1.30.27
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-loaded via a namespace (and not attached):
- [1] generics_0.1.4        shape_1.4.6.1         digest_0.6.39        
- [4] magrittr_2.0.4        evaluate_1.0.5        grid_4.5.2           
- [7] RColorBrewer_1.1-3    iterators_1.0.14      circlize_0.4.17      
-[10] fastmap_1.2.0         foreach_1.5.2         doParallel_1.0.17    
-[13] jsonlite_2.0.0        graph_1.88.1          GlobalOptions_0.1.3  
-[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1  scales_1.4.0         
-[19] XML_3.99-0.20         Rgraphviz_2.54.0      codetools_0.2-20     
-[22] cli_3.6.5             RProtoBufLib_2.22.0   rlang_1.1.7          
-[25] crayon_1.5.3          Biobase_2.70.0        yaml_2.3.12          
-[28] otel_0.2.0            cytolib_2.22.0        ncdfFlow_2.56.0      
-[31] tools_4.5.2           parallel_4.5.2        dplyr_1.2.0          
-[34] colorspace_2.1-2      ggplot2_4.0.2         GetoptLong_1.1.0     
-[37] BiocGenerics_0.56.0   vctrs_0.7.1           R6_2.6.1             
-[40] png_0.1-8             matrixStats_1.5.0     stats4_4.5.2         
-[43] lifecycle_1.0.5       flowCore_2.22.1       S4Vectors_0.48.0     
-[46] IRanges_2.44.0        clue_0.3-66           cluster_2.1.8.1      
-[49] pkgconfig_2.0.3       pillar_1.11.1         gtable_0.3.6         
-[52] data.table_1.18.2.1   glue_1.8.0            xfun_0.56            
-[55] tibble_3.3.1          tidyselect_1.2.1      knitr_1.51           
-[58] farver_2.1.2          rjson_0.2.23          htmltools_0.5.9      
-[61] rmarkdown_2.30        compiler_4.5.2        S7_0.2.1
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    As you may have noticed, the section of loaded via namespace (but not attached) packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment.

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    To see what packages are installed (but not yet loaded), we can use the installed.packages() function to return a list of R packages for your computer.

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    Install from GitHub

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    In addition to the CRAN and Bioconductor repositories, individual R packages can also be found on GitHub hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to CRAN or Bioconductor) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all.

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    While many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to deprecation since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it’s useful to check the commits and issues pages to see when the last contribution occurred. We will take a closer look at how to do so later on.

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    To install packages from GitHub, you will need the remotes package, which can be found on CRAN.

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    Spot Check #1

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    To install a package from CRAN, what function would you use? Click on the code-fold arrow below to reveal the answer.

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    With the remotes package now installed, we can attach it to our local environment.

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    Spot Check #2

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    What function would be used to do so?

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    And finally, we can use the install_github() function to download R packages from the invidual developers GitHub account.

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    Spot Check #3

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    How would you look up the help documentation for this function?

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    # Either by hovering over it within Positron or via
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    We will be installing a small R package flowSpectrum for this example. It’s one of the packages created by Christopher Hall, whose small series of Flow Cytometry Data Analysis in R tutorials were immensely useful when I was first getting started learning R. flowSpectrum can be used to generate spectrum-style plots for spectral flow cytometry data.

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    To install an R package from GitHub, we first need the GitHub username (so hally166 in this case), which is followed by a “/”, and then the name of the package repository (so flowSpectrum in this case). Our code should consequently be

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    When installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding.

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    This process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating R packages.

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    Troubleshooting Install Errors

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    We have now installed three R packages, dplyr, PeacoQC, and flowSpectrum. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies.

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    When encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below.

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    If you encounter an installation error this week, please take screenshots of the error message and post them to this Discussion. This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future.

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    Installing Specific-Package Versions

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    While we may be tempted to think of R packages as static, they change quite often, as their develipers add new features, fix bugs, etc. To help keep track of these changes (essential for reproducibility and replicability), R packages have version numbers.

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    When we run sessionInfo(), we can see an example of this, with the version number appearing after the package name.

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    R version 4.5.2 (2025-10-31)
-Platform: x86_64-pc-linux-gnu
-Running under: Debian GNU/Linux 13 (trixie)
-
-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
-
-locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
-
-time zone: America/New_York
-tzcode source: system (glibc)
-
-attached base packages:
-[1] stats     graphics  grDevices utils     datasets  methods   base     
-
-other attached packages:
-[1] PeacoQC_1.20.0      BiocManager_1.30.27
-
-loaded via a namespace (and not attached):
- [1] generics_0.1.4        shape_1.4.6.1         digest_0.6.39        
- [4] magrittr_2.0.4        evaluate_1.0.5        grid_4.5.2           
- [7] RColorBrewer_1.1-3    iterators_1.0.14      circlize_0.4.17      
-[10] fastmap_1.2.0         foreach_1.5.2         doParallel_1.0.17    
-[13] jsonlite_2.0.0        graph_1.88.1          GlobalOptions_0.1.3  
-[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1  scales_1.4.0         
-[19] XML_3.99-0.20         Rgraphviz_2.54.0      codetools_0.2-20     
-[22] cli_3.6.5             RProtoBufLib_2.22.0   rlang_1.1.7          
-[25] crayon_1.5.3          Biobase_2.70.0        yaml_2.3.12          
-[28] otel_0.2.0            cytolib_2.22.0        ncdfFlow_2.56.0      
-[31] tools_4.5.2           parallel_4.5.2        dplyr_1.2.0          
-[34] colorspace_2.1-2      ggplot2_4.0.2         GetoptLong_1.1.0     
-[37] BiocGenerics_0.56.0   vctrs_0.7.1           R6_2.6.1             
-[40] png_0.1-8             matrixStats_1.5.0     stats4_4.5.2         
-[43] lifecycle_1.0.5       flowCore_2.22.1       S4Vectors_0.48.0     
-[46] IRanges_2.44.0        clue_0.3-66           cluster_2.1.8.1      
-[49] pkgconfig_2.0.3       pillar_1.11.1         gtable_0.3.6         
-[52] data.table_1.18.2.1   glue_1.8.0            xfun_0.56            
-[55] tibble_3.3.1          tidyselect_1.2.1      knitr_1.51           
-[58] farver_2.1.2          rjson_0.2.23          htmltools_0.5.9      
-[61] rmarkdown_2.30        compiler_4.5.2        S7_0.2.1
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    Alternatively, we can retrieve the same information for the individual packages via the packageVersion() function

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    As well as from the citation() function.

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    citation("PeacoQC")
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    To cite package 'PeacoQC' in publications use:
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-  Emmaneel A (2025). _PeacoQC: Peak-based selection of high quality
-  cytometry data_. doi:10.18129/B9.bioc.PeacoQC
-  <https://doi.org/10.18129/B9.bioc.PeacoQC>, R package version 1.20.0,
-  <https://bioconductor.org/packages/PeacoQC>.
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-A BibTeX entry for LaTeX users is
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-  @Manual{,
-    title = {PeacoQC: Peak-based selection of high quality cytometry data},
-    author = {Annelies Emmaneel},
-    year = {2025},
-    note = {R package version 1.20.0},
-    url = {https://bioconductor.org/packages/PeacoQC},
-    doi = {10.18129/B9.bioc.PeacoQC},
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    How does a version number work? Lets say we have the following version number: 1.20.0

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    The first number of the version (1. in this case) denotes major changes, primarily those where after the version change the package may not be compatible with the code used in the prior version. As a consequence, this number changes rarely.

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    The second number (.20. in this case) is the minor version. Minor changes typically consist of new features that are added, that don’t affect the overall package function. These will change more frequently, especially for Bioconductor packages with fixed release cycles.

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    The final number (.0 in this case) is often used to denote small changes occuring within a minor release period, often bug-fixes or fixing typos within the documentation.

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    We may in the future need to install specific package versions (but wont be doing so today). As expected, which repository contains the R package influences how we would go about doing this.

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    For CRAN packages, we can use the remotes packages install_version() function. This allows us to provide the version number, and designate the repository location (the CRAN url in this case).

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    For GitHub-based R packages, the package versioning schema is not as strict as that of CRAN or Bioconductor. Typically, changes in R packagaes are put out by their developers as releases. When trying to install a particular release, we can add an additional argument to the install_github() function, specifying the release version’s tag number. For example:

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    Alternatively, if the developer doesn’t implement releases, you can provide the hash number of a particular commit.

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    Documentation and Websites

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    We have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package.

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    For CRAN-based packages, we can start off by searching for the package name. So, in the case of dplyr

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    Two main suggestions pop up. One is the package’s CRAN page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible.

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    Because of this, many CRAN-based R packages (especially those part of the tidyverse) use pkgdown-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr’s pkgdown-style website

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    We can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab.

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    GitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository’s ReadMe.

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    For Bioconductor-based packages, on the package’s page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with PeacoQC:

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    Additionally, package vignettes can also be reached via the packages help index page. These will usually appear under User guides, package vignettes, and other documentation.

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    Your Turn

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    Alright, we have now gone through the process of installing an R package from CRAN, Bioconductor, and GitHub. We will now install 20 other R packages we will need throughout the rest of the course.

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    Note

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    To make this interactive, I will task you to apply the previous concepts to figure out whether the packages need to be installed via CRAN, Bioconductor or GitHub.

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    Important

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    Feel free to view the website version to avoid accidental spoilers from the copied over index.qmd file. Alternatively, you can attempt to switch from the Source view to Visual Mode by right clicking with your mouse and selecting that option.

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    Tip

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    Start by searching each packages name. See if you can spot first either a CRAN or a Bioconductor website. Then enter the respective installation command (install.packages(), install(), install_github()) for the appropiate repository, add the package name, and run the code to see if the installation proceeds.

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    For cases where you are truly stuck, expand the code-fold below each package name to see the answer.

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    Note

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    Some of these packages may be dependencies of each other and may wind up installed before you get to them. If that is the case, no need to reinstall, count it as a win, and proceed to the next R package.

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    Remember,if you encountered any installation errors in the process, please take screenshots and post them on the the Discussion page to help with improved documentation.

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    R package: purrr

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    R package: flowCore

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    R package: flowWorkspace

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    R package: stringr

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    R package: ggplot2

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    R package: ggcyto

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    R package: openCyto

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    R package: FlowSOM

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    R package: saeyslab/CytoNorm

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    Congratulations! You have (hopefully) survived the package installation onslaught that is Week #1 of the course.

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    Remember to submit any encountered installation error screenshots to the Discussion page.

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    Wrap-Up

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    In this session, we walked through what are R packages, where to find them, how to install them, and a bit about troubleshooting any installation errors you may encounter during the process.

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    You then proceeded to install most of the R packages that you would need throughout the Cytometry in R course. These included tidyverse packages from the [CRAN] repository used for working with data structures and plots, as well as more cytometry focused R packages from [Bioconductor] repository.

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    If you have any questions, or want to discuss this week’s topics in more depth with the other course participants, please head over to the Discussion page and open a new topic.

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    Next week, we will start learning about file paths, by which we will be able to tell our computer where to find your fcs files, how to retrieve the file names, subset those that may be of particular interest, and copy them over to a new folder. In the processs, we will learn a little more about how variables, objects, and list work within R.

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    Until then, Best Wishes!

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    Additional Resources

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    Tidy Tales An usefu beginner-friendly blogpost covering additional aspects from a different perspective.

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    Introduction to Bioconductor A talk by Martin Morgan with more information about the Bioconductor project.

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    R Packages A book by Hadley Wickham and Jennifer Bryan, covering all the different internals of R packages.

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    Take-home Problems

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    Below you will find the optional take-home problems for Week #1. Learning how to code well requires continous practice, and that involves cycles of trying something, failing, and troubleshooting to get it working. The goal of these problems is to help you explore the topic in greater depth than the currated boundaries of this one lecture.

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    You are more than welcome to open a Discussion to engage with others in the course to discuss these questions. Once you are done tinkering, and want to get final instructor feedback on your work, place your files within a folder, and follow the instructions to submit it as a Pull Request to the Cytometry In R repositories homework branch.

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    Problem 1

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    We installed PeacoQC during this session, but we didn’t have time to explore what functions are present within the package. Using what you have learned about accessing documentation, figure out and list what functions it contains

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    Problem 2

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    Take a closer look at the list of Bioconductor cytometry packages. Report back on how many there are currently in Bioconductor, the author/maintainer with the most contributed cytometry R packages, and a couple packages that you would be interested in exploring more in-depth later in the course.

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    Problem 3

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    There is another way to install R packages, using the newer pak package. Positron uses this when installing suggested dependencies.

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    After learning more about it via the documentation and it’s pkgdown website, I would like you to attempt to install the following three R packages using this newer method: “broom”, “cytoMEM”, “DillonHammill/CytoExploreR”.

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    Take screenshots, and in a new quarto markdown document, describe how the installation process differed from what you saw for install.packages(), install() and install_github().

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    AGPL-3.0 CC BY-SA 4.0

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    - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + Cytometry in R – 01 - Installing R Packages + + + + + + + + + + + + + + + + + +
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    01 - Installing R Packages

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    +David Rach +
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    2026-02-01

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    Welcome to the first week of Cytometry in R! This week we will be diving into how R packages work, and the how to go about installing them.

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    Important

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    Before getting started, please make sure you have completed the creating a GitHub and Workstation Setup walk-throughs, since we will begin where they left off once the required software was successfully installed.

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    Important

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    Please make sure to sync your forked version of the CytometryInR repository, and pull any changes to your local computer’s CytometryInR project folder so that you have the most recent version of the code and data available.

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    Background

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    During Workstation Setup, you installed the R software to your local computer. R as a programming language that started up in the 1990s. While its original focus was on statistics, it is now widely used in various fields thanks to contributions of many open-source developers over the years.

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    This expanded reach is in part due to the ability to create R packages, that encapsulate additional functions, that can do new things beyond what the original software (ie. base R) was capable of doing.

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    Currently, there are thousands of R packages available. Furthermore, there is a vibrant community of individuals that help maintain and document how to use these packages, which has helped sustain and grow the R ecosystem over the last couple decades.

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    Regardless if you are working with flow cytometry, or in ecology, or in econometrics, or political science, a lot of the analysis and visualizations that you see in publications often involve R.

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    Tip

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    R packages can also just be made for fun! Among my favorite examples of this, there is an R package that lets you add the snake game to your recalculating screen, as well as R packages that provide the color-palette schemes needed to make your plots with Studio Ghibli, Wes Anderson, or Bluey colors.

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    These R packages start off as source code (which is what we will be learning to write during this course). When you install a R package to your computer, this human-readable source code gets converted into a binary format with which your computer can interact directly.

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    Expanding on this concept, a new R package can be made up of new code (primarily in the form of tools (ie. functions) that do a particular useful things) that is entirely self-contained, or reuse functions present in existing R packages to help make something new. When an R package relies on a function from another R package, it needs the other R package to be installed in order for everything to work properly. This is known as a package dependency.

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    To make distributing the thousands of R packages and their associated package dependencies easier, R packages are collected (ie. hosted) within repositories, which function as an intermediate distributor.

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    The three main locations for R packages from are CRAN (containing 23069 packages), Bioconductor (containing 2361 packages), and individual R packages hosted by their developers via GitHub.

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    The process of installing R packages will vary a bit depending on which repository the respective R package is in. For beginners, this often prooves to be a pain-point, as they will attempt to install an R package using one set of installation commands, only to get an error (because the R package is not in that repository).

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    In this session, we will work on installing the various R packages we will need through the course. While doing so, we will explore how to figure out which repository the individual package is in; what installation commands to use to download it; and how to look up the help documentation. We will also touch on how the functions within an R package are made available for our computer to use (via the library() call), and how to troubleshoot the more commonly encountered installation errors.

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    Getting Started

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    Set Up

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    Alright, with the background out of the way, let’s get started!

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    Important

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    Please make sure to sync your forked version of the CytometryInR repository, and pull any changes to your local computer’s CytometryInR project folder so that you have the most recent version of the code and data available.

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    Warning

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    Please remember to always copy over the new material from your local CytometryInR folder to a separate Project Folder that you created and named (ex. “Week_01” or “MyLearningFolder”, etc.). This will ensure any edits you make to the files do not affect your ability to bring in next week’s materials to the CytometryInR folder

    +
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    + +
    +

    Warning

    +
    +
    +

    After pulling the new data and code locally, open CytometryInR, open the course folder, and open the 01_InstallingRPackages folder. From here, copy the index.qmd file to your own working Project Folder (ex. Week_01) where you can work on it without causing any conflicts. Then return to Positron and open up your working project folder (ex. Week_01).

    +
    +
    +
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    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Next up, within Positron, let’s make sure to select R as the coding language being used for this session.

    +
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    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Now that R is running within Positron, the console (lower portion of the screenn) is now able to run (ie. execute) any R code that is sent to it.

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    +

    Checking for Loaded Packages

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    For the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active.

    +
    +
    +
    +
    +
    +
    +
    + +

    Accessing Help Documentation

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Within your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following sessionInfo() function

    +
    +
    +
    +
    +
    +
    +
    +
    sessionInfo()
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    If you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over.

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    In this case, we can see the help documentation corresponding for sessionInfo(). Beyond hovering over the function, this can also be accessed by adding a ? directly in front of the function, and then running that line of code.

    +
    +
    +
    +
    +
    +
    +
    +
    ?sessionInfo()
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    When executed, the function’s help file documentation will open up within the Help tab in the secondary side bar on the right-side of the screen. Glancing at the top of the page we can see the name of the package that contains the sessionInfo() function ({utils}). Scrolling down the help page past all the documentation, we can see a link to the index page.

    +
    +
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    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    After clicking, the Help tab switches from viewing the documentation for the sessionInfo() function, to showing all the functions within the utils package. Most R packages contain help documentation, so this process can be adapted to find out additional information about what a function does, and what arguments are needed to produce customized outputs.

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +

    sessionInfo()

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Within your .qmd file, let’s go ahead and run the following code-block:

    +
    +
    +
    +
    +
    +
    +
    +
    sessionInfo()
    +
    +
    R version 4.5.2 (2025-10-31)
+Platform: x86_64-pc-linux-gnu
+Running under: Debian GNU/Linux 13 (trixie)
+
+Matrix products: default
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
+
+locale:
+ [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
+ [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
+ [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
+ [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [9] LC_ADDRESS=C               LC_TELEPHONE=C            
+[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
+
+time zone: America/New_York
+tzcode source: system (glibc)
+
+attached base packages:
+[1] stats     graphics  grDevices utils     datasets  methods   base     
+
+loaded via a namespace (and not attached):
+ [1] compiler_4.5.2  fastmap_1.2.0   cli_3.6.5       tools_4.5.2    
+ [5] htmltools_0.5.9 otel_0.2.0      yaml_2.3.12     rmarkdown_2.30 
+ [9] knitr_1.51      jsonlite_2.0.0  xfun_0.56       digest_0.6.39  
+[13] rlang_1.1.7     evaluate_1.0.5
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    The outputs that get returned by sessionInfo() will vary a bit depending on your computer’s operating system, and the version of R you have installed.

    +

    For today, let’s focus on the last two elements of the output:

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    The R software itself is made up of several base R packages, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages.

    +

    As we install additional R packages and load them using the library() function throughout this session, sporadically re-run sessionInfo() to see how this list of R packages changes.

    +
    +
    +
    +
    +
    +
    +
    +

    Installing from CRAN

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    We will start by installing R packages that are part of the CRAN repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository.

    +

    These include the tidyverse packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today.

    +
    +
    +
    +
    +
    +
    +
    + +

    dplyr

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Our first R package we will install during this session is the dplyr package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function install.packages().

    +
    +
    +
    +
    +
    +
    +
    +
    ?install.packages()
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    For the install.packages() function, we place within the () the name of the R package from CRAN that we wish to install.

    +
    +
    +
    +
    +
    +
    +
    +
    install.packages("dplyr")
    +
    +
    +
    +
    + +
    +
    +
    +
    + +
    +

    Tip

    +
    +
    +

    A usual struggle point for beginners is that install.packages() requires ” ” to be placed around the package name. Forgetting them results in the error that we see below.

    +
    +
    +
    +
    +
    +
    install.packages(dplyr)
    +
    +
    Error:
+! object 'dplyr' not found
    +
    +
    +
    +
    +
    + +
    +
    +
    install.packages("dplyr")
    +
    +
    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Go ahead and click on “Run Cell” next to your code-block, to install the dplyr R package.

    +
    +
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    When a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system).

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Within this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN.

    +

    If the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder.

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    The final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the “Done” line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder).

    +
    +
    +
    +
    +
    +
    +
    + +

    Attaching packages via library()

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    If an R package has been installed successfully, we are now able to load it (ie. make it’s functions available) to our local environment using the library() function.

    +
    +
    +
    +
    +
    +
    +
    +
    ?library()
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Unlike install.packages(), where we needed “” around the package name, the library() function does not require “” around the package name. Let’s go ahead and load in dplyr, making its respective functions to our local environment.

    +
    +
    +
    +
    +
    +
    +
    +
    library(dplyr)
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    From the output, we can see that dplyr has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages.

    +

    With dplyr now loaded via the library() call, let’s check sessionInfo() to see what has changed.

    +
    +
    +
    +
    +
    +
    +
    +
    sessionInfo()
    +
    +
    R version 4.5.2 (2025-10-31)
+Platform: x86_64-pc-linux-gnu
+Running under: Debian GNU/Linux 13 (trixie)
+
+Matrix products: default
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
+
+locale:
+ [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
+ [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
+ [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
+ [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [9] LC_ADDRESS=C               LC_TELEPHONE=C            
+[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
+
+time zone: America/New_York
+tzcode source: system (glibc)
+
+attached base packages:
+[1] stats     graphics  grDevices utils     datasets  methods   base     
+
+other attached packages:
+[1] dplyr_1.2.0
+
+loaded via a namespace (and not attached):
+ [1] digest_0.6.39    R6_2.6.1         fastmap_1.2.0    tidyselect_1.2.1
+ [5] xfun_0.56        magrittr_2.0.4   glue_1.8.0       tibble_3.3.1    
+ [9] knitr_1.51       pkgconfig_2.0.3  htmltools_0.5.9  generics_0.1.4  
+[13] rmarkdown_2.30   lifecycle_1.0.5  cli_3.6.5        vctrs_0.7.1     
+[17] compiler_4.5.2   tools_4.5.2      evaluate_1.0.5   pillar_1.11.1   
+[21] yaml_2.3.12      otel_0.2.0       rlang_1.1.7      jsonlite_2.0.0
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Similar to what was seen for the base R packages, dplyr is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the dplyr packages select() function and it’s respective help page.

    +
    +
    +
    +
    +
    +
    +
    +
    ?select
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Since its parent package has been attached to our local environment (via the library() call), we can see dplyr functions appear as suggestions as we begin to type.

    +

    By contrast, is we check for the ggplot() function from the ggplot2 package (which we haven’t yet installed or attached via library()), no suggestions will pop up.

    +
    +
    +
    +
    +
    +
    +
    + +
    +
    +
    ?ggplot
    +
    +
    No documentation for 'ggplot' in specified packages and libraries:
+you could try '??ggplot'
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Beyond individual functions, some R packages also have help landing pages, that can be similarly accessed by adding a ? in front of the package name:

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +

    Unattaching

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    So far, we have installed an R package, and then attached it (via library()). How would we reverse these steps?

    +

    Well, to unload it from the local environment, there are a couple options. You could of course simply shut down Positron. The local environment only exist in context of when you open and close the session, which closing the program will do. All previously loaded R packages will be unattached, which is why when you start a new session you will need to load in all packages you plan on using via library().

    +

    Alternatively, although less used, you could detach() it via your console:

    +
    +
    +
    +
    +
    +
    +
    +
    detach("package:dplyr", unload=TRUE)
    +
    +
    +
    +
    +
    sessionInfo()
    +
    +
    R version 4.5.2 (2025-10-31)
+Platform: x86_64-pc-linux-gnu
+Running under: Debian GNU/Linux 13 (trixie)
+
+Matrix products: default
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
+
+locale:
+ [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
+ [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
+ [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
+ [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [9] LC_ADDRESS=C               LC_TELEPHONE=C            
+[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
+
+time zone: America/New_York
+tzcode source: system (glibc)
+
+attached base packages:
+[1] stats     graphics  grDevices utils     datasets  methods   base     
+
+loaded via a namespace (and not attached):
+ [1] digest_0.6.39    R6_2.6.1         fastmap_1.2.0    tidyselect_1.2.1
+ [5] xfun_0.56        magrittr_2.0.4   glue_1.8.0       tibble_3.3.1    
+ [9] knitr_1.51       pkgconfig_2.0.3  htmltools_0.5.9  generics_0.1.4  
+[13] rmarkdown_2.30   lifecycle_1.0.5  cli_3.6.5        vctrs_0.7.1     
+[17] compiler_4.5.2   tools_4.5.2      evaluate_1.0.5   pillar_1.11.1   
+[21] yaml_2.3.12      otel_0.2.0       rlang_1.1.7      jsonlite_2.0.0
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Looking at the sessionInfo() output, dplyr is no longer attached to the local environment. Consequently, if we try to once again look for the documentation, no information will be retrieved.

    +
    +
    +
    +
    +
    +
    +
    +
    ?dplyr
    +
    +
    No documentation for 'dplyr' in specified packages and libraries:
+you could try '??dplyr'
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    There is a workaround however, if we want to access functions from an unloaded R package. We can specify the R package’s name, followed by two :, and then the function name. The :: conveys the context to your computer that the package is present, but may not be attached.

    +
    +
    +
    +
    +
    +
    +
    +
    ?dplyr::select()
    +
    +
    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    This particular use case can be useful if we want to run a particular function, but not load in all a packages functions (which may have identical function names to other R packages we are using and cause some conflicts).

    +
    +
    +
    +
    +
    +
    +
    + +

    Removing Packages

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Just as we can install an R package, we can also uninstall an R package (although doing so is rare, most often when encountering package dependency conflict). To do so, we would use the remove.packages() function.

    +
    +
    +
    +
    +
    +
    +
    +
    ?remove.packages()
    +
    +
    +
    +
    +
    remove.packages("dplyr")
    +
    +
    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    This results in the package being removed entirely from our computer. We would then need to reinstall it if needed in the future.

    +
    +
    +
    +
    +
    +
    +
    + +

    Common Issues

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    As previously mentioned, CRAN is the main repository for R packages. But what if we tried to install an R package that is only found on Bioconductor or via GitHub using the install.packages() function?

    +

    To see what occurs, let’s try installing the PeacoQC package (which is found on Bioconductor).

    +
    +
    +
    +
    +
    +
    +
    +
    install.packages("PeacoQC")
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    As you can see, the initial warning message suggest that PeacoQC is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn’t figure out what was going on.

    +

    This is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN.

    +
    +
    +
    +
    +
    +
    +
    +

    Installing from Bioconductor

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Bioconductor is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this link you can find it’s current flow and mass cytometry R packages.

    +

    Bioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different standards for acceptance than CRAN. They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems.

    +
    +
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    To install an R package that is located on Bioconductor, we first need to install the BiocManager package from CRAN. This package will allow us to install Bioconductor packages from their respective repository.

    +
    +
    +
    +
    +
    +
    +
    +
    install.packages("BiocManager")
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Once BiocManager is installed, we can attach it to our local environment using the library() function

    +
    +
    +
    +
    +
    +
    +
    +
    library(BiocManager)
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    When loaded, you will see an output showing the current Bioconductor and R versions.

    +

    We can then use BiocManager’s install() function to go back and install PeacoQC().

    +
    +
    +
    +
    +
    +
    +
    +
    +
    + +
    +

    Tip

    +
    +
    +

    As always, don’t forget the “” when running an install() command.

    +
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    +
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    +
    ?install()
    +
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    install("PeacoQC")
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    We see a similar opening sequence of installation steps as what we saw when installing the dplyr package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation.

    +
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    +
    +
    +
    + +
    +

    Note

    +
    +
    +

    Behind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process

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    + + +
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    + +
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    +
    + +
    +

    .

    +
    +
    +

    Within the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with dplyr, with a “Done (packagename)” being printed upon successful installation.

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    + + +
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    +

    .

    +
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    +

    This process continues for each dependency being installed.

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    + + +
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    + +
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    + +
    +

    .

    +
    +
    +

    And finally, once all the dependencies are installed, PeacoQC starts to install.

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    + + +
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    + +
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    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Occasionally, during installation, you will see a pop-up windown like this one in the console. This let’s you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n].

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    + +
    +

    .

    +
    +
    +

    Alternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter.

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    .

    +
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    +

    Generally, it’s okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn’t cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option.

    +
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    +

    .

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    +

    With PeacoQC has been installed, we can load it via the library() call

    +
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    +
    +
    +
    +
    + +
    +

    Tip

    +
    +
    +

    Remeber, library() doesn’t require ” ”

    +
    +
    +
    +
    +
    +
    library(PeacoQC)
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    And we can check to see if it has been attached to the local environment

    +
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    +
    +
    +
    +
    +
    sessionInfo()
    +
    +
    R version 4.5.2 (2025-10-31)
+Platform: x86_64-pc-linux-gnu
+Running under: Debian GNU/Linux 13 (trixie)
+
+Matrix products: default
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
+
+locale:
+ [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
+ [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
+ [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
+ [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [9] LC_ADDRESS=C               LC_TELEPHONE=C            
+[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
+
+time zone: America/New_York
+tzcode source: system (glibc)
+
+attached base packages:
+[1] stats     graphics  grDevices utils     datasets  methods   base     
+
+other attached packages:
+[1] PeacoQC_1.20.0      BiocManager_1.30.27
+
+loaded via a namespace (and not attached):
+ [1] generics_0.1.4        shape_1.4.6.1         digest_0.6.39        
+ [4] magrittr_2.0.4        evaluate_1.0.5        grid_4.5.2           
+ [7] RColorBrewer_1.1-3    iterators_1.0.14      circlize_0.4.17      
+[10] fastmap_1.2.0         foreach_1.5.2         doParallel_1.0.17    
+[13] jsonlite_2.0.0        graph_1.88.1          GlobalOptions_0.1.3  
+[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1  scales_1.4.0         
+[19] XML_3.99-0.20         Rgraphviz_2.54.0      codetools_0.2-20     
+[22] cli_3.6.5             RProtoBufLib_2.22.0   rlang_1.1.7          
+[25] crayon_1.5.3          Biobase_2.70.0        yaml_2.3.12          
+[28] otel_0.2.0            cytolib_2.22.0        ncdfFlow_2.56.0      
+[31] tools_4.5.2           parallel_4.5.2        dplyr_1.2.0          
+[34] colorspace_2.1-2      ggplot2_4.0.2         GetoptLong_1.1.0     
+[37] BiocGenerics_0.56.0   vctrs_0.7.1           R6_2.6.1             
+[40] png_0.1-8             matrixStats_1.5.0     stats4_4.5.2         
+[43] lifecycle_1.0.5       flowCore_2.22.1       S4Vectors_0.48.0     
+[46] IRanges_2.44.0        clue_0.3-66           cluster_2.1.8.1      
+[49] pkgconfig_2.0.3       pillar_1.11.1         gtable_0.3.6         
+[52] data.table_1.18.2.1   glue_1.8.0            xfun_0.56            
+[55] tibble_3.3.1          tidyselect_1.2.1      knitr_1.51           
+[58] farver_2.1.2          rjson_0.2.23          htmltools_0.5.9      
+[61] rmarkdown_2.30        compiler_4.5.2        S7_0.2.1
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    As you may have noticed, the section of loaded via namespace (but not attached) packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment.

    +
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    + + +
    +
    + +
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    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    To see what packages are installed (but not yet loaded), we can use the installed.packages() function to return a list of R packages for your computer.

    +
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    +
    +
    +
    +
    +
    +
    installed.packages()
    +
    +
    +
    +
    +

    Install from GitHub

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    In addition to the CRAN and Bioconductor repositories, individual R packages can also be found on GitHub hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to CRAN or Bioconductor) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all.

    +
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    + +
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    +
    + +
    +

    .

    +
    +
    +

    While many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to deprecation since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it’s useful to check the commits and issues pages to see when the last contribution occurred. We will take a closer look at how to do so later on.

    +
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    + +
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    +
    +
    + +
    +

    .

    +
    +
    +

    To install packages from GitHub, you will need the remotes package, which can be found on CRAN.

    +
    +
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    +
    +
    +
    +
    +
    +
    +
    +
    + +
    +

    Spot Check #1

    +
    +
    +

    To install a package from CRAN, what function would you use? Click on the code-fold arrow below to reveal the answer.

    +
    +
    +
    +
    +
    +
    +
    +
    +Code +
    install.packages("remotes")
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    With the remotes package now installed, we can attach it to our local environment.

    +
    +
    +
    +
    +
    +
    +
    +
    +
    +
    +
    + +
    +

    Spot Check #2

    +
    +
    +

    What function would be used to do so?

    +
    +
    +
    +
    +
    +
    +
    +
    +Code +
    library(remotes)
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    And finally, we can use the install_github() function to download R packages from the invidual developers GitHub account.

    +
    +
    +
    +
    +
    +
    +
    +
    +
    +
    +
    + +
    +

    Spot Check #3

    +
    +
    +

    How would you look up the help documentation for this function?

    +
    +
    +
    +
    +
    +
    +
    +
    +Code +
    # Either by hovering over it within Positron or via
+
+?install_github()
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    We will be installing a small R package flowSpectrum for this example. It’s one of the packages created by Christopher Hall, whose small series of Flow Cytometry Data Analysis in R tutorials were immensely useful when I was first getting started learning R. flowSpectrum can be used to generate spectrum-style plots for spectral flow cytometry data.

    +
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    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    To install an R package from GitHub, we first need the GitHub username (so hally166 in this case), which is followed by a “/”, and then the name of the package repository (so flowSpectrum in this case). Our code should consequently be

    +
    +
    +
    +
    +
    +
    +
    +
    install_github("hally166/flowSpectrum")
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    When installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding.

    +

    This process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating R packages.

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    +

    Troubleshooting Install Errors

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    We have now installed three R packages, dplyr, PeacoQC, and flowSpectrum. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies.

    +

    When encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below.

    +
    +
    +
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    +
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    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    If you encounter an installation error this week, please take screenshots of the error message and post them to this Discussion. This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future.

    +
    +
    +
    +
    +
    +
    +
    +

    Installing Specific-Package Versions

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    While we may be tempted to think of R packages as static, they change quite often, as their develipers add new features, fix bugs, etc. To help keep track of these changes (essential for reproducibility and replicability), R packages have version numbers.

    +

    When we run sessionInfo(), we can see an example of this, with the version number appearing after the package name.

    +
    +
    +
    +
    +
    +
    +
    +
    sessionInfo()
    +
    +
    R version 4.5.2 (2025-10-31)
+Platform: x86_64-pc-linux-gnu
+Running under: Debian GNU/Linux 13 (trixie)
+
+Matrix products: default
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
+
+locale:
+ [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
+ [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
+ [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
+ [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [9] LC_ADDRESS=C               LC_TELEPHONE=C            
+[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
+
+time zone: America/New_York
+tzcode source: system (glibc)
+
+attached base packages:
+[1] stats     graphics  grDevices utils     datasets  methods   base     
+
+other attached packages:
+[1] PeacoQC_1.20.0      BiocManager_1.30.27
+
+loaded via a namespace (and not attached):
+ [1] generics_0.1.4        shape_1.4.6.1         digest_0.6.39        
+ [4] magrittr_2.0.4        evaluate_1.0.5        grid_4.5.2           
+ [7] RColorBrewer_1.1-3    iterators_1.0.14      circlize_0.4.17      
+[10] fastmap_1.2.0         foreach_1.5.2         doParallel_1.0.17    
+[13] jsonlite_2.0.0        graph_1.88.1          GlobalOptions_0.1.3  
+[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1  scales_1.4.0         
+[19] XML_3.99-0.20         Rgraphviz_2.54.0      codetools_0.2-20     
+[22] cli_3.6.5             RProtoBufLib_2.22.0   rlang_1.1.7          
+[25] crayon_1.5.3          Biobase_2.70.0        yaml_2.3.12          
+[28] otel_0.2.0            cytolib_2.22.0        ncdfFlow_2.56.0      
+[31] tools_4.5.2           parallel_4.5.2        dplyr_1.2.0          
+[34] colorspace_2.1-2      ggplot2_4.0.2         GetoptLong_1.1.0     
+[37] BiocGenerics_0.56.0   vctrs_0.7.1           R6_2.6.1             
+[40] png_0.1-8             matrixStats_1.5.0     stats4_4.5.2         
+[43] lifecycle_1.0.5       flowCore_2.22.1       S4Vectors_0.48.0     
+[46] IRanges_2.44.0        clue_0.3-66           cluster_2.1.8.1      
+[49] pkgconfig_2.0.3       pillar_1.11.1         gtable_0.3.6         
+[52] data.table_1.18.2.1   glue_1.8.0            xfun_0.56            
+[55] tibble_3.3.1          tidyselect_1.2.1      knitr_1.51           
+[58] farver_2.1.2          rjson_0.2.23          htmltools_0.5.9      
+[61] rmarkdown_2.30        compiler_4.5.2        S7_0.2.1
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Alternatively, we can retrieve the same information for the individual packages via the packageVersion() function

    +
    +
    +
    +
    +
    +
    +
    +
    packageVersion("PeacoQC")
    +
    +
    [1] '1.20.0'
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    As well as from the citation() function.

    +
    +
    +
    +
    +
    +
    +
    +
    citation("PeacoQC")
    +
    +
    To cite package 'PeacoQC' in publications use:
+
+  Emmaneel A (2025). _PeacoQC: Peak-based selection of high quality
+  cytometry data_. doi:10.18129/B9.bioc.PeacoQC
+  <https://doi.org/10.18129/B9.bioc.PeacoQC>, R package version 1.20.0,
+  <https://bioconductor.org/packages/PeacoQC>.
+
+A BibTeX entry for LaTeX users is
+
+  @Manual{,
+    title = {PeacoQC: Peak-based selection of high quality cytometry data},
+    author = {Annelies Emmaneel},
+    year = {2025},
+    note = {R package version 1.20.0},
+    url = {https://bioconductor.org/packages/PeacoQC},
+    doi = {10.18129/B9.bioc.PeacoQC},
+  }
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    How does a version number work? Lets say we have the following version number: 1.20.0

    +

    The first number of the version (1. in this case) denotes major changes, primarily those where after the version change the package may not be compatible with the code used in the prior version. As a consequence, this number changes rarely.

    +

    The second number (.20. in this case) is the minor version. Minor changes typically consist of new features that are added, that don’t affect the overall package function. These will change more frequently, especially for Bioconductor packages with fixed release cycles.

    +

    The final number (.0 in this case) is often used to denote small changes occuring within a minor release period, often bug-fixes or fixing typos within the documentation.

    +
    +
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    +
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    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    We may in the future need to install specific package versions (but wont be doing so today). As expected, which repository contains the R package influences how we would go about doing this.

    +

    For CRAN packages, we can use the remotes packages install_version() function. This allows us to provide the version number, and designate the repository location (the CRAN url in this case).

    +
    +
    +
    +
    +
    +
    +
    +
    remotes::install_version("ggplot2", version = "3.5.2", repos = "https://cloud.r-project.org")
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    For GitHub-based R packages, the package versioning schema is not as strict as that of CRAN or Bioconductor. Typically, changes in R packagaes are put out by their developers as releases. When trying to install a particular release, we can add an additional argument to the install_github() function, specifying the release version’s tag number. For example:

    +
    +
    +
    +
    +
    +
    +
    +
    remotes::install_github("DavidRach/Luciernaga", ref = "v0.99.7")
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Alternatively, if the developer doesn’t implement releases, you can provide the hash number of a particular commit.

    +
    +
    +
    +
    +
    +
    +
    +
    remotes::install_github("DavidRach/Luciernaga", ref = "8d1d694")
    +
    +
    +
    +
    +

    Documentation and Websites

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    We have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package.

    +

    For CRAN-based packages, we can start off by searching for the package name. So, in the case of dplyr

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
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    +
    +
    + +
    +

    .

    +
    +
    +

    Two main suggestions pop up. One is the package’s CRAN page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible.

    +
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    + + +
    +
    + +
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    +
    + +
    +

    .

    +
    +
    +

    Because of this, many CRAN-based R packages (especially those part of the tidyverse) use pkgdown-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr’s pkgdown-style website

    +
    +
    +
    +
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    We can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab.

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    .

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    GitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository’s ReadMe.

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    .

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    For Bioconductor-based packages, on the package’s page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with PeacoQC:

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    .

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    Additionally, package vignettes can also be reached via the packages help index page. These will usually appear under User guides, package vignettes, and other documentation.

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    Your Turn

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    .

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    Alright, we have now gone through the process of installing an R package from CRAN, Bioconductor, and GitHub. We will now install 20 other R packages we will need throughout the rest of the course.

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    Note

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    To make this interactive, I will task you to apply the previous concepts to figure out whether the packages need to be installed via CRAN, Bioconductor or GitHub.

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    Important

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    Feel free to view the website version to avoid accidental spoilers from the copied over index.qmd file. Alternatively, you can attempt to switch from the Source view to Visual Mode by right clicking with your mouse and selecting that option.

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    Tip

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    Start by searching each packages name. See if you can spot first either a CRAN or a Bioconductor website. Then enter the respective installation command (install.packages(), install(), install_github()) for the appropiate repository, add the package name, and run the code to see if the installation proceeds.

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    For cases where you are truly stuck, expand the code-fold below each package name to see the answer.

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    Note

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    Some of these packages may be dependencies of each other and may wind up installed before you get to them. If that is the case, no need to reinstall, count it as a win, and proceed to the next R package.

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    .

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    Remember,if you encountered any installation errors in the process, please take screenshots and post them on the the Discussion page to help with improved documentation.

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    1/20

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    R package: purrr

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    +Code +
    # Location: CRAN
+# Website: https://purrr.tidyverse.org/
+
+install.packages("purrr")
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    2/20

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    R package: flowCore

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/flowCore.html
+
+install("flowCore")
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    3/20

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    R package: flowWorkspace

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/flowWorkspace.html
+
+install("flowWorkspace")
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    4/20

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    R package: stringr

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    +Code +
    # Location: CRAN
+# Website: https://stringr.tidyverse.org/
+
+install.packages("stringr")
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    5/20

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    R package: ggplot2

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    +Code +
    # Location: CRAN
+# Website: https://ggplot2.tidyverse.org/
+
+install.packages("ggplot2")
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    6/20

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    R package: ggcyto

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/ggcyto.html
+
+install("ggcyto")
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    7/20

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    R package: tidyr

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    +Code +
    # Location: CRAN
+# Website: https://tidyr.tidyverse.org/
+
+install.packages("tidyr")
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    8/20

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    R package: openCyto

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/openCyto.html
+
+install("openCyto")
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    9/20

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    R package: FlowSOM

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/FlowSOM.html
+
+install("FlowSOM")
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    10/20

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    R package: xml2

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    +Code +
    # Location: CRAN
+# Website: https://xml2.r-lib.org/
+
+install.packages("xml2")
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    11/20

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    R package: saeyslab/CytoNorm

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    +Code +
    # Location: GitHub
+# Website: https://github.com/saeyslab/CytoNorm
+
+install_github("saeyslab/CytoNorm")
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    12/20

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    R package: lubridate

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    +Code +
    # Location: CRAN
+# Website: https://lubridate.tidyverse.org/
+
+install.packages("lubridate")
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    13/20

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    R package: httr2

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    +Code +
    # Location: CRAN
+# Website: https://httr2.r-lib.org/
+
+install.packages("httr2")
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    14/20

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    R package: flowGate

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/flowGate.html
+
+install("flowGate")
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    15/20

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    R package: devtools

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    +Code +
    # Location: CRAN
+# Website: https://devtools.r-lib.org/
+
+install.packages("devtools")
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    16/20

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    R package: plotly

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    +Code +
    # Location: CRAN
+# Website: https://plotly.com/r/getting-started/
+
+install.packages("plotly")
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    17/20

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    +

    R package: biosurf/cyCombine

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    +Code +
    # Location: GitHub
+# Website: https://github.com/biosurf/cyCombine
+
+install_github("biosurf/cyCombine")
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    18/20

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    R package: CytoML

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/CytoML.html
+
+install("CytoML")
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    19/20

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    R package: Rtsne

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    +Code +
    # Location: CRAN
+# Website: https://github.com/jkrijthe/Rtsne
+
+install.packages("Rtsne")
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    20/20

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    R package: uwot

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    +Code +
    # Location: CRAN
+# Website:https://jlmelville.github.io/uwot/
+
+install.packages("uwot")
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    +

    .

    +
    +
    +

    Congratulations! You have (hopefully) survived the package installation onslaught that is Week #1 of the course.

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    .

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    Remember to submit any encountered installation error screenshots to the Discussion page.

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    Wrap-Up

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    .

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    In this session, we walked through what are R packages, where to find them, how to install them, and a bit about troubleshooting any installation errors you may encounter during the process.

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    You then proceeded to install most of the R packages that you would need throughout the Cytometry in R course. These included tidyverse packages from the [CRAN] repository used for working with data structures and plots, as well as more cytometry focused R packages from [Bioconductor] repository.

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    If you have any questions, or want to discuss this week’s topics in more depth with the other course participants, please head over to the Discussion page and open a new topic.

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    Next week, we will start learning about file paths, by which we will be able to tell our computer where to find your fcs files, how to retrieve the file names, subset those that may be of particular interest, and copy them over to a new folder. In the processs, we will learn a little more about how variables, objects, and list work within R.

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    Until then, Best Wishes!

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    • David
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    Additional Resources

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    .

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    Tidy Tales An usefu beginner-friendly blogpost covering additional aspects from a different perspective.

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    Introduction to Bioconductor A talk by Martin Morgan with more information about the Bioconductor project.

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    R Packages A book by Hadley Wickham and Jennifer Bryan, covering all the different internals of R packages.

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    Take-home Problems

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    Below you will find the optional take-home problems for Week #1. Learning how to code well requires continous practice, and that involves cycles of trying something, failing, and troubleshooting to get it working. The goal of these problems is to help you explore the topic in greater depth than the currated boundaries of this one lecture.

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    You are more than welcome to open a Discussion to engage with others in the course to discuss these questions. Once you are done tinkering, and want to get final instructor feedback on your work, place your files within a folder, and follow the instructions to submit it as a Pull Request to the Cytometry In R repositories homework branch.

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    Problem 1

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    We installed PeacoQC during this session, but we didn’t have time to explore what functions are present within the package. Using what you have learned about accessing documentation, figure out and list what functions it contains

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    Problem 2

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    Take a closer look at the list of Bioconductor cytometry packages. Report back on how many there are currently in Bioconductor, the author/maintainer with the most contributed cytometry R packages, and a couple packages that you would be interested in exploring more in-depth later in the course.

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    Problem 3

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    There is another way to install R packages, using the newer pak package. Positron uses this when installing suggested dependencies.

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    After learning more about it via the documentation and it’s pkgdown website, I would like you to attempt to install the following three R packages using this newer method: “broom”, “cytoMEM”, “DillonHammill/CytoExploreR”.

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    Take screenshots, and in a new quarto markdown document, describe how the installation process differed from what you saw for install.packages(), install() and install_github().

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    AGPL-3.0 CC BY-SA 4.0

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    + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/course/01_InstallingRPackages/slides_inperson.html b/docs/course/01_InstallingRPackages/slides_inperson.html index adee48e..b198124 100644 --- a/docs/course/01_InstallingRPackages/slides_inperson.html +++ b/docs/course/01_InstallingRPackages/slides_inperson.html @@ -1,3196 +1,3196 @@ - - - - - - - - - - - - - - Cytometry in R – 01 - Installing R Packages - - - - - - - - - - - - - - - - - -
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    01 - Installing R Packages

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    -David Rach -
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    2026-02-01

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    Welcome to the first week of Cytometry in R! This week we will be diving into how R packages work, and the how to go about installing them.

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    Background

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    During Workstation Setup, you installed the R software to your local computer. R as a programming language that started up in the 1990s. While its original focus was on statistics, it is now widely used in various fields thanks to contributions of many open-source developers over the years.

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    This expanded reach is in part due to the ability to create R packages, that encapsulate additional functions, that can do new things beyond what the original software (ie. base R) was capable of doing.

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    Currently, there are thousands of R packages available. Furthermore, there is a vibrant community of individuals that help maintain and document how to use these packages, which has helped sustain and grow the R ecosystem over the last couple decades.

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    Regardless if you are working with flow cytometry, or in ecology, or in econometrics, or political science, a lot of the analysis and visualizations that you see in publications often involve R.

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    Expanding on this concept, a new R package can be made up of new code (primarily in the form of tools (ie. functions) that do a particular useful things) that is entirely self-contained, or reuse functions present in existing R packages to help make something new. When an R package relies on a function from another R package, it needs the other R package to be installed in order for everything to work properly. This is known as a package dependency.

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    The three main locations for R packages from are CRAN (containing 23069 packages), Bioconductor (containing 2361 packages), and individual R packages hosted by their developers via GitHub.

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    The process of installing R packages will vary a bit depending on which repository the respective R package is in. For beginners, this often prooves to be a pain-point, as they will attempt to install an R package using one set of installation commands, only to get an error (because the R package is not in that repository).

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    Getting Started

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    Checking for Loaded Packages

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    For the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active.

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    Accessing Help Documentation

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    Within your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following sessionInfo() function

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    sessionInfo()
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    If you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over.

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    sessionInfo()

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    Within your .qmd file, let’s go ahead and run the following code-block:

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    sessionInfo()
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    R version 4.5.2 (2025-10-31)
-Platform: x86_64-pc-linux-gnu
-Running under: Debian GNU/Linux 13 (trixie)
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-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
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-locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
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-attached base packages:
-[1] stats     graphics  grDevices utils     datasets  methods   base     
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-loaded via a namespace (and not attached):
- [1] compiler_4.5.2  fastmap_1.2.0   cli_3.6.5       tools_4.5.2    
- [5] htmltools_0.5.9 otel_0.2.0      yaml_2.3.12     rmarkdown_2.30 
- [9] knitr_1.51      jsonlite_2.0.0  xfun_0.56       digest_0.6.39  
-[13] rlang_1.1.7     evaluate_1.0.5
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    The outputs that get returned by sessionInfo() will vary a bit depending on your computer’s operating system, and the version of R you have installed.

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    For today, let’s focus on the last two elements of the output:

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    The R software itself is made up of several base R packages, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages.

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    As we install additional R packages and load them using the library() function throughout this session, sporadically re-run sessionInfo() to see how this list of R packages changes.

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    Installing from CRAN

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    We will start by installing R packages that are part of the CRAN repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository.

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    These include the tidyverse packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today.

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    dplyr

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    Our first R package we will install during this session is the dplyr package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function install.packages().

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    For the install.packages() function, we place within the () the name of the R package from CRAN that we wish to install.

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    Tip

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    A usual struggle point for beginners is that install.packages() requires ” ” to be placed around the package name. Forgetting them results in the error that we see below.

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    Go ahead and click on “Run Cell” next to your code-block, to install the dplyr R package.

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    When a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system).

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    Within this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN.

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    If the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder.

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    The final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the “Done” line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder).

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    Attaching packages via library()

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    If an R package has been installed successfully, we are now able to load it (ie. make it’s functions available) to our local environment using the library() function.

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    Unlike install.packages(), where we needed “” around the package name, the library() function does not require “” around the package name. Let’s go ahead and load in dplyr, making its respective functions to our local environment.

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    From the output, we can see that dplyr has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages.

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    With dplyr now loaded via the library() call, let’s check sessionInfo() to see what has changed.

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    R version 4.5.2 (2025-10-31)
-Platform: x86_64-pc-linux-gnu
-Running under: Debian GNU/Linux 13 (trixie)
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-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
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-locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
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-time zone: America/New_York
-tzcode source: system (glibc)
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-attached base packages:
-[1] stats     graphics  grDevices utils     datasets  methods   base     
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-other attached packages:
-[1] dplyr_1.2.0
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-loaded via a namespace (and not attached):
- [1] digest_0.6.39    R6_2.6.1         fastmap_1.2.0    tidyselect_1.2.1
- [5] xfun_0.56        magrittr_2.0.4   glue_1.8.0       tibble_3.3.1    
- [9] knitr_1.51       pkgconfig_2.0.3  htmltools_0.5.9  generics_0.1.4  
-[13] rmarkdown_2.30   lifecycle_1.0.5  cli_3.6.5        vctrs_0.7.1     
-[17] compiler_4.5.2   tools_4.5.2      evaluate_1.0.5   pillar_1.11.1   
-[21] yaml_2.3.12      otel_0.2.0       rlang_1.1.7      jsonlite_2.0.0
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    Similar to what was seen for the base R packages, dplyr is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the dplyr packages select() function and it’s respective help page.

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    Since its parent package has been attached to our local environment (via the library() call), we can see dplyr functions appear as suggestions as we begin to type.

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    By contrast, is we check for the ggplot() function from the ggplot2 package (which we haven’t yet installed or attached via library()), no suggestions will pop up.

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    Common Issues

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    As previously mentioned, CRAN is the main repository for R packages. But what if we tried to install an R package that is only found on Bioconductor or via GitHub using the install.packages() function?

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    To see what occurs, let’s try installing the PeacoQC package (which is found on Bioconductor).

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    As you can see, the initial warning message suggest that PeacoQC is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn’t figure out what was going on.

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    This is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN.

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    Installing from Bioconductor

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    Bioconductor is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this link you can find it’s current flow and mass cytometry R packages.

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    Bioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different standards for acceptance than CRAN. They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems.

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    To install an R package that is located on Bioconductor, we first need to install the BiocManager package from CRAN. This package will allow us to install Bioconductor packages from their respective repository.

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    Once BiocManager is installed, we can attach it to our local environment using the library() function

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    When loaded, you will see an output showing the current Bioconductor and R versions.

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    We can then use BiocManager’s install() function to go back and install PeacoQC().

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    Tip

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    As always, don’t forget the “” when running an install() command.

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    We see a similar opening sequence of installation steps as what we saw when installing the dplyr package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation.

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    Note

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    Behind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process

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    Within the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with dplyr, with a “Done (packagename)” being printed upon successful installation.

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    This process continues for each dependency being installed.

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    And finally, once all the dependencies are installed, PeacoQC starts to install.

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    Occasionally, during installation, you will see a pop-up windown like this one in the console. This let’s you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n].

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    Alternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter.

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    Generally, it’s okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn’t cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option.

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    With PeacoQC has been installed, we can load it via the library() call

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    Tip

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    Remeber, library() doesn’t require ” ”

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    And we can check to see if it has been attached to the local environment

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    R version 4.5.2 (2025-10-31)
-Platform: x86_64-pc-linux-gnu
-Running under: Debian GNU/Linux 13 (trixie)
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-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
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-locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
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-tzcode source: system (glibc)
-
-attached base packages:
-[1] stats     graphics  grDevices utils     datasets  methods   base     
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-other attached packages:
-[1] PeacoQC_1.20.0      BiocManager_1.30.27 dplyr_1.2.0        
-
-loaded via a namespace (and not attached):
- [1] generics_0.1.4        shape_1.4.6.1         digest_0.6.39        
- [4] magrittr_2.0.4        evaluate_1.0.5        grid_4.5.2           
- [7] RColorBrewer_1.1-3    iterators_1.0.14      circlize_0.4.17      
-[10] fastmap_1.2.0         foreach_1.5.2         doParallel_1.0.17    
-[13] jsonlite_2.0.0        graph_1.88.1          GlobalOptions_0.1.3  
-[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1  scales_1.4.0         
-[19] XML_3.99-0.20         Rgraphviz_2.54.0      codetools_0.2-20     
-[22] cli_3.6.5             RProtoBufLib_2.22.0   rlang_1.1.7          
-[25] crayon_1.5.3          Biobase_2.70.0        yaml_2.3.12          
-[28] otel_0.2.0            cytolib_2.22.0        ncdfFlow_2.56.0      
-[31] tools_4.5.2           parallel_4.5.2        colorspace_2.1-2     
-[34] ggplot2_4.0.2         GetoptLong_1.1.0      BiocGenerics_0.56.0  
-[37] vctrs_0.7.1           R6_2.6.1              png_0.1-8            
-[40] matrixStats_1.5.0     stats4_4.5.2          lifecycle_1.0.5      
-[43] flowCore_2.22.1       S4Vectors_0.48.0      IRanges_2.44.0       
-[46] clue_0.3-66           cluster_2.1.8.1       pkgconfig_2.0.3      
-[49] pillar_1.11.1         gtable_0.3.6          data.table_1.18.2.1  
-[52] glue_1.8.0            xfun_0.56             tibble_3.3.1         
-[55] tidyselect_1.2.1      knitr_1.51            farver_2.1.2         
-[58] rjson_0.2.23          htmltools_0.5.9       rmarkdown_2.30       
-[61] compiler_4.5.2        S7_0.2.1
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    As you may have noticed, the section of loaded via namespace (but not attached) packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment.

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    To see what packages are installed (but not yet loaded), we can use the installed.packages() function to return a list of R packages for your computer.

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    Install from GitHub

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    In addition to the CRAN and Bioconductor repositories, individual R packages can also be found on GitHub hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to CRAN or Bioconductor) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all.

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    While many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to deprecation since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it’s useful to check the commits and issues pages to see when the last contribution occurred. We will take a closer look at how to do so later on.

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    To install packages from GitHub, you will need the remotes package, which can be found on CRAN.

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    Spot Check #1

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    To install a package from CRAN, what function would you use? Click on the code-fold arrow below to reveal the answer.

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    With the remotes package now installed, we can attach it to our local environment.

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    Spot Check #2

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    What function would be used to do so?

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    And finally, we can use the install_github() function to download R packages from the invidual developers GitHub account.

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    Spot Check #3

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    How would you look up the help documentation for this function?

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    We will be installing a small R package flowSpectrum for this example. It’s one of the packages created by Christopher Hall, whose small series of Flow Cytometry Data Analysis in R tutorials were immensely useful when I was first getting started learning R. flowSpectrum can be used to generate spectrum-style plots for spectral flow cytometry data.

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    To install an R package from GitHub, we first need the GitHub username (so hally166 in this case), which is followed by a “/”, and then the name of the package repository (so flowSpectrum in this case). Our code should consequently be

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    When installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding.

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    This process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating R packages.

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    Troubleshooting Install Errors

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    We have now installed three R packages, dplyr, PeacoQC, and flowSpectrum. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies.

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    When encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below.

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    If you encounter an installation error this week, please take screenshots of the error message and post them to this Discussion. This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future.

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    Documentation and Websites

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    We have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package.

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    For CRAN-based packages, we can start off by searching for the package name. So, in the case of dplyr

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    Two main suggestions pop up. One is the package’s CRAN page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible.

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    Because of this, many CRAN-based R packages (especially those part of the tidyverse) use pkgdown-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr’s pkgdown-style website

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    We can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab.

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    GitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository’s ReadMe.

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    For Bioconductor-based packages, on the package’s page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with PeacoQC:

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    Additionally, package vignettes can also be reached via the packages help index page. These will usually appear under User guides, package vignettes, and other documentation.

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    Your Turn

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    Alright, we have now gone through the process of installing an R package from CRAN, Bioconductor, and GitHub. We will now install 20 other R packages we will need throughout the rest of the course.

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    Note

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    To make this interactive, I will task you to apply the previous concepts to figure out whether the packages need to be installed via CRAN, Bioconductor or GitHub.

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    Important

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    Feel free to view the website version to avoid accidental spoilers from the copied over index.qmd file. Alternatively, you can attempt to switch from the Source view to Visual Mode by right clicking with your mouse and selecting that option.

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    Tip

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    Start by searching each packages name. See if you can spot first either a CRAN or a Bioconductor website. Then enter the respective installation command (install.packages(), install(), install_github()) for the appropiate repository, add the package name, and run the code to see if the installation proceeds.

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    For cases where you are truly stuck, expand the code-fold below each package name to see the answer.

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    Note

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    Some of these packages may be dependencies of each other and may wind up installed before you get to them. If that is the case, no need to reinstall, count it as a win, and proceed to the next R package.

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    Remember,if you encountered any installation errors in the process, please take screenshots and post them on the the Discussion page to help with improved documentation.

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    R package: purrr

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    Congratulations! You have (hopefully) survived the package installation onslaught that is Week #1 of the course.

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    Remember to submit any encountered installation error screenshots to the Discussion page.

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    Wrap-Up

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    In this session, we walked through what are R packages, where to find them, how to install them, and a bit about troubleshooting any installation errors you may encounter during the process.

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    You then proceeded to install most of the R packages that you would need throughout the Cytometry in R course. These included tidyverse packages from the [CRAN] repository used for working with data structures and plots, as well as more cytometry focused R packages from [Bioconductor] repository.

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    If you have any questions, or want to discuss this week’s topics in more depth with the other course participants, please head over to the Discussion page and open a new topic.

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    Next week, we will start learning about file paths, by which we will be able to tell our computer where to find your fcs files, how to retrieve the file names, subset those that may be of particular interest, and copy them over to a new folder. In the processs, we will learn a little more about how variables, objects, and list work within R.

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    Until then, Best Wishes!

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    Additional Resources

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    Tidy Tales An usefu beginner-friendly blogpost covering additional aspects from a different perspective.

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    Introduction to Bioconductor A talk by Martin Morgan with more information about the Bioconductor project.

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    R Packages A book by Hadley Wickham and Jennifer Bryan, covering all the different internals of R packages.

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    Below you will find the optional take-home problems for Week #1. Learning how to code well requires continous practice, and that involves cycles of trying something, failing, and troubleshooting to get it working. The goal of these problems is to help you explore the topic in greater depth than the currated boundaries of this one lecture.

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    You are more than welcome to open a Discussion to engage with others in the course to discuss these questions. Once you are done tinkering, and want to get final instructor feedback on your work, place your files within a folder, and follow the instructions to submit it as a Pull Request to the Cytometry In R repositories homework branch.

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    Problem 1

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    We installed PeacoQC during this session, but we didn’t have time to explore what functions are present within the package. Using what you have learned about accessing documentation, figure out and list what functions it contains

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    Problem 2

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    Take a closer look at the list of Bioconductor cytometry packages. Report back on how many there are currently in Bioconductor, the author/maintainer with the most contributed cytometry R packages, and a couple packages that you would be interested in exploring more in-depth later in the course.

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    Problem 3

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    There is another way to install R packages, using the newer pak package. Positron uses this when installing suggested dependencies.

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    After learning more about it via the documentation and it’s pkgdown website, I would like you to attempt to install the following three R packages using this newer method: “broom”, “cytoMEM”, “DillonHammill/CytoExploreR”.

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    Take screenshots, and in a new quarto markdown document, describe how the installation process differed from what you saw for install.packages(), install() and install_github().

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    AGPL-3.0 CC BY-SA 4.0

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    - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + Cytometry in R – 01 - Installing R Packages + + + + + + + + + + + + + + + + + +
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    01 - Installing R Packages

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    +David Rach +
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    2026-02-01

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    Welcome to the first week of Cytometry in R! This week we will be diving into how R packages work, and the how to go about installing them.

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    Background

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    During Workstation Setup, you installed the R software to your local computer. R as a programming language that started up in the 1990s. While its original focus was on statistics, it is now widely used in various fields thanks to contributions of many open-source developers over the years.

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    This expanded reach is in part due to the ability to create R packages, that encapsulate additional functions, that can do new things beyond what the original software (ie. base R) was capable of doing.

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    Currently, there are thousands of R packages available. Furthermore, there is a vibrant community of individuals that help maintain and document how to use these packages, which has helped sustain and grow the R ecosystem over the last couple decades.

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    Regardless if you are working with flow cytometry, or in ecology, or in econometrics, or political science, a lot of the analysis and visualizations that you see in publications often involve R.

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    +
    + +
    +
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    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Expanding on this concept, a new R package can be made up of new code (primarily in the form of tools (ie. functions) that do a particular useful things) that is entirely self-contained, or reuse functions present in existing R packages to help make something new. When an R package relies on a function from another R package, it needs the other R package to be installed in order for everything to work properly. This is known as a package dependency.

    +
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    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    The three main locations for R packages from are CRAN (containing 23069 packages), Bioconductor (containing 2361 packages), and individual R packages hosted by their developers via GitHub.

    +
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    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    The process of installing R packages will vary a bit depending on which repository the respective R package is in. For beginners, this often prooves to be a pain-point, as they will attempt to install an R package using one set of installation commands, only to get an error (because the R package is not in that repository).

    +
    +
    +
    +
    +
    +
    +
    + +
    +
    +
    +

    Getting Started

    + +
    +
    +

    Checking for Loaded Packages

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    For the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active.

    +
    +
    +
    +
    +
    +
    +
    + +

    Accessing Help Documentation

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Within your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following sessionInfo() function

    +
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    +
    +
    +
    +
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    sessionInfo()
    +
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    +
    +
    + +
    +
    +
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    +
    + +
    +

    .

    +
    +
    +

    If you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over.

    +
    +
    +
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    +
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    + + +
    +
    + +
    +
    +
    ?sessionInfo()
    +
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    +
    +
    + + +
    +
    + +

    sessionInfo()

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Within your .qmd file, let’s go ahead and run the following code-block:

    +
    +
    +
    +
    +
    +
    +
    +
    sessionInfo()
    +
    +
    R version 4.5.2 (2025-10-31)
+Platform: x86_64-pc-linux-gnu
+Running under: Debian GNU/Linux 13 (trixie)
+
+Matrix products: default
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
+
+locale:
+ [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
+ [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
+ [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
+ [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [9] LC_ADDRESS=C               LC_TELEPHONE=C            
+[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
+
+time zone: America/New_York
+tzcode source: system (glibc)
+
+attached base packages:
+[1] stats     graphics  grDevices utils     datasets  methods   base     
+
+loaded via a namespace (and not attached):
+ [1] compiler_4.5.2  fastmap_1.2.0   cli_3.6.5       tools_4.5.2    
+ [5] htmltools_0.5.9 otel_0.2.0      yaml_2.3.12     rmarkdown_2.30 
+ [9] knitr_1.51      jsonlite_2.0.0  xfun_0.56       digest_0.6.39  
+[13] rlang_1.1.7     evaluate_1.0.5
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    The outputs that get returned by sessionInfo() will vary a bit depending on your computer’s operating system, and the version of R you have installed.

    +

    For today, let’s focus on the last two elements of the output:

    +
    +
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    +
    +
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    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    The R software itself is made up of several base R packages, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages.

    +

    As we install additional R packages and load them using the library() function throughout this session, sporadically re-run sessionInfo() to see how this list of R packages changes.

    +
    +
    +
    +
    +
    +
    +
    +

    Installing from CRAN

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    We will start by installing R packages that are part of the CRAN repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository.

    +

    These include the tidyverse packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today.

    +
    +
    +
    +
    +
    +
    +
    + +

    dplyr

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Our first R package we will install during this session is the dplyr package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function install.packages().

    +
    +
    +
    +
    +
    +
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    +
    ?install.packages()
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    For the install.packages() function, we place within the () the name of the R package from CRAN that we wish to install.

    +
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    +
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    +
    +
    +
    +
    install.packages("dplyr")
    +
    +
    +
    +
    + +
    +
    +
    +
    + +
    +

    Tip

    +
    +
    +

    A usual struggle point for beginners is that install.packages() requires ” ” to be placed around the package name. Forgetting them results in the error that we see below.

    +
    +
    +
    +
    +
    +
    install.packages(dplyr)
    +
    +
    Error:
+! object 'dplyr' not found
    +
    +
    +
    +
    +
    + +
    +
    +
    install.packages("dplyr")
    +
    +
    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Go ahead and click on “Run Cell” next to your code-block, to install the dplyr R package.

    +
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    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    When a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system).

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Within this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN.

    +

    If the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder.

    +
    +
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    + + +
    +
    + +
    +
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    +
    +
    +
    + +
    +

    .

    +
    +
    +

    The final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the “Done” line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder).

    +
    +
    +
    +
    +
    +
    +
    + +

    Attaching packages via library()

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    If an R package has been installed successfully, we are now able to load it (ie. make it’s functions available) to our local environment using the library() function.

    +
    +
    +
    +
    +
    +
    +
    +
    ?library()
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Unlike install.packages(), where we needed “” around the package name, the library() function does not require “” around the package name. Let’s go ahead and load in dplyr, making its respective functions to our local environment.

    +
    +
    +
    +
    +
    +
    +
    +
    library(dplyr)
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    From the output, we can see that dplyr has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages.

    +

    With dplyr now loaded via the library() call, let’s check sessionInfo() to see what has changed.

    +
    +
    +
    +
    +
    +
    +
    +
    sessionInfo()
    +
    +
    R version 4.5.2 (2025-10-31)
+Platform: x86_64-pc-linux-gnu
+Running under: Debian GNU/Linux 13 (trixie)
+
+Matrix products: default
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
+
+locale:
+ [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
+ [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
+ [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
+ [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [9] LC_ADDRESS=C               LC_TELEPHONE=C            
+[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
+
+time zone: America/New_York
+tzcode source: system (glibc)
+
+attached base packages:
+[1] stats     graphics  grDevices utils     datasets  methods   base     
+
+other attached packages:
+[1] dplyr_1.2.0
+
+loaded via a namespace (and not attached):
+ [1] digest_0.6.39    R6_2.6.1         fastmap_1.2.0    tidyselect_1.2.1
+ [5] xfun_0.56        magrittr_2.0.4   glue_1.8.0       tibble_3.3.1    
+ [9] knitr_1.51       pkgconfig_2.0.3  htmltools_0.5.9  generics_0.1.4  
+[13] rmarkdown_2.30   lifecycle_1.0.5  cli_3.6.5        vctrs_0.7.1     
+[17] compiler_4.5.2   tools_4.5.2      evaluate_1.0.5   pillar_1.11.1   
+[21] yaml_2.3.12      otel_0.2.0       rlang_1.1.7      jsonlite_2.0.0
    +
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Similar to what was seen for the base R packages, dplyr is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the dplyr packages select() function and it’s respective help page.

    +
    +
    +
    +
    +
    +
    +
    +
    ?select
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Since its parent package has been attached to our local environment (via the library() call), we can see dplyr functions appear as suggestions as we begin to type.

    +

    By contrast, is we check for the ggplot() function from the ggplot2 package (which we haven’t yet installed or attached via library()), no suggestions will pop up.

    +
    +
    +
    +
    +
    +
    +
    + +
    +
    +
    ?ggplot
    +
    +
    No documentation for 'ggplot' in specified packages and libraries:
+you could try '??ggplot'
    +
    +
    +
    +
    +
    + +

    Common Issues

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    As previously mentioned, CRAN is the main repository for R packages. But what if we tried to install an R package that is only found on Bioconductor or via GitHub using the install.packages() function?

    +

    To see what occurs, let’s try installing the PeacoQC package (which is found on Bioconductor).

    +
    +
    +
    +
    +
    +
    +
    +
    install.packages("PeacoQC")
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    As you can see, the initial warning message suggest that PeacoQC is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn’t figure out what was going on.

    +

    This is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN.

    +
    +
    +
    +
    +
    +
    +
    +

    Installing from Bioconductor

    +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Bioconductor is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this link you can find it’s current flow and mass cytometry R packages.

    +

    Bioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different standards for acceptance than CRAN. They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems.

    +
    +
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    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    To install an R package that is located on Bioconductor, we first need to install the BiocManager package from CRAN. This package will allow us to install Bioconductor packages from their respective repository.

    +
    +
    +
    +
    +
    +
    +
    +
    install.packages("BiocManager")
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Once BiocManager is installed, we can attach it to our local environment using the library() function

    +
    +
    +
    +
    +
    +
    +
    +
    library(BiocManager)
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    When loaded, you will see an output showing the current Bioconductor and R versions.

    +

    We can then use BiocManager’s install() function to go back and install PeacoQC().

    +
    +
    +
    +
    +
    +
    +
    +
    +
    + +
    +

    Tip

    +
    +
    +

    As always, don’t forget the “” when running an install() command.

    +
    +
    +
    +
    +
    +
    ?install()
    +
    +
    +
    +
    +
    install("PeacoQC")
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    We see a similar opening sequence of installation steps as what we saw when installing the dplyr package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation.

    +
    +
    +
    +
    +
    +
    +
    +
    +
    +
    + +
    +

    Note

    +
    +
    +

    Behind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process

    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Within the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with dplyr, with a “Done (packagename)” being printed upon successful installation.

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    This process continues for each dependency being installed.

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    And finally, once all the dependencies are installed, PeacoQC starts to install.

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Occasionally, during installation, you will see a pop-up windown like this one in the console. This let’s you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n].

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Alternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter.

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Generally, it’s okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn’t cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option.

    +
    +
    +
    +
    +
    +
    +
    + + +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    With PeacoQC has been installed, we can load it via the library() call

    +
    +
    +
    +
    +
    +
    +
    +
    +
    + +
    +

    Tip

    +
    +
    +

    Remeber, library() doesn’t require ” ”

    +
    +
    +
    +
    +
    +
    library(PeacoQC)
    +
    +
    +
    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    And we can check to see if it has been attached to the local environment

    +
    +
    +
    +
    +
    +
    +
    +
    sessionInfo()
    +
    +
    R version 4.5.2 (2025-10-31)
+Platform: x86_64-pc-linux-gnu
+Running under: Debian GNU/Linux 13 (trixie)
+
+Matrix products: default
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1;  LAPACK version 3.12.0
+
+locale:
+ [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
+ [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
+ [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
+ [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [9] LC_ADDRESS=C               LC_TELEPHONE=C            
+[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
+
+time zone: America/New_York
+tzcode source: system (glibc)
+
+attached base packages:
+[1] stats     graphics  grDevices utils     datasets  methods   base     
+
+other attached packages:
+[1] PeacoQC_1.20.0      BiocManager_1.30.27 dplyr_1.2.0        
+
+loaded via a namespace (and not attached):
+ [1] generics_0.1.4        shape_1.4.6.1         digest_0.6.39        
+ [4] magrittr_2.0.4        evaluate_1.0.5        grid_4.5.2           
+ [7] RColorBrewer_1.1-3    iterators_1.0.14      circlize_0.4.17      
+[10] fastmap_1.2.0         foreach_1.5.2         doParallel_1.0.17    
+[13] jsonlite_2.0.0        graph_1.88.1          GlobalOptions_0.1.3  
+[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1  scales_1.4.0         
+[19] XML_3.99-0.20         Rgraphviz_2.54.0      codetools_0.2-20     
+[22] cli_3.6.5             RProtoBufLib_2.22.0   rlang_1.1.7          
+[25] crayon_1.5.3          Biobase_2.70.0        yaml_2.3.12          
+[28] otel_0.2.0            cytolib_2.22.0        ncdfFlow_2.56.0      
+[31] tools_4.5.2           parallel_4.5.2        colorspace_2.1-2     
+[34] ggplot2_4.0.2         GetoptLong_1.1.0      BiocGenerics_0.56.0  
+[37] vctrs_0.7.1           R6_2.6.1              png_0.1-8            
+[40] matrixStats_1.5.0     stats4_4.5.2          lifecycle_1.0.5      
+[43] flowCore_2.22.1       S4Vectors_0.48.0      IRanges_2.44.0       
+[46] clue_0.3-66           cluster_2.1.8.1       pkgconfig_2.0.3      
+[49] pillar_1.11.1         gtable_0.3.6          data.table_1.18.2.1  
+[52] glue_1.8.0            xfun_0.56             tibble_3.3.1         
+[55] tidyselect_1.2.1      knitr_1.51            farver_2.1.2         
+[58] rjson_0.2.23          htmltools_0.5.9       rmarkdown_2.30       
+[61] compiler_4.5.2        S7_0.2.1
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    .

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    As you may have noticed, the section of loaded via namespace (but not attached) packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment.

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    To see what packages are installed (but not yet loaded), we can use the installed.packages() function to return a list of R packages for your computer.

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    installed.packages()
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    Install from GitHub

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    In addition to the CRAN and Bioconductor repositories, individual R packages can also be found on GitHub hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to CRAN or Bioconductor) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all.

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    .

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    While many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to deprecation since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it’s useful to check the commits and issues pages to see when the last contribution occurred. We will take a closer look at how to do so later on.

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    To install packages from GitHub, you will need the remotes package, which can be found on CRAN.

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    Spot Check #1

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    To install a package from CRAN, what function would you use? Click on the code-fold arrow below to reveal the answer.

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    install.packages("remotes")
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    With the remotes package now installed, we can attach it to our local environment.

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    Spot Check #2

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    What function would be used to do so?

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    +Code +
    library(remotes)
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    And finally, we can use the install_github() function to download R packages from the invidual developers GitHub account.

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    Spot Check #3

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    How would you look up the help documentation for this function?

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    +Code +
    # Either by hovering over it within Positron or via
+
+?install_github()
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    .

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    We will be installing a small R package flowSpectrum for this example. It’s one of the packages created by Christopher Hall, whose small series of Flow Cytometry Data Analysis in R tutorials were immensely useful when I was first getting started learning R. flowSpectrum can be used to generate spectrum-style plots for spectral flow cytometry data.

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    To install an R package from GitHub, we first need the GitHub username (so hally166 in this case), which is followed by a “/”, and then the name of the package repository (so flowSpectrum in this case). Our code should consequently be

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    install_github("hally166/flowSpectrum")
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    .

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    When installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding.

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    This process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating R packages.

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    Troubleshooting Install Errors

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    .

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    We have now installed three R packages, dplyr, PeacoQC, and flowSpectrum. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies.

    +

    When encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below.

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    .

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    If you encounter an installation error this week, please take screenshots of the error message and post them to this Discussion. This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future.

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    Documentation and Websites

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    .

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    We have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package.

    +

    For CRAN-based packages, we can start off by searching for the package name. So, in the case of dplyr

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    .

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    Two main suggestions pop up. One is the package’s CRAN page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible.

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    .

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    Because of this, many CRAN-based R packages (especially those part of the tidyverse) use pkgdown-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr’s pkgdown-style website

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    .

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    We can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab.

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    .

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    GitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository’s ReadMe.

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    .

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    For Bioconductor-based packages, on the package’s page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with PeacoQC:

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    .

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    Additionally, package vignettes can also be reached via the packages help index page. These will usually appear under User guides, package vignettes, and other documentation.

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    Your Turn

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    .

    +
    +
    +

    Alright, we have now gone through the process of installing an R package from CRAN, Bioconductor, and GitHub. We will now install 20 other R packages we will need throughout the rest of the course.

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    Note

    +
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    To make this interactive, I will task you to apply the previous concepts to figure out whether the packages need to be installed via CRAN, Bioconductor or GitHub.

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    Important

    +
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    Feel free to view the website version to avoid accidental spoilers from the copied over index.qmd file. Alternatively, you can attempt to switch from the Source view to Visual Mode by right clicking with your mouse and selecting that option.

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    Tip

    +
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    +

    Start by searching each packages name. See if you can spot first either a CRAN or a Bioconductor website. Then enter the respective installation command (install.packages(), install(), install_github()) for the appropiate repository, add the package name, and run the code to see if the installation proceeds.

    +

    For cases where you are truly stuck, expand the code-fold below each package name to see the answer.

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    Note

    +
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    Some of these packages may be dependencies of each other and may wind up installed before you get to them. If that is the case, no need to reinstall, count it as a win, and proceed to the next R package.

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    .

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    Remember,if you encountered any installation errors in the process, please take screenshots and post them on the the Discussion page to help with improved documentation.

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    1/20

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    R package: purrr

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    +Code +
    # Location: CRAN
+# Website: https://purrr.tidyverse.org/
+
+install.packages("purrr")
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    2/20

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    R package: flowCore

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/flowCore.html
+
+install("flowCore")
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    3/20

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    R package: flowWorkspace

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/flowWorkspace.html
+
+install("flowWorkspace")
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    4/20

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    R package: stringr

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    +Code +
    # Location: CRAN
+# Website: https://stringr.tidyverse.org/
+
+install.packages("stringr")
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    5/20

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    R package: ggplot2

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    +Code +
    # Location: CRAN
+# Website: https://ggplot2.tidyverse.org/
+
+install.packages("ggplot2")
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    6/20

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    R package: ggcyto

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/ggcyto.html
+
+install.packages("ggcyto")
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    7/20

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    R package: tidyr

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    +Code +
    # Location: CRAN
+# Website: https://tidyr.tidyverse.org/
+
+install.packages("tidyr")
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    8/20

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    R package: openCyto

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/openCyto.html
+
+install.packages("openCyto")
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    9/20

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    R package: FlowSOM

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/FlowSOM.html
+
+install.packages("FlowSOM")
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    10/20

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    R package: xml2

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    +Code +
    # Location: CRAN
+# Website: https://xml2.r-lib.org/
+
+install.packages("xml2")
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    11/20

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    R package: saeyslab/CytoNorm

    +
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    +
    +
    +
    +
    +Code +
    # Location: GitHub
+# Website: https://github.com/saeyslab/CytoNorm
+
+install_github("saeyslab/CytoNorm")
    +
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    12/20

    +
    +
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    R package: lubridate

    +
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    +Code +
    # Location: CRAN
+# Website: https://lubridate.tidyverse.org/
+
+install.packages("lubridate")
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    13/20

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    R package: httr2

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    +Code +
    # Location: CRAN
+# Website: https://httr2.r-lib.org/
+
+install.packages("httr2")
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    14/20

    +
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    +

    R package: flowGate

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/flowGate.html
+
+install("flowGate")
    +
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    15/20

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    R package: devtools

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    +Code +
    # Location: CRAN
+# Website: https://devtools.r-lib.org/
+
+install.packages("devtools")
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    16/20

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    R package: plotly

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    +Code +
    # Location: CRAN
+# Website: https://plotly.com/r/getting-started/
+
+install.packages("plotly")
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    17/20

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    R package: biosurf/cyCombine

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    +Code +
    # Location: GitHub
+# Website: https://github.com/biosurf/cyCombine
+
+install_github("biosurf/cyCombine")
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    18/20

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    R package: CytoML

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    +Code +
    # Location: Bioconductor
+# Website: https://www.bioconductor.org/packages/release/bioc/html/CytoML.html
+
+install("CytoML")
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    19/20

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    R package: Rtsne

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    +Code +
    # Location: CRAN
+# Website: https://github.com/jkrijthe/Rtsne
+
+install.packages("Rtsne")
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    20/20

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    R package: uwot

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    +Code +
    # Location: CRAN
+# Website:https://jlmelville.github.io/uwot/
+
+install.packages("uwot")
    +
    +
    +
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    +
    + +
    +
    +
    +
    +
    +
    + +
    +

    .

    +
    +
    +

    Congratulations! You have (hopefully) survived the package installation onslaught that is Week #1 of the course.

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    +

    .

    +
    +
    +

    Remember to submit any encountered installation error screenshots to the Discussion page.

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    +

    Wrap-Up

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    + +
    +

    .

    +
    +
    +

    In this session, we walked through what are R packages, where to find them, how to install them, and a bit about troubleshooting any installation errors you may encounter during the process.

    +

    You then proceeded to install most of the R packages that you would need throughout the Cytometry in R course. These included tidyverse packages from the [CRAN] repository used for working with data structures and plots, as well as more cytometry focused R packages from [Bioconductor] repository.

    +

    If you have any questions, or want to discuss this week’s topics in more depth with the other course participants, please head over to the Discussion page and open a new topic.

    +

    Next week, we will start learning about file paths, by which we will be able to tell our computer where to find your fcs files, how to retrieve the file names, subset those that may be of particular interest, and copy them over to a new folder. In the processs, we will learn a little more about how variables, objects, and list work within R.

    +

    Until then, Best Wishes!

    +
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    • David
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    Additional Resources

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    + +
    +

    .

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    +

    Tidy Tales An usefu beginner-friendly blogpost covering additional aspects from a different perspective.

    +

    Introduction to Bioconductor A talk by Martin Morgan with more information about the Bioconductor project.

    +

    R Packages A book by Hadley Wickham and Jennifer Bryan, covering all the different internals of R packages.

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    + +
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    Take-home Problems

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    +

    .

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    +

    Below you will find the optional take-home problems for Week #1. Learning how to code well requires continous practice, and that involves cycles of trying something, failing, and troubleshooting to get it working. The goal of these problems is to help you explore the topic in greater depth than the currated boundaries of this one lecture.

    +

    You are more than welcome to open a Discussion to engage with others in the course to discuss these questions. Once you are done tinkering, and want to get final instructor feedback on your work, place your files within a folder, and follow the instructions to submit it as a Pull Request to the Cytometry In R repositories homework branch.

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    + +
    +

    Problem 1

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    +
    +

    We installed PeacoQC during this session, but we didn’t have time to explore what functions are present within the package. Using what you have learned about accessing documentation, figure out and list what functions it contains

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    + +
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    + +
    +

    Problem 2

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    +
    +

    Take a closer look at the list of Bioconductor cytometry packages. Report back on how many there are currently in Bioconductor, the author/maintainer with the most contributed cytometry R packages, and a couple packages that you would be interested in exploring more in-depth later in the course.

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    +
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    + +
    +
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    +
    +
    + +
    +

    Problem 3

    +
    +
    +

    There is another way to install R packages, using the newer pak package. Positron uses this when installing suggested dependencies.

    +

    After learning more about it via the documentation and it’s pkgdown website, I would like you to attempt to install the following three R packages using this newer method: “broom”, “cytoMEM”, “DillonHammill/CytoExploreR”.

    +

    Take screenshots, and in a new quarto markdown document, describe how the installation process differed from what you saw for install.packages(), install() and install_github().

    +
    +
    +
    +
    +
    +
    + +
    +

    AGPL-3.0 CC BY-SA 4.0

    +
    + + +
    +
    +
    + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/course/02_FilePaths/Downsampler.html b/docs/course/02_FilePaths/Downsampler.html index c859924..420d5c3 100644 --- a/docs/course/02_FilePaths/Downsampler.html +++ b/docs/course/02_FilePaths/Downsampler.html @@ -246,7 +246,7 @@
  • - +
  • + Intro to R @@ -1536,8 +1536,8 @@

    Take-home Problems

  • - + Intro to R @@ -546,8 +546,8 @@

    flowCore

    plotly::ggplotly(plot)
    -
    - +
    +
    @@ -593,8 +593,8 @@

    flowCore

    plotly::ggplotly(plot)
    -
    - +
    +

    flowCore is also one of the many Bioconductor packages maintained by Mike Jiang. In many ways (as those who completed the optional take-home problems for Week #1 know) reminiscent of this xkcd comic:

    diff --git a/docs/course/03_InsideFCSFile/slides.html b/docs/course/03_InsideFCSFile/slides.html index 9d2593e..a99ebef 100644 --- a/docs/course/03_InsideFCSFile/slides.html +++ b/docs/course/03_InsideFCSFile/slides.html @@ -485,8 +485,8 @@

    flowCore

    -
    - +
    +
    @@ -497,8 +497,8 @@

    flowCore

    -
    - +
    +
    diff --git a/docs/course/04_IntroToTidyverse/BonusContent.html b/docs/course/04_IntroToTidyverse/BonusContent.html index 6891acf..b89f25e 100644 --- a/docs/course/04_IntroToTidyverse/BonusContent.html +++ b/docs/course/04_IntroToTidyverse/BonusContent.html @@ -247,7 +247,7 @@
  • - +
  • + Intro to R diff --git a/docs/course/05_GatingSets/Downsampling.html b/docs/course/05_GatingSets/Downsampling.html index 70f4a36..0d73e82 100644 --- a/docs/course/05_GatingSets/Downsampling.html +++ b/docs/course/05_GatingSets/Downsampling.html @@ -246,7 +246,7 @@
  • - +
  • + Intro to R @@ -377,8 +377,10 @@

    05 - Gating Sets

     -

    For the YouTube livestream schedule, see here

    -

    For screen-shot slides, click here

    +

    For the YouTube livestream recording, see here

    + +

    For screen-shot slides, click here


    @@ -440,8 +442,9 @@

    flowFrame

    library(flowCore)
    -
    flowFrame <- read.FCS(filename=fcs_files[1], truncate_max_range = FALSE, transformation = FALSE)
-flowFrame
    +
    flowFrame <- read.FCS(filename=fcs_files[1], truncate_max_range = FALSE,
+ transformation = FALSE)
+flowFrame
    flowFrame object '2025_07_26_AB_02_INF052_00_Ctrl.fcs'
 with 10000 cells and 43 observables:
@@ -499,8 +502,9 @@ 
    flowFrame
    
 
    flowSet
    
 
    Consequently, we will need to use another function if we want to read in multiple .fcs files at once. For flowCore, this function is the read.flowSet() function.
    
 
    
-
    flowSet <- read.flowSet(files=fcs_files, truncate_max_range = FALSE, transformation = FALSE)
-flowSet
    
+
    flowSet <- read.flowSet(files=fcs_files, truncate_max_range = FALSE,
+ transformation = FALSE)
+flowSet
    
 
    
 
    A flowSet with 6 experiments.
 
@@ -509,7 +513,8 @@ 
    flowSet
    
 
    
 
    Alternatively, we can designate specific files within “fcs_files” we want to read in using the [] and c() notation style we have encountered previously.
    
 
    
-
    read.flowSet(files=fcs_files[c(1, 3:4)], truncate_max_range = FALSE, transformation = FALSE)
    
+
    read.flowSet(files=fcs_files[c(1, 3:4)],
+ truncate_max_range = FALSE, transformation = FALSE)
    
 
    
 
    A flowSet with 3 experiments.
 
@@ -532,7 +537,7 @@ 
    flowSet
    
 
    str(flowSet)
    
 
    
 
    Formal class 'flowSet' [package "flowCore"] with 2 slots
-  ..@ frames   :<environment: 0x55d40ab8dbe8> 
+  ..@ frames   :<environment: 0x560d90048618> 
   ..@ phenoData:Formal class 'AnnotatedDataFrame' [package "Biobase"] with 4 slots
   .. .. ..@ varMetadata      :'data.frame': 1 obs. of  1 variable:
   .. .. .. ..$ labelDescription: chr "Name"
@@ -566,7 +571,7 @@ 
    flowSet
    
 
    
 
    Memory Usage
    
 
    Both “flowFrame” and “flowSet” objects were implemented in the flowCore package, which is the oldest extant flow cytometry R package on Bioconductor. Consequently, a large proportion of the other flow cytometry R packages read in .fcs files as “flowFrame” and “flowSet” objects.
    
-
    One consideration of this method is the contents of your .fcs files are read into your computer’s random access memory (RAM). While for individual .fcs files or small experiments this present a problem for most modern computers, when working with large spectral flow cytometry files containing millions of events (or trying to analyze many .fcs files at once), you may encounter situations where you can quickly exceed your computers available RAM.
    
+
    One consideration of this method is the contents of your .fcs files are read into your computer’s random access memory (RAM). While for individual .fcs files or small experiments this will not present a problem for most modern computers, when working with large spectral flow cytometry files containing millions of events (or trying to analyze many .fcs files at once), you may encounter situations where you can quickly exceed your computers available RAM.
    
 
    To build some contextual understanding of the problem, let’s learn how to check how much memory is being used by our individual variables/objects within our R session. We will primarily use the lobstr R packages obj_size() function, as it better handles evaluating complicated objects than base R’s object.size() function.
    
 
    We can check and see the memory usage by our flowFrame object
    
 
    
@@ -593,33 +598,47 @@ 
    Memory Usage
    
 
    
 
    mem_used()
    
 
    
-
    146.98 MB
    
+
    146.99 MB
    
 
    
 
    
-
    Ultimately, how many .fcs files you are able to read in and interact with before running out of available RAM memory space will be dictated by your individual computers hardware configuration. You can check programmatically how much RAM you have available, although the specific function you will need to use will depend on your computer’s operating system.
    
+
    Ultimately, how many .fcs files you are able to read in and interact with before running out of available RAM memory space will be dictated by your individual computers hardware configuration. There are various ways you can check programmatically how much RAM your computer has available, although the specific functions will vary depending on your computers operating system, since they often involve system-level code outside R. Using the ps R package’s ps_system_memory() function is one of the easier ways for Windows users.
    
 
    To simplify the process, here is an additional example of where a conditional can prove useful, allowing us to check in an operating system specific manner. It takes the output of the Sys.info() function, namely the “sysname” argument and then retrieves the relavent function.
    
 
    
 
    OperatingSystem <- Sys.info()[["sysname"]]
 
 if (OperatingSystem == "Windows") { # Windows
-    memory.limit()
-
-  } else if (OperatingSystem == "Darwin") { # MacOS
-    system("top -l 1 | grep PhysMem")
-
-  } else if (OperatingSystem == "Linux") { # Linux
-    system("free -h")
-
-  } else {message("A wild FreeBSD-User appears")}
    
-
    
-
    When evaluating the returned outputs, primarily consider the total, used and free outputs.
    
+  Memory <- ps::ps_system_memory()
+  message("Total GB ", round(Memory$total / 1024^3, 2))
+  message("Free GB ", round(Memory$free / 1024^3, 2))
+
+  } else if (OperatingSystem == "Darwin") { # MacOS
+    system("top -l 1 | grep PhysMem")
+
+  } else if (OperatingSystem == "Linux") { # Linux
+    system("free -h")
+
+  } else {message("A wild FreeBSD-User appears")}
    
+
    
+
    
+
    # install.packages("ps") # CRAN
+library(ps)
+Memory <- ps::ps_system_memory()
+message("Total GB ", round(Memory$total / 1024^3, 2))
    
+
    
+
    Total GB 62.5
    
+
    
+
    message("Free GB ", round(Memory$free / 1024^3, 2))
    
+
    
+
    Free GB 53.49
    
+
    
+
    
 
 
    
 
    cytoframe
    
 
    In addition to the flowCore R package, additional flow cytometry infrastructure support is provided by the flowWorkspace package. Instead of the reading all the .fcs files contents into active RAM, flowWorkspace reduces the memory overhead by using “pointers” to interact with the object in it’s current storage location (either on your harddrive, SSD, etc.), only reading in components to RAM as needed.
    
 
    
-
    # BiocManager::install("flowWorkspace") #Bioconductor
-library(flowWorkspace)
    
+
    # BiocManager::install("flowWorkspace") #Bioconductor
+library(flowWorkspace)
    
 
    
 
    As part of improvements to flowWorkspace, some behavior of
 GatingSet objects has changed. For details, please read the section
@@ -630,9 +649,9 @@ 
    cytoframe
    
 
    
 
    Because of these differences in how data is interracted with, we end up with parallel equivalents to the traditional flowFrame and flowSet type objects. These include “cytoframe” for single .fcs files
    
 
    
-
    cytoframe <- load_cytoframe_from_fcs(fcs_files[1], truncate_max_range = FALSE, transformation = FALSE)
-
-cytoframe
    
+
    cytoframe <- load_cytoframe_from_fcs(fcs_files[1], truncate_max_range = FALSE, transformation = FALSE)
+
+cytoframe
    
 
    
 
    cytoframe object '2025_07_26_AB_02_INF052_00_Ctrl.fcs'
 with 10000 cells and 43 observables:
@@ -653,7 +672,7 @@ 
    cytoframe
    
 
    
 
    
 
    
-
    class(cytoframe)
    
+
    class(cytoframe)
    
 
    
 
    [1] "cytoframe"
 attr(,"package")
@@ -662,7 +681,7 @@ 
    cytoframe
    
 
    
 
    Which also still errors out when not given a scalar object
    
 
    
-
    load_cytoframe_from_fcs(fcs_files, truncate_max_range = FALSE, transformation = FALSE)
    
+
    load_cytoframe_from_fcs(fcs_files, truncate_max_range = FALSE, transformation = FALSE)
    
 
    
 
    Error:
 ! Expected string vector of length 1
    
@@ -673,9 +692,9 @@ 
    cytoframe
    
 
    cytoset
    
 
    As well as “cytoset” to handle multiple .fcs files.
    
 
    
-
    cytoset <- load_cytoset_from_fcs(fcs_files, truncate_max_range = FALSE, transformation = FALSE)
-
-cytoset
    
+
    cytoset <- load_cytoset_from_fcs(fcs_files, truncate_max_range = FALSE, transformation = FALSE)
+
+cytoset
    
 
    
 
    A cytoset with 6 samples.
 
@@ -684,7 +703,7 @@ 
    cytoset
    
 
    
 
    
 
    
-
    class(cytoset)
    
+
    class(cytoset)
    
 
    
 
    [1] "cytoset"
 attr(,"package")
@@ -693,7 +712,7 @@ 
    cytoset
    
 
    
 
    Unlike “flowFrame” and “flowSet”, when we run str(), for “cytoframe” and “cytoset” objects we don’t get back quite as much information.
    
 
    
-
    str(cytoframe)
    
+
    str(cytoframe)
    
 
    
 
    Formal class 'cytoframe' [package "flowWorkspace"] with 5 slots
   ..@ pointer    :<externalptr> 
@@ -718,11 +737,11 @@ 
    cytoset
    
 
    
 
    
 
    
-
    str(cytoset)
    
+
    str(cytoset)
    
 
    
 
    Formal class 'cytoset' [package "flowWorkspace"] with 3 slots
   ..@ pointer  :<externalptr> 
-  ..@ frames   :<environment: 0x55d414e7fdf0> 
+  ..@ frames   :<environment: 0x560d9ade0fc8> 
   ..@ phenoData:Formal class 'AnnotatedDataFrame' [package "Biobase"] with 4 slots
   .. .. ..@ varMetadata      :'data.frame': 0 obs. of  1 variable:
   .. .. .. ..$ labelDescription: chr(0) 
@@ -738,26 +757,26 @@ 
    cytoset
    
 
    
 
    Due to flowWorkspace use of pointers, the missing data remains stored on the drive, only being retrieved right before it is required. This reduces the overall RAM utilization. Let’s double check the differences in memory utilization for flowFrame/cytoframe:
    
 
    
-
    obj_size(flowFrame)
    
+
    obj_size(flowFrame)
    
 
    
 
    3.53 MB
    
 
    
 
    
 
    
-
    obj_size(cytoframe)
    
+
    obj_size(cytoframe)
    
 
    
 
    5.40 kB
    
 
    
 
    
 
    And similarly the case for flowSet and cytoset:
    
 
    
-
    obj_size(flowSet)
    
+
    obj_size(flowSet)
    
 
    
 
    20.99 MB
    
 
    
 
    
 
    
-
    obj_size(cytoset)
    
+
    obj_size(cytoset)
    
 
    
 
    3.88 kB
    
 
    
@@ -769,10 +788,10 @@ 
    Interconverting
    
 
    Despite both R packages having been around for a while, many Bioconductor and GitHub often only implement methods to handle either flowFrames or cytoframes (although newer R packages are now allowing for both). Consequently, as we move forward in the course, it helps to be aware of which ones we are working with, and have the ability to interconvert between them as needed.
    
 
    To go from a flowFrame to a cytoframe, we can use the flowFrame_to_cytoframe() function
    
 
    
-
    ConvertedToCytoframe <- flowFrame_to_cytoframe(flowFrame)
-ConvertedToCytoframe
    
+
    ConvertedToCytoframe <- flowFrame_to_cytoframe(flowFrame)
+ConvertedToCytoframe
    
 
    
-
    cytoframe object 'file806b23cd6a2e'
+
    cytoframe object 'file382b177c06ea'
 with 10000 cells and 43 observables:
                name      desc       range  minRange    maxRange
 $P1            Time        NA     878.809         0     878.809
@@ -791,15 +810,15 @@ 
    Interconverting
    
 
    
 
    
 
    
-
    obj_size(ConvertedToCytoframe)
    
+
    obj_size(ConvertedToCytoframe)
    
 
    
 
    5.40 kB
    
 
    
 
    
 
    To go from a cytoframe to a flowFrame, we can use the cytoframe_to_flowFrame() function
    
 
    
-
    ConvertedToFlowframe <- flowWorkspace::cytoframe_to_flowFrame(cytoframe)
-ConvertedToFlowframe
    
+
    ConvertedToFlowframe <- flowWorkspace::cytoframe_to_flowFrame(cytoframe)
+ConvertedToFlowframe
    
 
    
 
    flowFrame object '2025_07_26_AB_02_INF052_00_Ctrl.fcs'
 with 10000 cells and 43 observables:
@@ -819,15 +838,15 @@ 
    Interconverting
    
 
    
 
    
 
    
-
    obj_size(ConvertedToFlowframe)
    
+
    obj_size(ConvertedToFlowframe)
    
 
    
 
    3.53 MB
    
 
    
 
    
 
    To go from a flowSet to a cytoSet, we can use the flowSet_to_cytoset() funciton
    
 
    
-
    ConvertedToCytoset <- flowSet_to_cytoset(flowSet)
-ConvertedToCytoset
    
+
    ConvertedToCytoset <- flowSet_to_cytoset(flowSet)
+ConvertedToCytoset
    
 
    
 
    A cytoset with 6 samples.
 
@@ -836,15 +855,15 @@ 
    Interconverting
    
 
    
 
    
 
    
-
    obj_size(ConvertedToCytoset)
    
+
    obj_size(ConvertedToCytoset)
    
 
    
 
    3.88 kB
    
 
    
 
    
 
    To go from a cytoSet to a flowSet, we can use the cytoset_to_flowSet() function.
    
 
    
-
    ConvertedToFlowset <- cytoset_to_flowSet(flowSet)
-ConvertedToFlowset
    
+
    ConvertedToFlowset <- cytoset_to_flowSet(flowSet)
+ConvertedToFlowset
    
 
    
 
    A flowSet with 6 experiments.
 
@@ -852,7 +871,7 @@ 
    Interconverting
    
 
    
 
    
 
    
-
    obj_size(ConvertedToFlowset)
    
+
    obj_size(ConvertedToFlowset)
    
 
    
 
    20.99 MB
    
 
    
@@ -862,14 +881,14 @@ 
    Interconverting
    
 
    Gating Sets
    
 
    Fortunately, regardless of whether we are using flowFrame/flowSet (RAM) and cytoframe/cytoset (memory pointers), both routes end up converging at the next step, where the underlying .fcs files are passed off to the GatingSet() function.
    
 
    
-
    GatingSet1 <- GatingSet(flowSet)
-GatingSet1 
    
+
    GatingSet1 <- GatingSet(flowSet)
+GatingSet1 
    
 
    
 
    A GatingSet with 6 samples
    
 
    
 
    
 
    
-
    class(GatingSet1)
    
+
    class(GatingSet1)
    
 
    
 
    [1] "GatingSet"
 attr(,"package")
@@ -877,14 +896,14 @@ 
    Gating Sets
    
 
    
 
    
 
    
-
    GatingSet2 <- GatingSet(cytoset)
-GatingSet2
    
+
    GatingSet2 <- GatingSet(cytoset)
+GatingSet2
    
 
    
 
    A GatingSet with 6 samples
    
 
    
 
    
 
    
-
    class(GatingSet1)
    
+
    class(GatingSet1)
    
 
    
 
    [1] "GatingSet"
 attr(,"package")
@@ -902,34 +921,34 @@ 
    CytoML
    
 
    Since our goal is to examine a fully assembled GatingSet object, we will be using it today to bring in a FlowJo workspace to R. However, since this is a free Cytometry in R course, and not about to have everyone pay for a license for a one-off topic, in the pre-course Floreada walkthrough I documented how to convert a free Floreada.io workspae into a FlowJo.wsp that can also be used (please note that as of early 2026, some scaling bugs may be present and require troubleshooting).
    
 
    To get started, let’s first attach CytoML to our local environment via the library() call.
    
 
    
-
    # BiocManager::install("CytoML") #Bioconductor
-library(CytoML)
    
+
    # BiocManager::install("CytoML") #Bioconductor
+library(CytoML)
    
 
    
 
    The .wsp files within this week’s data where created via Floreada.io. The main difference between the two files is one is a copy of the original that was opened within FlowJo, and subsequently swtiched from logicle to bi-exponential transformation.
    
 
    We will need to provide the appropiate file path for our desired .wsp file. We can start by identifying which are present using list.files()
    
 
    
-
    Folder # Defined Above
    
+
    Folder # Defined Above
    
 
    
 
    [1] "data"
    
 
    
-
    FlowJoWsp <- list.files(path = Folder, pattern = ".wsp", full = TRUE)
-FlowJoWsp
    
+
    FlowJoWsp <- list.files(path = Folder, pattern = ".wsp", full = TRUE)
+FlowJoWsp
    
 
    
 
    [1] "data/FlowJoWSP_OpenedCopy.wsp" "data/FlowJoWSP_Unopened.wsp"  
    
 
    
 
    
 
    In our case, we will proceed by using str_detect() to select the .wsp that contains the pattern “Opened”
    
 
    
-
    ThisWorkspace <- FlowJoWsp[stringr::str_detect(FlowJoWsp, "Opened")]
-ThisWorkspace
    
+
    ThisWorkspace <- FlowJoWsp[stringr::str_detect(FlowJoWsp, "Opened")]
+ThisWorkspace
    
 
    
 
    [1] "data/FlowJoWSP_OpenedCopy.wsp"
    
 
    
 
    
 
    With our single .wsp filepath now identified, we can now proceed to set up the intermediate object using open_flowjo_xml()
    
 
    
-
    ws <- open_flowjo_xml(ThisWorkspace)
-ws
    
+
    ws <- open_flowjo_xml(ThisWorkspace)
+ws
    
 
    
 
    File location:  data/FlowJoWSP_OpenedCopy.wsp 
 
@@ -939,7 +958,7 @@ 
    CytoML
    
 
    
 
    
 
    
-
    class(ws)
    
+
    class(ws)
    
 
    
 
    [1] "flowjo_workspace"
 attr(,"package")
@@ -949,7 +968,7 @@ 
    CytoML
    
 
    Having set up the intermediate flowjo_workspace object, we can attempt to read in the actual data from the .wsp into a GatingSet using the flowjo_to_gatingset() function.
    
 
    However, due to how I named the original .fcs files (“GROUPNAME” being individual specimens, “TUBENAME” being either Ctrl or SEB), and downsampled to the same number of cells, we will encounter the following error
    
 
    
-
    gs <- flowjo_to_gatingset(ws=ws, name=1, path = Folder)
    
+
    gs <- flowjo_to_gatingset(ws=ws, name=1, path = Folder)
    
 
    
 
    Error:
 ! Multiple FCS files match sample 00_Ctrl.fcs by filename, event count, and keywords.
@@ -959,7 +978,7 @@ 
    CytoML
    
 /home/david/Documents/CytometryInR/course/05_GatingSets/data/2025_07_26_AB_02_INF179_00_Ctrl.fcs
 Please move incorrect files out of this directory or its subdirectories.
    
 
    
-
    gs
    
+
    gs
    
 
    
 
    Error:
 ! object 'gs' not found
    
@@ -967,20 +986,20 @@ 
    CytoML
    
 
    
 
    As with any error, my first move is to check the help documentation. In this case, my initial response is to see if I can identify an argument that will help differentiate between the names for each specimen.
    
 
    
-
    ?flowjo_to_gatingset
    
+
    ?flowjo_to_gatingset
    
 
    
 
    
 
    In this case, I find that the “additional.keys” argument would likely work for this troubleshooting
    
 
    
 
    
-
    gs <- flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME")
-gs
    
+
    gs <- flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME")
+gs
    
 
    
 
    A GatingSet with 6 samples
    
 
    
 
    
 
    
-
    class(gs)
    
+
    class(gs)
    
 
    
 
    [1] "GatingSet"
 attr(,"package")
@@ -993,31 +1012,31 @@ 
    System Time
    
 
    Especially when working with CytoML, it is often good to have an idea of how long it will take a particular function to run (to better plan how to use our time while waiting, whether to go grab coffee, etc.). There are a couple ways to do so.
    
 
    One, using the system.time() function from base R, in which we surround whatever line of code we wish to evaluate in {}
    
 
    
-
    system.time({
-
-flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME")
-
-})
    
+
    system.time({
+
+flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME")
+
+})
    
 
    
 
       user  system elapsed 
-  0.501   0.008   0.509 
    
+  0.554   0.004   0.559 
    
 
    
 
    
 
    Alternatively, if we install the bench package, we can use the mark function to evaluate how long it takes on average across numerous iterations.
    
 
    
-
    # install.packages("bench") # CRAN
-library(bench)
    
+
    # install.packages("bench") # CRAN
+library(bench)
    
 
    
 
    
-
    mark(
-  Test <- flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME"),
-  iterations= 5
-  )
    
+
    mark(
+  Test <- flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME"),
+  iterations= 5
+  )
    
 
    
 
    # A tibble: 1 × 6
   expression                             min median `itr/sec` mem_alloc `gc/sec`
   <bch:expr>                           <bch> <bch:>     <dbl> <bch:byt>    <dbl>
-1 Test <- flowjo_to_gatingset(ws = ws… 505ms  527ms      1.92    13.3KB        0
    
+1 Test <- flowjo_to_gatingset(ws = ws… 539ms  550ms      1.78    13.3KB        0
    
 
    
 
    
 
    
@@ -1026,18 +1045,18 @@ 
    Gates
    
 
    Now that we have loaded the contents of the FlowJo/Floreada workspace, we can start exploring the various infrastructural capabilities of a GatingSet object.
    
 
    Let’s start by evaluating whether the manually-drawn gates I drew survived the journey. To do this, I can generate a visual gating treee using the plot() function.
    
 
    
-
    plot(gs)
    
+
    plot(gs)
    
 
    
 
    
 
    
-
    
+
    
 
    
 
    
 
    
 
    
 
    We can also retrieve the individual gates and their gaing paths using the gs_get_pop_paths() function.
    
 
    
-
    gs_get_pop_paths(gs)
    
+
    gs_get_pop_paths(gs)
    
 
    
 
     [1] "root"                                             
  [2] "/Scatter"                                         
@@ -1066,8 +1085,8 @@ 
    Gates
    
 
    Counts
    
 
    If we wanted to retrieve counts of cells found within the individual gates, we could do so with gs_pop_get_count_fast()
    
 
    
-
    Data <- gs_pop_get_count_fast(gs)
-head(Data, 5)
    
+
    Data <- gs_pop_get_count_fast(gs)
+head(Data, 5)
    
 
    
 
                     name                         Population
                <char>                             <char>
@@ -1090,7 +1109,7 @@ 
    Counts
    
 
    Metadata
    
 
    Since GatingSets contain multiple .fcs files, we may want to be able to subset them based on metadata for a particular variable. We can check to see current metadata using the pData() function.
    
 
    
-
    pData(gs)
    
+
    pData(gs)
    
 
    
 
                              name
 00_Ctrl.fcs_INF052 00_Ctrl.fcs
@@ -1103,10 +1122,10 @@ 
    Metadata
    
 
    
 
    It currently doesn’t have much, but we will explore how to change this more over the next few weeks. For now, just know that we could add additional metadata via either a .csv file, or by retrieving additional description keywords from within the .fcs files themselves (as shown below)
    
 
    
-
    AlternateGS <- flowjo_to_gatingset(ws=ws, name=1, path = Folder,
- additional.keys="GROUPNAME",
- keywords=c("$DATE", "$CYT", "GROUPNAME"))
-pData(AlternateGS)
    
+
    AlternateGS <- flowjo_to_gatingset(ws=ws, name=1, path = Folder,
+ additional.keys="GROUPNAME",
+ keywords=c("$DATE", "$CYT", "GROUPNAME"))
+pData(AlternateGS)
    
 
    
 
                       GROUPNAME   $CYT       $DATE        name
 00_Ctrl.fcs_INF052    INF052 Aurora 26-Jul-2025 00_Ctrl.fcs
@@ -1165,13 +1184,13 @@ 
    ggcyto
    
 
    packageVersion
    
 
    Let’s start off by checking what version of both the ggplot2 and ggcyto packages you currently have installed on your computer.
    
 
    
-
    packageVersion("ggplot2")
    
+
    packageVersion("ggplot2")
    
 
    
 
    [1] '4.0.2'
    
 
    
 
    
 
    
-
    packageVersion("ggcyto")
    
+
    packageVersion("ggcyto")
    
 
    
 
    [1] '1.39.1'
    
 
    
@@ -1184,8 +1203,8 @@ 
    packageVersion
    
 
    remove.packages
    
 
    Since ggcyto has a hard-coded dependency on ggplot2, if you have the older versions, I would recommend uninstaling both first, using the remove.packages() function.
    
 
    
-
    remove.packages("ggplot2")
-remove.packages("ggcyto")
    
+
    remove.packages("ggplot2")
+remove.packages("ggcyto")
    
 
    
 
    Once this is done, I recommend exiting and then reopening Positron. This will ensure all currently-loaded R packages are unattached from the environment. However, you will loose all your environmental variables, so will need to reload them to get back to this point. If you are working with code chunks inside a Quarto Markdown File (.qmd), you can quickly accomplish this by scrolling down to the point of the document where you left off, and selecting the “Run Above” option showin on the code chunk.
    
 
    
@@ -1194,11 +1213,11 @@ 
    remove.packages
    
 
    Installing correct versions
    
 
    To reinstall ggplot2, you just need to install again from CRAN (as with it’s rolling-release model any changes the developers make become immediately available to everyone)
    
 
    
-
    install.packages("ggplot2")
    
+
    install.packages("ggplot2")
    
 
    
 
    If you need to reinstall ggcyto, because of Bioconductor’s twice yearly release cycle, you will need to install the “developmental” version to take advantage of the fixes. Since this is for a one-off package, the easiest installation approach if to go via the GitHub using the remotes package’s install_github()
    
 
    
-
    remotes::install_github("RGLab/ggcyto")
    
+
    remotes::install_github("RGLab/ggcyto")
    
 
    
 
 
@@ -1206,8 +1225,8 @@ 
    Installing cor
 
    Plotting
    
 
    Once you have the current versions of both ggplot2 and ggcyto, we can proceed to attach them to your local environment via the library() function.
    
 
    
-
    library(ggplot2)
-library(ggcyto)
    
+
    library(ggplot2)
+library(ggcyto)
    
 
    
 
    Loading required package: ncdfFlow
    
 
    
@@ -1217,54 +1236,54 @@ 
    Plotting
    
 
    
 
    As was mentioned, ggcyto follows the ggplot2 grammar of graphics syntax, which we will learn more extensively next week. For now, lets look at a simple example
    
 
    
-
    ggcyto(gs[1], subset="root", aes(x="FSC-A", y="SSC-A")) + geom_hex(bins=100) 
    
+
    ggcyto(gs[1], subset="root", aes(x="FSC-A", y="SSC-A")) + geom_hex(bins=100) 
    
 
    
 
    The function responsible for plotting is the ggcyto() function. The first argument (“gs[1]”) is designating which .fcs file in our GatingSet we are trying to visualize.
    
 
    The second argument (“subset”) corresponds to which gating node we want to visualize. In this case, when set to “root”, we are seeing all cells present in the .fcs file. If we however wanted to visualize the cells within the CD4+ gate, we would swap the value provided to this argument.
    
 
    
-
    ggcyto(gs[1], subset="CD4+", aes(x="FSC-A", y="SSC-A")) + geom_hex(bins=100) 
    
+
    ggcyto(gs[1], subset="CD4+", aes(x="FSC-A", y="SSC-A")) + geom_hex(bins=100) 
    
 
    
 
    The next argument “aes” stands for aesthetics (more on this next week). You will notice it has its own set of parenthesis, in which we designate the markers/fluorophores we want to visualize on the x and y axis.
    
 
    The final argument (“+ geom_hex(bins=100)”) specifies we want to generate a flow cytometry style plot, with it’s bin arguments value setting the resolution.
    
 
    Now that we have walked through the arguments, let’s visualize the data
    
 
    
-
    ggcyto(gs[1], subset="CD4+", aes(x="FSC-A", y="SSC-A")) + geom_hex(bins=100) 
    
+
    ggcyto(gs[1], subset="CD4+", aes(x="FSC-A", y="SSC-A")) + geom_hex(bins=100) 
    
 
    
 
    
 
    
-
    
+
    
 
    
 
    
 
    
 
    
 
    Alternatively, if we switched things around
    
 
    
-
    ggcyto(gs[1], subset="CD8+", aes(x="IFNg", y="TNFa")) + geom_hex(bins=100) 
    
+
    ggcyto(gs[1], subset="CD8+", aes(x="IFNg", y="TNFa")) + geom_hex(bins=100) 
    
 
    
 
    
 
    
-
    
+
    
 
    
 
    
 
    
 
    
 
    Briefly, if we didn’t remember the marker, we could specify the fluorophore
    
 
    
-
    ggcyto(gs[1], subset="CD8+", aes(x="BV750-A", y="PE-Dazzle594-A")) + geom_hex(bins=100) 
    
+
    ggcyto(gs[1], subset="CD8+", aes(x="BV750-A", y="PE-Dazzle594-A")) + geom_hex(bins=100) 
    
 
    
 
    
 
    
-
    
+
    
 
    
 
    
 
    
 
    
 
    
-
    ggcyto(gs[6], subset="Tcells", aes(x="CD4", y="CD8")) + geom_hex(bins=100)
    
+
    ggcyto(gs[6], subset="Tcells", aes(x="CD4", y="CD8")) + geom_hex(bins=100)
    
 
    
 
    
 
    
-
    
+
    
 
    
 
    
 
    
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+  Cytometry in R – 05 - Gating Sets
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    05 - Gating Sets
    
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+David Rach 
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    2026-03-03
    
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    AGPL-3.0 CC BY-SA 4.0
    
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    Background
    
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    Welcome to the fifth week of the Cytometry in R course!!! At this point, we are through a significant portion of the “Intro to R” material, and will start encountering more “Cytometry-focused” material moving forward.
    
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    If we think of a typical flow cytometry experiment, there is more to the analysis than simply acquiring the .fcs file. While there is substantial information present within an .fcs file, in the context of analyzing them with commercial software, we rely on additional infrastructural elements to organize the various files, transform (scale), compensate (for conventional flow), visualize, derrive statistics, etc.
    
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    This infrastructural requirement within the R context is primarily handled by the flowCore and flowWorkspace R packages from Bioconductor. Today, we will build on what we learned during Week 03 but in the context of working and interacting with multiple .fcs files. This will provide a solid foundation to explore in greater depth how individual components of our typical workflow are represented within the R context.
    
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    Walk Through
    
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    Housekeeping
    
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    As we do every week, on GitHub, sync your forked version of the CytometryInR course to bring in the most recent updates. Then within Positron, pull in those changes to your local computer.
    
+
    After setting up a “Week05” project folder, copy over the contents of “course/05_GatingSets/data” to that folder. This will hopefully prevent merge issues next week when attempting to pull in new course material. Once you have your new project folder organized, remember to commit and push your changes to GitHub to maintain remote version control.
    
+
    If you encounter issues syncing due to the Take-Home Problem merge conflict, see this walkthrough. The updated homework submission protocol can be found here
    
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    flowFrame
    
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    Let’s start off by recalling the approach we first saw during Week 03, where using the flowCore package we loaded the contents of our .fcs file into R as a “flowFrame” object.
    
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    To do this, we first identified the .fcs files we were interested using file.path() to specify the folder, and list.files() to find contents containing “.fcs”.
    
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    # Folder <- file.path("course", "05_GatingSets", "data") # For Testing
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+ Folder <- file.path("data") # For Quarto Rendering
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+fcs_files <- list.files(Folder, pattern=".fcs", full.names=TRUE)
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+fcs_files
    
+
    
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    [1] "data/2025_07_26_AB_02_INF052_00_Ctrl.fcs"
+[2] "data/2025_07_26_AB_02_INF052_00_SEB.fcs" 
+[3] "data/2025_07_26_AB_02_INF100_00_Ctrl.fcs"
+[4] "data/2025_07_26_AB_02_INF100_00_SEB.fcs" 
+[5] "data/2025_07_26_AB_02_INF179_00_Ctrl.fcs"
+[6] "data/2025_07_26_AB_02_INF179_00_SEB.fcs" 
    
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    We then identified an individual .fcs file of interest using the [] method of indexing.
    
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    [1] "data/2025_07_26_AB_02_INF052_00_Ctrl.fcs"
    
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    Then, after making sure flowCore was attached to our local environment (via the library() function), we could use read.FCS() to read in our .fcs files contents to R.
    
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    # BiocManager::install("flowCore") #Bioconductor
+library(flowCore)
    
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    flowFrame <- read.FCS(filename=fcs_files[1], truncate_max_range = FALSE,
+ transformation = FALSE)
+flowFrame
    
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    flowFrame object '2025_07_26_AB_02_INF052_00_Ctrl.fcs'
+with 10000 cells and 43 observables:
+               name      desc     range  minRange    maxRange
+$P1            Time        NA    896745         0     878.809
+$P2           SSC-W        NA   4194304         0 4194303.000
+$P3           SSC-H        NA   4194304         0 4194303.000
+$P4           SSC-A        NA   4194304         0 4194303.000
+$P5           FSC-W        NA   4194304         0 4194303.000
+...             ...       ...       ...       ...         ...
+$P39     APC-R700-A    CD107a   4194304      -111     4192506
+$P40   Zombie NIR-A Viability   4194304      -111     4192506
+$P41 APC-Fire 750-A      CD27   4194304      -111     4192506
+$P42 APC-Fire 810-A      CCR7   4194304      -111     4192506
+$P43           AF-A        NA   4194304      -111     4194303
+472 keywords are stored in the 'description' slot
    
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    As we start to think about the wider infrastructural handling of our .fcs files, what would have occurred if we had provided multiple .fcs file paths to read.FCS()? Let’s go ahead and check by not providing an index number.
    
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    Error in `read.FCS()`:
+! 'filename' must be character scalar
    
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    As you can tell, this error message is not particularly interpretable. It however arises from type of object we are passing to the function, whereby an individual file.path (fcs_files[1]) appears as class “character” with a single value (ie. a scalar), but the combined vector (fcs_files) contains multiple values.
    
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    fcs_files[1]
    
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    [1] "data/2025_07_26_AB_02_INF052_00_Ctrl.fcs"
    
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    str(fcs_files[1])
    
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     chr "data/2025_07_26_AB_02_INF052_00_Ctrl.fcs"
    
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    fcs_files
    
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    [1] "data/2025_07_26_AB_02_INF052_00_Ctrl.fcs"
+[2] "data/2025_07_26_AB_02_INF052_00_SEB.fcs" 
+[3] "data/2025_07_26_AB_02_INF100_00_Ctrl.fcs"
+[4] "data/2025_07_26_AB_02_INF100_00_SEB.fcs" 
+[5] "data/2025_07_26_AB_02_INF179_00_Ctrl.fcs"
+[6] "data/2025_07_26_AB_02_INF179_00_SEB.fcs" 
    
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    str(fcs_files)
    
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     chr [1:6] "data/2025_07_26_AB_02_INF052_00_Ctrl.fcs" ...
    
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    flowSet
    
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    Consequently, we will need to use another function if we want to read in multiple .fcs files at once. For flowCore, this function is the read.flowSet() function.
    
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    flowSet <- read.flowSet(files=fcs_files, truncate_max_range = FALSE,
+ transformation = FALSE)
+flowSet
    
+
    
+
    A flowSet with 6 experiments.
+
+column names(43): Time SSC-W ... APC-Fire 810-A AF-A
    
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    Alternatively, we can designate specific files within “fcs_files” we want to read in using the [] and c() notation style we have encountered previously.
    
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    read.flowSet(files=fcs_files[c(1, 3:4)],
+ truncate_max_range = FALSE, transformation = FALSE)
    
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    A flowSet with 3 experiments.
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+column names(43): Time SSC-W ... APC-Fire 810-A AF-A
    
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    On follow-up, we can see that read.flowSet() has created a “flowSet” class object.
    
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    class(flowSet)
    
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    [1] "flowSet"
+attr(,"package")
+[1] "flowCore"
    
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    Which we can also confirm by glancing at the right secondary sidebar to see the created Variables within our environment. Applying our investigatory skills from Week 3, we surmise that “flowSet” is another Bioconductor style S4-type object that within its frame slot contains individual “flowFrames”.
    
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    If instead of class() we had used str(), we would have seen a similar output ton what we see in the Variables panel.
    
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    str(flowSet)
    
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+
    Formal class 'flowSet' [package "flowCore"] with 2 slots
+  ..@ frames   :<environment: 0x55684288f168> 
+  ..@ phenoData:Formal class 'AnnotatedDataFrame' [package "Biobase"] with 4 slots
+  .. .. ..@ varMetadata      :'data.frame': 1 obs. of  1 variable:
+  .. .. .. ..$ labelDescription: chr "Name"
+  .. .. ..@ data             :'data.frame': 6 obs. of  1 variable:
+  .. .. .. ..$ name: 'AsIs' chr [1:6] "2025_07_26_AB_02_INF052_00_Ctrl.fcs" "2025_07_26_AB_02_INF052_00_SEB.fcs" "2025_07_26_AB_02_INF100_00_Ctrl.fcs" "2025_07_26_AB_02_INF100_00_SEB.fcs" ...
+  .. .. ..@ dimLabels        : chr [1:2] "rowNames" "columnNames"
+  .. .. ..@ .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slot
+  .. .. .. .. ..@ .Data:List of 1
+  .. .. .. .. .. ..$ : int [1:3] 1 1 0
+  .. .. .. .. ..$ names: chr "AnnotatedDataFrame"
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    Reminder
    
+
    
+
    
+
    While not today’s focus, remember we could access individual components inside the flowSet using the @ accessors covered during Week 3
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    Memory Usage
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Both “flowFrame” and “flowSet” objects were implemented in the flowCore package, which is the oldest extant flow cytometry R package on Bioconductor. Consequently, a large proportion of the other flow cytometry R packages read in .fcs files as “flowFrame” and “flowSet” objects.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    One consideration of this method is the contents of your .fcs files are read into your computer’s random access memory (RAM). While for individual .fcs files or small experiments this will not present a problem for most modern computers, when working with large spectral flow cytometry files containing millions of events (or trying to analyze many .fcs files at once), you may encounter situations where you can quickly exceed your computers available RAM.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    To build some contextual understanding of the problem, let’s learn how to check how much memory is being used by our individual variables/objects within our R session. We will primarily use the lobstr R packages obj_size() function, as it better handles evaluating complicated objects than base R’s object.size() function.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    We can check and see the memory usage by our flowFrame object
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    # Base R
+object.size(flowFrame)
    
+
    
+
    3570896 bytes
    
+
    
+
    # install.packages("lobstr") # CRAN
+library(lobstr)
+obj_size(flowFrame)
    
+
    
+
    3.53 MB
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    And contrast to the greater ammount of space occupied by our flowSet object (which contains multiple flowFrames)
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    obj_size(flowSet)
    
+
    
+
    20.99 MB
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    If we were curious how much memory total we are using within R at the current moment, we can check using the mem_used() function:
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    mem_used()
    
+
    
+
    146.81 MB
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Ultimately, how many .fcs files you are able to read in and interact with before running out of available RAM memory space will be dictated by your individual computers hardware configuration. There are various ways you can check programmatically how much RAM your computer has available, although the specific functions will vary depending on your computers operating system, since they often involve system-level code outside R. Using the ps R package’s ps_system_memory() function is one of the easier ways for Windows users.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    To simplify the process, here is an additional example of where a conditional can prove useful, allowing us to check in an operating system specific manner. It takes the output of the Sys.info() function, namely the “sysname” argument and then retrieves the relavent function.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    OperatingSystem <- Sys.info()[["sysname"]]
+
+if (OperatingSystem == "Windows") { # Windows
+  # install.packages("ps") # CRAN
+   Memory <- ps::ps_system_memory()
+   message("Total GB ", round(Memory$total / 1024^3, 2))
+   message("Free GB ", round(Memory$free / 1024^3, 2))
+
+  } else if (OperatingSystem == "Darwin") { # MacOS
+    system("top -l 1 | grep PhysMem")
+
+  } else if (OperatingSystem == "Linux") { # Linux
+    system("free -h")
+
+  } else {message("A wild FreeBSD-User appears")}
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    # install.packages("ps") # CRAN
+library(ps)
+Memory <- ps::ps_system_memory()
+message("Total GB ", round(Memory$total / 1024^3, 2))
+message("Free GB ", round(Memory$free / 1024^3, 2))
    
+
    
+
    
+
    
+
    
+
    cytoframe
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    In addition to the flowCore R package, additional flow cytometry infrastructure support is provided by the flowWorkspace package. Instead of the reading all the .fcs files contents into active RAM, flowWorkspace reduces the memory overhead by using “pointers” to interact with the object in it’s current storage location (either on your harddrive, SSD, etc.), only reading in components to RAM as needed.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    # BiocManager::install("flowWorkspace") #Bioconductor
+library(flowWorkspace)
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Because of these differences in how data is interracted with, we end up with parallel equivalents to the traditional flowFrame and flowSet type objects. These include “cytoframe” for single .fcs files
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    cytoframe <- load_cytoframe_from_fcs(fcs_files[1], truncate_max_range = FALSE, transformation = FALSE)
+
+cytoframe
    
+
    
+
    cytoframe object '2025_07_26_AB_02_INF052_00_Ctrl.fcs'
+with 10000 cells and 43 observables:
+               name      desc       range  minRange    maxRange
+$P1            Time        NA     878.809         0     878.809
+$P2           SSC-W        NA 4194303.000         0 4194303.000
+$P3           SSC-H        NA 4194303.000         0 4194303.000
+$P4           SSC-A        NA 4194303.000         0 4194303.000
+$P5           FSC-W        NA 4194303.000         0 4194303.000
+...             ...       ...         ...       ...         ...
+$P39     APC-R700-A    CD107a     4192506      -111     4192506
+$P40   Zombie NIR-A Viability     4192506      -111     4192506
+$P41 APC-Fire 750-A      CD27     4192506      -111     4192506
+$P42 APC-Fire 810-A      CCR7     4192506      -111     4192506
+$P43           AF-A        NA     4194303      -111     4194303
+472 keywords are stored in the 'description' slot
+row names(0):
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    class(cytoframe)
    
+
    
+
    [1] "cytoframe"
+attr(,"package")
+[1] "flowWorkspace"
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Which also still errors out when not given a scalar object
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    load_cytoframe_from_fcs(fcs_files, truncate_max_range = FALSE, transformation = FALSE)
    
+
    
+
    Error:
+! Expected string vector of length 1
    
+
    
+
    
+
    
+
    
+
    
+
    cytoset
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    As well as “cytoset” to handle multiple .fcs files.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    cytoset <- load_cytoset_from_fcs(fcs_files, truncate_max_range = FALSE, transformation = FALSE)
+
+cytoset
    
+
    
+
    A cytoset with 6 samples.
+
+  column names:
+    Time, SSC-W, SSC-H, SSC-A, FSC-W, FSC-H, FSC-A, SSC-B-W, SSC-B-H, SSC-B-A, BUV395-A, BUV563-A, BUV615-A, BUV661-A, BUV737-A, BUV805-A, Pacific Blue-A, BV480-A, BV570-A, BV605-A, BV650-A, BV711-A, BV750-A, BV786-A, Alexa Fluor 488-A, Spark Blue 550-A, Spark Blue 574-A, RB613-A, RB705-A, RB780-A, PE-A, PE-Dazzle594-A, PE-Cy5-A, PE-Fire 700-A, PE-Fire 744-A, PE-Vio770-A, APC-A, Alexa Fluor 647-A, APC-R700-A, Zombie NIR-A, APC-Fire 750-A, APC-Fire 810-A, AF-A
    
+
    
+
    
+
    
+
    
+
    
+
    class(cytoset)
    
+
    
+
    [1] "cytoset"
+attr(,"package")
+[1] "flowWorkspace"
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Unlike “flowFrame” and “flowSet”, when we run str(), for “cytoframe” and “cytoset” objects we don’t get back quite as much information.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    str(cytoframe)
    
+
    
+
    Formal class 'cytoframe' [package "flowWorkspace"] with 5 slots
+  ..@ pointer    :<externalptr> 
+  ..@ use.exprs  : logi TRUE
+  ..@ exprs      : num[0 , 0 ] 
+  ..@ parameters :Formal class 'AnnotatedDataFrame' [package "Biobase"] with 4 slots
+  .. .. ..@ varMetadata      :'data.frame': 5 obs. of  1 variable:
+  .. .. .. ..$ labelDescription: chr [1:5] "Name of Parameter" "Description of Parameter" "Range of Parameter" "Minimum Parameter Value after Transformation" ...
+  .. .. ..@ data             :'data.frame': 0 obs. of  5 variables:
+  .. .. .. ..$ name       : chr(0) 
+  .. .. .. ..$ description: chr(0) 
+  .. .. .. ..$ range      : num(0) 
+  .. .. .. ..$ minRange   : num(0) 
+  .. .. .. ..$ maxRange   : num(0) 
+  .. .. ..@ dimLabels        : chr [1:2] "rowNames" "columnNames"
+  .. .. ..@ .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slot
+  .. .. .. .. ..@ .Data:List of 1
+  .. .. .. .. .. ..$ : int [1:3] 1 1 0
+  .. .. .. .. ..$ names: chr "AnnotatedDataFrame"
+  ..@ description:List of 1
+  .. ..$ note: chr "empty"
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    str(cytoset)
    
+
    
+
    Formal class 'cytoset' [package "flowWorkspace"] with 3 slots
+  ..@ pointer  :<externalptr> 
+  ..@ frames   :<environment: 0x55684dc35038> 
+  ..@ phenoData:Formal class 'AnnotatedDataFrame' [package "Biobase"] with 4 slots
+  .. .. ..@ varMetadata      :'data.frame': 0 obs. of  1 variable:
+  .. .. .. ..$ labelDescription: chr(0) 
+  .. .. ..@ data             :'data.frame': 0 obs. of  0 variables
+  .. .. ..@ dimLabels        : chr [1:2] "rowNames" "columnNames"
+  .. .. ..@ .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slot
+  .. .. .. .. ..@ .Data:List of 1
+  .. .. .. .. .. ..$ : int [1:3] 1 1 0
+  .. .. .. .. ..$ names: chr "AnnotatedDataFrame"
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    This is similarly the case when glancing at the right secondary side bar, as the respective objects under variables appear to have empty matrices where normally we would have seen the MFI values.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Due to flowWorkspace use of pointers, the missing data remains stored on the drive, only being retrieved right before it is required. This reduces the overall RAM utilization. Let’s double check the differences in memory utilization for flowFrame/cytoframe:
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    obj_size(flowFrame)
    
+
    
+
    3.53 MB
    
+
    
+
    
+
    
+
    
+
    
+
    obj_size(cytoframe)
    
+
    
+
    5.40 kB
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    And similarly the case for flowSet and cytoset:
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    obj_size(flowSet)
    
+
    
+
    20.99 MB
    
+
    
+
    
+
    
+
    
+
    
+
    obj_size(cytoset)
    
+
    
+
    3.88 kB
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Additionally, with computer hardware increasingly switching from spinning disk hard-drives to faster solid state drives, the performance penalty previously experienced when not running from RAM is not as large of a concern as in previous years.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    Interconverting
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Despite both R packages having been around for a while, many Bioconductor and GitHub often only implement methods to handle either flowFrames or cytoframes (although newer R packages are now allowing for both). Consequently, as we move forward in the course, it helps to be aware of which ones we are working with, and have the ability to interconvert between them as needed.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    To go from a flowFrame to a cytoframe, we can use the flowFrame_to_cytoframe() function
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    ConvertedToCytoframe <- flowFrame_to_cytoframe(flowFrame)
+ConvertedToCytoframe
    
+
    
+
    cytoframe object 'file376c7b6c7cf1'
+with 10000 cells and 43 observables:
+               name      desc       range  minRange    maxRange
+$P1            Time        NA     878.809         0     878.809
+$P2           SSC-W        NA 4194303.000         0 4194303.000
+$P3           SSC-H        NA 4194303.000         0 4194303.000
+$P4           SSC-A        NA 4194303.000         0 4194303.000
+$P5           FSC-W        NA 4194303.000         0 4194303.000
+...             ...       ...         ...       ...         ...
+$P39     APC-R700-A    CD107a     4192506      -111     4192506
+$P40   Zombie NIR-A Viability     4192506      -111     4192506
+$P41 APC-Fire 750-A      CD27     4192506      -111     4192506
+$P42 APC-Fire 810-A      CCR7     4192506      -111     4192506
+$P43           AF-A        NA     4194303      -111     4194303
+472 keywords are stored in the 'description' slot
+row names(0):
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    obj_size(ConvertedToCytoframe)
    
+
    
+
    5.40 kB
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    To go from a cytoframe to a flowFrame, we can use the cytoframe_to_flowFrame() function
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    ConvertedToFlowframe <- flowWorkspace::cytoframe_to_flowFrame(cytoframe)
+ConvertedToFlowframe
    
+
    
+
    flowFrame object '2025_07_26_AB_02_INF052_00_Ctrl.fcs'
+with 10000 cells and 43 observables:
+               name      desc       range  minRange    maxRange
+$P1            Time        NA     878.809         0     878.809
+$P2           SSC-W        NA 4194303.000         0 4194303.000
+$P3           SSC-H        NA 4194303.000         0 4194303.000
+$P4           SSC-A        NA 4194303.000         0 4194303.000
+$P5           FSC-W        NA 4194303.000         0 4194303.000
+...             ...       ...         ...       ...         ...
+$P39     APC-R700-A    CD107a     4192506      -111     4192506
+$P40   Zombie NIR-A Viability     4192506      -111     4192506
+$P41 APC-Fire 750-A      CD27     4192506      -111     4192506
+$P42 APC-Fire 810-A      CCR7     4192506      -111     4192506
+$P43           AF-A        NA     4194303      -111     4194303
+472 keywords are stored in the 'description' slot
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    obj_size(ConvertedToFlowframe)
    
+
    
+
    3.53 MB
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    To go from a flowSet to a cytoSet, we can use the flowSet_to_cytoset() funciton
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    ConvertedToCytoset <- flowSet_to_cytoset(flowSet)
+ConvertedToCytoset
    
+
    
+
    A cytoset with 6 samples.
+
+  column names:
+    Time, SSC-W, SSC-H, SSC-A, FSC-W, FSC-H, FSC-A, SSC-B-W, SSC-B-H, SSC-B-A, BUV395-A, BUV563-A, BUV615-A, BUV661-A, BUV737-A, BUV805-A, Pacific Blue-A, BV480-A, BV570-A, BV605-A, BV650-A, BV711-A, BV750-A, BV786-A, Alexa Fluor 488-A, Spark Blue 550-A, Spark Blue 574-A, RB613-A, RB705-A, RB780-A, PE-A, PE-Dazzle594-A, PE-Cy5-A, PE-Fire 700-A, PE-Fire 744-A, PE-Vio770-A, APC-A, Alexa Fluor 647-A, APC-R700-A, Zombie NIR-A, APC-Fire 750-A, APC-Fire 810-A, AF-A
    
+
    
+
    
+
    
+
    
+
    
+
    obj_size(ConvertedToCytoset)
    
+
    
+
    3.88 kB
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    To go from a cytoSet to a flowSet, we can use the cytoset_to_flowSet() function.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    ConvertedToFlowset <- cytoset_to_flowSet(flowSet)
+ConvertedToFlowset
    
+
    
+
    A flowSet with 6 experiments.
+
+column names(43): Time SSC-W ... APC-Fire 810-A AF-A
    
+
    
+
    
+
    
+
    
+
    
+
    obj_size(ConvertedToFlowset)
    
+
    
+
    20.99 MB
    
+
    
+
    
+
    
+
    
+
    
+
    Gating Sets
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Fortunately, regardless of whether we are using flowFrame/flowSet (RAM) and cytoframe/cytoset (memory pointers), both routes end up converging at the next step, where the underlying .fcs files are passed off to the GatingSet() function.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    GatingSet1 <- GatingSet(flowSet)
+GatingSet1 
    
+
    
+
    A GatingSet with 6 samples
    
+
    
+
    
+
    
+
    
+
    
+
    class(GatingSet1)
    
+
    
+
    [1] "GatingSet"
+attr(,"package")
+[1] "flowWorkspace"
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    GatingSet2 <- GatingSet(cytoset)
+GatingSet2
    
+
    
+
    A GatingSet with 6 samples
    
+
    
+
    
+
    
+
    
+
    
+
    class(GatingSet1)
    
+
    
+
    [1] "GatingSet"
+attr(,"package")
+[1] "flowWorkspace"
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    As we prefaced in the background, beyond the .fcs files themselves, we need infrastructural elements with which to interact with the underlying data, which allows us to organize the various files, transform (scale), compensate (for conventional flow), visualize, derrive statistics, etc. A GatingSet serves as the infrastructural framework that allows us to do this in R.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    If we investigate our current GatingSet objects, we won’t see much
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    This will change as we start layering on additional elements. However, rather than try to cram everything into a single week, we will explore in greater depth the individual components over the next three weeks. Instead, for the rest of today, we will work backward, by exploring a GatingSet objecct and what it is capable of doing once fully assembled.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    CytoML
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    The CytoML R package (also maintained by Mike Jiang) is a sister package to the flowWorkspace. It’s main purpose is to permit bringing in existing FlowJo, Diva and Cytobank Workspaces, with all their gates, transformations, etc. into R as fully assembled GatingSet objects. For those who already use one of these commercial softwares, it can be quite useful tool.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Since our goal is to examine a fully assembled GatingSet object, we will be using it today to bring in a FlowJo workspace to R. However, since this is a free Cytometry in R course, and not about to have everyone pay for a license for a one-off topic, in the pre-course Floreada walkthrough I documented how to convert a free Floreada.io workspae into a FlowJo.wsp that can also be used (please note that as of early 2026, some scaling bugs may be present and require troubleshooting).
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    To get started, let’s first attach CytoML to our local environment via the library() call.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    # BiocManager::install("CytoML") #Bioconductor
+library(CytoML)
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    The .wsp files within this week’s data where created via Floreada.io. The main difference between the two files is one is a copy of the original that was opened within FlowJo, and subsequently swtiched from logicle to bi-exponential transformation.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    We will need to provide the appropiate file path for our desired .wsp file. We can start by identifying which are present using list.files()
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    Folder # Defined Above
    
+
    
+
    [1] "data"
    
+
    
+
    FlowJoWsp <- list.files(path = Folder, pattern = ".wsp", full = TRUE)
+FlowJoWsp
    
+
    
+
    [1] "data/FlowJoWSP_OpenedCopy.wsp" "data/FlowJoWSP_Unopened.wsp"  
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    In our case, we will proceed by using str_detect() to select the .wsp that contains the pattern “Opened”
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    ThisWorkspace <- FlowJoWsp[stringr::str_detect(FlowJoWsp, "Opened")]
+ThisWorkspace
    
+
    
+
    [1] "data/FlowJoWSP_OpenedCopy.wsp"
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    With our single .wsp filepath now identified, we can now proceed to set up the intermediate object using open_flowjo_xml()
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    ws <- open_flowjo_xml(ThisWorkspace)
+ws
    
+
    
+
    File location:  data/FlowJoWSP_OpenedCopy.wsp 
+
+Groups in Workspace
+         Name Num.Samples
+1 All Samples           6
    
+
    
+
    
+
    
+
    
+
    
+
    class(ws)
    
+
    
+
    [1] "flowjo_workspace"
+attr(,"package")
+[1] "CytoML"
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Having set up the intermediate flowjo_workspace object, we can attempt to read in the actual data from the .wsp into a GatingSet using the flowjo_to_gatingset() function.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    However, due to how I named the original .fcs files (“GROUPNAME” being individual specimens, “TUBENAME” being either Ctrl or SEB), and downsampled to the same number of cells, we will encounter the following error
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    gs <- flowjo_to_gatingset(ws=ws, name=1, path = Folder)
    
+
    
+
    Error:
+! Multiple FCS files match sample 00_Ctrl.fcs by filename, event count, and keywords.
+Candidates are: 
+/home/david/Documents/CytometryInR/course/05_GatingSets/data/2025_07_26_AB_02_INF052_00_Ctrl.fcs
+/home/david/Documents/CytometryInR/course/05_GatingSets/data/2025_07_26_AB_02_INF100_00_Ctrl.fcs
+/home/david/Documents/CytometryInR/course/05_GatingSets/data/2025_07_26_AB_02_INF179_00_Ctrl.fcs
+Please move incorrect files out of this directory or its subdirectories.
    
+
    
+
    gs
    
+
    
+
    Error:
+! object 'gs' not found
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    As with any error, my first move is to check the help documentation. In this case, my initial response is to see if I can identify an argument that will help differentiate between the names for each specimen.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    ?flowjo_to_gatingset
    
+
    
+
    
+
    
+
    
+
+
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    In this case, I find that the “additional.keys” argument would likely work for this troubleshooting
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
+
    
+
    
+
+
    
+
    
+
    gs <- flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME")
+gs
    
+
    
+
    A GatingSet with 6 samples
    
+
    
+
    
+
    
+
    
+
    
+
    class(gs)
    
+
    
+
    [1] "GatingSet"
+attr(,"package")
+[1] "flowWorkspace"
    
+
    
+
    
+
    
+
    
+
    
+
    System Time
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Especially when working with CytoML, it is often good to have an idea of how long it will take a particular function to run (to better plan how to use our time while waiting, whether to go grab coffee, etc.). There are a couple ways to do so.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    One, using the system.time() function from base R, in which we surround whatever line of code we wish to evaluate in {}
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    system.time({
+
+flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME")
+
+})
    
+
    
+
       user  system elapsed 
+  0.508   0.008   0.518 
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Alternatively, if we install the bench package, we can use the mark function to evaluate how long it takes on average across numerous iterations.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    # install.packages("bench") # CRAN
+library(bench)
    
+
    
+
    
+
    
+
    
+
    mark(
+  Test <- flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys="GROUPNAME"),
+  iterations= 5
+  )
    
+
    
+
    # A tibble: 1 × 6
+  expression                             min median `itr/sec` mem_alloc `gc/sec`
+  <bch:expr>                           <bch> <bch:>     <dbl> <bch:byt>    <dbl>
+1 Test <- flowjo_to_gatingset(ws = ws… 515ms  528ms      1.88    13.3KB        0
    
+
    
+
    
+
    
+
    
+
    
+
    Gates
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Now that we have loaded the contents of the FlowJo/Floreada workspace, we can start exploring the various infrastructural capabilities of a GatingSet object.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Let’s start by evaluating whether the manually-drawn gates I drew survived the journey. To do this, I can generate a visual gating treee using the plot() function.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    plot(gs)
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    We can also retrieve the individual gates and their gaing paths using the gs_get_pop_paths() function.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    gs_get_pop_paths(gs)
    
+
    
+
     [1] "root"                                             
+ [2] "/Scatter"                                         
+ [3] "/Scatter/Singlets"                                
+ [4] "/Scatter/Singlets/Live"                           
+ [5] "/Scatter/Singlets/Live/Tcells"                    
+ [6] "/Scatter/Singlets/Live/Tcells/CD4+"               
+ [7] "/Scatter/Singlets/Live/Tcells/CD4+/TNFa+IFNg+"    
+ [8] "/Scatter/Singlets/Live/Tcells/CD4+/TNFa+IFNg-"    
+ [9] "/Scatter/Singlets/Live/Tcells/CD4+/TNFa-IFNg+"    
+[10] "/Scatter/Singlets/Live/Tcells/CD4+/TNFa-IFNg-"    
+[11] "/Scatter/Singlets/Live/Tcells/CD4-CD8-"           
+[12] "/Scatter/Singlets/Live/Tcells/CD4-CD8-/TNFa+IFNg+"
+[13] "/Scatter/Singlets/Live/Tcells/CD4-CD8-/TNFa+IFNg-"
+[14] "/Scatter/Singlets/Live/Tcells/CD4-CD8-/TNFa-IFNg+"
+[15] "/Scatter/Singlets/Live/Tcells/CD4-CD8-/TNFa-IFNg-"
+[16] "/Scatter/Singlets/Live/Tcells/CD8+"               
+[17] "/Scatter/Singlets/Live/Tcells/CD8+/TNFa+IFNg+"    
+[18] "/Scatter/Singlets/Live/Tcells/CD8+/TNFa+IFNg-"    
+[19] "/Scatter/Singlets/Live/Tcells/CD8+/TNFa-IFNg+"    
+[20] "/Scatter/Singlets/Live/Tcells/CD8+/TNFa-IFNg-"    
    
+
    
+
    
+
    
+
    
+
    
+
    Counts
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    If we wanted to retrieve counts of cells found within the individual gates, we could do so with gs_pop_get_count_fast()
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    Data <- gs_pop_get_count_fast(gs)
+head(Data, 5)
    
+
    
+
                     name                         Population
+               <char>                             <char>
+1: 00_Ctrl.fcs_INF052                           /Scatter
+2: 00_Ctrl.fcs_INF052                  /Scatter/Singlets
+3: 00_Ctrl.fcs_INF052             /Scatter/Singlets/Live
+4: 00_Ctrl.fcs_INF052      /Scatter/Singlets/Live/Tcells
+5: 00_Ctrl.fcs_INF052 /Scatter/Singlets/Live/Tcells/CD4+
+                          Parent Count ParentCount
+                          <char> <int>       <int>
+1:                          root 10000       10000
+2:                      /Scatter  9986       10000
+3:             /Scatter/Singlets  9708        9986
+4:        /Scatter/Singlets/Live  9708        9708
+5: /Scatter/Singlets/Live/Tcells  6151        9708
    
+
    
+
    
+
    
+
    
+
    
+
    Metadata
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Since GatingSets contain multiple .fcs files, we may want to be able to subset them based on metadata for a particular variable. We can check to see current metadata using the pData() function.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    pData(gs)
    
+
    
+
                              name
+00_Ctrl.fcs_INF052 00_Ctrl.fcs
+00_Ctrl.fcs_INF100 00_Ctrl.fcs
+00_Ctrl.fcs_INF179 00_Ctrl.fcs
+00_SEB.fcs_INF052   00_SEB.fcs
+00_SEB.fcs_INF100   00_SEB.fcs
+00_SEB.fcs_INF179   00_SEB.fcs
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    It currently doesn’t have much, but we will explore how to change this more over the next few weeks. For now, just know that we could add additional metadata via either a .csv file, or by retrieving additional description keywords from within the .fcs files themselves (as shown below)
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    AlternateGS <- flowjo_to_gatingset(ws=ws, name=1, path = Folder,
+ additional.keys="GROUPNAME",
+ keywords=c("$DATE", "$CYT", "GROUPNAME"))
+pData(AlternateGS)
    
+
    
+
                       GROUPNAME   $CYT       $DATE        name
+00_Ctrl.fcs_INF052    INF052 Aurora 26-Jul-2025 00_Ctrl.fcs
+00_Ctrl.fcs_INF100    INF100 Aurora 26-Jul-2025 00_Ctrl.fcs
+00_Ctrl.fcs_INF179    INF179 Aurora 26-Jul-2025 00_Ctrl.fcs
+00_SEB.fcs_INF052     INF052 Aurora 26-Jul-2025  00_SEB.fcs
+00_SEB.fcs_INF100     INF100 Aurora 26-Jul-2025  00_SEB.fcs
+00_SEB.fcs_INF179     INF179 Aurora 26-Jul-2025  00_SEB.fcs
    
+
    
+
    
+
    
+
    
+
    
+
    ggcyto
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    As you can surmise, a lot of the infrastructural style handling done by commercial softwares is being orchestrated/mediated through our GatingSet object. Since it’s able to create and retain gating information, how would we go about visualizing the underlying data contained within each?
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Within R, most plots are generated using the ggplot2 package from the tidyverse (which we will explore next week), which builds of the “Grammar of Graphics” concept, combining layers together to create the final plots. The Bioconductor ggcyto R package extends this concept to enable flow cytometry data contained within a GatingSet to be plotted.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
+
    
+
    Important
    
+
    
+
    
+
    As is the case with most free open-source software (FOSS), R packages will change over time as their developers add new features, make improvements, or alter internal functions to speed things up.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    Important
    
+
    
+
    
+
    ggplot2 recently had a major version change, with significant internal changes occuring. As a consequence of these changes, ggcyto functions that relied on the old ggplot2 functions broke and had to be updated.
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
+
    
+
    Important
    
+
    
+
    
+
    Any updates to CRAN packages are reflected immediately. By contrast, Bioconductor is on a twice yearly release cycle, so to take advantage of the ggcyto “fixes” that allow it to interact with the new version of ggplot2, we will need to make sure we have the “developmental” version installed.
    
+
    
+
    
+
    
+
    
+
    
+
+
    packageVersion
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Let’s start off by checking what version of both the ggplot2 and ggcyto packages you currently have installed on your computer.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    packageVersion("ggplot2")
    
+
    
+
    [1] '4.0.2'
    
+
    
+
    
+
    
+
    
+
    
+
    packageVersion("ggcyto")
    
+
    
+
    [1] '1.39.1'
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    If you were able to retrieve the following package versions (or greater”) for ggplot2 and ggcyto, you should be all set and can skip the subsequent reinstallation steps.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    If you however found you have the older package versions (ex. ggplot2 3.5.2 or ggcyto 1.37.1) currently installed, you will likely encounter errors when trying to run the functions to plot your data below (since the changes are not fully backward-compatible with older versions).
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    remove.packages
    
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Since ggcyto has a hard-coded dependency on ggplot2, if you have the older versions, I would recommend uninstaling both first, using the remove.packages() function.
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    
+
    remove.packages("ggplot2")
+remove.packages("ggcyto")
    
+
    
+
    
+
    
+
    
+
+
    
+
    
+
    
+
    
+
    
+
    
+
+
    
+
    .
    
+
    
+
    
+
    Once this is done, I recommend exiting and then reopening Positron. This will ensure all currently-loaded R packages are unattached from the environment. However, you will loose all your environmental variables, so will need to reload them to get back to this point. If you are working with code chunks inside a Quarto Markdown File (.qmd), you can quickly accomplish this by scrolling down to the point of the document where you left off, and selecting the “Run Above” option showin on the code chunk.
    
+
    
+
    
+
    
+
    
+
    
+
    
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    Today, we looked at the two main representations of flow cytometry data in R, the older flowCore implemented flowFrame/flowSet objects that are stored in RAM, and the flowWorkspace cytoFrame/cytoSet objects that operate through memory pointers. We started our learning journey to understand GatingSet objects, and how to use them to mediate/orchestrate in R many of the infrastructural steps that would normally be performed by commercial software. And finally, we briefly covered how to use the ggcyto to visualize data contained within our GatingSets.
    
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    Similar to our utilization of tidyverse functions last week, we will be using GatingSets continously throughout the rest of the course. Over the next few weeks we will instead of retrieving already assembled GatingSets via CytoML assemble them from scratch within R.
    
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    Additional Resources
    
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    flowWorkspace Bioconductor Vignette The Bioconductor vignettes are always a good place to start with any of the Cytoverse packages, the vignette for flowWorkspace is no exception. If you want to understand more about how to subset cytosets, or the various functions and arguments in a GatingSet, this should be your first stop.
    
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    CytoML Bioconductor Vignette If you use FlowJo, Diva, or CytoBank routinely, and want to understand more about how to bring in your own experiments to R, the CytoML vignettes should be your next stop.
    
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    ggcyto Bioconductor Vignette. There are several vignettes that can be found on the ggcyto Bioconductor website on how to plot your flow cytometry data, this one surmize many of the points we will be covering over the next few weeks.
    
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    Bioc2023 Workshop: Reproducible and programmatic analysis of flow cytometry experiments with the cytoverse Ozette hosted a workshop covering many of the cytoverse R packages at the Bioconductor conference (BioC) back in 2023. Some of the contents we will cover in greater depth over the next few weeks.
    
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  • - +
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    + + + + +
    + + + + +

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    AGPL-3.0 CC BY-SA 4.0

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    +

    Cytometry in R is a free weekly mini-course being offered both in-person and online by the Flow Cytometry Shared Resource staff at the University of Maryland Greenebaum Comprehensive Cancer Center. Its primary audience is for those with prior flow cytometry knowledge, who have limited previous experience with the programming language R. However, we welcome everyone regardless of their existing  flow cytometry  or coding experience.

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    This course is a passion project arising from our desire to contribute back to the community. We are excited that so many of you have chosen to sign up, and look forward to helping you get started on your own learning journeys.

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    For more information on topics-covered, please see our schedule.

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    If you did not previously complete the interest form, and would like to be added to our mailing list, please complete the form here

    +


    +
    +

    About

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    +
    +

    Motivation

    +

    While many cytometry enthusiast express an interest in learning how to carry out flow cytometry analyses in R, they often do not know where to start. Additionally, many of the limited existing resources are focused towards users with intermediate bioinformatic skills, contributing to a greater barrier for entry for those just starting out. Our motivation in offering this mini-course tailored towards beginners is to make the learning journey smoother than the one we ourselves experienced.

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    +

    While designing the course, we kept the following concepts in mind:

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      +

    • Beginning coders benefit both by having detailed examples that they can initially work through on their own time, as well as less defined problems that through troubleshooting enable the acquisition of the thought-process and skills needed for coding.

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    • Some topics will take individuals a longer time to fully grasp. Providing a format and resources that enable being able to revisit the material multiple times is incredibly helpful. Likewise, life is busy, and missing a workshop session is highly probable. If this happens, it shouldn’t make or break the ability of the individual to understanding the rest of the course.

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    • Consistency is key, and being able to apply what you are learning to your own datasets, files, and questions of interest helps achieve this.

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    +


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    Course Details

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    +

    Each week, the mini-course will cover a particular topic for an hour. This individual class is offered on multiple days, at different times, both in-person and online. We invite you to attend the one that best fits your schedule each week. If life gets busy and you can’t make regular day, the online livestream recordings will be available on YouTube.

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    Course Materials

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    We will release the course materials for the upcoming week on Sundays 2200 EST (Monday 0300 GMT+0) via our course website and GitHub. These materials will normally be Quarto Markdown documents containing code, explanation, and other resources needed for that week. If you have your own data, you can use your own data! If you don’t have any data, we will make sure to provide some of our own available data for each lesson so that you can use it and be able to follow along.

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    In our commitment to open-source and open-science, all teaching materials are freely offered under a CC-BY-SA license, while all code examples are offered under the AGPL3-0 copyleft license.

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    In-Person (Baltimore)

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    For those who are local and attending in person, the class will be offered on Monday, Tuesday and Thursday from 4-5 pm EST in Bressler Research Building Conference Room 7-035 (around the corner from the Flow Core).

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    We invite you to make whichever session best fits your schedule. If you have your own laptop, feel free to bring it. If you don’t have a laptop, please reach out, the Flow Core has 6 laptops running Linux that we can lend out to participants for use during the session.

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    For those who arrive early, we will have a limited number of second screens with provided mouse and keyboard that you can plug a laptop into via HDMI cable to set up a larger workstation. For those arriving later, the room has enough space (and electrical plugs) for up to 20 people, but you will need to balance a laptop on your lap.

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    Online (Worldwide)

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    For those joining us virtually, we will have three separate livestreams throughout the week on YouTube. These will be offered on:

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    • Tuesday 2200 EST (Wednesday 0300 GMT+0)
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    • Wednesday 1600 EST (Wednesday 2100 GMT+0)
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    • Thursday 1000 EST (Thursday 1500 GMT+0)
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    +



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    Recordings

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    All three livestreams will be recorded and available on YouTube immediately afterwards. Our plan is to eventually circle back after the course and properly edit them (ie. less minutes of random background noise, highlighting the relevant lines of code, time-stamps, subtitles, translations, etc.) later on as time allows, so that they can serve as a more permanent resource. 

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    +
    +

    Discussion Forum

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    +

    We will be using our GitHub Discussions page as a community forum. This will allow us to answer questions, and benefit from insights from others in the community. One advantage of having so many people signed up for the course is that if you have a question, someone else likely does as well, so go start a post and ask it!

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    +
    +
    +

    Optional Take-Home Problems

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    +

    Each week, we will offer optional take-home problems. These are intended to allow you to work with your own data on similar problems, but in a not-so-structured manner. Challenges that you and overcome during the process will help grow your problem solving and debugging skills, and help solidify concepts covered during the course.

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    To get feedback on these problems, you can reach out to the community on the Discussions page, or once far enough open a pull request to the homework branch and we will provide additional feedback.

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    +
    +

    Cost

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    Is there a cost to participate? No, it’s absolutely free! Is there a catch? Yes, you learn R, and may wind up with strong feelings about flowframes vs. cytoframes. This is also our first year offering this course, so we will sporadically ask you to fill out a feedback forms to help us improve.

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    +



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    Computing Requirements

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    For those attending online, you will need a computer with internet access. Operating system shouldn’t matter, as we will be offering code examples for Windows, Mac and Linux. As with all things flow-cytometry software, having a faster CPU with multiple cores, more RAM and greater storage space is generally helpful, but not a deal breaker.

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    You will need to be able to install the required software (R, Rtools, Positron, Quarto, and Git) as well as install and compile R packages from the CRAN and Bioconductor repositories (as well as a few GitHub-based R packages). Installation walkthroughs for each computer operating system can be found here.

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    For those using university or company administered computers, please be aware that you may not have the necessary permissions to install these directly, and may need to reach out to your IT department to help get these initial requirements set up. If you are using your own computer, congratulations, you are your system administrator, and should already have the necessary permissions.

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    +

    For those attending in-person, we have set up a pop-up computer lab in the conference room. For those who arrive early, we have a limited number of second screens with provided mouse and keyboard that you can plug a laptop into via HDMI cable to set up a workstation. For those arriving later, the room has enough space (and electrical plugs) for 20 people, but you will need to balance a laptop on your lap. If you have your own laptop, feel free to bring it. If you don’t have a laptop, the flow core has 6 loaner laptops running Linux that we can let participants use for that session.

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    +
    +
    +
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    License

    +

    In our commitment to open-science and open-source, all teaching materials are freely offered under a CC-BY-SA license, while all code examples are offered under the AGPL3-0 copyleft license.

    +



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    AGPL-3.0 CC BY-SA 4.0

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    Made with Quarto

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    AGPL-3.0 CC-BY-SA

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    + + + + +======= @@ -693,4 +1391,5 @@

    License

    +>>>>>>> 23a81a59a64966e782d820f6b60f087d577c3b25 \ No newline at end of file diff --git a/docs/search.json b/docs/search.json index 5382d97..36fdc5a 100644 --- a/docs/search.json +++ b/docs/search.json @@ -4,7 +4,7 @@ "href": "course/05_GatingSets/index.html", "title": "05 - Gating Sets", "section": "", - "text": "For the YouTube livestream schedule, see here\nFor screen-shot slides, click here", + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", "crumbs": [ "About", "Intro to R", @@ -16,7 +16,7 @@ "href": "course/05_GatingSets/index.html#flowframe", "title": "05 - Gating Sets", "section": "flowFrame", - "text": "flowFrame\nLet’s start off by recalling the approach we first saw during Week 03, where using the flowCore package we loaded the contents of our .fcs file into R as a “flowFrame” object.\nTo do this, we first identified the .fcs files we were interested using file.path() to specify the folder, and list.files() to find contents containing “.fcs”.\n\n# Folder <- file.path(\"course\", \"05_GatingSets\", \"data\") # For Testing\n\n Folder <- file.path(\"data\") # For Quarto Rendering\n\nfcs_files <- list.files(Folder, pattern=\".fcs\", full.names=TRUE)\n\nfcs_files\n\n[1] \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\"\n[2] \"data/2025_07_26_AB_02_INF052_00_SEB.fcs\" \n[3] \"data/2025_07_26_AB_02_INF100_00_Ctrl.fcs\"\n[4] \"data/2025_07_26_AB_02_INF100_00_SEB.fcs\" \n[5] \"data/2025_07_26_AB_02_INF179_00_Ctrl.fcs\"\n[6] \"data/2025_07_26_AB_02_INF179_00_SEB.fcs\" \n\n\nWe then identified an individual .fcs file of interest using the [] method of indexing.\n\nfcs_files[1]\n\n[1] \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\"\n\n\nThen, after making sure flowCore was attached to our local environment (via the library() function), we could use read.FCS() to read in our .fcs files contents to R.\n\n# BiocManager::install(\"flowCore\") #Bioconductor\nlibrary(flowCore)\n\n\nflowFrame <- read.FCS(filename=fcs_files[1], truncate_max_range = FALSE, transformation = FALSE)\nflowFrame\n\nflowFrame object '2025_07_26_AB_02_INF052_00_Ctrl.fcs'\nwith 10000 cells and 43 observables:\n name desc range minRange maxRange\n$P1 Time NA 896745 0 878.809\n$P2 SSC-W NA 4194304 0 4194303.000\n$P3 SSC-H NA 4194304 0 4194303.000\n$P4 SSC-A NA 4194304 0 4194303.000\n$P5 FSC-W NA 4194304 0 4194303.000\n... ... ... ... ... ...\n$P39 APC-R700-A CD107a 4194304 -111 4192506\n$P40 Zombie NIR-A Viability 4194304 -111 4192506\n$P41 APC-Fire 750-A CD27 4194304 -111 4192506\n$P42 APC-Fire 810-A CCR7 4194304 -111 4192506\n$P43 AF-A NA 4194304 -111 4194303\n472 keywords are stored in the 'description' slot\n\n\nAs we start to think about the wider infrastructural handling of our .fcs files, what would have occurred if we had provided multiple .fcs file paths to read.FCS()? Let’s go ahead and check by not providing an index number.\n\nread.FCS(filename=fcs_files, truncate_max_range = FALSE, transformation = FALSE)\n\nError in `read.FCS()`:\n! 'filename' must be character scalar\n\n\nAs you can tell, this error message is not particularly interpretable. It however arises from type of object we are passing to the function, whereby an individual file.path (fcs_files[1]) appears as class “character” with a single value (ie. a scalar), but the combined vector (fcs_files) contains multiple values.\n\nfcs_files[1]\n\n[1] \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\"\n\nstr(fcs_files[1])\n\n chr \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\"\n\n\n\nfcs_files\n\n[1] \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\"\n[2] \"data/2025_07_26_AB_02_INF052_00_SEB.fcs\" \n[3] \"data/2025_07_26_AB_02_INF100_00_Ctrl.fcs\"\n[4] \"data/2025_07_26_AB_02_INF100_00_SEB.fcs\" \n[5] \"data/2025_07_26_AB_02_INF179_00_Ctrl.fcs\"\n[6] \"data/2025_07_26_AB_02_INF179_00_SEB.fcs\" \n\nstr(fcs_files)\n\n chr [1:6] \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\" ...", + "text": "flowFrame\nLet’s start off by recalling the approach we first saw during Week 03, where using the flowCore package we loaded the contents of our .fcs file into R as a “flowFrame” object.\nTo do this, we first identified the .fcs files we were interested using file.path() to specify the folder, and list.files() to find contents containing “.fcs”.\n\n# Folder <- file.path(\"course\", \"05_GatingSets\", \"data\") # For Testing\n\n Folder <- file.path(\"data\") # For Quarto Rendering\n\nfcs_files <- list.files(Folder, pattern=\".fcs\", full.names=TRUE)\n\nfcs_files\n\n[1] \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\"\n[2] \"data/2025_07_26_AB_02_INF052_00_SEB.fcs\" \n[3] \"data/2025_07_26_AB_02_INF100_00_Ctrl.fcs\"\n[4] \"data/2025_07_26_AB_02_INF100_00_SEB.fcs\" \n[5] \"data/2025_07_26_AB_02_INF179_00_Ctrl.fcs\"\n[6] \"data/2025_07_26_AB_02_INF179_00_SEB.fcs\" \n\n\nWe then identified an individual .fcs file of interest using the [] method of indexing.\n\nfcs_files[1]\n\n[1] \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\"\n\n\nThen, after making sure flowCore was attached to our local environment (via the library() function), we could use read.FCS() to read in our .fcs files contents to R.\n\n# BiocManager::install(\"flowCore\") #Bioconductor\nlibrary(flowCore)\n\n\nflowFrame <- read.FCS(filename=fcs_files[1], truncate_max_range = FALSE,\n transformation = FALSE)\nflowFrame\n\nflowFrame object '2025_07_26_AB_02_INF052_00_Ctrl.fcs'\nwith 10000 cells and 43 observables:\n name desc range minRange maxRange\n$P1 Time NA 896745 0 878.809\n$P2 SSC-W NA 4194304 0 4194303.000\n$P3 SSC-H NA 4194304 0 4194303.000\n$P4 SSC-A NA 4194304 0 4194303.000\n$P5 FSC-W NA 4194304 0 4194303.000\n... ... ... ... ... ...\n$P39 APC-R700-A CD107a 4194304 -111 4192506\n$P40 Zombie NIR-A Viability 4194304 -111 4192506\n$P41 APC-Fire 750-A CD27 4194304 -111 4192506\n$P42 APC-Fire 810-A CCR7 4194304 -111 4192506\n$P43 AF-A NA 4194304 -111 4194303\n472 keywords are stored in the 'description' slot\n\n\nAs we start to think about the wider infrastructural handling of our .fcs files, what would have occurred if we had provided multiple .fcs file paths to read.FCS()? Let’s go ahead and check by not providing an index number.\n\nread.FCS(filename=fcs_files, truncate_max_range = FALSE, transformation = FALSE)\n\nError in `read.FCS()`:\n! 'filename' must be character scalar\n\n\nAs you can tell, this error message is not particularly interpretable. It however arises from type of object we are passing to the function, whereby an individual file.path (fcs_files[1]) appears as class “character” with a single value (ie. a scalar), but the combined vector (fcs_files) contains multiple values.\n\nfcs_files[1]\n\n[1] \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\"\n\nstr(fcs_files[1])\n\n chr \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\"\n\n\n\nfcs_files\n\n[1] \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\"\n[2] \"data/2025_07_26_AB_02_INF052_00_SEB.fcs\" \n[3] \"data/2025_07_26_AB_02_INF100_00_Ctrl.fcs\"\n[4] \"data/2025_07_26_AB_02_INF100_00_SEB.fcs\" \n[5] \"data/2025_07_26_AB_02_INF179_00_Ctrl.fcs\"\n[6] \"data/2025_07_26_AB_02_INF179_00_SEB.fcs\" \n\nstr(fcs_files)\n\n chr [1:6] \"data/2025_07_26_AB_02_INF052_00_Ctrl.fcs\" ...", "crumbs": [ "About", "Intro to R", @@ -28,7 +28,7 @@ "href": "course/05_GatingSets/index.html#flowset", "title": "05 - Gating Sets", "section": "flowSet", - "text": "flowSet\nConsequently, we will need to use another function if we want to read in multiple .fcs files at once. For flowCore, this function is the read.flowSet() function.\n\nflowSet <- read.flowSet(files=fcs_files, truncate_max_range = FALSE, transformation = FALSE)\nflowSet\n\nA flowSet with 6 experiments.\n\ncolumn names(43): Time SSC-W ... APC-Fire 810-A AF-A\n\n\nAlternatively, we can designate specific files within “fcs_files” we want to read in using the [] and c() notation style we have encountered previously.\n\nread.flowSet(files=fcs_files[c(1, 3:4)], truncate_max_range = FALSE, transformation = FALSE)\n\nA flowSet with 3 experiments.\n\ncolumn names(43): Time SSC-W ... APC-Fire 810-A AF-A\n\n\nOn follow-up, we can see that read.flowSet() has created a “flowSet” class object.\n\nclass(flowSet)\n\n[1] \"flowSet\"\nattr(,\"package\")\n[1] \"flowCore\"\n\n\nWhich we can also confirm by glancing at the right secondary sidebar to see the created Variables within our environment. Applying our investigatory skills from Week 3, we surmise that “flowSet” is another Bioconductor style S4-type object that within its frame slot contains individual “flowFrames”.\n\nIf instead of class() we had used str(), we would have seen a similar output ton what we see in the Variables panel.\n\nstr(flowSet)\n\nFormal class 'flowSet' [package \"flowCore\"] with 2 slots\n ..@ frames :<environment: 0x55d40ab8dbe8> \n ..@ phenoData:Formal class 'AnnotatedDataFrame' [package \"Biobase\"] with 4 slots\n .. .. ..@ varMetadata :'data.frame': 1 obs. of 1 variable:\n .. .. .. ..$ labelDescription: chr \"Name\"\n .. .. ..@ data :'data.frame': 6 obs. of 1 variable:\n .. .. .. ..$ name: 'AsIs' chr [1:6] \"2025_07_26_AB_02_INF052_00_Ctrl.fcs\" \"2025_07_26_AB_02_INF052_00_SEB.fcs\" \"2025_07_26_AB_02_INF100_00_Ctrl.fcs\" \"2025_07_26_AB_02_INF100_00_SEB.fcs\" ...\n .. .. ..@ dimLabels : chr [1:2] \"rowNames\" \"columnNames\"\n .. .. ..@ .__classVersion__:Formal class 'Versions' [package \"Biobase\"] with 1 slot\n .. .. .. .. ..@ .Data:List of 1\n .. .. .. .. .. ..$ : int [1:3] 1 1 0\n .. .. .. .. ..$ names: chr \"AnnotatedDataFrame\"\n\n\n\n\n\n\n\n\n\n\nReminder\n\n\n\nWhile not today’s focus, remember we could access individual components inside the flowSet using the @ accessors covered during Week 3", + "text": "flowSet\nConsequently, we will need to use another function if we want to read in multiple .fcs files at once. For flowCore, this function is the read.flowSet() function.\n\nflowSet <- read.flowSet(files=fcs_files, truncate_max_range = FALSE,\n transformation = FALSE)\nflowSet\n\nA flowSet with 6 experiments.\n\ncolumn names(43): Time SSC-W ... APC-Fire 810-A AF-A\n\n\nAlternatively, we can designate specific files within “fcs_files” we want to read in using the [] and c() notation style we have encountered previously.\n\nread.flowSet(files=fcs_files[c(1, 3:4)],\n truncate_max_range = FALSE, transformation = FALSE)\n\nA flowSet with 3 experiments.\n\ncolumn names(43): Time SSC-W ... APC-Fire 810-A AF-A\n\n\nOn follow-up, we can see that read.flowSet() has created a “flowSet” class object.\n\nclass(flowSet)\n\n[1] \"flowSet\"\nattr(,\"package\")\n[1] \"flowCore\"\n\n\nWhich we can also confirm by glancing at the right secondary sidebar to see the created Variables within our environment. Applying our investigatory skills from Week 3, we surmise that “flowSet” is another Bioconductor style S4-type object that within its frame slot contains individual “flowFrames”.\n\nIf instead of class() we had used str(), we would have seen a similar output ton what we see in the Variables panel.\n\nstr(flowSet)\n\nFormal class 'flowSet' [package \"flowCore\"] with 2 slots\n ..@ frames :<environment: 0x560d90048618> \n ..@ phenoData:Formal class 'AnnotatedDataFrame' [package \"Biobase\"] with 4 slots\n .. .. ..@ varMetadata :'data.frame': 1 obs. of 1 variable:\n .. .. .. ..$ labelDescription: chr \"Name\"\n .. .. ..@ data :'data.frame': 6 obs. of 1 variable:\n .. .. .. ..$ name: 'AsIs' chr [1:6] \"2025_07_26_AB_02_INF052_00_Ctrl.fcs\" \"2025_07_26_AB_02_INF052_00_SEB.fcs\" \"2025_07_26_AB_02_INF100_00_Ctrl.fcs\" \"2025_07_26_AB_02_INF100_00_SEB.fcs\" ...\n .. .. ..@ dimLabels : chr [1:2] \"rowNames\" \"columnNames\"\n .. .. ..@ .__classVersion__:Formal class 'Versions' [package \"Biobase\"] with 1 slot\n .. .. .. .. ..@ .Data:List of 1\n .. .. .. .. .. ..$ : int [1:3] 1 1 0\n .. .. .. .. ..$ names: chr \"AnnotatedDataFrame\"\n\n\n\n\n\n\n\n\n\n\nReminder\n\n\n\nWhile not today’s focus, remember we could access individual components inside the flowSet using the @ accessors covered during Week 3", "crumbs": [ "About", "Intro to R", @@ -40,7 +40,7 @@ "href": "course/05_GatingSets/index.html#memory-usage", "title": "05 - Gating Sets", "section": "Memory Usage", - "text": "Memory Usage\nBoth “flowFrame” and “flowSet” objects were implemented in the flowCore package, which is the oldest extant flow cytometry R package on Bioconductor. Consequently, a large proportion of the other flow cytometry R packages read in .fcs files as “flowFrame” and “flowSet” objects.\nOne consideration of this method is the contents of your .fcs files are read into your computer’s random access memory (RAM). While for individual .fcs files or small experiments this present a problem for most modern computers, when working with large spectral flow cytometry files containing millions of events (or trying to analyze many .fcs files at once), you may encounter situations where you can quickly exceed your computers available RAM.\nTo build some contextual understanding of the problem, let’s learn how to check how much memory is being used by our individual variables/objects within our R session. We will primarily use the lobstr R packages obj_size() function, as it better handles evaluating complicated objects than base R’s object.size() function.\nWe can check and see the memory usage by our flowFrame object\n\n# Base R\nobject.size(flowFrame)\n\n3570896 bytes\n\n# install.packages(\"lobstr\") # CRAN\nlibrary(lobstr)\nobj_size(flowFrame)\n\n3.53 MB\n\n\nAnd contrast to the greater ammount of space occupied by our flowSet object (which contains multiple flowFrames)\n\nobj_size(flowSet)\n\n20.99 MB\n\n\nIf we were curious how much memory total we are using within R at the current moment, we can check using the mem_used() function:\n\nmem_used()\n\n146.98 MB\n\n\nUltimately, how many .fcs files you are able to read in and interact with before running out of available RAM memory space will be dictated by your individual computers hardware configuration. You can check programmatically how much RAM you have available, although the specific function you will need to use will depend on your computer’s operating system.\nTo simplify the process, here is an additional example of where a conditional can prove useful, allowing us to check in an operating system specific manner. It takes the output of the Sys.info() function, namely the “sysname” argument and then retrieves the relavent function.\n\nOperatingSystem <- Sys.info()[[\"sysname\"]]\n\nif (OperatingSystem == \"Windows\") { # Windows\n memory.limit()\n\n } else if (OperatingSystem == \"Darwin\") { # MacOS\n system(\"top -l 1 | grep PhysMem\")\n\n } else if (OperatingSystem == \"Linux\") { # Linux\n system(\"free -h\")\n\n } else {message(\"A wild FreeBSD-User appears\")}\n\nWhen evaluating the returned outputs, primarily consider the total, used and free outputs.", + "text": "Memory Usage\nBoth “flowFrame” and “flowSet” objects were implemented in the flowCore package, which is the oldest extant flow cytometry R package on Bioconductor. Consequently, a large proportion of the other flow cytometry R packages read in .fcs files as “flowFrame” and “flowSet” objects.\nOne consideration of this method is the contents of your .fcs files are read into your computer’s random access memory (RAM). While for individual .fcs files or small experiments this will not present a problem for most modern computers, when working with large spectral flow cytometry files containing millions of events (or trying to analyze many .fcs files at once), you may encounter situations where you can quickly exceed your computers available RAM.\nTo build some contextual understanding of the problem, let’s learn how to check how much memory is being used by our individual variables/objects within our R session. We will primarily use the lobstr R packages obj_size() function, as it better handles evaluating complicated objects than base R’s object.size() function.\nWe can check and see the memory usage by our flowFrame object\n\n# Base R\nobject.size(flowFrame)\n\n3570896 bytes\n\n# install.packages(\"lobstr\") # CRAN\nlibrary(lobstr)\nobj_size(flowFrame)\n\n3.53 MB\n\n\nAnd contrast to the greater ammount of space occupied by our flowSet object (which contains multiple flowFrames)\n\nobj_size(flowSet)\n\n20.99 MB\n\n\nIf we were curious how much memory total we are using within R at the current moment, we can check using the mem_used() function:\n\nmem_used()\n\n146.99 MB\n\n\nUltimately, how many .fcs files you are able to read in and interact with before running out of available RAM memory space will be dictated by your individual computers hardware configuration. There are various ways you can check programmatically how much RAM your computer has available, although the specific functions will vary depending on your computers operating system, since they often involve system-level code outside R. Using the ps R package’s ps_system_memory() function is one of the easier ways for Windows users.\nTo simplify the process, here is an additional example of where a conditional can prove useful, allowing us to check in an operating system specific manner. It takes the output of the Sys.info() function, namely the “sysname” argument and then retrieves the relavent function.\n\nOperatingSystem <- Sys.info()[[\"sysname\"]]\n\nif (OperatingSystem == \"Windows\") { # Windows\n Memory <- ps::ps_system_memory()\n message(\"Total GB \", round(Memory$total / 1024^3, 2))\n message(\"Free GB \", round(Memory$free / 1024^3, 2))\n\n } else if (OperatingSystem == \"Darwin\") { # MacOS\n system(\"top -l 1 | grep PhysMem\")\n\n } else if (OperatingSystem == \"Linux\") { # Linux\n system(\"free -h\")\n\n } else {message(\"A wild FreeBSD-User appears\")}\n\n\n# install.packages(\"ps\") # CRAN\nlibrary(ps)\nMemory <- ps::ps_system_memory()\nmessage(\"Total GB \", round(Memory$total / 1024^3, 2))\n\nTotal GB 62.5\n\nmessage(\"Free GB \", round(Memory$free / 1024^3, 2))\n\nFree GB 53.49", "crumbs": [ "About", "Intro to R", @@ -64,7 +64,7 @@ "href": "course/05_GatingSets/index.html#cytoset", "title": "05 - Gating Sets", "section": "cytoset", - "text": "cytoset\nAs well as “cytoset” to handle multiple .fcs files.\n\ncytoset <- load_cytoset_from_fcs(fcs_files, truncate_max_range = FALSE, transformation = FALSE)\n\ncytoset\n\nA cytoset with 6 samples.\n\n column names:\n Time, SSC-W, SSC-H, SSC-A, FSC-W, FSC-H, FSC-A, SSC-B-W, SSC-B-H, SSC-B-A, BUV395-A, BUV563-A, BUV615-A, BUV661-A, BUV737-A, BUV805-A, Pacific Blue-A, BV480-A, BV570-A, BV605-A, BV650-A, BV711-A, BV750-A, BV786-A, Alexa Fluor 488-A, Spark Blue 550-A, Spark Blue 574-A, RB613-A, RB705-A, RB780-A, PE-A, PE-Dazzle594-A, PE-Cy5-A, PE-Fire 700-A, PE-Fire 744-A, PE-Vio770-A, APC-A, Alexa Fluor 647-A, APC-R700-A, Zombie NIR-A, APC-Fire 750-A, APC-Fire 810-A, AF-A\n\n\n\nclass(cytoset)\n\n[1] \"cytoset\"\nattr(,\"package\")\n[1] \"flowWorkspace\"\n\n\nUnlike “flowFrame” and “flowSet”, when we run str(), for “cytoframe” and “cytoset” objects we don’t get back quite as much information.\n\nstr(cytoframe)\n\nFormal class 'cytoframe' [package \"flowWorkspace\"] with 5 slots\n ..@ pointer :<externalptr> \n ..@ use.exprs : logi TRUE\n ..@ exprs : num[0 , 0 ] \n ..@ parameters :Formal class 'AnnotatedDataFrame' [package \"Biobase\"] with 4 slots\n .. .. ..@ varMetadata :'data.frame': 5 obs. of 1 variable:\n .. .. .. ..$ labelDescription: chr [1:5] \"Name of Parameter\" \"Description of Parameter\" \"Range of Parameter\" \"Minimum Parameter Value after Transformation\" ...\n .. .. ..@ data :'data.frame': 0 obs. of 5 variables:\n .. .. .. ..$ name : chr(0) \n .. .. .. ..$ description: chr(0) \n .. .. .. ..$ range : num(0) \n .. .. .. ..$ minRange : num(0) \n .. .. .. ..$ maxRange : num(0) \n .. .. ..@ dimLabels : chr [1:2] \"rowNames\" \"columnNames\"\n .. .. ..@ .__classVersion__:Formal class 'Versions' [package \"Biobase\"] with 1 slot\n .. .. .. .. ..@ .Data:List of 1\n .. .. .. .. .. ..$ : int [1:3] 1 1 0\n .. .. .. .. ..$ names: chr \"AnnotatedDataFrame\"\n ..@ description:List of 1\n .. ..$ note: chr \"empty\"\n\n\n\nstr(cytoset)\n\nFormal class 'cytoset' [package \"flowWorkspace\"] with 3 slots\n ..@ pointer :<externalptr> \n ..@ frames :<environment: 0x55d414e7fdf0> \n ..@ phenoData:Formal class 'AnnotatedDataFrame' [package \"Biobase\"] with 4 slots\n .. .. ..@ varMetadata :'data.frame': 0 obs. of 1 variable:\n .. .. .. ..$ labelDescription: chr(0) \n .. .. ..@ data :'data.frame': 0 obs. of 0 variables\n .. .. ..@ dimLabels : chr [1:2] \"rowNames\" \"columnNames\"\n .. .. ..@ .__classVersion__:Formal class 'Versions' [package \"Biobase\"] with 1 slot\n .. .. .. .. ..@ .Data:List of 1\n .. .. .. .. .. ..$ : int [1:3] 1 1 0\n .. .. .. .. ..$ names: chr \"AnnotatedDataFrame\"\n\n\nThis is similarly the case when glancing at the right secondary side bar, as the respective objects under variables appear to have empty matrices where normally we would have seen the MFI values.\n\nDue to flowWorkspace use of pointers, the missing data remains stored on the drive, only being retrieved right before it is required. This reduces the overall RAM utilization. Let’s double check the differences in memory utilization for flowFrame/cytoframe:\n\nobj_size(flowFrame)\n\n3.53 MB\n\n\n\nobj_size(cytoframe)\n\n5.40 kB\n\n\nAnd similarly the case for flowSet and cytoset:\n\nobj_size(flowSet)\n\n20.99 MB\n\n\n\nobj_size(cytoset)\n\n3.88 kB\n\n\nAdditionally, with computer hardware increasingly switching from spinning disk hard-drives to faster solid state drives, the performance penalty previously experienced when not running from RAM is not as large of a concern as in previous years.", + "text": "cytoset\nAs well as “cytoset” to handle multiple .fcs files.\n\ncytoset <- load_cytoset_from_fcs(fcs_files, truncate_max_range = FALSE, transformation = FALSE)\n\ncytoset\n\nA cytoset with 6 samples.\n\n column names:\n Time, SSC-W, SSC-H, SSC-A, FSC-W, FSC-H, FSC-A, SSC-B-W, SSC-B-H, SSC-B-A, BUV395-A, BUV563-A, BUV615-A, BUV661-A, BUV737-A, BUV805-A, Pacific Blue-A, BV480-A, BV570-A, BV605-A, BV650-A, BV711-A, BV750-A, BV786-A, Alexa Fluor 488-A, Spark Blue 550-A, Spark Blue 574-A, RB613-A, RB705-A, RB780-A, PE-A, PE-Dazzle594-A, PE-Cy5-A, PE-Fire 700-A, PE-Fire 744-A, PE-Vio770-A, APC-A, Alexa Fluor 647-A, APC-R700-A, Zombie NIR-A, APC-Fire 750-A, APC-Fire 810-A, AF-A\n\n\n\nclass(cytoset)\n\n[1] \"cytoset\"\nattr(,\"package\")\n[1] \"flowWorkspace\"\n\n\nUnlike “flowFrame” and “flowSet”, when we run str(), for “cytoframe” and “cytoset” objects we don’t get back quite as much information.\n\nstr(cytoframe)\n\nFormal class 'cytoframe' [package \"flowWorkspace\"] with 5 slots\n ..@ pointer :<externalptr> \n ..@ use.exprs : logi TRUE\n ..@ exprs : num[0 , 0 ] \n ..@ parameters :Formal class 'AnnotatedDataFrame' [package \"Biobase\"] with 4 slots\n .. .. ..@ varMetadata :'data.frame': 5 obs. of 1 variable:\n .. .. .. ..$ labelDescription: chr [1:5] \"Name of Parameter\" \"Description of Parameter\" \"Range of Parameter\" \"Minimum Parameter Value after Transformation\" ...\n .. .. ..@ data :'data.frame': 0 obs. of 5 variables:\n .. .. .. ..$ name : chr(0) \n .. .. .. ..$ description: chr(0) \n .. .. .. ..$ range : num(0) \n .. .. .. ..$ minRange : num(0) \n .. .. .. ..$ maxRange : num(0) \n .. .. ..@ dimLabels : chr [1:2] \"rowNames\" \"columnNames\"\n .. .. ..@ .__classVersion__:Formal class 'Versions' [package \"Biobase\"] with 1 slot\n .. .. .. .. ..@ .Data:List of 1\n .. .. .. .. .. ..$ : int [1:3] 1 1 0\n .. .. .. .. ..$ names: chr \"AnnotatedDataFrame\"\n ..@ description:List of 1\n .. ..$ note: chr \"empty\"\n\n\n\nstr(cytoset)\n\nFormal class 'cytoset' [package \"flowWorkspace\"] with 3 slots\n ..@ pointer :<externalptr> \n ..@ frames :<environment: 0x560d9ade0fc8> \n ..@ phenoData:Formal class 'AnnotatedDataFrame' [package \"Biobase\"] with 4 slots\n .. .. ..@ varMetadata :'data.frame': 0 obs. of 1 variable:\n .. .. .. ..$ labelDescription: chr(0) \n .. .. ..@ data :'data.frame': 0 obs. of 0 variables\n .. .. ..@ dimLabels : chr [1:2] \"rowNames\" \"columnNames\"\n .. .. ..@ .__classVersion__:Formal class 'Versions' [package \"Biobase\"] with 1 slot\n .. .. .. .. ..@ .Data:List of 1\n .. .. .. .. .. ..$ : int [1:3] 1 1 0\n .. .. .. .. ..$ names: chr \"AnnotatedDataFrame\"\n\n\nThis is similarly the case when glancing at the right secondary side bar, as the respective objects under variables appear to have empty matrices where normally we would have seen the MFI values.\n\nDue to flowWorkspace use of pointers, the missing data remains stored on the drive, only being retrieved right before it is required. This reduces the overall RAM utilization. Let’s double check the differences in memory utilization for flowFrame/cytoframe:\n\nobj_size(flowFrame)\n\n3.53 MB\n\n\n\nobj_size(cytoframe)\n\n5.40 kB\n\n\nAnd similarly the case for flowSet and cytoset:\n\nobj_size(flowSet)\n\n20.99 MB\n\n\n\nobj_size(cytoset)\n\n3.88 kB\n\n\nAdditionally, with computer hardware increasingly switching from spinning disk hard-drives to faster solid state drives, the performance penalty previously experienced when not running from RAM is not as large of a concern as in previous years.", "crumbs": [ "About", "Intro to R", @@ -76,7 +76,7 @@ "href": "course/05_GatingSets/index.html#interconverting", "title": "05 - Gating Sets", "section": "Interconverting", - "text": "Interconverting\nDespite both R packages having been around for a while, many Bioconductor and GitHub often only implement methods to handle either flowFrames or cytoframes (although newer R packages are now allowing for both). Consequently, as we move forward in the course, it helps to be aware of which ones we are working with, and have the ability to interconvert between them as needed.\nTo go from a flowFrame to a cytoframe, we can use the flowFrame_to_cytoframe() function\n\nConvertedToCytoframe <- flowFrame_to_cytoframe(flowFrame)\nConvertedToCytoframe\n\ncytoframe object 'file806b23cd6a2e'\nwith 10000 cells and 43 observables:\n name desc range minRange maxRange\n$P1 Time NA 878.809 0 878.809\n$P2 SSC-W NA 4194303.000 0 4194303.000\n$P3 SSC-H NA 4194303.000 0 4194303.000\n$P4 SSC-A NA 4194303.000 0 4194303.000\n$P5 FSC-W NA 4194303.000 0 4194303.000\n... ... ... ... ... ...\n$P39 APC-R700-A CD107a 4192506 -111 4192506\n$P40 Zombie NIR-A Viability 4192506 -111 4192506\n$P41 APC-Fire 750-A CD27 4192506 -111 4192506\n$P42 APC-Fire 810-A CCR7 4192506 -111 4192506\n$P43 AF-A NA 4194303 -111 4194303\n472 keywords are stored in the 'description' slot\nrow names(0):\n\n\n\nobj_size(ConvertedToCytoframe)\n\n5.40 kB\n\n\nTo go from a cytoframe to a flowFrame, we can use the cytoframe_to_flowFrame() function\n\nConvertedToFlowframe <- flowWorkspace::cytoframe_to_flowFrame(cytoframe)\nConvertedToFlowframe\n\nflowFrame object '2025_07_26_AB_02_INF052_00_Ctrl.fcs'\nwith 10000 cells and 43 observables:\n name desc range minRange maxRange\n$P1 Time NA 878.809 0 878.809\n$P2 SSC-W NA 4194303.000 0 4194303.000\n$P3 SSC-H NA 4194303.000 0 4194303.000\n$P4 SSC-A NA 4194303.000 0 4194303.000\n$P5 FSC-W NA 4194303.000 0 4194303.000\n... ... ... ... ... ...\n$P39 APC-R700-A CD107a 4192506 -111 4192506\n$P40 Zombie NIR-A Viability 4192506 -111 4192506\n$P41 APC-Fire 750-A CD27 4192506 -111 4192506\n$P42 APC-Fire 810-A CCR7 4192506 -111 4192506\n$P43 AF-A NA 4194303 -111 4194303\n472 keywords are stored in the 'description' slot\n\n\n\nobj_size(ConvertedToFlowframe)\n\n3.53 MB\n\n\nTo go from a flowSet to a cytoSet, we can use the flowSet_to_cytoset() funciton\n\nConvertedToCytoset <- flowSet_to_cytoset(flowSet)\nConvertedToCytoset\n\nA cytoset with 6 samples.\n\n column names:\n Time, SSC-W, SSC-H, SSC-A, FSC-W, FSC-H, FSC-A, SSC-B-W, SSC-B-H, SSC-B-A, BUV395-A, BUV563-A, BUV615-A, BUV661-A, BUV737-A, BUV805-A, Pacific Blue-A, BV480-A, BV570-A, BV605-A, BV650-A, BV711-A, BV750-A, BV786-A, Alexa Fluor 488-A, Spark Blue 550-A, Spark Blue 574-A, RB613-A, RB705-A, RB780-A, PE-A, PE-Dazzle594-A, PE-Cy5-A, PE-Fire 700-A, PE-Fire 744-A, PE-Vio770-A, APC-A, Alexa Fluor 647-A, APC-R700-A, Zombie NIR-A, APC-Fire 750-A, APC-Fire 810-A, AF-A\n\n\n\nobj_size(ConvertedToCytoset)\n\n3.88 kB\n\n\nTo go from a cytoSet to a flowSet, we can use the cytoset_to_flowSet() function.\n\nConvertedToFlowset <- cytoset_to_flowSet(flowSet)\nConvertedToFlowset\n\nA flowSet with 6 experiments.\n\ncolumn names(43): Time SSC-W ... APC-Fire 810-A AF-A\n\n\n\nobj_size(ConvertedToFlowset)\n\n20.99 MB", + "text": "Interconverting\nDespite both R packages having been around for a while, many Bioconductor and GitHub often only implement methods to handle either flowFrames or cytoframes (although newer R packages are now allowing for both). Consequently, as we move forward in the course, it helps to be aware of which ones we are working with, and have the ability to interconvert between them as needed.\nTo go from a flowFrame to a cytoframe, we can use the flowFrame_to_cytoframe() function\n\nConvertedToCytoframe <- flowFrame_to_cytoframe(flowFrame)\nConvertedToCytoframe\n\ncytoframe object 'file382b177c06ea'\nwith 10000 cells and 43 observables:\n name desc range minRange maxRange\n$P1 Time NA 878.809 0 878.809\n$P2 SSC-W NA 4194303.000 0 4194303.000\n$P3 SSC-H NA 4194303.000 0 4194303.000\n$P4 SSC-A NA 4194303.000 0 4194303.000\n$P5 FSC-W NA 4194303.000 0 4194303.000\n... ... ... ... ... ...\n$P39 APC-R700-A CD107a 4192506 -111 4192506\n$P40 Zombie NIR-A Viability 4192506 -111 4192506\n$P41 APC-Fire 750-A CD27 4192506 -111 4192506\n$P42 APC-Fire 810-A CCR7 4192506 -111 4192506\n$P43 AF-A NA 4194303 -111 4194303\n472 keywords are stored in the 'description' slot\nrow names(0):\n\n\n\nobj_size(ConvertedToCytoframe)\n\n5.40 kB\n\n\nTo go from a cytoframe to a flowFrame, we can use the cytoframe_to_flowFrame() function\n\nConvertedToFlowframe <- flowWorkspace::cytoframe_to_flowFrame(cytoframe)\nConvertedToFlowframe\n\nflowFrame object '2025_07_26_AB_02_INF052_00_Ctrl.fcs'\nwith 10000 cells and 43 observables:\n name desc range minRange maxRange\n$P1 Time NA 878.809 0 878.809\n$P2 SSC-W NA 4194303.000 0 4194303.000\n$P3 SSC-H NA 4194303.000 0 4194303.000\n$P4 SSC-A NA 4194303.000 0 4194303.000\n$P5 FSC-W NA 4194303.000 0 4194303.000\n... ... ... ... ... ...\n$P39 APC-R700-A CD107a 4192506 -111 4192506\n$P40 Zombie NIR-A Viability 4192506 -111 4192506\n$P41 APC-Fire 750-A CD27 4192506 -111 4192506\n$P42 APC-Fire 810-A CCR7 4192506 -111 4192506\n$P43 AF-A NA 4194303 -111 4194303\n472 keywords are stored in the 'description' slot\n\n\n\nobj_size(ConvertedToFlowframe)\n\n3.53 MB\n\n\nTo go from a flowSet to a cytoSet, we can use the flowSet_to_cytoset() funciton\n\nConvertedToCytoset <- flowSet_to_cytoset(flowSet)\nConvertedToCytoset\n\nA cytoset with 6 samples.\n\n column names:\n Time, SSC-W, SSC-H, SSC-A, FSC-W, FSC-H, FSC-A, SSC-B-W, SSC-B-H, SSC-B-A, BUV395-A, BUV563-A, BUV615-A, BUV661-A, BUV737-A, BUV805-A, Pacific Blue-A, BV480-A, BV570-A, BV605-A, BV650-A, BV711-A, BV750-A, BV786-A, Alexa Fluor 488-A, Spark Blue 550-A, Spark Blue 574-A, RB613-A, RB705-A, RB780-A, PE-A, PE-Dazzle594-A, PE-Cy5-A, PE-Fire 700-A, PE-Fire 744-A, PE-Vio770-A, APC-A, Alexa Fluor 647-A, APC-R700-A, Zombie NIR-A, APC-Fire 750-A, APC-Fire 810-A, AF-A\n\n\n\nobj_size(ConvertedToCytoset)\n\n3.88 kB\n\n\nTo go from a cytoSet to a flowSet, we can use the cytoset_to_flowSet() function.\n\nConvertedToFlowset <- cytoset_to_flowSet(flowSet)\nConvertedToFlowset\n\nA flowSet with 6 experiments.\n\ncolumn names(43): Time SSC-W ... APC-Fire 810-A AF-A\n\n\n\nobj_size(ConvertedToFlowset)\n\n20.99 MB", "crumbs": [ "About", "Intro to R", @@ -112,7 +112,7 @@ "href": "course/05_GatingSets/index.html#system-time", "title": "05 - Gating Sets", "section": "System Time", - "text": "System Time\nEspecially when working with CytoML, it is often good to have an idea of how long it will take a particular function to run (to better plan how to use our time while waiting, whether to go grab coffee, etc.). There are a couple ways to do so.\nOne, using the system.time() function from base R, in which we surround whatever line of code we wish to evaluate in {}\n\nsystem.time({\n\nflowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys=\"GROUPNAME\")\n\n})\n\n user system elapsed \n 0.501 0.008 0.509 \n\n\nAlternatively, if we install the bench package, we can use the mark function to evaluate how long it takes on average across numerous iterations.\n\n# install.packages(\"bench\") # CRAN\nlibrary(bench)\n\n\nmark(\n Test <- flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys=\"GROUPNAME\"),\n iterations= 5\n )\n\n# A tibble: 1 × 6\n expression min median `itr/sec` mem_alloc `gc/sec`\n <bch:expr> <bch> <bch:> <dbl> <bch:byt> <dbl>\n1 Test <- flowjo_to_gatingset(ws = ws… 505ms 527ms 1.92 13.3KB 0", + "text": "System Time\nEspecially when working with CytoML, it is often good to have an idea of how long it will take a particular function to run (to better plan how to use our time while waiting, whether to go grab coffee, etc.). There are a couple ways to do so.\nOne, using the system.time() function from base R, in which we surround whatever line of code we wish to evaluate in {}\n\nsystem.time({\n\nflowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys=\"GROUPNAME\")\n\n})\n\n user system elapsed \n 0.554 0.004 0.559 \n\n\nAlternatively, if we install the bench package, we can use the mark function to evaluate how long it takes on average across numerous iterations.\n\n# install.packages(\"bench\") # CRAN\nlibrary(bench)\n\n\nmark(\n Test <- flowjo_to_gatingset(ws=ws, name=1, path = Folder, additional.keys=\"GROUPNAME\"),\n iterations= 5\n )\n\n# A tibble: 1 × 6\n expression min median `itr/sec` mem_alloc `gc/sec`\n <bch:expr> <bch> <bch:> <dbl> <bch:byt> <dbl>\n1 Test <- flowjo_to_gatingset(ws = ws… 539ms 550ms 1.78 13.3KB 0", "crumbs": [ "About", "Intro to R", @@ -180,1131 +180,958 @@ ] }, { - "objectID": "course/04_IntroToTidyverse/index.html", - "href": "course/04_IntroToTidyverse/index.html", - "title": "04 - Introduction to Tidyverse", + "objectID": "course/05_GatingSets/slides.html#flowframe", + "href": "course/05_GatingSets/slides.html#flowframe", + "title": "05 - Gating Sets", + "section": "flowFrame", + "text": "flowFrame\n\n\n\n\n\n\n\n\n.\n\n\nLet’s start off by recalling the approach we first saw during Week 03, where using the flowCore package we loaded the contents of our .fcs file into R as a “flowFrame” object." + }, + { + "objectID": "course/05_GatingSets/slides.html#flowset", + "href": "course/05_GatingSets/slides.html#flowset", + "title": "05 - Gating Sets", + "section": "flowSet", + "text": "flowSet\n\n\n\n\n\n\n\n\n.\n\n\nConsequently, we will need to use another function if we want to read in multiple .fcs files at once. For flowCore, this function is the read.flowSet() function.\n\n\n\n\n\n\n\nflowSet <- read.flowSet(files=fcs_files, truncate_max_range = FALSE,\n transformation = FALSE)\nflowSet\n\nA flowSet with 6 experiments.\n\ncolumn names(43): Time SSC-W ... APC-Fire 810-A AF-A" + }, + { + "objectID": "course/05_GatingSets/slides.html#memory-usage", + "href": "course/05_GatingSets/slides.html#memory-usage", + "title": "05 - Gating Sets", + "section": "Memory Usage", + "text": "Memory Usage\n\n\n\n\n\n\n\n\n.\n\n\nBoth “flowFrame” and “flowSet” objects were implemented in the flowCore package, which is the oldest extant flow cytometry R package on Bioconductor. Consequently, a large proportion of the other flow cytometry R packages read in .fcs files as “flowFrame” and “flowSet” objects.\n\n\n\n\n\n\n\n\n\n\n\n\n\n.\n\n\nOne consideration of this method is the contents of your .fcs files are read into your computer’s random access memory (RAM). While for individual .fcs files or small experiments this will not present a problem for most modern computers, when working with large spectral flow cytometry files containing millions of events (or trying to analyze many .fcs files at once), you may encounter situations where you can quickly exceed your computers available RAM." + }, + { + "objectID": "course/05_GatingSets/slides.html#cytoframe", + "href": "course/05_GatingSets/slides.html#cytoframe", + "title": "05 - Gating Sets", + "section": "cytoframe", + "text": "cytoframe\n\n\n\n\n\n\n\n\n.\n\n\nIn addition to the flowCore R package, additional flow cytometry infrastructure support is provided by the flowWorkspace package. Instead of the reading all the .fcs files contents into active RAM, flowWorkspace reduces the memory overhead by using “pointers” to interact with the object in it’s current storage location (either on your harddrive, SSD, etc.), only reading in components to RAM as needed.\n\n\n\n\n\n\n\n# BiocManager::install(\"flowWorkspace\") #Bioconductor\nlibrary(flowWorkspace)" + }, + { + "objectID": "course/05_GatingSets/slides.html#cytoset", + "href": "course/05_GatingSets/slides.html#cytoset", + "title": "05 - Gating Sets", + "section": "cytoset", + "text": "cytoset\n\n\n\n\n\n\n\n\n.\n\n\nAs well as “cytoset” to handle multiple .fcs files.\n\n\n\n\n\n\n\ncytoset <- load_cytoset_from_fcs(fcs_files, truncate_max_range = FALSE, transformation = FALSE)\n\ncytoset\n\nA cytoset with 6 samples.\n\n column names:\n Time, SSC-W, SSC-H, SSC-A, FSC-W, FSC-H, FSC-A, SSC-B-W, SSC-B-H, SSC-B-A, BUV395-A, BUV563-A, BUV615-A, BUV661-A, BUV737-A, BUV805-A, Pacific Blue-A, BV480-A, BV570-A, BV605-A, BV650-A, BV711-A, BV750-A, BV786-A, Alexa Fluor 488-A, Spark Blue 550-A, Spark Blue 574-A, RB613-A, RB705-A, RB780-A, PE-A, PE-Dazzle594-A, PE-Cy5-A, PE-Fire 700-A, PE-Fire 744-A, PE-Vio770-A, APC-A, Alexa Fluor 647-A, APC-R700-A, Zombie NIR-A, APC-Fire 750-A, APC-Fire 810-A, AF-A\n\n\n\n\n\nclass(cytoset)\n\n[1] \"cytoset\"\nattr(,\"package\")\n[1] \"flowWorkspace\"" + }, + { + "objectID": "course/05_GatingSets/slides.html#interconverting", + "href": "course/05_GatingSets/slides.html#interconverting", + "title": "05 - Gating Sets", + "section": "Interconverting", + "text": "Interconverting\n\n\n\n\n\n\n\n\n.\n\n\nDespite both R packages having been around for a while, many Bioconductor and GitHub often only implement methods to handle either flowFrames or cytoframes (although newer R packages are now allowing for both). Consequently, as we move forward in the course, it helps to be aware of which ones we are working with, and have the ability to interconvert between them as needed." + }, + { + "objectID": "course/05_GatingSets/slides.html#gating-sets", + "href": "course/05_GatingSets/slides.html#gating-sets", + "title": "05 - Gating Sets", + "section": "Gating Sets", + "text": "Gating Sets\n\n\n\n\n\n\n\n\n.\n\n\nFortunately, regardless of whether we are using flowFrame/flowSet (RAM) and cytoframe/cytoset (memory pointers), both routes end up converging at the next step, where the underlying .fcs files are passed off to the GatingSet() function.\n\n\n\n\n\n\n\nGatingSet1 <- GatingSet(flowSet)\nGatingSet1 \n\nA GatingSet with 6 samples\n\n\n\n\n\nclass(GatingSet1)\n\n[1] \"GatingSet\"\nattr(,\"package\")\n[1] \"flowWorkspace\"" + }, + { + "objectID": "course/05_GatingSets/slides.html#cytoml", + "href": "course/05_GatingSets/slides.html#cytoml", + "title": "05 - Gating Sets", + "section": "CytoML", + "text": "CytoML\n\n\n\n\n\n\n\n\n.\n\n\nThe CytoML R package (also maintained by Mike Jiang) is a sister package to the flowWorkspace. It’s main purpose is to permit bringing in existing FlowJo, Diva and Cytobank Workspaces, with all their gates, transformations, etc. into R as fully assembled GatingSet objects. For those who already use one of these commercial softwares, it can be quite useful tool.\n\n\n\n\n\n\n\n\n\n\n\n\n\n.\n\n\nSince our goal is to examine a fully assembled GatingSet object, we will be using it today to bring in a FlowJo workspace to R. However, since this is a free Cytometry in R course, and not about to have everyone pay for a license for a one-off topic, in the pre-course Floreada walkthrough I documented how to convert a free Floreada.io workspae into a FlowJo.wsp that can also be used (please note that as of early 2026, some scaling bugs may be present and require troubleshooting)." + }, + { + "objectID": "course/05_GatingSets/slides.html#system-time", + "href": "course/05_GatingSets/slides.html#system-time", + "title": "05 - Gating Sets", + "section": "System Time", + "text": "System Time\n\n\n\n\n\n\n\n\n.\n\n\nEspecially when working with CytoML, it is often good to have an idea of how long it will take a particular function to run (to better plan how to use our time while waiting, whether to go grab coffee, etc.). There are a couple ways to do so." + }, + { + "objectID": "course/05_GatingSets/slides.html#gates", + "href": "course/05_GatingSets/slides.html#gates", + "title": "05 - Gating Sets", + "section": "Gates", + "text": "Gates\n\n\n\n\n\n\n\n\n.\n\n\nNow that we have loaded the contents of the FlowJo/Floreada workspace, we can start exploring the various infrastructural capabilities of a GatingSet object." + }, + { + "objectID": "course/05_GatingSets/slides.html#counts", + "href": "course/05_GatingSets/slides.html#counts", + "title": "05 - Gating Sets", + "section": "Counts", + "text": "Counts\n\n\n\n\n\n\n\n\n.\n\n\nIf we wanted to retrieve counts of cells found within the individual gates, we could do so with gs_pop_get_count_fast()\n\n\n\n\n\n\n\nData <- gs_pop_get_count_fast(gs)\nhead(Data, 5)\n\n name Population\n <char> <char>\n1: 00_Ctrl.fcs_INF052 /Scatter\n2: 00_Ctrl.fcs_INF052 /Scatter/Singlets\n3: 00_Ctrl.fcs_INF052 /Scatter/Singlets/Live\n4: 00_Ctrl.fcs_INF052 /Scatter/Singlets/Live/Tcells\n5: 00_Ctrl.fcs_INF052 /Scatter/Singlets/Live/Tcells/CD4+\n Parent Count ParentCount\n <char> <int> <int>\n1: root 10000 10000\n2: /Scatter 9986 10000\n3: /Scatter/Singlets 9708 9986\n4: /Scatter/Singlets/Live 9708 9708\n5: /Scatter/Singlets/Live/Tcells 6151 9708" + }, + { + "objectID": "course/05_GatingSets/slides.html#metadata", + "href": "course/05_GatingSets/slides.html#metadata", + "title": "05 - Gating Sets", + "section": "Metadata", + "text": "Metadata\n\n\n\n\n\n\n\n\n.\n\n\nSince GatingSets contain multiple .fcs files, we may want to be able to subset them based on metadata for a particular variable. We can check to see current metadata using the pData() function.\n\n\n\n\n\n\n\npData(gs)\n\n name\n00_Ctrl.fcs_INF052 00_Ctrl.fcs\n00_Ctrl.fcs_INF100 00_Ctrl.fcs\n00_Ctrl.fcs_INF179 00_Ctrl.fcs\n00_SEB.fcs_INF052 00_SEB.fcs\n00_SEB.fcs_INF100 00_SEB.fcs\n00_SEB.fcs_INF179 00_SEB.fcs" + }, + { + "objectID": "course/05_GatingSets/slides.html#ggcyto", + "href": "course/05_GatingSets/slides.html#ggcyto", + "title": "05 - Gating Sets", + "section": "ggcyto", + "text": "ggcyto\n\n\n\n\n\n\n\n\n.\n\n\nAs you can surmise, a lot of the infrastructural style handling done by commercial softwares is being orchestrated/mediated through our GatingSet object. Since it’s able to create and retain gating information, how would we go about visualizing the underlying data contained within each?" + }, + { + "objectID": "course/05_GatingSets/slides.html#plotting", + "href": "course/05_GatingSets/slides.html#plotting", + "title": "05 - Gating Sets", + "section": "Plotting", + "text": "Plotting\n\n\n\n\n\n\n\n\n.\n\n\nOnce you have the current versions of both ggplot2 and ggcyto, we can proceed to attach them to your local environment via the library() function.\n\n\n\n\n\n\n\nlibrary(ggplot2)\nlibrary(ggcyto)" + }, + { + "objectID": "course/04_IntroToTidyverse/BonusContent.html", + "href": "course/04_IntroToTidyverse/BonusContent.html", + "title": "Bonus Content", + "section": "", + "text": "thefilepath <- file.path(\"data\", \"Dataset.csv\")\n\nthefilepath\n\n[1] \"data/Dataset.csv\"\nData <- read.csv(file=thefilepath, check.names=FALSE)\ncolnames(Data)\n\n [1] \"bid\" \"timepoint\" \"Condition\" \n [4] \"Date\" \"infant_sex\" \"ptype\" \n [7] \"root\" \"singletsFSC\" \"singletsSSC\" \n[10] \"singletsSSCB\" \"CD45\" \"NotMonocytes\" \n[13] \"nonDebris\" \"lymphocytes\" \"live\" \n[16] \"Dump+\" \"Dump-\" \"Tcells\" \n[19] \"Vd2+\" \"Vd2-\" \"Va7.2+\" \n[22] \"Va7.2-\" \"CD4+\" \"CD4-\" \n[25] \"CD8+\" \"CD8-\" \"Tcells_count\" \n[28] \"lymphocytes_count\" \"Monocytes\" \"Debris\" \n[31] \"CD45_count\"" + }, + { + "objectID": "course/04_IntroToTidyverse/BonusContent.html#pull", + "href": "course/04_IntroToTidyverse/BonusContent.html#pull", + "title": "Bonus Content", + "section": "Pull", + "text": "Pull" + }, + { + "objectID": "course/04_IntroToTidyverse/BonusContent.html#case-when", + "href": "course/04_IntroToTidyverse/BonusContent.html#case-when", + "title": "Bonus Content", + "section": "Case-When", + "text": "Case-When\nCase-when is an useful function, but may be a bit much to try to teach in the main segment. Basically, when the condition on the left side of the ~ is fulfilled, it will execute what is being specified on the right hand side.\nIn turn, we can combine these together by adding a “,”. I tend to use this mutate str_detect case_when combination when encountering messy data out in the while where I need to selectively change particular cell values in a consistent reproducible manner" + }, + { + "objectID": "course/04_IntroToTidyverse/BonusContent.html#selecting-columns-base-r", + "href": "course/04_IntroToTidyverse/BonusContent.html#selecting-columns-base-r", + "title": "Bonus Content", + "section": "Selecting Columns (Base R)", + "text": "Selecting Columns (Base R)\nAs we saw last week, there are multiple ways to select values from particular columns in base R. If we had wanted to retrieve the “Date” column, why not first identify its index position, and use [,] to extract the underlying data?\n\ncolnames(Data)\n\n [1] \"bid\" \"timepoint\" \"Condition\" \n [4] \"Date\" \"infant_sex\" \"ptype\" \n [7] \"root\" \"singletsFSC\" \"singletsSSC\" \n[10] \"singletsSSCB\" \"CD45\" \"NotMonocytes\" \n[13] \"nonDebris\" \"lymphocytes\" \"live\" \n[16] \"Dump+\" \"Dump-\" \"Tcells\" \n[19] \"Vd2+\" \"Vd2-\" \"Va7.2+\" \n[22] \"Va7.2-\" \"CD4+\" \"CD4-\" \n[25] \"CD8+\" \"CD8-\" \"Tcells_count\" \n[28] \"lymphocytes_count\" \"Monocytes\" \"Debris\" \n[31] \"CD45_count\" \n\n\n\ncolnames(Data)[4]\n\n[1] \"Date\"\n\n\n\nDataColumn <- Data[,4] # Column specified after the ,\nDataColumn\n\n [1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [6] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [11] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [16] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [21] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [26] \"2025-07-26\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\"\n [31] \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\"\n [36] \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\"\n [41] \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\"\n [46] \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-31\" \"2025-07-31\"\n [51] \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\"\n [56] \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\"\n [61] \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\"\n [66] \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\"\n [71] \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\"\n [76] \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\"\n [81] \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\"\n [86] \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\"\n [91] \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\"\n [96] \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-07\" \"2025-08-07\"\n[101] \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\"\n[106] \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\"\n[111] \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\"\n[116] \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\"\n[121] \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-22\"\n[126] \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\"\n[131] \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\"\n[136] \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\"\n[141] \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\"\n[146] \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\"\n[151] \"2025-08-22\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\"\n[156] \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\"\n[161] \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\"\n[166] \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\"\n[171] \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\"\n[176] \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-30\" \"2025-08-30\"\n[181] \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\"\n[186] \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\"\n[191] \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\"\n[196] \"2025-08-30\"\n\n\nHowever, looking at the output, we see this looks like the values, not a column. Our suspicions are confirmed when running DataColumn\n\nstr(DataColumn)\n\n chr [1:196] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" ...\n\n\nThis is similarly the case when we use the $ accessor.\n\nDataColumn <- Data$Date\nstr(DataColumn)\n\n chr [1:196] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" ...\n\n\n\nhead(DataColumn, 3)\n\n[1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n\n\nBy contrast, when selecting two columns, the structure is maintained.\n\nTwoColumns <- Data[,4:5]\n\nWhy is the data.frame column structure lost in base R when isolating a single data.frame column? And who thought to make it that convoluted? If we were an R course in early 2010s, we might go into an explanation, but fortunately, we don’t need to understand why, we have the dplyr R package to rescue us." + }, + { + "objectID": "course/03_InsideFCSFile/index.html", + "href": "course/03_InsideFCSFile/index.html", + "title": "03 - Inside an FCS File", "section": "", "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", "crumbs": [ "About", "Intro to R", - "04 - Intro to Tidyverse" + "03 - Inside a .FCS file" ] }, { - "objectID": "course/04_IntroToTidyverse/index.html#read.csv", - "href": "course/04_IntroToTidyverse/index.html#read.csv", - "title": "04 - Introduction to Tidyverse", - "section": "read.csv", - "text": "read.csv\nWe will start by first loading in our copied over dataset (Dataset.csv) from it’s location in the project folder. If you are following the organization scheme we have been using throughout the course, your file path will look something like this:\n\nthefilepath <- file.path(\"data\", \"Dataset.csv\")\n\nthefilepath\n\n[1] \"data/Dataset.csv\"\n\n\n\n\n\n\n\n\nReminder\n\n\n\nWe encourage using the file.path function to build our file paths, as this keeps our code reproducible and replicable when a project folder is copied to other people’s computers that differ on whether the operating system uses forward or backward slash separation between folders.\n\n\nAbove, we directly specified the name (Dataset) and filetype (.csv) of the file we wanted in the last argument of the file.path (“Dataset.csv”). This allows us to skip the list.files() step we used last week as we have provided the full file path. While this approach can be faster, if we accidentally mistype the file name, we could end up with an error at the next step due to no files being found with the mistyped name.\nSince our dataset is stored as a .csv file, we will be using the read.csv() function from the utils package (included in our base R software installation) to read it into R. We will also use the colnames() function from last week to get a read-out of the column names.\n\nData <- read.csv(file=thefilepath, check.names=FALSE)\ncolnames(Data)\n\n [1] \"bid\" \"timepoint\" \"Condition\" \n [4] \"Date\" \"infant_sex\" \"ptype\" \n [7] \"root\" \"singletsFSC\" \"singletsSSC\" \n[10] \"singletsSSCB\" \"CD45\" \"NotMonocytes\" \n[13] \"nonDebris\" \"lymphocytes\" \"live\" \n[16] \"Dump+\" \"Dump-\" \"Tcells\" \n[19] \"Vd2+\" \"Vd2-\" \"Va7.2+\" \n[22] \"Va7.2-\" \"CD4+\" \"CD4-\" \n[25] \"CD8+\" \"CD8-\" \"Tcells_count\" \n[28] \"lymphocytes_count\" \"Monocytes\" \"Debris\" \n[31] \"CD45_count\" \n\n\nAs we look at the line of code, we now have enough context to decipher that the “file” argument is where we provide a file path to an individual file, but what does the “check.names” argument do?\nLet’s see what happens to the column names when we set “check.names” argument to TRUE:\n\nData_Alternative <- read.csv(thefilepath, check.names=TRUE)\ncolnames(Data_Alternative)\n\n [1] \"bid\" \"timepoint\" \"Condition\" \n [4] \"Date\" \"infant_sex\" \"ptype\" \n [7] \"root\" \"singletsFSC\" \"singletsSSC\" \n[10] \"singletsSSCB\" \"CD45\" \"NotMonocytes\" \n[13] \"nonDebris\" \"lymphocytes\" \"live\" \n[16] \"Dump.\" \"Dump..1\" \"Tcells\" \n[19] \"Vd2.\" \"Vd2..1\" \"Va7.2.\" \n[22] \"Va7.2..1\" \"CD4.\" \"CD4..1\" \n[25] \"CD8.\" \"CD8..1\" \"Tcells_count\" \n[28] \"lymphocytes_count\" \"Monocytes\" \"Debris\" \n[31] \"CD45_count\" \n\n\nAs we can see, any column name that contained a special character or a space was automatically converted over to R-approved syntax. However, this resulted in the loss of both +” and “-”, leaving us unable to determine whether we are looking at cells within or outside a particular gate.\n\nBecause of this, it is often better to rename columns individually after import, which we will learn how to do later today.\nFollowing up with what we practiced last week, lets use the head() function to visualize the first few rows of data.\n\nhead(Data, 3)\n\n bid timepoint Condition Date infant_sex ptype root singletsFSC\n1 INF0052 0 Ctrl 2025-07-26 Male HEU-hi 2098368 1894070\n2 INF0100 0 Ctrl 2025-07-26 Male HEU-lo 2020184 1791890\n3 INF0100 4 Ctrl 2025-07-26 Male HEU-lo 1155040 1033320\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1666179 1537396 0.5952943 0.8820349 0.8627649 0.6420138\n2 1697083 1579098 0.9106762 0.9052256 0.8602660 0.2145848\n3 875465 845446 0.9705765 0.9845400 0.9578793 0.7403110\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9020581 0.21090996 0.6911482 0.2804264 0.008120361 0.9918796 0.01448070\n2 0.8908981 0.06252775 0.8283703 0.6748298 0.007265620 0.9927344 0.01577499\n3 0.8757665 0.20023803 0.6755285 0.6119129 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Monocytes Debris CD45_count\n1 587573 0.11796509 0.13723513 915203\n2 308583 0.09477437 0.13973396 1438047\n3 607477 0.01545999 0.04212072 820570\n\n\nWhen working in Positron, we could have alternatively clicked on the little grid icon next to our created variable “Data” in the right secondary sidebar, which would have opened the data in our Editor window. From this same window, we can see it is stored as a “data.frame” object type.\n\nWe could also achieve the same window to open using the View() function:\n\nView(Data)\n\nWrapping up our brief recap of last week functions, we can check an objects type using both the class() and str() functions.\n\nclass(Data)\n\n[1] \"data.frame\"\n\n\n\nstr(Data)\n\n'data.frame': 196 obs. of 31 variables:\n $ bid : chr \"INF0052\" \"INF0100\" \"INF0100\" \"INF0100\" ...\n $ timepoint : int 0 0 4 9 0 4 9 4 9 0 ...\n $ Condition : chr \"Ctrl\" \"Ctrl\" \"Ctrl\" \"Ctrl\" ...\n $ Date : chr \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" ...\n $ infant_sex : chr \"Male\" \"Male\" \"Male\" \"Male\" ...\n $ ptype : chr \"HEU-hi\" \"HEU-lo\" \"HEU-lo\" \"HEU-lo\" ...\n $ root : int 2098368 2020184 1155040 358624 1362216 1044808 1434840 972056 1521928 2363512 ...\n $ singletsFSC : int 1894070 1791890 1033320 328624 1206309 917398 1265022 875707 1359574 2136616 ...\n $ singletsSSC : int 1666179 1697083 875465 289327 1032946 735579 988445 767323 1175755 1875394 ...\n $ singletsSSCB : int 1537396 1579098 845446 276289 982736 685592 940454 718000 1097478 1732620 ...\n $ CD45 : num 0.595 0.911 0.971 0.982 0.957 ...\n $ NotMonocytes : num 0.882 0.905 0.985 0.986 0.956 ...\n $ nonDebris : num 0.863 0.86 0.958 0.941 0.841 ...\n $ lymphocytes : num 0.642 0.215 0.74 0.651 0.705 ...\n $ live : num 0.902 0.891 0.876 0.915 0.895 ...\n $ Dump+ : num 0.2109 0.0625 0.2002 0.2147 0.3383 ...\n $ Dump- : num 0.691 0.828 0.676 0.701 0.557 ...\n $ Tcells : num 0.28 0.675 0.612 0.631 0.44 ...\n $ Vd2+ : num 0.00812 0.00727 0.00465 0.01135 0.00475 ...\n $ Vd2- : num 0.992 0.993 0.995 0.989 0.995 ...\n $ Va7.2+ : num 0.0145 0.0158 0.0158 0.017 0.0133 ...\n $ Va7.2- : num 0.977 0.977 0.98 0.972 0.982 ...\n $ CD4+ : num 0.634 0.612 0.664 0.438 0.739 ...\n $ CD4- : num 0.343 0.365 0.316 0.534 0.243 ...\n $ CD8+ : num 0.273 0.336 0.286 0.486 0.195 ...\n $ CD8- : num 0.0698 0.0293 0.0294 0.0476 0.0476 ...\n $ Tcells_count : int 164771 208241 371723 111552 291777 271870 487937 220634 415867 184930 ...\n $ lymphocytes_count: int 587573 308583 607477 176662 663667 510730 726238 451047 710964 652155 ...\n $ Monocytes : num 0.118 0.0948 0.0155 0.0145 0.0444 ...\n $ Debris : num 0.1372 0.1397 0.0421 0.0587 0.1592 ...\n $ CD45_count : int 915203 1438047 820570 271304 940733 675857 921660 701657 1066884 1017713 ...", + "objectID": "course/03_InsideFCSFile/index.html#getting-set-up", + "href": "course/03_InsideFCSFile/index.html#getting-set-up", + "title": "03 - Inside an FCS File", + "section": "Getting Set Up", + "text": "Getting Set Up\n\n\nSet up File Paths\nHaving copied over the new data to your working project folder (Week 3 or whatever your chosen name), let’s identify the file paths between our working directory and the fcs files. If you retained the same project organization structure we had during Week #2, it may look similar to the following:\n\nPathToDataFolder <- file.path(\"data\")\n\n\nPathToDataFolder\n\n[1] \"data\"\n\n\n\n\n\n\nLocate .fcs files\nWe will now locate our .fcs files. As we saw last week, our computer will need the full file.paths to these individual files, so we will set the list.files() “full.names” argument to TRUE.\n\nfcs_files <- list.files(PathToDataFolder, pattern=\".fcs\", full.names=TRUE)\nfcs_files\n\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n\nBy contrast, if the “full.names” argument was set to FALSE, we would have retrieved just the file names\n\nlist.files(PathToDataFolder, pattern=\".fcs\", full.names=FALSE)\n\n[1] \"CellCounts4L_AB_05_ND050_05.fcs\"\n\n\nThis would have been the equivalent of running the basename function on the “full.names=TRUE” output.\n\nbasename(fcs_files)\n\n[1] \"CellCounts4L_AB_05_ND050_05.fcs\"", "crumbs": [ "About", "Intro to R", - "04 - Intro to Tidyverse" + "03 - Inside a .FCS file" ] }, { - "objectID": "course/04_IntroToTidyverse/index.html#data.frame", - "href": "course/04_IntroToTidyverse/index.html#data.frame", - "title": "04 - Introduction to Tidyverse", - "section": "data.frame", - "text": "data.frame\nOr alternatively using the new-to-us glimpse() function\n\nglimpse(Data)\n\nError in `glimpse()`:\n! could not find function \"glimpse\"\n\n\n\n\n\n\n\n\nCheckpoint 1\n\n\n\nThis however returns an error. Any idea why this might be occuring?\n\n\n\n\nCode\n# We haven't attached/loaded the package in which the function glimpse is within\n\n\n\n\n\n\n\n\nCheckpoint 2\n\n\n\nHow would we locate a package a not-yet-loaded function is within?\n\n\n\n\nCode\n# We can use double ? to search all installed packages for a function, regardless\n# if the package is attached to the environment or not\n\n??glimpse\n\n\n\nFrom the list of search matches (in the right secondary sidebar), it looks likely that the glimpse() function in the dplyr package was the one we were looking for. This is one the main tidyverse packages we will be using throughout the course. Let’s attach it to our environment via the library() call first and try running glimpse() again.\n\nlibrary(dplyr)\nglimpse(Data)\n\nRows: 196\nColumns: 31\n$ bid <chr> \"INF0052\", \"INF0100\", \"INF0100\", \"INF0100\", \"INF0179…\n$ timepoint <int> 0, 0, 4, 9, 0, 4, 9, 4, 9, 0, 0, 4, 9, 0, 4, 9, 4, 9…\n$ Condition <chr> \"Ctrl\", \"Ctrl\", \"Ctrl\", \"Ctrl\", \"Ctrl\", \"Ctrl\", \"Ctr…\n$ Date <chr> \"2025-07-26\", \"2025-07-26\", \"2025-07-26\", \"2025-07-2…\n$ infant_sex <chr> \"Male\", \"Male\", \"Male\", \"Male\", \"Male\", \"Male\", \"Mal…\n$ ptype <chr> \"HEU-hi\", \"HEU-lo\", \"HEU-lo\", \"HEU-lo\", \"HU\", \"HU\", …\n$ root <int> 2098368, 2020184, 1155040, 358624, 1362216, 1044808,…\n$ singletsFSC <int> 1894070, 1791890, 1033320, 328624, 1206309, 917398, …\n$ singletsSSC <int> 1666179, 1697083, 875465, 289327, 1032946, 735579, 9…\n$ singletsSSCB <int> 1537396, 1579098, 845446, 276289, 982736, 685592, 94…\n$ CD45 <dbl> 0.5952943, 0.9106762, 0.9705765, 0.9819573, 0.957259…\n$ NotMonocytes <dbl> 0.8820349, 0.9052256, 0.9845400, 0.9855070, 0.955627…\n$ nonDebris <dbl> 0.8627649, 0.8602660, 0.9578793, 0.9412615, 0.840783…\n$ lymphocytes <dbl> 0.6420138, 0.2145848, 0.7403110, 0.6511588, 0.705478…\n$ live <dbl> 0.9020581, 0.8908981, 0.8757665, 0.9153242, 0.895214…\n$ `Dump+` <dbl> 0.21090996, 0.06252775, 0.20023803, 0.21469246, 0.33…\n$ `Dump-` <dbl> 0.6911482, 0.8283703, 0.6755285, 0.7006317, 0.556895…\n$ Tcells <dbl> 0.2804264, 0.6748298, 0.6119129, 0.6314431, 0.439643…\n$ `Vd2+` <dbl> 0.008120361, 0.007265620, 0.004651313, 0.011348967, …\n$ `Vd2-` <dbl> 0.9918796, 0.9927344, 0.9953487, 0.9886510, 0.995246…\n$ `Va7.2+` <dbl> 0.014480704, 0.015774991, 0.015794019, 0.017023451, …\n$ `Va7.2-` <dbl> 0.9773989, 0.9769594, 0.9795547, 0.9716276, 0.981924…\n$ `CD4+` <dbl> 0.6341164, 0.6119112, 0.6639621, 0.4378944, 0.739256…\n$ `CD4-` <dbl> 0.3432825, 0.3650482, 0.3155925, 0.5337331, 0.242668…\n$ `CD8+` <dbl> 0.2734826, 0.3357696, 0.2862104, 0.4861231, 0.195063…\n$ `CD8-` <dbl> 0.06979990, 0.02927858, 0.02938209, 0.04761008, 0.04…\n$ Tcells_count <int> 164771, 208241, 371723, 111552, 291777, 271870, 4879…\n$ lymphocytes_count <int> 587573, 308583, 607477, 176662, 663667, 510730, 7262…\n$ Monocytes <dbl> 0.11796509, 0.09477437, 0.01545999, 0.01449297, 0.04…\n$ Debris <dbl> 0.13723513, 0.13973396, 0.04212072, 0.05873854, 0.15…\n$ CD45_count <int> 915203, 1438047, 820570, 271304, 940733, 675857, 921…\n\n\nWe notice that while similar to the str() output, glimpse() handles spacing a little differently, and includes the dimensions at the top. However, we can also retrieve the dimensions directly using the dim() function (which maintains the row followed by column position convention of base R (ex. [196,31]))\n\ndim(Data)\n\n[1] 196 31", + "objectID": "course/03_InsideFCSFile/index.html#flowcore", + "href": "course/03_InsideFCSFile/index.html#flowcore", + "title": "03 - Inside an FCS File", + "section": "flowCore", + "text": "flowCore\nWe will be using the flowCore package, which is the oldest and most-frequently downloaded flow cytometry package on Bioconductor.\n\n\nCode\n# I have attached this code for anyone that is interested in seeing how these plots were made. The content is not part of today's lesson, so if you are just starting off, we will cover the details of data-tidying and creating ggplot objects over the next several weeks. Best, David\n\n# Load required packages via a library call\n\nlibrary(dplyr) # CRAN\nlibrary(stringr) # CRAN\nlibrary(ggplot2) # CRAN\n#library(plotly) # Using the :: to access \n\n# Loading in the dataset contained within the .csv file\nBioconductorFlow_path <- file.path(PathToDataFolder, \"BioconductorFlow.csv\")\nBioconductorFlowPackages <- read.csv(BioconductorFlow_path, check.names=FALSE)\nBioconductorFlowPackages <- BioconductorFlowPackages |>\n arrange(desc(since)) |> mutate(package = factor(package, levels = package))\n\n# Newer Base R Pipe : |> \n# Older mostly equivalent Magrittr Pipe %>% \n\n\n\n\nCode\n# Notice the code-chunk eval arguments above dictate the shape of the final rendered plot. \n\n# Taking the imported dataset and passing it to ggplot2 to create the first plot. \n\nplot <- ggplot(BioconductorFlowPackages,\n aes(x = 0, xend = since, y = package, yend = package)) +\n geom_segment(linewidth = 2, color = \"steelblue\") +\n scale_x_continuous(trans = \"reverse\", \n breaks = seq(0, max(BioconductorFlowPackages$since), by = 5)) +\n labs(\n x = \"Years in Bioconductor\",\n y = NULL,\n title = \"Bioconductor Flow Cytometry R packages\"\n ) +\n theme_bw()\n\n# Taking the static plot and making it interactive using the plotly package\n\nplotly::ggplotly(plot)\n\n\n\n\n\n\n\n\nCode\n# Retrieving the names of Bioconductor flow cytometry R packages in correct release order. \n\nHistoricalOrder <- BioconductorFlowPackages |> pull(package)\n\n# Bringing in 2025 package usage dataset from a .csv file\nBioconductorUsage_path <- file.path(PathToDataFolder, \"BioconductorDownloads.csv\")\nBioconductorUsage <- read.csv(BioconductorUsage_path, check.names=FALSE)\nBioconductorUsage <- BioconductorUsage |> dplyr::filter(Month %in% \"all\")\n\n# Note, dplyr::filter is used due to flowCore also having a filter function, which causes conflicts once it is attached to the local environment. \n\n# Combining both data.frames for use in the plot\n\nDataset <- left_join(BioconductorFlowPackages, BioconductorUsage, by=\"package\")\n\n# Rearranging the order in which packages are displayed\n\nDataset$package <- factor(Dataset$package, levels=HistoricalOrder)\n\n\n\n\nCode\n# Generating the 2nd plot with ggplot2\n\nplot <- ggplot(Dataset, aes(x = since, y = Nb_of_distinct_IPs)) +\n geom_point(aes(color = package), size = 3, alpha = 0.7) + \n labs(\n x = \"Years in Bioconductor\",\n y = \"Number of Yearly Downloads\",\n title = \"\",\n color = \"Package\"\n ) +\n theme_bw()\n\n# Making it interactive with plotly\n\nplotly::ggplotly(plot)\n\n\n\n\n\n\nflowCore is also one of the many Bioconductor packages maintained by Mike Jiang. In many ways (as those who completed the optional take-home problems for Week #1 know) reminiscent of this xkcd comic:\n\nAs with all our R packages, we first need to make sure flowCore is attached to our local environment via the library call.\n\nlibrary(flowCore)\n\nThe function we will be using today is the read.FCS() function. Do you remember how to access the help documentation?\n\n\nCode\n# Or when in Positron, hovering over the highlighted function name within the code-chunk\n\n?flowCore::read.FCS\n\n\nTo start, lets select just the first .fcs file. We will do this by indexing the first item within fcs_files via the square brackets [].\n\nfirstfile <- fcs_files[1]\nfirstfile\n\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"", "crumbs": [ "About", "Intro to R", - "04 - Intro to Tidyverse" + "03 - Inside a .FCS file" ] }, { - "objectID": "course/04_IntroToTidyverse/index.html#column-value-type", - "href": "course/04_IntroToTidyverse/index.html#column-value-type", - "title": "04 - Introduction to Tidyverse", - "section": "Column value type", - "text": "Column value type\nAs we saw last week, functions often need values that match a certain type (the paintbrush needing paint analogy). As we inspect the columns of Data, we can notice some of the columns contain values within that are character (ie. “char”) values. Others appear to contain numeric values (which are subtyped as either double (“ie. dbl”) or integer (ie. “int”)). At first glance, we do not appear to have any logical (ie. TRUE or FALSE) columns in this dataset.\n\nIf we were trying to verify type of values contained within a data.frame column, we could employ several similarly-named functions (is.character(), is.numeric() or is.logical()) to check\n\n# colnames(Data) # To recheck the column names\n\nis.character(Data$bid)\n\n[1] TRUE\n\n\n\nis.numeric(Data$bid)\n\n[1] FALSE\n\n\n\n# colnames(Data) # To recheck the column names\n\nis.character(Data$Tcells_count)\n\n[1] FALSE\n\n\nFor numeric columns using the is.numeric() function, we can also be subtype specific using either is.integer() or is.double().\n\n# colnames(Data) # To recheck the column names\n\nis.numeric(Data$Tcells_count)\n\n[1] TRUE\n\nis.integer(Data$Tcells_count)\n\n[1] TRUE\n\nis.double(Data$Tcells_count)\n\n[1] FALSE\n\n\n\n\n\n\n\n\nReminder\n\n\n\nAs we observed last week with keywords, column names that contain special characters like $ or spaces will need to be surrounded with tick marks in order for the function to be able to run.\n\n\n\n# colnames(Data) # To recheck the column names\nis.numeric(Data$CD8-)\n\nError in parse(text = input): <text>:2:21: unexpected ')'\n1: # colnames(Data) # To recheck the column names\n2: is.numeric(Data$CD8-)\n ^\n\n\n\n# colnames(Data) # To recheck the column names\nis.numeric(Data$`CD8-`)\n\n[1] TRUE", + "objectID": "course/03_InsideFCSFile/index.html#flowframe", + "href": "course/03_InsideFCSFile/index.html#flowframe", + "title": "03 - Inside an FCS File", + "section": "flowFrame", + "text": "flowFrame\nFor read.FCS(), it accepts several arguments. The argument “filename” is where we provide our file.path to .fcs file that we wish to load into R. Let’s go ahead and do so\n\nread.FCS(filename=firstfile)\n\nPlease note, if you are doing this with your own .fcs files, you will need to provide two additional arguments, “transformation” = FALSE, and “truncate_max_range” = FALSE for the files to be read in correctly. We will revisit the reasons why in Week #5.\n\nread.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE)\n\nflowFrame object 'CellCounts4L_AB_05-ND050-05.fcs'\nwith 100 cells and 61 observables:\n name desc range minRange maxRange\n$P1 Time NA 272140 0 272139\n$P2 UV1-A NA 4194304 -111 4194303\n$P3 UV2-A NA 4194304 -111 4194303\n$P4 UV3-A NA 4194304 -111 4194303\n$P5 UV4-A NA 4194304 -111 4194303\n... ... ... ... ... ...\n$P57 R4-A NA 4194304 -111 4194303\n$P58 R5-A NA 4194304 -111 4194303\n$P59 R6-A NA 4194304 -111 4194303\n$P60 R7-A NA 4194304 -111 4194303\n$P61 R8-A NA 4194304 -111 4194303\n476 keywords are stored in the 'description' slot\n\n\nIn this case, we can see the .fcs file has been read into R as a “flowFrame” object. We can also see the file name, as well as details about the number of cells, and number of columns (whether detectors (for raw spectral flow data) or fluorophores (for unmixed spectral flow data)).\n\nDirectly below we see what resembles a table. At first glance, the only column with an immediately discernable purpose is the one with the name column, which is listing the detectors present on a Cytek Aurora.\n\nAnd finally, at the bottom we reach a line that tells us that for this .fcs files, 599 keyword can be found in a description slot.\n\n\n\nSo let’s get our bearings, we have loaded in an .fcs file to R, but let’s use some of the concepts we covered last week to try to understand a bit about what type or class of object we are working with. From the output, we saw the words flowFrame object, so let’s read it back in again, but assign it to an variable/object called flowFrame so that we can use the type-discerning functions we worked with last week on.\n\nflowFrame <- read.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE)\n\nAs we create this variable, if we have the session tab selected on our right secondary side bar, we see it appear:\n\nIf we were to use the type-determining functions we learned last week\n\nclass(flowFrame)\n\n[1] \"flowFrame\"\nattr(,\"package\")\n[1] \"flowCore\"\n\n\nflowFrames are a class of object with a structure defined within the flowCore package. They are used to work with the data contained within individual .fcs files. Looking again at the right secondary side bar, we can see that it shows up as a ““S4 class flowFrame package flowCore”“” with 3 slots, with the words flowFrame adjacent to it.\nA perfectly valid first reaction to first reading this is “well how should I know what any of this means?”. Powering through this initial discomfort, let’s go ahead and click on the dropdown arrow next to the variables name and see if we get any additional clarity on the issue.\n\nWhen we do so, three additional drop-downs appear. Based on the previous line that mentioned 3 slots, we could infer that each line corresponds to one of those slots.\nWhat we are encountering with flowFrame is our first example of an S4 object type. These more-complicated object types are quite common for the various Bioconductor affilitated R packages.\nThese objects will usually appear with either S4 or S3 in their metadata, and are made up of various simpler object types that are cobbled together within the larger object, usually occupying individual slots.\nWhat advantage this bundling provides will be something we revisit throughout the course as you encounter more of these S4/S3 objects.\n\n\n\nexprs\nThe first slot within the flowFrame object shows up with the name “exprs”. For the exprs object, glancing at it’s middle column, we can based on the 100 rows and 61 columns, that it is likely a matrix-style object. We might also recall we saw similar numbers in the printed output when we ran read.FCS()earlier.\n\nWhich likely means that “exprs” slot is where the MFI data for the individual acquired cells within our .fcs file is being stored. Within Positron, for a matrix object, we can click on the little grid symbol on the far right to open up the table within editor.\n\nIf we utilize the scroll bars, we can see that the individual detectors (in the case of uploading a raw spectral fcs file, they would appear as fluorophores for unmixed spectral or conventional fcs files) occupy the individual columns, which are named. The rows are not named, but number 100, matching the number of cells present in the .fcs file. Additionally, on the far left there is a little summary table about the overall data.\n\nLet’s go ahead and assign this matrix to a new variable/object so that we can explore it later. Since flowFrame is an S4 object, it’s slots can be individually accessed by adding the @ symbol and the respective slot name.\n\nMFI_Matrix <- flowFrame@exprs\n\nAlternatively, we can use the Bioconductor helper function exprs() to get data held in that slot\n\nMFI_Matrix_Alternate <- exprs(flowFrame)\n\nIn the case of the above, this displayed text output to the console would be unwiedly to display all at once. If we wanted to only see the first five rows, we could use the head() function, and provide a value of 5.\n\nhead(MFI_Matrix, 5)\n\n Time UV1-A UV2-A UV3-A UV4-A UV5-A UV6-A\n[1,] 38823 37.79983 -184.479996 353.87714 1106.22998 1145.18140 2130.21899\n[2,] 39780 234.23021 -98.456429 26.43876 70.65833 -89.93541 -29.14263\n[3,] 267292 -117.96355 40.732426 473.94574 1177.86975 1516.70935 1985.46130\n[4,] 128101 289.87671 -2.723389 -54.11960 -163.71489 32.62989 -134.90411\n[5,] 255221 -104.50541 -71.163338 567.57562 610.23627 1416.61328 2868.16040\n UV7-A UV8-A UV9-A UV10-A UV11-A UV12-A UV13-A\n[1,] 4376.34277 3246.7952 32050.65039 8123.2637 1992.5785 1070.3323 956.43573\n[2,] -26.34649 -162.6675 17.98848 271.9152 154.8575 163.5411 -32.81524\n[3,] 3658.87671 4140.1724 59792.16406 14013.7969 3427.4324 1668.7588 1071.14636\n[4,] 739.71960 402.9025 427.37534 315.6364 -223.0423 145.7121 127.03777\n[5,] 4034.58789 3234.6626 40126.46484 10325.0371 1974.0907 1033.8450 -21.57245\n UV14-A UV15-A UV16-A SSC-H SSC-A V1-A V2-A\n[1,] 290.8685 385.49921 670.97687 657613 750760.12 1171.1390 154.5628\n[2,] -104.9198 103.41382 71.41528 83481 81552.85 266.2424 705.2527\n[3,] 730.1430 214.93053 252.75406 890845 1183519.00 1196.0931 1183.1105\n[4,] -207.8978 -55.37944 -45.10131 75103 72457.33 227.9926 556.9189\n[5,] 273.6271 960.16290 341.20633 415791 501690.97 717.2498 929.9780\n V3-A V4-A V5-A V6-A V7-A V8-A\n[1,] 1346.4488525 1706.9260 1923.50940 898.2527 3162.55371 83596.5078\n[2,] 244.3218689 341.0508 381.15939 87.1600 151.68785 119.5544\n[3,] 2087.0092773 824.6352 1635.27258 1613.9069 4653.16260 176981.6094\n[4,] -0.8137281 205.4732 18.12125 179.6371 -69.50061 -132.4348\n[5,] 1358.4512939 788.6506 1208.81006 1156.7040 3118.42627 104951.2578\n V9-A V10-A V11-A V12-A V13-A V14-A\n[1,] 32506.7617 27161.5137 6236.072754 2220.303223 2023.39966 753.589355\n[2,] -79.7691 -109.1783 -73.991196 114.375542 -11.53453 124.986206\n[3,] 69236.4297 57626.8984 13175.838867 4534.874023 3434.38989 1995.172363\n[4,] 129.2739 231.8918 -5.473321 8.792875 -24.62049 -8.212234\n[5,] 42090.0781 34104.3164 7620.552734 3103.544189 2426.43359 650.836304\n V15-A V16-A FSC-H FSC-A SSC-B-H SSC-B-A B1-A\n[1,] 510.9540 228.34962 1055905 1217097.50 716733 815959.06 606.6683\n[2,] -207.3494 -28.96272 79696 83439.11 104575 103132.83 195.2795\n[3,] 1321.8030 615.05560 1092481 1453969.38 757351 982038.31 2010.5110\n[4,] -133.7503 -34.32619 64760 60415.23 67955 66806.13 -146.8936\n[5,] 290.2892 473.32599 1038362 1184479.00 425296 522873.12 1015.5981\n B2-A B3-A B4-A B5-A B6-A B7-A\n[1,] 416.98294 4172.4712 192400.0938 93929.9375 54236.3320 19342.6445\n[2,] 333.25662 332.1675 -230.9639 196.7810 292.8945 -187.2845\n[3,] 2150.21826 10106.9551 437801.5625 212176.1562 124294.3594 45068.3008\n[4,] -34.90987 165.7988 675.0156 136.3076 482.8665 133.0948\n[5,] 639.77527 6034.0200 244022.6094 118871.4609 68616.9688 24067.7949\n B8-A B9-A B10-A B11-A B12-A B13-A\n[1,] 10507.24219 9498.1270 4465.50928 1668.048096 2199.9475 1581.7345\n[2,] 70.90886 -334.3563 188.05545 -663.359619 -163.2331 27.9856\n[3,] 24289.59180 22500.1914 10624.99219 4684.497559 3471.7749 2727.3904\n[4,] 432.28091 246.8794 -94.44906 2.905877 106.8489 283.3633\n[5,] 14182.12793 13019.7100 5577.33984 2753.355957 1279.3009 1423.0276\n B14-A R1-A R2-A R3-A R4-A R5-A\n[1,] 1487.56860 147.1335 129.867630 35.90353 267.23999 49.79849\n[2,] 205.82298 -142.9224 66.516052 113.63218 -94.41375 98.13978\n[3,] 2371.95850 -128.3749 -105.482544 726.48547 18.87000 95.47879\n[4,] 33.24665 127.5455 122.607941 37.83584 -82.87500 -343.83768\n[5,] 1565.72742 -266.4482 -3.350622 -178.39566 -117.10875 -100.10384\n R6-A R7-A R8-A\n[1,] -732.7097 42.83144 248.56728\n[2,] 143.4497 -263.28741 -85.83299\n[3,] -194.4526 -84.08820 -301.46066\n[4,] 82.3745 60.27896 -94.38461\n[5,] -182.0066 184.36417 186.17207\n\n\nThis is much more workable, especially on a small laptop screen. We can see that there are names for each column corresponding to detector/fluorophore/metal depending on the .fcs file we are accessing. Lets retrieve these column names using the colnames() function.\n\nColumnNames <- colnames(MFI_Matrix)\nColumnNames\n\n $P1N $P2N $P3N $P4N $P5N $P6N $P7N $P8N \n \"Time\" \"UV1-A\" \"UV2-A\" \"UV3-A\" \"UV4-A\" \"UV5-A\" \"UV6-A\" \"UV7-A\" \n $P9N $P10N $P11N $P12N $P13N $P14N $P15N $P16N \n \"UV8-A\" \"UV9-A\" \"UV10-A\" \"UV11-A\" \"UV12-A\" \"UV13-A\" \"UV14-A\" \"UV15-A\" \n $P17N $P18N $P19N $P20N $P21N $P22N $P23N $P24N \n \"UV16-A\" \"SSC-H\" \"SSC-A\" \"V1-A\" \"V2-A\" \"V3-A\" \"V4-A\" \"V5-A\" \n $P25N $P26N $P27N $P28N $P29N $P30N $P31N $P32N \n \"V6-A\" \"V7-A\" \"V8-A\" \"V9-A\" \"V10-A\" \"V11-A\" \"V12-A\" \"V13-A\" \n $P33N $P34N $P35N $P36N $P37N $P38N $P39N $P40N \n \"V14-A\" \"V15-A\" \"V16-A\" \"FSC-H\" \"FSC-A\" \"SSC-B-H\" \"SSC-B-A\" \"B1-A\" \n $P41N $P42N $P43N $P44N $P45N $P46N $P47N $P48N \n \"B2-A\" \"B3-A\" \"B4-A\" \"B5-A\" \"B6-A\" \"B7-A\" \"B8-A\" \"B9-A\" \n $P49N $P50N $P51N $P52N $P53N $P54N $P55N $P56N \n \"B10-A\" \"B11-A\" \"B12-A\" \"B13-A\" \"B14-A\" \"R1-A\" \"R2-A\" \"R3-A\" \n $P57N $P58N $P59N $P60N $P61N \n \"R4-A\" \"R5-A\" \"R6-A\" \"R7-A\" \"R8-A\" \n\n\nSomething interesting occurred when this occurred, we can see in addition to the detector names directly above each a “$P#N” pattern appear, with # standing for increasing numbers. If we recall, we saw something similar in the first output column when we first ran read.FCS().\n\nLets break out the str() and class() functions from last week and see what we can find out about why this is occuring.\n\nstr(ColumnNames)\n\n Named chr [1:61] \"Time\" \"UV1-A\" \"UV2-A\" \"UV3-A\" \"UV4-A\" \"UV5-A\" \"UV6-A\" ...\n - attr(*, \"names\")= chr [1:61] \"$P1N\" \"$P2N\" \"$P3N\" \"$P4N\" ...\n\n\nIn this case we can see that we don’t just have a vector (list) similar to what we saw with Fluorophores object last week, because instead of a chr [1:61] we get back a Named chr [1:61] designation. What we see is that in this case, each value has a corresponding index name as well. (ex. $P1N, $P2N, etc.) Let’s double check with class() function.\n\nclass(ColumnNames)\n\n[1] \"character\"\n\n\nWe can see that everything is character, but it doesn’t inform us that each index was named. This is one of the reasons it is best when trying to see what type of an object something is, to use multiple functions, to avoid missing some important details.\nIf we were trying to remove the names, being left with just the values (similar to what we saw with the vector-style list last week), we could use the unname() function:\n\nunname(ColumnNames)\n\n [1] \"Time\" \"UV1-A\" \"UV2-A\" \"UV3-A\" \"UV4-A\" \"UV5-A\" \"UV6-A\" \n [8] \"UV7-A\" \"UV8-A\" \"UV9-A\" \"UV10-A\" \"UV11-A\" \"UV12-A\" \"UV13-A\" \n[15] \"UV14-A\" \"UV15-A\" \"UV16-A\" \"SSC-H\" \"SSC-A\" \"V1-A\" \"V2-A\" \n[22] \"V3-A\" \"V4-A\" \"V5-A\" \"V6-A\" \"V7-A\" \"V8-A\" \"V9-A\" \n[29] \"V10-A\" \"V11-A\" \"V12-A\" \"V13-A\" \"V14-A\" \"V15-A\" \"V16-A\" \n[36] \"FSC-H\" \"FSC-A\" \"SSC-B-H\" \"SSC-B-A\" \"B1-A\" \"B2-A\" \"B3-A\" \n[43] \"B4-A\" \"B5-A\" \"B6-A\" \"B7-A\" \"B8-A\" \"B9-A\" \"B10-A\" \n[50] \"B11-A\" \"B12-A\" \"B13-A\" \"B14-A\" \"R1-A\" \"R2-A\" \"R3-A\" \n[57] \"R4-A\" \"R5-A\" \"R6-A\" \"R7-A\" \"R8-A\" \n\n\n\n\nLet’s return to the right sidebar to continue our exploration, by clicking on the dropdown arrow for exprs in the side-bar\n\nThe output is less user-friendly than what we saw when clicking on the little grid. If we scroll down far enough, we get down as far as [,61], which corresponds to the total number of columns.\n\nIn base R, column order can be defined by placing the corresponding column index number after a comma “,”. So for this case, the first column would be designated would be [,1] while the last column would be designated [,61].\n\nMFI_Matrix[,1]\n\n [1] 38823 39780 267292 128101 255221 79210 196643 83855 109315 26128\n [11] 114423 120001 71831 70551 197021 239994 252611 223012 152780 171822\n [21] 172611 168464 191503 253015 73885 82221 176641 128533 4117 191632\n [31] 191229 58093 141776 265894 55593 227555 233212 248578 95165 171934\n [41] 1360 251847 195764 147503 118723 1060 90033 253553 268268 74610\n [51] 23531 150119 226391 201568 179264 79944 196686 252667 117309 3903\n [61] 77690 195142 229873 254472 179943 236618 68193 87154 28541 78622\n [71] 155664 50115 40866 70753 260118 12033 96149 20740 37461 73998\n [81] 231939 192329 88649 197664 86006 142486 159539 251298 104864 164090\n [91] 102380 218968 145182 239323 261272 118979 17202 194277 229284 258723\n\n\n\nMFI_Matrix[,61]\n\n [1] 248.567276 -85.832993 -301.460663 -94.384613 186.172073 -461.407745\n [7] 843.507080 277.516113 -106.166855 281.633545 195.927261 818.865723\n [13] 734.996460 209.356476 206.442596 279.859894 518.165222 56.947498\n [19] 285.751007 857.126343 -94.384613 -213.030518 62.585236 138.409653\n [25] 118.012444 328.255768 -61.635056 185.285233 464.384979 5.637739\n [31] -66.385956 31.229273 1198.241211 185.475266 873.279419 457.607025\n [37] -73.353951 37.880539 729.168640 221.772171 -169.512238 348.272888\n [43] -338.391022 845.534119 -4.434176 620.024597 610.269409 -193.900208\n [49] 230.830566 -23.754517 607.102112 14.949510 -34.333195 -169.132172\n [55] -96.158287 220.631958 125.297165 -15.202891 -126.057304 193.393448\n [61] 90.203819 -277.706146 590.505615 911.096619 -92.230873 347.259369\n [67] 135.559113 369.430267 -62.015125 -180.597672 -146.517868 810.440796\n [73] 134.038818 -165.268097 727.711731 -88.746880 62.901962 203.275330\n [79] 436.196289 -242.676147 -40.857769 222.278946 -170.272385 525.513245\n [85] -41.491222 176.670258 201.501648 175.530045 329.839386 474.140167\n [91] -48.142490 -174.833252 46.052090 357.584656 -26.541714 191.493088\n [97] 211.320190 124.790398 -113.324883 343.268616\n\n\nWhat would happen if used a column index number that didn’t exist? Let’s check.\n\nMFI_Matrix[,350]\n\nError in `MFI_Matrix[, 350]`:\n! subscript out of bounds\n\n\nWe get back an error message telling us the subscript is out of bounds.\nSo if columns are specified by a number after the comma (ex. [,1]), how are rows specified? In R, rows would be specified by a number before the comma [1,]\n\nMFI_Matrix[1,]\n\n Time UV1-A UV2-A UV3-A UV4-A \n 38823.00000 37.79983 -184.48000 353.87714 1106.22998 \n UV5-A UV6-A UV7-A UV8-A UV9-A \n 1145.18140 2130.21899 4376.34277 3246.79517 32050.65039 \n UV10-A UV11-A UV12-A UV13-A UV14-A \n 8123.26367 1992.57849 1070.33228 956.43573 290.86853 \n UV15-A UV16-A SSC-H SSC-A V1-A \n 385.49921 670.97687 657613.00000 750760.12500 1171.13904 \n V2-A V3-A V4-A V5-A V6-A \n 154.56281 1346.44885 1706.92603 1923.50940 898.25269 \n V7-A V8-A V9-A V10-A V11-A \n 3162.55371 83596.50781 32506.76172 27161.51367 6236.07275 \n V12-A V13-A V14-A V15-A V16-A \n 2220.30322 2023.39966 753.58936 510.95404 228.34962 \n FSC-H FSC-A SSC-B-H SSC-B-A B1-A \n1055905.00000 1217097.50000 716733.00000 815959.06250 606.66833 \n B2-A B3-A B4-A B5-A B6-A \n 416.98294 4172.47119 192400.09375 93929.93750 54236.33203 \n B7-A B8-A B9-A B10-A B11-A \n 19342.64453 10507.24219 9498.12695 4465.50928 1668.04810 \n B12-A B13-A B14-A R1-A R2-A \n 2199.94751 1581.73450 1487.56860 147.13348 129.86763 \n R3-A R4-A R5-A R6-A R7-A \n 35.90353 267.23999 49.79849 -732.70966 42.83144 \n R8-A \n 248.56728 \n\n\nAnd while not the focus of today, we could retrieve individual values from a matrix by specifying both a row and a column index number. So for example, if we wanted the MFI value for the UV1-A detector for the first acquired cell (knowing that UV1-A is the 2nd column):\n\nMFI_Matrix[1,2]\n\n UV1-A \n37.79983 \n\n\nFrom our exploration, this looks to be all the information contained within the “exprs” slot, so let’s back up and check on the next slot.\n\n\n\n\nparameters\nAs we look at the next slot in the flowFrame object, we can see that parameters looks like it is going to be another more complex object, as it is showing up as an AnnotatedDataFrame object (defined by the Biobase R package, and itself contains 4 slots).\n\n\nHaving carved our way this far into the heart of an .fcs file, we are not about to call it quits now, so CHARGE my fellow cytometrist!!! Click that drop-down arrow!\n\nHaving survived our charge into the unknown, the four parameter slots appear to be “varMetadata”, “data”, “dimLabels” and “._classVersion_”.\n\n\nvarMetadata\nFortunately for us, both “varMetadata” and “data” at least appear to be table-like objects of a type known as a “data.frame”, so lets click on the grid to open in our editor window.\nIn the case of varMetadata, we seem to have retrieved a column of metadata names.\n\nThese look reminiscent of what we saw at the top of the read.FCS() column outputs previously\n\n\n\ndata\nClicking on the grid for parameters’s data slot will end opening the actual content that was displayed.\n\nLet’s try to retrieve the data contained within this slot and save it as it’s own variable/object within our R session. First, we need to open flowFrame object, then use @ to get inside its parameters slot. Since parameters is also a complex object (AnnotatedDataFrame specifically), we will need to use another @ to get inside its data slot:\n\nParameterData <- flowFrame@parameters@data\n\nhead(ParameterData, 10)\n\n name desc range minRange maxRange\n$P1 Time <NA> 272140 0.00000 272139\n$P2 UV1-A <NA> 4194304 -111.00000 4194303\n$P3 UV2-A <NA> 4194304 -111.00000 4194303\n$P4 UV3-A <NA> 4194304 -111.00000 4194303\n$P5 UV4-A <NA> 4194304 -111.00000 4194303\n$P6 UV5-A <NA> 4194304 -111.00000 4194303\n$P7 UV6-A <NA> 4194304 -111.00000 4194303\n$P8 UV7-A <NA> 4194304 -26.34649 4194303\n$P9 UV8-A <NA> 4194304 -111.00000 4194303\n$P10 UV9-A <NA> 4194304 0.00000 4194303\n\n\nAnd similarly, we could access with the Bioconductor helper function parameters(), but we would need to specify the accessor for data outside the parenthesis.\n\nParameterData_Alternate <- parameters(flowFrame)@data\n\nIf we ran the str() function, we get the following insight into ParameterData’s object type\n\nstr(ParameterData)\n\n'data.frame': 61 obs. of 5 variables:\n $ name : 'AsIs' Named chr \"Time\" \"UV1-A\" \"UV2-A\" \"UV3-A\" ...\n ..- attr(*, \"names\")= chr [1:61] \"$P1N\" \"$P2N\" \"$P3N\" \"$P4N\" ...\n $ desc : 'AsIs' Named chr NA NA NA NA ...\n ..- attr(*, \"names\")= chr [1:61] NA NA NA NA ...\n $ range : num 272140 4194304 4194304 4194304 4194304 ...\n $ minRange: num 0 -111 -111 -111 -111 ...\n $ maxRange: num 272139 4194303 4194303 4194303 4194303 ...\n\n\nWe can see this class of object is a “data.frame”. This is one of the more common object types in R, and we will be seeing these extensively throughout the course. We see that each of the columns appears to be designated by a $ followed by the column name, and then type of column (numeric, character, etc).\n\nIf we are trying to see these columns in R, we notice that data.frame is not like the previous S4 class objets we interacted with, as the @ symbol after doesn’t bring up any suggestions\n\nParameterData@\n\nBy contrast, adding the $ we saw when using the str() function does retrieve the underlying information\n\nParameterData$\n\n\nAs you become more familiar with R, remembering to check what kind of object you are working with, and how to access the contents will with practice become more familiar to you.\nSimilar to what we saw with a matrix, we can subset a data.frame based on the column or row index using square brackets [].\n\nParameterData[,1]\n\n $P1N $P2N $P3N $P4N $P5N $P6N $P7N $P8N \n \"Time\" \"UV1-A\" \"UV2-A\" \"UV3-A\" \"UV4-A\" \"UV5-A\" \"UV6-A\" \"UV7-A\" \n $P9N $P10N $P11N $P12N $P13N $P14N $P15N $P16N \n \"UV8-A\" \"UV9-A\" \"UV10-A\" \"UV11-A\" \"UV12-A\" \"UV13-A\" \"UV14-A\" \"UV15-A\" \n $P17N $P18N $P19N $P20N $P21N $P22N $P23N $P24N \n \"UV16-A\" \"SSC-H\" \"SSC-A\" \"V1-A\" \"V2-A\" \"V3-A\" \"V4-A\" \"V5-A\" \n $P25N $P26N $P27N $P28N $P29N $P30N $P31N $P32N \n \"V6-A\" \"V7-A\" \"V8-A\" \"V9-A\" \"V10-A\" \"V11-A\" \"V12-A\" \"V13-A\" \n $P33N $P34N $P35N $P36N $P37N $P38N $P39N $P40N \n \"V14-A\" \"V15-A\" \"V16-A\" \"FSC-H\" \"FSC-A\" \"SSC-B-H\" \"SSC-B-A\" \"B1-A\" \n $P41N $P42N $P43N $P44N $P45N $P46N $P47N $P48N \n \"B2-A\" \"B3-A\" \"B4-A\" \"B5-A\" \"B6-A\" \"B7-A\" \"B8-A\" \"B9-A\" \n $P49N $P50N $P51N $P52N $P53N $P54N $P55N $P56N \n \"B10-A\" \"B11-A\" \"B12-A\" \"B13-A\" \"B14-A\" \"R1-A\" \"R2-A\" \"R3-A\" \n $P57N $P58N $P59N $P60N $P61N \n \"R4-A\" \"R5-A\" \"R6-A\" \"R7-A\" \"R8-A\" \n\n\nThe individual detectors or fluorophore appear under “name”. For now, based on what we know, the $P# appears to be some sort of name being used as an internal consistent reference to the respective.\n“desc” is appearing empty for this raw spectral fcs file, but if you were to checked an unmixed file, this would be occupied the marker/ligand name assigned to it during the experiment setup.\n“range”, “minRange” and “maxRange” are beyond the scope of today, but are used by both instrument manufacturers and software vendors when setting appropiate scaling for a plot. For the actual details, see the Flow Cytometry Standard documentation.\nHaving exhausted our options under parameters “varMetadata” and “data” slots, let’s continue to the next slot.\n\n\ndimLabels\n\nIn this case, not much is returned. Yey!\n\nflowFrame@parameters@dimLabels\n\n[1] \"rowNames\" \"columnNames\"\n\n\n\n\nclassVersion\nContinuing on to the last slot “.__classVersion__”\n\nflowFrame@parameters@.__classVersion__\n\nAnnotatedDataFrame \n \"1.1.0\" \n\n\nAlso mercifully short, both of these seem to be more involved in defining the S4 class object, and don’t contain anything we need to retrieve today.\n\n\n\n\nDescription\nAt this point, we have explored both “exprs” and “parameter” slots for the flowFrame object we created. Let’s tackle the final slot, named description.\n\nWhen doing so, a very large list is opened within the Positron variables window. While we could scroll through it, it might be easier to retrieve certain number of rows via the console to make interpreting this more structured.\n\nTo retrieve the list itself, we would need to access the description slot of the flowFrame object. Since it is a slot, we will need to use the @ accessor.\n\n\nDescriptionList <- flowFrame@description\n\n\nDescriptionList \n\n$`$BEGINANALYSIS`\n[1] \"0\"\n\n$`$BEGINDATA`\n[1] \"33312\"\n\n$`$BEGINSTEXT`\n[1] \"0\"\n\n$`$BTIM`\n[1] \"13:55:29.85\"\n\n$`$BYTEORD`\n[1] \"4,3,2,1\"\n\n$`$CYT`\n[1] \"Aurora\"\n\n$`$CYTOLIB_VERSION`\n[1] \"2.22.0\"\n\n$`$CYTSN`\n[1] \"V0333\"\n\n$`$DATATYPE`\n[1] \"F\"\n\n$`$DATE`\n[1] \"04-Aug-2025\"\n\n$`$ENDANALYSIS`\n[1] \"0\"\n\n$`$ENDDATA`\n[1] \"57711\"\n\n$`$ENDSTEXT`\n[1] \"0\"\n\n$`$ETIM`\n[1] \"13:55:57.02\"\n\n$`$FIL`\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n$`$INST`\n[1] \"UMBC\"\n\n$`$MODE`\n[1] \"L\"\n\n$`$NEXTDATA`\n[1] \"0\"\n\n$`$OP`\n[1] \"David Rach\"\n\n$`$P10B`\n[1] \"32\"\n\n$`$P10E`\n[1] \"0,0\"\n\n$`$P10N`\n[1] \"UV9-A\"\n\n$`$P10R`\n[1] \"4194304\"\n\n$`$P10TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P10V`\n[1] \"710\"\n\n$`$P11B`\n[1] \"32\"\n\n$`$P11E`\n[1] \"0,0\"\n\n$`$P11N`\n[1] \"UV10-A\"\n\n$`$P11R`\n[1] \"4194304\"\n\n$`$P11TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P11V`\n[1] \"377\"\n\n$`$P12B`\n[1] \"32\"\n\n$`$P12E`\n[1] \"0,0\"\n\n$`$P12N`\n[1] \"UV11-A\"\n\n$`$P12R`\n[1] \"4194304\"\n\n$`$P12TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P12V`\n[1] \"469\"\n\n$`$P13B`\n[1] \"32\"\n\n$`$P13E`\n[1] \"0,0\"\n\n$`$P13N`\n[1] \"UV12-A\"\n\n$`$P13R`\n[1] \"4194304\"\n\n$`$P13TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P13V`\n[1] \"434\"\n\n$`$P14B`\n[1] \"32\"\n\n$`$P14E`\n[1] \"0,0\"\n\n$`$P14N`\n[1] \"UV13-A\"\n\n$`$P14R`\n[1] \"4194304\"\n\n$`$P14TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P14V`\n[1] \"564\"\n\n$`$P15B`\n[1] \"32\"\n\n$`$P15E`\n[1] \"0,0\"\n\n$`$P15N`\n[1] \"UV14-A\"\n\n$`$P15R`\n[1] \"4194304\"\n\n$`$P15TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P15V`\n[1] \"975\"\n\n$`$P16B`\n[1] \"32\"\n\n$`$P16E`\n[1] \"0,0\"\n\n$`$P16N`\n[1] \"UV15-A\"\n\n$`$P16R`\n[1] \"4194304\"\n\n$`$P16TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P16V`\n[1] \"737\"\n\n$`$P17B`\n[1] \"32\"\n\n$`$P17E`\n[1] \"0,0\"\n\n$`$P17N`\n[1] \"UV16-A\"\n\n$`$P17R`\n[1] \"4194304\"\n\n$`$P17TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P17V`\n[1] \"1069\"\n\n$`$P18B`\n[1] \"32\"\n\n$`$P18E`\n[1] \"0,0\"\n\n$`$P18N`\n[1] \"SSC-H\"\n\n$`$P18R`\n[1] \"4194304\"\n\n$`$P18TYPE`\n[1] \"Side_Scatter\"\n\n$`$P18V`\n[1] \"334\"\n\n$`$P19B`\n[1] \"32\"\n\n$`$P19E`\n[1] \"0,0\"\n\n$`$P19N`\n[1] \"SSC-A\"\n\n$`$P19R`\n[1] \"4194304\"\n\n$`$P19TYPE`\n[1] \"Side_Scatter\"\n\n$`$P19V`\n[1] \"334\"\n\n$`$P1B`\n[1] \"32\"\n\n$`$P1E`\n[1] \"0,0\"\n\n$`$P1N`\n[1] \"Time\"\n\n$`$P1R`\n[1] \"272140\"\n\n$`$P1TYPE`\n[1] \"Time\"\n\n$`$P20B`\n[1] \"32\"\n\n$`$P20E`\n[1] \"0,0\"\n\n$`$P20N`\n[1] \"V1-A\"\n\n$`$P20R`\n[1] \"4194304\"\n\n$`$P20TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P20V`\n[1] \"352\"\n\n$`$P21B`\n[1] \"32\"\n\n$`$P21E`\n[1] \"0,0\"\n\n$`$P21N`\n[1] \"V2-A\"\n\n$`$P21R`\n[1] \"4194304\"\n\n$`$P21TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P21V`\n[1] \"412\"\n\n$`$P22B`\n[1] \"32\"\n\n$`$P22E`\n[1] \"0,0\"\n\n$`$P22N`\n[1] \"V3-A\"\n\n$`$P22R`\n[1] \"4194304\"\n\n$`$P22TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P22V`\n[1] \"304\"\n\n$`$P23B`\n[1] \"32\"\n\n$`$P23E`\n[1] \"0,0\"\n\n$`$P23N`\n[1] \"V4-A\"\n\n$`$P23R`\n[1] \"4194304\"\n\n$`$P23TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P23V`\n[1] \"217\"\n\n$`$P24B`\n[1] \"32\"\n\n$`$P24E`\n[1] \"0,0\"\n\n$`$P24N`\n[1] \"V5-A\"\n\n$`$P24R`\n[1] \"4194304\"\n\n$`$P24TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P24V`\n[1] \"257\"\n\n$`$P25B`\n[1] \"32\"\n\n$`$P25E`\n[1] \"0,0\"\n\n$`$P25N`\n[1] \"V6-A\"\n\n$`$P25R`\n[1] \"4194304\"\n\n$`$P25TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P25V`\n[1] \"218\"\n\n$`$P26B`\n[1] \"32\"\n\n$`$P26E`\n[1] \"0,0\"\n\n$`$P26N`\n[1] \"V7-A\"\n\n$`$P26R`\n[1] \"4194304\"\n\n$`$P26TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P26V`\n[1] \"303\"\n\n$`$P27B`\n[1] \"32\"\n\n$`$P27E`\n[1] \"0,0\"\n\n$`$P27N`\n[1] \"V8-A\"\n\n$`$P27R`\n[1] \"4194304\"\n\n$`$P27TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P27V`\n[1] \"461\"\n\n$`$P28B`\n[1] \"32\"\n\n$`$P28E`\n[1] \"0,0\"\n\n$`$P28N`\n[1] \"V9-A\"\n\n$`$P28R`\n[1] \"4194304\"\n\n$`$P28TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P28V`\n[1] \"320\"\n\n$`$P29B`\n[1] \"32\"\n\n$`$P29E`\n[1] \"0,0\"\n\n$`$P29N`\n[1] \"V10-A\"\n\n$`$P29R`\n[1] \"4194304\"\n\n$`$P29TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P29V`\n[1] \"359\"\n\n$`$P2B`\n[1] \"32\"\n\n$`$P2E`\n[1] \"0,0\"\n\n$`$P2N`\n[1] \"UV1-A\"\n\n$`$P2R`\n[1] \"4194304\"\n\n$`$P2TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P2V`\n[1] \"1008\"\n\n$`$P30B`\n[1] \"32\"\n\n$`$P30E`\n[1] \"0,0\"\n\n$`$P30N`\n[1] \"V11-A\"\n\n$`$P30R`\n[1] \"4194304\"\n\n$`$P30TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P30V`\n[1] \"271\"\n\n$`$P31B`\n[1] \"32\"\n\n$`$P31E`\n[1] \"0,0\"\n\n$`$P31N`\n[1] \"V12-A\"\n\n$`$P31R`\n[1] \"4194304\"\n\n$`$P31TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P31V`\n[1] \"234\"\n\n$`$P32B`\n[1] \"32\"\n\n$`$P32E`\n[1] \"0,0\"\n\n$`$P32N`\n[1] \"V13-A\"\n\n$`$P32R`\n[1] \"4194304\"\n\n$`$P32TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P32V`\n[1] \"236\"\n\n$`$P33B`\n[1] \"32\"\n\n$`$P33E`\n[1] \"0,0\"\n\n$`$P33N`\n[1] \"V14-A\"\n\n$`$P33R`\n[1] \"4194304\"\n\n$`$P33TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P33V`\n[1] \"318\"\n\n$`$P34B`\n[1] \"32\"\n\n$`$P34E`\n[1] \"0,0\"\n\n$`$P34N`\n[1] \"V15-A\"\n\n$`$P34R`\n[1] \"4194304\"\n\n$`$P34TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P34V`\n[1] \"602\"\n\n$`$P35B`\n[1] \"32\"\n\n$`$P35E`\n[1] \"0,0\"\n\n$`$P35N`\n[1] \"V16-A\"\n\n$`$P35R`\n[1] \"4194304\"\n\n$`$P35TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P35V`\n[1] \"372\"\n\n$`$P36B`\n[1] \"32\"\n\n$`$P36E`\n[1] \"0,0\"\n\n$`$P36N`\n[1] \"FSC-H\"\n\n$`$P36R`\n[1] \"4194304\"\n\n$`$P36TYPE`\n[1] \"Forward_Scatter\"\n\n$`$P36V`\n[1] \"55\"\n\n$`$P37B`\n[1] \"32\"\n\n$`$P37E`\n[1] \"0,0\"\n\n$`$P37N`\n[1] \"FSC-A\"\n\n$`$P37R`\n[1] \"4194304\"\n\n$`$P37TYPE`\n[1] \"Forward_Scatter\"\n\n$`$P37V`\n[1] \"55\"\n\n$`$P38B`\n[1] \"32\"\n\n$`$P38E`\n[1] \"0,0\"\n\n$`$P38N`\n[1] \"SSC-B-H\"\n\n$`$P38R`\n[1] \"4194304\"\n\n$`$P38TYPE`\n[1] \"Side_Scatter\"\n\n$`$P38V`\n[1] \"241\"\n\n$`$P39B`\n[1] \"32\"\n\n$`$P39E`\n[1] \"0,0\"\n\n$`$P39N`\n[1] \"SSC-B-A\"\n\n$`$P39R`\n[1] \"4194304\"\n\n$`$P39TYPE`\n[1] \"Side_Scatter\"\n\n$`$P39V`\n[1] \"241\"\n\n$`$P3B`\n[1] \"32\"\n\n$`$P3E`\n[1] \"0,0\"\n\n$`$P3N`\n[1] \"UV2-A\"\n\n$`$P3R`\n[1] \"4194304\"\n\n$`$P3TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P3V`\n[1] \"286\"\n\n$`$P40B`\n[1] \"32\"\n\n$`$P40E`\n[1] \"0,0\"\n\n$`$P40N`\n[1] \"B1-A\"\n\n$`$P40R`\n[1] \"4194304\"\n\n$`$P40TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P40V`\n[1] \"1013\"\n\n$`$P41B`\n[1] \"32\"\n\n$`$P41E`\n[1] \"0,0\"\n\n$`$P41N`\n[1] \"B2-A\"\n\n$`$P41R`\n[1] \"4194304\"\n\n$`$P41TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P41V`\n[1] \"483\"\n\n$`$P42B`\n[1] \"32\"\n\n$`$P42E`\n[1] \"0,0\"\n\n$`$P42N`\n[1] \"B3-A\"\n\n$`$P42R`\n[1] \"4194304\"\n\n$`$P42TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P42V`\n[1] \"471\"\n\n$`$P43B`\n[1] \"32\"\n\n$`$P43E`\n[1] \"0,0\"\n\n$`$P43N`\n[1] \"B4-A\"\n\n$`$P43R`\n[1] \"4194304\"\n\n$`$P43TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P43V`\n[1] \"473\"\n\n$`$P44B`\n[1] \"32\"\n\n$`$P44E`\n[1] \"0,0\"\n\n$`$P44N`\n[1] \"B5-A\"\n\n$`$P44R`\n[1] \"4194304\"\n\n$`$P44TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P44V`\n[1] \"467\"\n\n$`$P45B`\n[1] \"32\"\n\n$`$P45E`\n[1] \"0,0\"\n\n$`$P45N`\n[1] \"B6-A\"\n\n$`$P45R`\n[1] \"4194304\"\n\n$`$P45TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P45V`\n[1] \"284\"\n\n$`$P46B`\n[1] \"32\"\n\n$`$P46E`\n[1] \"0,0\"\n\n$`$P46N`\n[1] \"B7-A\"\n\n$`$P46R`\n[1] \"4194304\"\n\n$`$P46TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P46V`\n[1] \"531\"\n\n$`$P47B`\n[1] \"32\"\n\n$`$P47E`\n[1] \"0,0\"\n\n$`$P47N`\n[1] \"B8-A\"\n\n$`$P47R`\n[1] \"4194304\"\n\n$`$P47TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P47V`\n[1] \"432\"\n\n$`$P48B`\n[1] \"32\"\n\n$`$P48E`\n[1] \"0,0\"\n\n$`$P48N`\n[1] \"B9-A\"\n\n$`$P48R`\n[1] \"4194304\"\n\n$`$P48TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P48V`\n[1] \"675\"\n\n$`$P49B`\n[1] \"32\"\n\n$`$P49E`\n[1] \"0,0\"\n\n$`$P49N`\n[1] \"B10-A\"\n\n$`$P49R`\n[1] \"4194304\"\n\n$`$P49TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P49V`\n[1] \"490\"\n\n$`$P4B`\n[1] \"32\"\n\n$`$P4E`\n[1] \"0,0\"\n\n$`$P4N`\n[1] \"UV3-A\"\n\n$`$P4R`\n[1] \"4194304\"\n\n$`$P4TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P4V`\n[1] \"677\"\n\n$`$P50B`\n[1] \"32\"\n\n$`$P50E`\n[1] \"0,0\"\n\n$`$P50N`\n[1] \"B11-A\"\n\n$`$P50R`\n[1] \"4194304\"\n\n$`$P50TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P50V`\n[1] \"286\"\n\n$`$P51B`\n[1] \"32\"\n\n$`$P51E`\n[1] \"0,0\"\n\n$`$P51N`\n[1] \"B12-A\"\n\n$`$P51R`\n[1] \"4194304\"\n\n$`$P51TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P51V`\n[1] \"407\"\n\n$`$P52B`\n[1] \"32\"\n\n$`$P52E`\n[1] \"0,0\"\n\n$`$P52N`\n[1] \"B13-A\"\n\n$`$P52R`\n[1] \"4194304\"\n\n$`$P52TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P52V`\n[1] \"700\"\n\n$`$P53B`\n[1] \"32\"\n\n$`$P53E`\n[1] \"0,0\"\n\n$`$P53N`\n[1] \"B14-A\"\n\n$`$P53R`\n[1] \"4194304\"\n\n$`$P53TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P53V`\n[1] \"693\"\n\n$`$P54B`\n[1] \"32\"\n\n$`$P54E`\n[1] \"0,0\"\n\n$`$P54N`\n[1] \"R1-A\"\n\n$`$P54R`\n[1] \"4194304\"\n\n$`$P54TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P54V`\n[1] \"158\"\n\n$`$P55B`\n[1] \"32\"\n\n$`$P55E`\n[1] \"0,0\"\n\n$`$P55N`\n[1] \"R2-A\"\n\n$`$P55R`\n[1] \"4194304\"\n\n$`$P55TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P55V`\n[1] \"245\"\n\n$`$P56B`\n[1] \"32\"\n\n$`$P56E`\n[1] \"0,0\"\n\n$`$P56N`\n[1] \"R3-A\"\n\n$`$P56R`\n[1] \"4194304\"\n\n$`$P56TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P56V`\n[1] \"338\"\n\n$`$P57B`\n[1] \"32\"\n\n$`$P57E`\n[1] \"0,0\"\n\n$`$P57N`\n[1] \"R4-A\"\n\n$`$P57R`\n[1] \"4194304\"\n\n$`$P57TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P57V`\n[1] \"238\"\n\n$`$P58B`\n[1] \"32\"\n\n$`$P58E`\n[1] \"0,0\"\n\n$`$P58N`\n[1] \"R5-A\"\n\n$`$P58R`\n[1] \"4194304\"\n\n$`$P58TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P58V`\n[1] \"191\"\n\n$`$P59B`\n[1] \"32\"\n\n$`$P59E`\n[1] \"0,0\"\n\n$`$P59N`\n[1] \"R6-A\"\n\n$`$P59R`\n[1] \"4194304\"\n\n$`$P59TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P59V`\n[1] \"274\"\n\n$`$P5B`\n[1] \"32\"\n\n$`$P5E`\n[1] \"0,0\"\n\n$`$P5N`\n[1] \"UV4-A\"\n\n$`$P5R`\n[1] \"4194304\"\n\n$`$P5TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P5V`\n[1] \"1022\"\n\n$`$P60B`\n[1] \"32\"\n\n$`$P60E`\n[1] \"0,0\"\n\n$`$P60N`\n[1] \"R7-A\"\n\n$`$P60R`\n[1] \"4194304\"\n\n$`$P60TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P60V`\n[1] \"524\"\n\n$`$P61B`\n[1] \"32\"\n\n$`$P61E`\n[1] \"0,0\"\n\n$`$P61N`\n[1] \"R8-A\"\n\n$`$P61R`\n[1] \"4194304\"\n\n$`$P61TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P61V`\n[1] \"243\"\n\n$`$P6B`\n[1] \"32\"\n\n$`$P6E`\n[1] \"0,0\"\n\n$`$P6N`\n[1] \"UV5-A\"\n\n$`$P6R`\n[1] \"4194304\"\n\n$`$P6TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P6V`\n[1] \"616\"\n\n$`$P7B`\n[1] \"32\"\n\n$`$P7E`\n[1] \"0,0\"\n\n$`$P7N`\n[1] \"UV6-A\"\n\n$`$P7R`\n[1] \"4194304\"\n\n$`$P7TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P7V`\n[1] \"506\"\n\n$`$P8B`\n[1] \"32\"\n\n$`$P8E`\n[1] \"0,0\"\n\n$`$P8N`\n[1] \"UV7-A\"\n\n$`$P8R`\n[1] \"4194304\"\n\n$`$P8TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P8V`\n[1] \"661\"\n\n$`$P9B`\n[1] \"32\"\n\n$`$P9E`\n[1] \"0,0\"\n\n$`$P9N`\n[1] \"UV8-A\"\n\n$`$P9R`\n[1] \"4194304\"\n\n$`$P9TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P9V`\n[1] \"514\"\n\n$`$PAR`\n[1] \"61\"\n\n$`$PROJ`\n[1] \"CellCounts4L_AB_05\"\n\n$`$SPILLOVER`\n UV1-A UV2-A UV3-A UV4-A UV5-A UV6-A UV7-A UV8-A UV9-A UV10-A UV11-A\n [1,] 1e+00 0 0 0 0 0 0 0 0 0 0\n [2,] 1e-06 1 0 0 0 0 0 0 0 0 0\n [3,] 0e+00 0 1 0 0 0 0 0 0 0 0\n [4,] 0e+00 0 0 1 0 0 0 0 0 0 0\n [5,] 0e+00 0 0 0 1 0 0 0 0 0 0\n [6,] 0e+00 0 0 0 0 1 0 0 0 0 0\n [7,] 0e+00 0 0 0 0 0 1 0 0 0 0\n [8,] 0e+00 0 0 0 0 0 0 1 0 0 0\n [9,] 0e+00 0 0 0 0 0 0 0 1 0 0\n[10,] 0e+00 0 0 0 0 0 0 0 0 1 0\n[11,] 0e+00 0 0 0 0 0 0 0 0 0 1\n[12,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[13,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[14,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[15,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[16,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[17,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[18,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[19,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[20,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[21,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[22,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[23,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[24,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[25,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[26,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[27,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[28,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[29,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[30,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[31,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[32,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[33,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[34,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[35,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[36,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[37,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[38,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[39,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[40,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[41,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[42,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[43,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[44,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[45,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[46,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[47,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[48,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[49,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[50,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[51,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[52,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[53,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[54,] 0e+00 0 0 0 0 0 0 0 0 0 0\n UV12-A UV13-A UV14-A UV15-A UV16-A V1-A V2-A V3-A V4-A V5-A V6-A V7-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 1 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 1 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 1 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 1 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 1 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 1 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 1 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 1 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 1 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 1 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 1 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 1\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0\n V8-A V9-A V10-A V11-A V12-A V13-A V14-A V15-A V16-A B1-A B2-A B3-A B4-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n B5-A B6-A B7-A B8-A B9-A B10-A B11-A B12-A B13-A B14-A R1-A R2-A R3-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n R4-A R5-A R6-A R7-A R8-A\n [1,] 0 0 0 0 0\n [2,] 0 0 0 0 0\n [3,] 0 0 0 0 0\n [4,] 0 0 0 0 0\n [5,] 0 0 0 0 0\n [6,] 0 0 0 0 0\n [7,] 0 0 0 0 0\n [8,] 0 0 0 0 0\n [9,] 0 0 0 0 0\n[10,] 0 0 0 0 0\n[11,] 0 0 0 0 0\n[12,] 0 0 0 0 0\n[13,] 0 0 0 0 0\n[14,] 0 0 0 0 0\n[15,] 0 0 0 0 0\n[16,] 0 0 0 0 0\n[17,] 0 0 0 0 0\n[18,] 0 0 0 0 0\n[19,] 0 0 0 0 0\n[20,] 0 0 0 0 0\n[21,] 0 0 0 0 0\n[22,] 0 0 0 0 0\n[23,] 0 0 0 0 0\n[24,] 0 0 0 0 0\n[25,] 0 0 0 0 0\n[26,] 0 0 0 0 0\n[27,] 0 0 0 0 0\n[28,] 0 0 0 0 0\n[29,] 0 0 0 0 0\n[30,] 0 0 0 0 0\n[31,] 0 0 0 0 0\n[32,] 0 0 0 0 0\n[33,] 0 0 0 0 0\n[34,] 0 0 0 0 0\n[35,] 0 0 0 0 0\n[36,] 0 0 0 0 0\n[37,] 0 0 0 0 0\n[38,] 0 0 0 0 0\n[39,] 0 0 0 0 0\n[40,] 0 0 0 0 0\n[41,] 0 0 0 0 0\n[42,] 0 0 0 0 0\n[43,] 0 0 0 0 0\n[44,] 0 0 0 0 0\n[45,] 0 0 0 0 0\n[46,] 0 0 0 0 0\n[47,] 0 0 0 0 0\n[48,] 0 0 0 0 0\n[49,] 0 0 0 0 0\n[50,] 1 0 0 0 0\n[51,] 0 1 0 0 0\n[52,] 0 0 1 0 0\n[53,] 0 0 0 1 0\n[54,] 0 0 0 0 1\n\n$`$TIMESTEP`\n[1] \"0.0001\"\n\n$`$TOT`\n[1] \"100\"\n\n$`$VOL`\n[1] \"30.31\"\n\n$`APPLY COMPENSATION`\n[1] \"FALSE\"\n\n$CHARSET\n[1] \"utf-8\"\n\n$CREATOR\n[1] \"SpectroFlo 3.3.0\"\n\n$FCSversion\n[1] \"3\"\n\n$FILENAME\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n$`FSC ASF`\n[1] \"1.21\"\n\n$GROUPNAME\n[1] \"ND050\"\n\n$GUID\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n$LASER1ASF\n[1] \"1.09\"\n\n$LASER1DELAY\n[1] \"-19.525\"\n\n$LASER1NAME\n[1] \"Violet\"\n\n$LASER2ASF\n[1] \"1.14\"\n\n$LASER2DELAY\n[1] \"0\"\n\n$LASER2NAME\n[1] \"Blue\"\n\n$LASER3ASF\n[1] \"1.02\"\n\n$LASER3DELAY\n[1] \"20.15\"\n\n$LASER3NAME\n[1] \"Red\"\n\n$LASER4ASF\n[1] \"0.92\"\n\n$LASER4DELAY\n[1] \"40.725\"\n\n$LASER4NAME\n[1] \"UV\"\n\n$ORIGINALGUID\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n$P10DISPLAY\n[1] \"LOG\"\n\n$P11DISPLAY\n[1] \"LOG\"\n\n$P12DISPLAY\n[1] \"LOG\"\n\n$P13DISPLAY\n[1] \"LOG\"\n\n$P14DISPLAY\n[1] \"LOG\"\n\n$P15DISPLAY\n[1] \"LOG\"\n\n$P16DISPLAY\n[1] \"LOG\"\n\n$P17DISPLAY\n[1] \"LOG\"\n\n$P18DISPLAY\n[1] \"LIN\"\n\n$P19DISPLAY\n[1] \"LIN\"\n\n$P1DISPLAY\n[1] \"LOG\"\n\n$P20DISPLAY\n[1] \"LOG\"\n\n$P21DISPLAY\n[1] \"LOG\"\n\n$P22DISPLAY\n[1] \"LOG\"\n\n$P23DISPLAY\n[1] \"LOG\"\n\n$P24DISPLAY\n[1] \"LOG\"\n\n$P25DISPLAY\n[1] \"LOG\"\n\n$P26DISPLAY\n[1] \"LOG\"\n\n$P27DISPLAY\n[1] \"LOG\"\n\n$P28DISPLAY\n[1] \"LOG\"\n\n$P29DISPLAY\n[1] \"LOG\"\n\n$P2DISPLAY\n[1] \"LOG\"\n\n$P30DISPLAY\n[1] \"LOG\"\n\n$P31DISPLAY\n[1] \"LOG\"\n\n$P32DISPLAY\n[1] \"LOG\"\n\n$P33DISPLAY\n[1] \"LOG\"\n\n$P34DISPLAY\n[1] \"LOG\"\n\n$P35DISPLAY\n[1] \"LOG\"\n\n$P36DISPLAY\n[1] \"LIN\"\n\n$P37DISPLAY\n[1] \"LIN\"\n\n$P38DISPLAY\n[1] \"LIN\"\n\n$P39DISPLAY\n[1] \"LIN\"\n\n$P3DISPLAY\n[1] \"LOG\"\n\n$P40DISPLAY\n[1] \"LOG\"\n\n$P41DISPLAY\n[1] \"LOG\"\n\n$P42DISPLAY\n[1] \"LOG\"\n\n$P43DISPLAY\n[1] \"LOG\"\n\n$P44DISPLAY\n[1] \"LOG\"\n\n$P45DISPLAY\n[1] \"LOG\"\n\n$P46DISPLAY\n[1] \"LOG\"\n\n$P47DISPLAY\n[1] \"LOG\"\n\n$P48DISPLAY\n[1] \"LOG\"\n\n$P49DISPLAY\n[1] \"LOG\"\n\n$P4DISPLAY\n[1] \"LOG\"\n\n$P50DISPLAY\n[1] \"LOG\"\n\n$P51DISPLAY\n[1] \"LOG\"\n\n$P52DISPLAY\n[1] \"LOG\"\n\n$P53DISPLAY\n[1] \"LOG\"\n\n$P54DISPLAY\n[1] \"LOG\"\n\n$P55DISPLAY\n[1] \"LOG\"\n\n$P56DISPLAY\n[1] \"LOG\"\n\n$P57DISPLAY\n[1] \"LOG\"\n\n$P58DISPLAY\n[1] \"LOG\"\n\n$P59DISPLAY\n[1] \"LOG\"\n\n$P5DISPLAY\n[1] \"LOG\"\n\n$P60DISPLAY\n[1] \"LOG\"\n\n$P61DISPLAY\n[1] \"LOG\"\n\n$P6DISPLAY\n[1] \"LOG\"\n\n$P7DISPLAY\n[1] \"LOG\"\n\n$P8DISPLAY\n[1] \"LOG\"\n\n$P9DISPLAY\n[1] \"LOG\"\n\n$THRESHOLD\n[1] \"(FSC,50000)\"\n\n$TUBENAME\n[1] \"05\"\n\n$USERSETTINGNAME\n[1] \"DTR_CellCounts\"\n\n$`WINDOW EXTENSION`\n[1] \"3\"\n\n\nThe returned list is a little too large to reasonably explore. We can attempt to subset using the head() function as shown below\n\nhead(DescriptionList, 5)\n\n$`$BEGINANALYSIS`\n[1] \"0\"\n\n$`$BEGINDATA`\n[1] \"33312\"\n\n$`$BEGINSTEXT`\n[1] \"0\"\n\n$`$BTIM`\n[1] \"13:55:29.85\"\n\n$`$BYTEORD`\n[1] \"4,3,2,1\"\n\n\nAlternatively, it might be better to subset based on position index\n\nDescriptionList[1:10]\n\n$`$BEGINANALYSIS`\n[1] \"0\"\n\n$`$BEGINDATA`\n[1] \"33312\"\n\n$`$BEGINSTEXT`\n[1] \"0\"\n\n$`$BTIM`\n[1] \"13:55:29.85\"\n\n$`$BYTEORD`\n[1] \"4,3,2,1\"\n\n$`$CYT`\n[1] \"Aurora\"\n\n$`$CYTOLIB_VERSION`\n[1] \"2.22.0\"\n\n$`$CYTSN`\n[1] \"V0333\"\n\n$`$DATATYPE`\n[1] \"F\"\n\n$`$DATE`\n[1] \"04-Aug-2025\"\n\n\nAnd just as we saw for exprs and parameters, there is also a Bioconductor helper keyword() function to access this same information directly from the flowFrame.\n\nDescriptionList_Alternate <- keyword(flowFrame)\n\nIf we run the class() function, we can see that DescriptionList is an actual “list”.\n\nclass(DescriptionList)\n\n[1] \"list\"\n\n\nThis is in contrast to the vectors we have previously generated. While these are also list like, they are what are known as as atomic list, which contain values that are all either characters, numerics or logicals.\n\nFluorophores <- c(\"BV421\", \"FITC\", \"PE\", \"APC\")\nclass(Fluorophores)\n\n[1] \"character\"\n\n\n\nPanelAntibodyCounts <- c(5, 12, 19, 26, 34, 46, 51)\nclass(PanelAntibodyCounts)\n\n[1] \"numeric\"\n\n\n\nSpecimenIndexToKeep <- c(TRUE, TRUE, FALSE, TRUE)\nclass(SpecimenIndexToKeep)\n\n[1] \"logical\"\n\n\nA list on the other hand is not restricted to contain objects composed entirely of a certain atomic type. For example, I could include the three previous vectors into a list using the list() function.\n\nMyListofVectors <- list(Fluorophores, PanelAntibodyCounts, SpecimenIndexToKeep)\nstr(MyListofVectors)\n\nList of 3\n $ : chr [1:4] \"BV421\" \"FITC\" \"PE\" \"APC\"\n $ : num [1:7] 5 12 19 26 34 46 51\n $ : logi [1:4] TRUE TRUE FALSE TRUE\n\n\nWe can see that with the Description/Keyword list we retrieved from our flowFrame shares a somewhat similar format.\n\nstr(DescriptionList[1:10])\n\nList of 10\n $ $BEGINANALYSIS : chr \"0\"\n $ $BEGINDATA : chr \"33312\"\n $ $BEGINSTEXT : chr \"0\"\n $ $BTIM : chr \"13:55:29.85\"\n $ $BYTEORD : chr \"4,3,2,1\"\n $ $CYT : chr \"Aurora\"\n $ $CYTOLIB_VERSION: chr \"2.22.0\"\n $ $CYTSN : chr \"V0333\"\n $ $DATATYPE : chr \"F\"\n $ $DATE : chr \"04-Aug-2025\"\n\n\nBut in this case, there are also names present ($BEGINANALYSIS, $BEGINDATA, etc). What if we had tried to provide names to our List of Vectors? Would the format match?\nWhen we assigned a name to each of the vectors (by providing an equal to = ), we get the same kind of structure format to what we see in Description.\n\nMyNamedListofVectors <- list(FluorophoresNamed=Fluorophores,\n PanelAntibodyCountsNamed=PanelAntibodyCounts,\n SpecimenIndexToKeepNamed=SpecimenIndexToKeep)\n\nstr(MyNamedListofVectors)\n\nList of 3\n $ FluorophoresNamed : chr [1:4] \"BV421\" \"FITC\" \"PE\" \"APC\"\n $ PanelAntibodyCountsNamed: num [1:7] 5 12 19 26 34 46 51\n $ SpecimenIndexToKeepNamed: logi [1:4] TRUE TRUE FALSE TRUE\n\n\nWe could then subsequently be able to isolate items from that list using the $ operator.\n\nMyNamedListofVectors$\n\n\nAlternatively, we could also access by list index position\n\nMyNamedListofVectors[1]\n\n$FluorophoresNamed\n[1] \"BV421\" \"FITC\" \"PE\" \"APC\" \n\n\nRemembering back to the original output from read.FCS() we remember that it mentioned 599 keywords being in the description slot, so now we know that this is what was being referenced.", "crumbs": [ "About", "Intro to R", - "04 - Intro to Tidyverse" + "03 - Inside a .FCS file" ] }, { - "objectID": "course/04_IntroToTidyverse/index.html#select-columns", - "href": "course/04_IntroToTidyverse/index.html#select-columns", - "title": "04 - Introduction to Tidyverse", - "section": "select (Columns)", - "text": "select (Columns)\nNow that we have read in our data, and have a general picture of the structure and contents, lets start learning the main dplyr functions we will be using throughout the course. To do this, lets go ahead and attach dplyr to our local environment via the library() call.\n\nlibrary(dplyr)\n\nWe will start with the select() function. It is used to “select” a column from a data.frame type object. In the simplest usage, we provide the name of our data.frame variable/object as the first argument after the opening parenthesis. This is then followed by the name of the column we want to select as the second argument (let’s place around the “” around the column name for now)\n\nDateColumn <- select(Data, \"Date\")\nDateColumn[1:10,]\n\n [1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [6] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n\n\nThis results in the column being selected, resulting in the new object containing only that subsetted out column from the original Data object.\n\nPipe Operators\nWhile the above line of code works to select a column, when you encounter select() out in the wild, it will more often be in a line of code that looks like this:\n\nDateColumn <- Data |> select(\"Date\")\nDateColumn[1:10,]\n\n [1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [6] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n\n\n… “What in the world is that thing |> ?” …\nGlad you asked! An useful feature of the tidyverse packages is their use of pipes (either the original magrittr package’s “%>%” or base R version >4.1.0's “|>”“), usually appearing like this:\n\n# magrittr %>% pipe\n\nDateColumn <- Data %>% select(\"Date\")\n\n# base R |> pipe\nDateColumn <- Data |> select(\"Date\")\n\n… “How do we interpret/read that line of code?” …\nLet’s break it down, starting off just to the right of the assignment arrow (<-) with our data.frame “Data”.\n\nData\n\nWe then proceed to read to the right, adding in our pipe operator. The pipe essentially serves as an intermediate passing the contents of data onward to the subsequent function.\n\nData |> \n\nIn our case, this subsequent function is the select() function, which will select a particular column from the available data. When using the pipe, the first argument slot we saw for “select(Data,”Date”)” is occupied by the contents Data that are being passed by the pipe.\n\nData |> select()\n\nTo complete the transfer, we provide the desired column name to select() to act on (“Date” in this case)\n\nData |> select(\"Date\")\n\nIn summary, contents of Data are passed to the pipe, and select runs on those contents to select the Date column\n\nData |> select(\"Date\")\n\nOne of the main advantages for using pipes, is they can be linked together, passing resulting objects of one operation on to the next pipe and subsequent function. We can see this in operation in the example below where we hand off the isolated “Date” column to the nrow() function to determine number of rows. We will use pipes throughout the course, so you will gradually gain familiarity as you encounter them.\n\nData |> select(\"Date\") |> nrow()\n\n[1] 196\n\n\nFor those with prior R experience, you will be more familiar with the older magrittr %>% pipe. The base R |> pipe operator was introduced starting with R version 4.1.0. While mostly interchangeable, they have a few nuances that come into play for more advance use cases. You are welcome to use whichever you prefer (my current preference is |> as it’s one less key to press).\n\n\nR Quirks\n\n\n\n\n\n\nOdd R Behavior # 1\n\n\n\nWhile we used “” around the column name in our previous example, unlike what we encountered with install.packages() when we forget to include quotation marks, select() still retrieves the correct column despite Date not being an environment variable:\n\n\n\nData |> select(Date) |> head(3)\n\n Date\n1 2025-07-26\n2 2025-07-26\n3 2025-07-26\n\n\n\n\n\n\n\n\n.\n\n\n\nThe reasons for this Odd R behaviour are nuanced and for another day. For now, think of it as dplyr R package is picking up the slack, and using context to infer it’s a column name and not an environmental variable/object.\n\n\n\n\nSelecting multiple columns\nSince we are able to select one column, can we select multiple (similar to a [Data[,2:5]] approach in base R)? We can, and they can be positioned anywhere within the data.frame:\n\nSubset <- Data |> select(bid, timepoint, Condition, Tcells, `CD8+`, `CD4+`)\n\nhead(Subset, 3)\n\n bid timepoint Condition Tcells CD8+ CD4+\n1 INF0052 0 Ctrl 0.2804264 0.2734826 0.6341164\n2 INF0100 0 Ctrl 0.6748298 0.3357696 0.6119112\n3 INF0100 4 Ctrl 0.6119129 0.2862104 0.6639621\n\n\nYou will notice that the order in which we selected the columns will dictate their position in the subsetted data.frame object:\n\nSubset <- Data |> select(bid, Tcells, `CD8+`, `CD4+`, timepoint, Condition, )\n\nhead(Subset, 3)\n\n bid Tcells CD8+ CD4+ timepoint Condition\n1 INF0052 0.2804264 0.2734826 0.6341164 0 Ctrl\n2 INF0100 0.6748298 0.3357696 0.6119112 0 Ctrl\n3 INF0100 0.6119129 0.2862104 0.6639621 4 Ctrl", + "objectID": "course/03_InsideFCSFile/index.html#early-metadata", + "href": "course/03_InsideFCSFile/index.html#early-metadata", + "title": "03 - Inside an FCS File", + "section": "Early Metadata", + "text": "Early Metadata\nWithin the initial portion, we are getting back metadata keywords related to where and how the particular file was acquired. Keywords of potential interest include:\n\n\n\n\n\n\nStart Time\n\n\n\nWhat time was the .fcs file acquired\n\n\n\n\nDescriptionList$`$BTIM`\n\n[1] \"13:55:29.85\"\n\n\n\n\n\n\n\n\n\nCytometer\n\n\n\nWhat type of cytometer was the .fcs file acquired on\n\n\n\n\nDescriptionList$`$CYT`\n\n[1] \"Aurora\"\n\n\n\n\n\n\n\n\n\n\n\nCytometer Serial Number\n\n\n\nManufacturer Serial Number of the Cytometer\n\n\n\n\nDescriptionList$`$CYTSN`\n\n[1] \"V0333\"\n\n\n\n\n\n\n\n\n\nFCS File Acquisition Date\n\n\n\nWhat was the date of acquisition\n\n\n\n\nDescriptionList$`$DATE`\n\n[1] \"04-Aug-2025\"\n\n\n\n\n\n\n\n\n\n\n\nAcquisition End Time\n\n\n\nWhat time was acquisition stopped\n\n\n\n\nDescriptionList$`$ETIM`\n\n[1] \"13:55:57.02\"\n\n\n\n\n\n\n\n\n\nFile Name\n\n\n\nName of the .fcs file\n\n\n\n\nDescriptionList$`$FIL`\n\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n\n\n\n\n\n\n\n\n\n\nOperator\n\n\n\nWho acquired the .fcs file\n\n\n\n\nDescriptionList$`$OP`\n\n[1] \"David Rach\"", "crumbs": [ "About", "Intro to R", - "04 - Intro to Tidyverse" + "03 - Inside a .FCS file" ] }, { - "objectID": "course/04_IntroToTidyverse/index.html#relocate", - "href": "course/04_IntroToTidyverse/index.html#relocate", - "title": "04 - Introduction to Tidyverse", - "section": "relocate", - "text": "relocate\nAlternatively, we occasionally want to move one column. While we could respecify the location using select(), specifying the names of all the other columns out in a line of code to just to rearrange one does not sound like a good use of time. For this reason, the second dplyr function we will be learning is the relocate() function.\nLooking at our Data object, let’s say we wanted to move the Tcells column from its current location to the second column position (right after the bid column). The line of code to do so would look like:\n\nData |> relocate(Tcells, .after=bid) |> head(3)\n\n bid Tcells timepoint Condition Date infant_sex ptype root\n1 INF0052 0.2804264 0 Ctrl 2025-07-26 Male HEU-hi 2098368\n2 INF0100 0.6748298 0 Ctrl 2025-07-26 Male HEU-lo 2020184\n3 INF0100 0.6119129 4 Ctrl 2025-07-26 Male HEU-lo 1155040\n singletsFSC singletsSSC singletsSSCB CD45 NotMonocytes nonDebris\n1 1894070 1666179 1537396 0.5952943 0.8820349 0.8627649\n2 1791890 1697083 1579098 0.9106762 0.9052256 0.8602660\n3 1033320 875465 845446 0.9705765 0.9845400 0.9578793\n lymphocytes live Dump+ Dump- Vd2+ Vd2- Va7.2+\n1 0.6420138 0.9020581 0.21090996 0.6911482 0.008120361 0.9918796 0.01448070\n2 0.2145848 0.8908981 0.06252775 0.8283703 0.007265620 0.9927344 0.01577499\n3 0.7403110 0.8757665 0.20023803 0.6755285 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Monocytes Debris CD45_count\n1 587573 0.11796509 0.13723513 915203\n2 308583 0.09477437 0.13973396 1438047\n3 607477 0.01545999 0.04212072 820570\n\n# |> head(3) is used only to make the website output visualization manageable :D\n\nSimilar to what we saw with select(), this approach can also be used for more than 1 column:\n\nData |> relocate(Tcells, Monocytes, .after=bid) |> head(3)\n\n bid Tcells Monocytes timepoint Condition Date infant_sex ptype\n1 INF0052 0.2804264 0.11796509 0 Ctrl 2025-07-26 Male HEU-hi\n2 INF0100 0.6748298 0.09477437 0 Ctrl 2025-07-26 Male HEU-lo\n3 INF0100 0.6119129 0.01545999 4 Ctrl 2025-07-26 Male HEU-lo\n root singletsFSC singletsSSC singletsSSCB CD45 NotMonocytes nonDebris\n1 2098368 1894070 1666179 1537396 0.5952943 0.8820349 0.8627649\n2 2020184 1791890 1697083 1579098 0.9106762 0.9052256 0.8602660\n3 1155040 1033320 875465 845446 0.9705765 0.9845400 0.9578793\n lymphocytes live Dump+ Dump- Vd2+ Vd2- Va7.2+\n1 0.6420138 0.9020581 0.21090996 0.6911482 0.008120361 0.9918796 0.01448070\n2 0.2145848 0.8908981 0.06252775 0.8283703 0.007265620 0.9927344 0.01577499\n3 0.7403110 0.8757665 0.20023803 0.6755285 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Debris CD45_count\n1 587573 0.13723513 915203\n2 308583 0.13973396 1438047\n3 607477 0.04212072 820570\n\n# |> head(3) is used only to make the website output visualization manageable :D\n\nWe can also modify the argument so that columns are placed before a certain column\n\nData |> relocate(Tcells, .before=Date) |> head(3)\n\n bid timepoint Condition Tcells Date infant_sex ptype root\n1 INF0052 0 Ctrl 0.2804264 2025-07-26 Male HEU-hi 2098368\n2 INF0100 0 Ctrl 0.6748298 2025-07-26 Male HEU-lo 2020184\n3 INF0100 4 Ctrl 0.6119129 2025-07-26 Male HEU-lo 1155040\n singletsFSC singletsSSC singletsSSCB CD45 NotMonocytes nonDebris\n1 1894070 1666179 1537396 0.5952943 0.8820349 0.8627649\n2 1791890 1697083 1579098 0.9106762 0.9052256 0.8602660\n3 1033320 875465 845446 0.9705765 0.9845400 0.9578793\n lymphocytes live Dump+ Dump- Vd2+ Vd2- Va7.2+\n1 0.6420138 0.9020581 0.21090996 0.6911482 0.008120361 0.9918796 0.01448070\n2 0.2145848 0.8908981 0.06252775 0.8283703 0.007265620 0.9927344 0.01577499\n3 0.7403110 0.8757665 0.20023803 0.6755285 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Monocytes Debris CD45_count\n1 587573 0.11796509 0.13723513 915203\n2 308583 0.09477437 0.13973396 1438047\n3 607477 0.01545999 0.04212072 820570\n\n# |> head(3) is used only to make the website output visualization manageable :D\n\nAnd as we might suspect, we could specify a column index location rather than using a column name.\n\nData |> relocate(Date, .before=1) |> head(3)\n\n Date bid timepoint Condition infant_sex ptype root singletsFSC\n1 2025-07-26 INF0052 0 Ctrl Male HEU-hi 2098368 1894070\n2 2025-07-26 INF0100 0 Ctrl Male HEU-lo 2020184 1791890\n3 2025-07-26 INF0100 4 Ctrl Male HEU-lo 1155040 1033320\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1666179 1537396 0.5952943 0.8820349 0.8627649 0.6420138\n2 1697083 1579098 0.9106762 0.9052256 0.8602660 0.2145848\n3 875465 845446 0.9705765 0.9845400 0.9578793 0.7403110\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9020581 0.21090996 0.6911482 0.2804264 0.008120361 0.9918796 0.01448070\n2 0.8908981 0.06252775 0.8283703 0.6748298 0.007265620 0.9927344 0.01577499\n3 0.8757665 0.20023803 0.6755285 0.6119129 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Monocytes Debris CD45_count\n1 587573 0.11796509 0.13723513 915203\n2 308583 0.09477437 0.13973396 1438047\n3 607477 0.01545999 0.04212072 820570\n\n# |> head(3) is used only to make the website output visualization manageable :D", + "objectID": "course/03_InsideFCSFile/index.html#detector-values", + "href": "course/03_InsideFCSFile/index.html#detector-values", + "title": "03 - Inside an FCS File", + "section": "Detector Values", + "text": "Detector Values\nThe next major stretch of keywords encode parameter values associated with the individual detectors for at the time of acquisition.\n\nDetectors <- DescriptionList[20:384]\nDetectors\n\n$`$P10B`\n[1] \"32\"\n\n$`$P10E`\n[1] \"0,0\"\n\n$`$P10N`\n[1] \"UV9-A\"\n\n$`$P10R`\n[1] \"4194304\"\n\n$`$P10TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P10V`\n[1] \"710\"\n\n$`$P11B`\n[1] \"32\"\n\n$`$P11E`\n[1] \"0,0\"\n\n$`$P11N`\n[1] \"UV10-A\"\n\n$`$P11R`\n[1] \"4194304\"\n\n$`$P11TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P11V`\n[1] \"377\"\n\n$`$P12B`\n[1] \"32\"\n\n$`$P12E`\n[1] \"0,0\"\n\n$`$P12N`\n[1] \"UV11-A\"\n\n$`$P12R`\n[1] \"4194304\"\n\n$`$P12TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P12V`\n[1] \"469\"\n\n$`$P13B`\n[1] \"32\"\n\n$`$P13E`\n[1] \"0,0\"\n\n$`$P13N`\n[1] \"UV12-A\"\n\n$`$P13R`\n[1] \"4194304\"\n\n$`$P13TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P13V`\n[1] \"434\"\n\n$`$P14B`\n[1] \"32\"\n\n$`$P14E`\n[1] \"0,0\"\n\n$`$P14N`\n[1] \"UV13-A\"\n\n$`$P14R`\n[1] \"4194304\"\n\n$`$P14TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P14V`\n[1] \"564\"\n\n$`$P15B`\n[1] \"32\"\n\n$`$P15E`\n[1] \"0,0\"\n\n$`$P15N`\n[1] \"UV14-A\"\n\n$`$P15R`\n[1] \"4194304\"\n\n$`$P15TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P15V`\n[1] \"975\"\n\n$`$P16B`\n[1] \"32\"\n\n$`$P16E`\n[1] \"0,0\"\n\n$`$P16N`\n[1] \"UV15-A\"\n\n$`$P16R`\n[1] \"4194304\"\n\n$`$P16TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P16V`\n[1] \"737\"\n\n$`$P17B`\n[1] \"32\"\n\n$`$P17E`\n[1] \"0,0\"\n\n$`$P17N`\n[1] \"UV16-A\"\n\n$`$P17R`\n[1] \"4194304\"\n\n$`$P17TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P17V`\n[1] \"1069\"\n\n$`$P18B`\n[1] \"32\"\n\n$`$P18E`\n[1] \"0,0\"\n\n$`$P18N`\n[1] \"SSC-H\"\n\n$`$P18R`\n[1] \"4194304\"\n\n$`$P18TYPE`\n[1] \"Side_Scatter\"\n\n$`$P18V`\n[1] \"334\"\n\n$`$P19B`\n[1] \"32\"\n\n$`$P19E`\n[1] \"0,0\"\n\n$`$P19N`\n[1] \"SSC-A\"\n\n$`$P19R`\n[1] \"4194304\"\n\n$`$P19TYPE`\n[1] \"Side_Scatter\"\n\n$`$P19V`\n[1] \"334\"\n\n$`$P1B`\n[1] \"32\"\n\n$`$P1E`\n[1] \"0,0\"\n\n$`$P1N`\n[1] \"Time\"\n\n$`$P1R`\n[1] \"272140\"\n\n$`$P1TYPE`\n[1] \"Time\"\n\n$`$P20B`\n[1] \"32\"\n\n$`$P20E`\n[1] \"0,0\"\n\n$`$P20N`\n[1] \"V1-A\"\n\n$`$P20R`\n[1] \"4194304\"\n\n$`$P20TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P20V`\n[1] \"352\"\n\n$`$P21B`\n[1] \"32\"\n\n$`$P21E`\n[1] \"0,0\"\n\n$`$P21N`\n[1] \"V2-A\"\n\n$`$P21R`\n[1] \"4194304\"\n\n$`$P21TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P21V`\n[1] \"412\"\n\n$`$P22B`\n[1] \"32\"\n\n$`$P22E`\n[1] \"0,0\"\n\n$`$P22N`\n[1] \"V3-A\"\n\n$`$P22R`\n[1] \"4194304\"\n\n$`$P22TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P22V`\n[1] \"304\"\n\n$`$P23B`\n[1] \"32\"\n\n$`$P23E`\n[1] \"0,0\"\n\n$`$P23N`\n[1] \"V4-A\"\n\n$`$P23R`\n[1] \"4194304\"\n\n$`$P23TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P23V`\n[1] \"217\"\n\n$`$P24B`\n[1] \"32\"\n\n$`$P24E`\n[1] \"0,0\"\n\n$`$P24N`\n[1] \"V5-A\"\n\n$`$P24R`\n[1] \"4194304\"\n\n$`$P24TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P24V`\n[1] \"257\"\n\n$`$P25B`\n[1] \"32\"\n\n$`$P25E`\n[1] \"0,0\"\n\n$`$P25N`\n[1] \"V6-A\"\n\n$`$P25R`\n[1] \"4194304\"\n\n$`$P25TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P25V`\n[1] \"218\"\n\n$`$P26B`\n[1] \"32\"\n\n$`$P26E`\n[1] \"0,0\"\n\n$`$P26N`\n[1] \"V7-A\"\n\n$`$P26R`\n[1] \"4194304\"\n\n$`$P26TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P26V`\n[1] \"303\"\n\n$`$P27B`\n[1] \"32\"\n\n$`$P27E`\n[1] \"0,0\"\n\n$`$P27N`\n[1] \"V8-A\"\n\n$`$P27R`\n[1] \"4194304\"\n\n$`$P27TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P27V`\n[1] \"461\"\n\n$`$P28B`\n[1] \"32\"\n\n$`$P28E`\n[1] \"0,0\"\n\n$`$P28N`\n[1] \"V9-A\"\n\n$`$P28R`\n[1] \"4194304\"\n\n$`$P28TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P28V`\n[1] \"320\"\n\n$`$P29B`\n[1] \"32\"\n\n$`$P29E`\n[1] \"0,0\"\n\n$`$P29N`\n[1] \"V10-A\"\n\n$`$P29R`\n[1] \"4194304\"\n\n$`$P29TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P29V`\n[1] \"359\"\n\n$`$P2B`\n[1] \"32\"\n\n$`$P2E`\n[1] \"0,0\"\n\n$`$P2N`\n[1] \"UV1-A\"\n\n$`$P2R`\n[1] \"4194304\"\n\n$`$P2TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P2V`\n[1] \"1008\"\n\n$`$P30B`\n[1] \"32\"\n\n$`$P30E`\n[1] \"0,0\"\n\n$`$P30N`\n[1] \"V11-A\"\n\n$`$P30R`\n[1] \"4194304\"\n\n$`$P30TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P30V`\n[1] \"271\"\n\n$`$P31B`\n[1] \"32\"\n\n$`$P31E`\n[1] \"0,0\"\n\n$`$P31N`\n[1] \"V12-A\"\n\n$`$P31R`\n[1] \"4194304\"\n\n$`$P31TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P31V`\n[1] \"234\"\n\n$`$P32B`\n[1] \"32\"\n\n$`$P32E`\n[1] \"0,0\"\n\n$`$P32N`\n[1] \"V13-A\"\n\n$`$P32R`\n[1] \"4194304\"\n\n$`$P32TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P32V`\n[1] \"236\"\n\n$`$P33B`\n[1] \"32\"\n\n$`$P33E`\n[1] \"0,0\"\n\n$`$P33N`\n[1] \"V14-A\"\n\n$`$P33R`\n[1] \"4194304\"\n\n$`$P33TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P33V`\n[1] \"318\"\n\n$`$P34B`\n[1] \"32\"\n\n$`$P34E`\n[1] \"0,0\"\n\n$`$P34N`\n[1] \"V15-A\"\n\n$`$P34R`\n[1] \"4194304\"\n\n$`$P34TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P34V`\n[1] \"602\"\n\n$`$P35B`\n[1] \"32\"\n\n$`$P35E`\n[1] \"0,0\"\n\n$`$P35N`\n[1] \"V16-A\"\n\n$`$P35R`\n[1] \"4194304\"\n\n$`$P35TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P35V`\n[1] \"372\"\n\n$`$P36B`\n[1] \"32\"\n\n$`$P36E`\n[1] \"0,0\"\n\n$`$P36N`\n[1] \"FSC-H\"\n\n$`$P36R`\n[1] \"4194304\"\n\n$`$P36TYPE`\n[1] \"Forward_Scatter\"\n\n$`$P36V`\n[1] \"55\"\n\n$`$P37B`\n[1] \"32\"\n\n$`$P37E`\n[1] \"0,0\"\n\n$`$P37N`\n[1] \"FSC-A\"\n\n$`$P37R`\n[1] \"4194304\"\n\n$`$P37TYPE`\n[1] \"Forward_Scatter\"\n\n$`$P37V`\n[1] \"55\"\n\n$`$P38B`\n[1] \"32\"\n\n$`$P38E`\n[1] \"0,0\"\n\n$`$P38N`\n[1] \"SSC-B-H\"\n\n$`$P38R`\n[1] \"4194304\"\n\n$`$P38TYPE`\n[1] \"Side_Scatter\"\n\n$`$P38V`\n[1] \"241\"\n\n$`$P39B`\n[1] \"32\"\n\n$`$P39E`\n[1] \"0,0\"\n\n$`$P39N`\n[1] \"SSC-B-A\"\n\n$`$P39R`\n[1] \"4194304\"\n\n$`$P39TYPE`\n[1] \"Side_Scatter\"\n\n$`$P39V`\n[1] \"241\"\n\n$`$P3B`\n[1] \"32\"\n\n$`$P3E`\n[1] \"0,0\"\n\n$`$P3N`\n[1] \"UV2-A\"\n\n$`$P3R`\n[1] \"4194304\"\n\n$`$P3TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P3V`\n[1] \"286\"\n\n$`$P40B`\n[1] \"32\"\n\n$`$P40E`\n[1] \"0,0\"\n\n$`$P40N`\n[1] \"B1-A\"\n\n$`$P40R`\n[1] \"4194304\"\n\n$`$P40TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P40V`\n[1] \"1013\"\n\n$`$P41B`\n[1] \"32\"\n\n$`$P41E`\n[1] \"0,0\"\n\n$`$P41N`\n[1] \"B2-A\"\n\n$`$P41R`\n[1] \"4194304\"\n\n$`$P41TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P41V`\n[1] \"483\"\n\n$`$P42B`\n[1] \"32\"\n\n$`$P42E`\n[1] \"0,0\"\n\n$`$P42N`\n[1] \"B3-A\"\n\n$`$P42R`\n[1] \"4194304\"\n\n$`$P42TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P42V`\n[1] \"471\"\n\n$`$P43B`\n[1] \"32\"\n\n$`$P43E`\n[1] \"0,0\"\n\n$`$P43N`\n[1] \"B4-A\"\n\n$`$P43R`\n[1] \"4194304\"\n\n$`$P43TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P43V`\n[1] \"473\"\n\n$`$P44B`\n[1] \"32\"\n\n$`$P44E`\n[1] \"0,0\"\n\n$`$P44N`\n[1] \"B5-A\"\n\n$`$P44R`\n[1] \"4194304\"\n\n$`$P44TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P44V`\n[1] \"467\"\n\n$`$P45B`\n[1] \"32\"\n\n$`$P45E`\n[1] \"0,0\"\n\n$`$P45N`\n[1] \"B6-A\"\n\n$`$P45R`\n[1] \"4194304\"\n\n$`$P45TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P45V`\n[1] \"284\"\n\n$`$P46B`\n[1] \"32\"\n\n$`$P46E`\n[1] \"0,0\"\n\n$`$P46N`\n[1] \"B7-A\"\n\n$`$P46R`\n[1] \"4194304\"\n\n$`$P46TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P46V`\n[1] \"531\"\n\n$`$P47B`\n[1] \"32\"\n\n$`$P47E`\n[1] \"0,0\"\n\n$`$P47N`\n[1] \"B8-A\"\n\n$`$P47R`\n[1] \"4194304\"\n\n$`$P47TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P47V`\n[1] \"432\"\n\n$`$P48B`\n[1] \"32\"\n\n$`$P48E`\n[1] \"0,0\"\n\n$`$P48N`\n[1] \"B9-A\"\n\n$`$P48R`\n[1] \"4194304\"\n\n$`$P48TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P48V`\n[1] \"675\"\n\n$`$P49B`\n[1] \"32\"\n\n$`$P49E`\n[1] \"0,0\"\n\n$`$P49N`\n[1] \"B10-A\"\n\n$`$P49R`\n[1] \"4194304\"\n\n$`$P49TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P49V`\n[1] \"490\"\n\n$`$P4B`\n[1] \"32\"\n\n$`$P4E`\n[1] \"0,0\"\n\n$`$P4N`\n[1] \"UV3-A\"\n\n$`$P4R`\n[1] \"4194304\"\n\n$`$P4TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P4V`\n[1] \"677\"\n\n$`$P50B`\n[1] \"32\"\n\n$`$P50E`\n[1] \"0,0\"\n\n$`$P50N`\n[1] \"B11-A\"\n\n$`$P50R`\n[1] \"4194304\"\n\n$`$P50TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P50V`\n[1] \"286\"\n\n$`$P51B`\n[1] \"32\"\n\n$`$P51E`\n[1] \"0,0\"\n\n$`$P51N`\n[1] \"B12-A\"\n\n$`$P51R`\n[1] \"4194304\"\n\n$`$P51TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P51V`\n[1] \"407\"\n\n$`$P52B`\n[1] \"32\"\n\n$`$P52E`\n[1] \"0,0\"\n\n$`$P52N`\n[1] \"B13-A\"\n\n$`$P52R`\n[1] \"4194304\"\n\n$`$P52TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P52V`\n[1] \"700\"\n\n$`$P53B`\n[1] \"32\"\n\n$`$P53E`\n[1] \"0,0\"\n\n$`$P53N`\n[1] \"B14-A\"\n\n$`$P53R`\n[1] \"4194304\"\n\n$`$P53TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P53V`\n[1] \"693\"\n\n$`$P54B`\n[1] \"32\"\n\n$`$P54E`\n[1] \"0,0\"\n\n$`$P54N`\n[1] \"R1-A\"\n\n$`$P54R`\n[1] \"4194304\"\n\n$`$P54TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P54V`\n[1] \"158\"\n\n$`$P55B`\n[1] \"32\"\n\n$`$P55E`\n[1] \"0,0\"\n\n$`$P55N`\n[1] \"R2-A\"\n\n$`$P55R`\n[1] \"4194304\"\n\n$`$P55TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P55V`\n[1] \"245\"\n\n$`$P56B`\n[1] \"32\"\n\n$`$P56E`\n[1] \"0,0\"\n\n$`$P56N`\n[1] \"R3-A\"\n\n$`$P56R`\n[1] \"4194304\"\n\n$`$P56TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P56V`\n[1] \"338\"\n\n$`$P57B`\n[1] \"32\"\n\n$`$P57E`\n[1] \"0,0\"\n\n$`$P57N`\n[1] \"R4-A\"\n\n$`$P57R`\n[1] \"4194304\"\n\n$`$P57TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P57V`\n[1] \"238\"\n\n$`$P58B`\n[1] \"32\"\n\n$`$P58E`\n[1] \"0,0\"\n\n$`$P58N`\n[1] \"R5-A\"\n\n$`$P58R`\n[1] \"4194304\"\n\n$`$P58TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P58V`\n[1] \"191\"\n\n$`$P59B`\n[1] \"32\"\n\n$`$P59E`\n[1] \"0,0\"\n\n$`$P59N`\n[1] \"R6-A\"\n\n$`$P59R`\n[1] \"4194304\"\n\n$`$P59TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P59V`\n[1] \"274\"\n\n$`$P5B`\n[1] \"32\"\n\n$`$P5E`\n[1] \"0,0\"\n\n$`$P5N`\n[1] \"UV4-A\"\n\n$`$P5R`\n[1] \"4194304\"\n\n$`$P5TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P5V`\n[1] \"1022\"\n\n$`$P60B`\n[1] \"32\"\n\n$`$P60E`\n[1] \"0,0\"\n\n$`$P60N`\n[1] \"R7-A\"\n\n$`$P60R`\n[1] \"4194304\"\n\n$`$P60TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P60V`\n[1] \"524\"\n\n$`$P61B`\n[1] \"32\"\n\n$`$P61E`\n[1] \"0,0\"\n\n$`$P61N`\n[1] \"R8-A\"\n\n$`$P61R`\n[1] \"4194304\"\n\n$`$P61TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P61V`\n[1] \"243\"\n\n$`$P6B`\n[1] \"32\"\n\n$`$P6E`\n[1] \"0,0\"\n\n$`$P6N`\n[1] \"UV5-A\"\n\n$`$P6R`\n[1] \"4194304\"\n\n$`$P6TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P6V`\n[1] \"616\"\n\n$`$P7B`\n[1] \"32\"\n\n$`$P7E`\n[1] \"0,0\"\n\n$`$P7N`\n[1] \"UV6-A\"\n\n$`$P7R`\n[1] \"4194304\"\n\n$`$P7TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P7V`\n[1] \"506\"\n\n$`$P8B`\n[1] \"32\"\n\n$`$P8E`\n[1] \"0,0\"\n\n$`$P8N`\n[1] \"UV7-A\"\n\n$`$P8R`\n[1] \"4194304\"\n\n$`$P8TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P8V`\n[1] \"661\"\n\n$`$P9B`\n[1] \"32\"\n\n$`$P9E`\n[1] \"0,0\"\n\n$`$P9N`\n[1] \"UV8-A\"\n\n$`$P9R`\n[1] \"4194304\"\n\n$`$P9TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P9V`\n[1] \"514\"\n\n\nFortunately for all involved, there is a consistently repeating pattern for the keywords corresponding to each detector. We can see that here for $P7B, $P7E, $P7N, $P7R, $P7TYPE, $P7V\n\nWhen referencing to the Flow Cytometry Standard documentation, here are what the particular keyword letters mean:\n\n\n\n\n\n\nB\n\n\n\nNumber of bits reserved for parameter number n\n\n\n\n\nDescriptionList$`$P7B`\n\n[1] \"32\"\n\n\n\n\n\n\n\n\n\nE\n\n\n\nAmplification type for parameter n. \n\n\n\n\nDescriptionList$`$P7E`\n\n[1] \"0,0\"\n\n\n\n\n\n\n\n\n\n\n\nN\n\n\n\nShort Name for parameter n. \n\n\n\n\nDescriptionList$`$P7N`\n\n[1] \"UV6-A\"\n\n\n\n\n\n\n\n\n\nR\n\n\n\nRange for parameter number n. \n\n\n\n\nDescriptionList$`$P7R`\n\n[1] \"4194304\"\n\n\n\n\n\n\n\n\n\n\n\nTYPE\n\n\n\nDetector type for parameter n. \n\n\n\n\nDescriptionList$`$P7TYPE`\n\n[1] \"Raw_Fluorescence\"\n\n\n\n\n\n\n\n\n\nV\n\n\n\nDetector voltage for parameter n. \n\n\n\n\nDescriptionList$`$P7V`\n\n[1] \"506\"\n\n\n\n\n\nWhile not immediately obvious, understanding what these keywords encoded has proven useful for our core. In our case, we have built an automated InstrumentQC dashboard for all the instruments at our core.\n\n\n\nBy extracting out from our daily QC bead .fcs files the stored N (Detector Name) and V (Gain/Voltage) values for all the individual detectors, it allows us to plot Levey-Jennings Plots for our individual instruments, giving us usually around a months warning before an individual laser begins to fail. This helps with scheduling the Field-Service Engineer visit before it starts impacting the actual data.\n\n\n\nWhile most of the detectors keywords are similar (only changing there individual name and voltage) there are a couple exceptions.\nFor the FSC/SSC parameters, instead of Raw_Fluorescence value for Type, we see the corresponding Scatter value get return. This in term is what is used by various commercial softwares to show those axis as linear instead of biexponential when selected.\n\n\n\nThis is similarly the case for the Time parameter, where in addition to Type being set to Time, the range also appears different to Raw/Scatters value.", "crumbs": [ "About", "Intro to R", - "04 - Intro to Tidyverse" + "03 - Inside a .FCS file" ] }, { - "objectID": "course/04_IntroToTidyverse/index.html#rename", - "href": "course/04_IntroToTidyverse/index.html#rename", - "title": "04 - Introduction to Tidyverse", - "section": "rename", - "text": "rename\nAt this point, we are able to both move and select particular columns, allowing us to rearrange and subset a larger data.frame object however we want it to appear. However, as we encountered, some of the names contain special characters and spaces, requiring use of tick marks (``) to avoid issues. How can we change a column name?\nIn base R, we could change individual column names by assigning a new value with the assignment arrow to the corresponding column name index. For example, looking at our Subset object, wen could rename CD8+ as follows:\n\ncolnames(Subset)\n\n[1] \"bid\" \"Tcells\" \"CD8+\" \"CD4+\" \"timepoint\" \"Condition\"\n\ncolnames(Subset)[3]\n\n[1] \"CD8+\"\n\n\n\ncolnames(Subset)[3] <- \"CD8Positive\"\ncolnames(Subset)\n\n[1] \"bid\" \"Tcells\" \"CD8Positive\" \"CD4+\" \"timepoint\" \n[6] \"Condition\" \n\n\nWith the tidyverse, we can use the rename() function which removes the need to look up the column index number. The way we write the argument is placing within the parenthesis the old name to the right of the equals sign, with the new name to the left\n\nRenamed <- Subset |> rename(CD4_Positive = `CD4+`)\ncolnames(Renamed)\n\n[1] \"bid\" \"Tcells\" \"CD8Positive\" \"CD4_Positive\" \"timepoint\" \n[6] \"Condition\" \n\n\nIf we wanted to rename multiple column names at once, we would just need to include a comma between the individual rename arguments within the parenthesis.\n\nRenamed_Multiple <- Subset |> rename(specimen = bid, timepoint_months = timepoint, stimulation = Condition, CD4Positive=`CD4+`)\ncolnames(Renamed_Multiple)\n\n[1] \"specimen\" \"Tcells\" \"CD8Positive\" \"CD4Positive\" \n[5] \"timepoint_months\" \"stimulation\"", + "objectID": "course/03_InsideFCSFile/index.html#middle-metadata", + "href": "course/03_InsideFCSFile/index.html#middle-metadata", + "title": "03 - Inside an FCS File", + "section": "Middle Metadata", + "text": "Middle Metadata\nOnce we are out of the detector keywords, we find the last of the $Metadata associated keywords.\n\nDetectors <- DescriptionList[385:398]\nDetectors\n\n$`$PAR`\n[1] \"61\"\n\n$`$PROJ`\n[1] \"CellCounts4L_AB_05\"\n\n$`$SPILLOVER`\n UV1-A UV2-A UV3-A UV4-A UV5-A UV6-A UV7-A UV8-A UV9-A UV10-A UV11-A\n [1,] 1e+00 0 0 0 0 0 0 0 0 0 0\n [2,] 1e-06 1 0 0 0 0 0 0 0 0 0\n [3,] 0e+00 0 1 0 0 0 0 0 0 0 0\n [4,] 0e+00 0 0 1 0 0 0 0 0 0 0\n [5,] 0e+00 0 0 0 1 0 0 0 0 0 0\n [6,] 0e+00 0 0 0 0 1 0 0 0 0 0\n [7,] 0e+00 0 0 0 0 0 1 0 0 0 0\n [8,] 0e+00 0 0 0 0 0 0 1 0 0 0\n [9,] 0e+00 0 0 0 0 0 0 0 1 0 0\n[10,] 0e+00 0 0 0 0 0 0 0 0 1 0\n[11,] 0e+00 0 0 0 0 0 0 0 0 0 1\n[12,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[13,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[14,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[15,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[16,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[17,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[18,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[19,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[20,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[21,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[22,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[23,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[24,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[25,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[26,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[27,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[28,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[29,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[30,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[31,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[32,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[33,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[34,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[35,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[36,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[37,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[38,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[39,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[40,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[41,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[42,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[43,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[44,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[45,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[46,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[47,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[48,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[49,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[50,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[51,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[52,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[53,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[54,] 0e+00 0 0 0 0 0 0 0 0 0 0\n UV12-A UV13-A UV14-A UV15-A UV16-A V1-A V2-A V3-A V4-A V5-A V6-A V7-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 1 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 1 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 1 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 1 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 1 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 1 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 1 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 1 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 1 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 1 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 1 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 1\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0\n V8-A V9-A V10-A V11-A V12-A V13-A V14-A V15-A V16-A B1-A B2-A B3-A B4-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n B5-A B6-A B7-A B8-A B9-A B10-A B11-A B12-A B13-A B14-A R1-A R2-A R3-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n R4-A R5-A R6-A R7-A R8-A\n [1,] 0 0 0 0 0\n [2,] 0 0 0 0 0\n [3,] 0 0 0 0 0\n [4,] 0 0 0 0 0\n [5,] 0 0 0 0 0\n [6,] 0 0 0 0 0\n [7,] 0 0 0 0 0\n [8,] 0 0 0 0 0\n [9,] 0 0 0 0 0\n[10,] 0 0 0 0 0\n[11,] 0 0 0 0 0\n[12,] 0 0 0 0 0\n[13,] 0 0 0 0 0\n[14,] 0 0 0 0 0\n[15,] 0 0 0 0 0\n[16,] 0 0 0 0 0\n[17,] 0 0 0 0 0\n[18,] 0 0 0 0 0\n[19,] 0 0 0 0 0\n[20,] 0 0 0 0 0\n[21,] 0 0 0 0 0\n[22,] 0 0 0 0 0\n[23,] 0 0 0 0 0\n[24,] 0 0 0 0 0\n[25,] 0 0 0 0 0\n[26,] 0 0 0 0 0\n[27,] 0 0 0 0 0\n[28,] 0 0 0 0 0\n[29,] 0 0 0 0 0\n[30,] 0 0 0 0 0\n[31,] 0 0 0 0 0\n[32,] 0 0 0 0 0\n[33,] 0 0 0 0 0\n[34,] 0 0 0 0 0\n[35,] 0 0 0 0 0\n[36,] 0 0 0 0 0\n[37,] 0 0 0 0 0\n[38,] 0 0 0 0 0\n[39,] 0 0 0 0 0\n[40,] 0 0 0 0 0\n[41,] 0 0 0 0 0\n[42,] 0 0 0 0 0\n[43,] 0 0 0 0 0\n[44,] 0 0 0 0 0\n[45,] 0 0 0 0 0\n[46,] 0 0 0 0 0\n[47,] 0 0 0 0 0\n[48,] 0 0 0 0 0\n[49,] 0 0 0 0 0\n[50,] 1 0 0 0 0\n[51,] 0 1 0 0 0\n[52,] 0 0 1 0 0\n[53,] 0 0 0 1 0\n[54,] 0 0 0 0 1\n\n$`$TIMESTEP`\n[1] \"0.0001\"\n\n$`$TOT`\n[1] \"100\"\n\n$`$VOL`\n[1] \"30.31\"\n\n$`APPLY COMPENSATION`\n[1] \"FALSE\"\n\n$CHARSET\n[1] \"utf-8\"\n\n$CREATOR\n[1] \"SpectroFlo 3.3.0\"\n\n$FCSversion\n[1] \"3\"\n\n$FILENAME\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n$`FSC ASF`\n[1] \"1.21\"\n\n$GROUPNAME\n[1] \"ND050\"\n\n$GUID\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n\nAmong those of potential interest\n\n\n\n\n\n\nProj\n\n\n\nOften corresponding to the experiment file name\n\n\n\n\nDescriptionList$`$PROJ`\n\n[1] \"CellCounts4L_AB_05\"\n\n\n\n\n\n\n\n\n\nSpillover\n\n\n\nWhere the internal spillover matrix is stored (we will revisit during compensation)\n\n\n\n\nDescriptionList$`$SPILLOVER`\n\n UV1-A UV2-A UV3-A UV4-A UV5-A UV6-A UV7-A UV8-A UV9-A UV10-A UV11-A\n [1,] 1e+00 0 0 0 0 0 0 0 0 0 0\n [2,] 1e-06 1 0 0 0 0 0 0 0 0 0\n [3,] 0e+00 0 1 0 0 0 0 0 0 0 0\n [4,] 0e+00 0 0 1 0 0 0 0 0 0 0\n [5,] 0e+00 0 0 0 1 0 0 0 0 0 0\n [6,] 0e+00 0 0 0 0 1 0 0 0 0 0\n [7,] 0e+00 0 0 0 0 0 1 0 0 0 0\n [8,] 0e+00 0 0 0 0 0 0 1 0 0 0\n [9,] 0e+00 0 0 0 0 0 0 0 1 0 0\n[10,] 0e+00 0 0 0 0 0 0 0 0 1 0\n[11,] 0e+00 0 0 0 0 0 0 0 0 0 1\n[12,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[13,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[14,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[15,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[16,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[17,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[18,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[19,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[20,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[21,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[22,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[23,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[24,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[25,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[26,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[27,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[28,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[29,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[30,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[31,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[32,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[33,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[34,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[35,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[36,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[37,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[38,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[39,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[40,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[41,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[42,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[43,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[44,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[45,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[46,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[47,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[48,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[49,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[50,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[51,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[52,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[53,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[54,] 0e+00 0 0 0 0 0 0 0 0 0 0\n UV12-A UV13-A UV14-A UV15-A UV16-A V1-A V2-A V3-A V4-A V5-A V6-A V7-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 1 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 1 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 1 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 1 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 1 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 1 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 1 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 1 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 1 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 1 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 1 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 1\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0\n V8-A V9-A V10-A V11-A V12-A V13-A V14-A V15-A V16-A B1-A B2-A B3-A B4-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n B5-A B6-A B7-A B8-A B9-A B10-A B11-A B12-A B13-A B14-A R1-A R2-A R3-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n R4-A R5-A R6-A R7-A R8-A\n [1,] 0 0 0 0 0\n [2,] 0 0 0 0 0\n [3,] 0 0 0 0 0\n [4,] 0 0 0 0 0\n [5,] 0 0 0 0 0\n [6,] 0 0 0 0 0\n [7,] 0 0 0 0 0\n [8,] 0 0 0 0 0\n [9,] 0 0 0 0 0\n[10,] 0 0 0 0 0\n[11,] 0 0 0 0 0\n[12,] 0 0 0 0 0\n[13,] 0 0 0 0 0\n[14,] 0 0 0 0 0\n[15,] 0 0 0 0 0\n[16,] 0 0 0 0 0\n[17,] 0 0 0 0 0\n[18,] 0 0 0 0 0\n[19,] 0 0 0 0 0\n[20,] 0 0 0 0 0\n[21,] 0 0 0 0 0\n[22,] 0 0 0 0 0\n[23,] 0 0 0 0 0\n[24,] 0 0 0 0 0\n[25,] 0 0 0 0 0\n[26,] 0 0 0 0 0\n[27,] 0 0 0 0 0\n[28,] 0 0 0 0 0\n[29,] 0 0 0 0 0\n[30,] 0 0 0 0 0\n[31,] 0 0 0 0 0\n[32,] 0 0 0 0 0\n[33,] 0 0 0 0 0\n[34,] 0 0 0 0 0\n[35,] 0 0 0 0 0\n[36,] 0 0 0 0 0\n[37,] 0 0 0 0 0\n[38,] 0 0 0 0 0\n[39,] 0 0 0 0 0\n[40,] 0 0 0 0 0\n[41,] 0 0 0 0 0\n[42,] 0 0 0 0 0\n[43,] 0 0 0 0 0\n[44,] 0 0 0 0 0\n[45,] 0 0 0 0 0\n[46,] 0 0 0 0 0\n[47,] 0 0 0 0 0\n[48,] 0 0 0 0 0\n[49,] 0 0 0 0 0\n[50,] 1 0 0 0 0\n[51,] 0 1 0 0 0\n[52,] 0 0 1 0 0\n[53,] 0 0 0 1 0\n[54,] 0 0 0 0 1\n\n\n\n\n\n\n\n\n\nTOT\n\n\n\nTotal events (in this case my downsampled 100 cells)\n\n\n\n\nDescriptionList$`$TOT`\n\n[1] \"100\"\n\n\n\n\n\n\n\n\n\nVolume\n\n\n\nVolume amount acquired during acquisition.\n\n\n\n\nDescriptionList$`$VOL`\n\n[1] \"30.31\"\n\n\n\n\n\n\n\n\n\nSoftware\n\n\n\nSoftware used and version\n\n\n\n\nDescriptionList$CREATOR\n\n[1] \"SpectroFlo 3.3.0\"\n\n\n\nYou will notice at this point, the keyword names including a “$” symbol have stopped, so tick marks are no longer required (except when there is a space in the name). The only $ remaining is being used as a selector for a particular item in the list.\n\nDetectors <- DescriptionList[390:398]\nDetectors\n\n$`$VOL`\n[1] \"30.31\"\n\n$`APPLY COMPENSATION`\n[1] \"FALSE\"\n\n$CHARSET\n[1] \"utf-8\"\n\n$CREATOR\n[1] \"SpectroFlo 3.3.0\"\n\n$FCSversion\n[1] \"3\"\n\n$FILENAME\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n$`FSC ASF`\n[1] \"1.21\"\n\n$GROUPNAME\n[1] \"ND050\"\n\n$GUID\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n\n\n\n\n\n\n\nFILENAME\n\n\n\nBasically the full file.path to the .fcs file of interest.\n\n\n\n\nDescriptionList$FILENAME\n\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n\n\n\n\n\n\n\n\nGROUPNAME\n\n\n\nThe Name assigned to the acquisition Group.\n\n\n\n\nDescriptionList$GROUPNAME\n\n[1] \"ND050\"", "crumbs": [ "About", "Intro to R", - "04 - Intro to Tidyverse" + "03 - Inside a .FCS file" ] }, { - "objectID": "course/04_IntroToTidyverse/index.html#pull", - "href": "course/04_IntroToTidyverse/index.html#pull", - "title": "04 - Introduction to Tidyverse", - "section": "pull", - "text": "pull\nSometimes, we may want to retrieve individual values present in a column, to use within either a vector or a list. We can do this using the pull() function, which will retrieve the column contents and strip the column formatting\n\nData |> pull(Date) |> head(5)\n\n[1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n\n\nThis can be useful when we are doing data exploration, and trying to determine how many unique variants might be present. For example, if we wanted to see what days individual samples were acquired, we could pull() the data and pass it to the unique() function:\n\nData |> pull(Date) |> unique()\n\n[1] \"2025-07-26\" \"2025-07-29\" \"2025-07-31\" \"2025-08-05\" \"2025-08-07\"\n[6] \"2025-08-22\" \"2025-08-28\" \"2025-08-30\"", + "objectID": "course/03_InsideFCSFile/index.html#laser-metadata", + "href": "course/03_InsideFCSFile/index.html#laser-metadata", + "title": "03 - Inside an FCS File", + "section": "Laser Metadata", + "text": "Laser Metadata\nNext up, there is a small stretch of keywords containing the values associated with the individual lasers as far as delays and area scaling factors for a particular day (also useful when plotted).\n\nDetectors <- DescriptionList[399:410]\nDetectors\n\n$LASER1ASF\n[1] \"1.09\"\n\n$LASER1DELAY\n[1] \"-19.525\"\n\n$LASER1NAME\n[1] \"Violet\"\n\n$LASER2ASF\n[1] \"1.14\"\n\n$LASER2DELAY\n[1] \"0\"\n\n$LASER2NAME\n[1] \"Blue\"\n\n$LASER3ASF\n[1] \"1.02\"\n\n$LASER3DELAY\n[1] \"20.15\"\n\n$LASER3NAME\n[1] \"Red\"\n\n$LASER4ASF\n[1] \"0.92\"\n\n$LASER4DELAY\n[1] \"40.725\"\n\n$LASER4NAME\n[1] \"UV\"", "crumbs": [ "About", "Intro to R", - "04 - Intro to Tidyverse" + "03 - Inside a .FCS file" ] }, { - "objectID": "course/04_IntroToTidyverse/index.html#filter-rows", - "href": "course/04_IntroToTidyverse/index.html#filter-rows", - "title": "04 - Introduction to Tidyverse", - "section": "filter (Rows)", - "text": "filter (Rows)\nSo far, we have been working with dplyr functions primarily used when working with and subsetting columns (including select(), pull(), rename() and relocate()). What if we wanted to work with rows of a data.frame? This is where the filter() function is used.\nThe Condition column in this Dataset appears to be indicating whether the samples were stimulated. Let’s see how many unique values are contained within that column\n\nData |> pull(Condition) |> unique() \n\n[1] \"Ctrl\" \"PPD\" \"SEB\" \n\n\nIn the case of this dataset, looks like the .fcs files where treated with either left alone, treated with PPD (Purified Protein Derrivative) or SEB. What if we wanted to subset only those treated with PPD?\nWithin filter(), we would specify the column name as the first argument, and ask that only values equal to (==) “PPD” be returned. Notice in this case, “” are needed, as we are asking for a matching character value.\n\nPPDOnly <- Data |> filter(Condition == \"PPD\")\nhead(PPDOnly, 5)\n\n bid timepoint Condition Date infant_sex ptype root singletsFSC\n1 INF0052 0 PPD 2025-07-26 Male HEU-hi 2363512 2136616\n2 INF0100 0 PPD 2025-07-26 Male HEU-lo 2049112 1821676\n3 INF0100 4 PPD 2025-07-26 Male HEU-lo 1063496 946587\n4 INF0100 9 PPD 2025-07-26 Male HEU-lo 788368 714198\n5 INF0179 0 PPD 2025-07-26 Male HU 1380336 1242311\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1875394 1732620 0.5873838 0.8619837 0.8429685 0.6408044\n2 1717636 1597085 0.9063081 0.9251961 0.8771889 0.2174284\n3 796056 767297 0.9709891 0.9848719 0.9556049 0.7313503\n4 626387 600011 0.9822803 0.9842139 0.8123041 0.6223228\n5 1047081 1000877 0.9470275 0.9575685 0.9134438 0.6996502\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9009254 0.20743228 0.6934931 0.2835676 0.007408209 0.9925918 0.01507057\n2 0.8929673 0.06181426 0.8311531 0.6735798 0.007137230 0.9928628 0.01671801\n3 0.8782307 0.20727202 0.6709587 0.5989873 0.005254643 0.9947454 0.01609790\n4 0.9566639 0.23164587 0.7250180 0.6489405 0.011935922 0.9880641 0.01855298\n5 0.8856898 0.33186111 0.5538287 0.4441538 0.004382972 0.9956170 0.01297237\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9775212 0.6340345 0.3434867 0.2744119 0.06907479 184930\n2 0.9761448 0.6145707 0.3615741 0.3312279 0.03034620 211987\n3 0.9786475 0.6559480 0.3226994 0.2912084 0.03149109 326378\n4 0.9695111 0.4306889 0.5388222 0.4908558 0.04796636 238021\n5 0.9826447 0.7499194 0.2327253 0.1850897 0.04763554 294549\n lymphocytes_count Monocytes Debris CD45_count\n1 652155 0.13801632 0.15703150 1017713\n2 314717 0.07480391 0.12281107 1447451\n3 544883 0.01512811 0.04439511 745037\n4 366784 0.01578611 0.18769586 589379\n5 663169 0.04243146 0.08655621 947858\n\n\nWhile this works, using “==” to match can glitch, especially with character values. Using the %in% operator is a better way of identifying and extracting only the rows whose Condition column contains “PPD”\n\nData |> filter(Condition %in% \"PPD\") |> head(5)\n\n bid timepoint Condition Date infant_sex ptype root singletsFSC\n1 INF0052 0 PPD 2025-07-26 Male HEU-hi 2363512 2136616\n2 INF0100 0 PPD 2025-07-26 Male HEU-lo 2049112 1821676\n3 INF0100 4 PPD 2025-07-26 Male HEU-lo 1063496 946587\n4 INF0100 9 PPD 2025-07-26 Male HEU-lo 788368 714198\n5 INF0179 0 PPD 2025-07-26 Male HU 1380336 1242311\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1875394 1732620 0.5873838 0.8619837 0.8429685 0.6408044\n2 1717636 1597085 0.9063081 0.9251961 0.8771889 0.2174284\n3 796056 767297 0.9709891 0.9848719 0.9556049 0.7313503\n4 626387 600011 0.9822803 0.9842139 0.8123041 0.6223228\n5 1047081 1000877 0.9470275 0.9575685 0.9134438 0.6996502\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9009254 0.20743228 0.6934931 0.2835676 0.007408209 0.9925918 0.01507057\n2 0.8929673 0.06181426 0.8311531 0.6735798 0.007137230 0.9928628 0.01671801\n3 0.8782307 0.20727202 0.6709587 0.5989873 0.005254643 0.9947454 0.01609790\n4 0.9566639 0.23164587 0.7250180 0.6489405 0.011935922 0.9880641 0.01855298\n5 0.8856898 0.33186111 0.5538287 0.4441538 0.004382972 0.9956170 0.01297237\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9775212 0.6340345 0.3434867 0.2744119 0.06907479 184930\n2 0.9761448 0.6145707 0.3615741 0.3312279 0.03034620 211987\n3 0.9786475 0.6559480 0.3226994 0.2912084 0.03149109 326378\n4 0.9695111 0.4306889 0.5388222 0.4908558 0.04796636 238021\n5 0.9826447 0.7499194 0.2327253 0.1850897 0.04763554 294549\n lymphocytes_count Monocytes Debris CD45_count\n1 652155 0.13801632 0.15703150 1017713\n2 314717 0.07480391 0.12281107 1447451\n3 544883 0.01512811 0.04439511 745037\n4 366784 0.01578611 0.18769586 589379\n5 663169 0.04243146 0.08655621 947858\n\n\nSimilar to what we saw for select(), we can grab rows that contain various values at once. We would just need to modify the second part of the argument. If we wanted to grab rows whose Condition column contained either PPD or SEB, we would need to provide that argument as a vector, placing both within c()/\n\nData |> filter(Condition %in% c(\"PPD\", \"SEB\")) |> head(5)\n\n bid timepoint Condition Date infant_sex ptype root singletsFSC\n1 INF0052 0 PPD 2025-07-26 Male HEU-hi 2363512 2136616\n2 INF0100 0 PPD 2025-07-26 Male HEU-lo 2049112 1821676\n3 INF0100 4 PPD 2025-07-26 Male HEU-lo 1063496 946587\n4 INF0100 9 PPD 2025-07-26 Male HEU-lo 788368 714198\n5 INF0179 0 PPD 2025-07-26 Male HU 1380336 1242311\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1875394 1732620 0.5873838 0.8619837 0.8429685 0.6408044\n2 1717636 1597085 0.9063081 0.9251961 0.8771889 0.2174284\n3 796056 767297 0.9709891 0.9848719 0.9556049 0.7313503\n4 626387 600011 0.9822803 0.9842139 0.8123041 0.6223228\n5 1047081 1000877 0.9470275 0.9575685 0.9134438 0.6996502\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9009254 0.20743228 0.6934931 0.2835676 0.007408209 0.9925918 0.01507057\n2 0.8929673 0.06181426 0.8311531 0.6735798 0.007137230 0.9928628 0.01671801\n3 0.8782307 0.20727202 0.6709587 0.5989873 0.005254643 0.9947454 0.01609790\n4 0.9566639 0.23164587 0.7250180 0.6489405 0.011935922 0.9880641 0.01855298\n5 0.8856898 0.33186111 0.5538287 0.4441538 0.004382972 0.9956170 0.01297237\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9775212 0.6340345 0.3434867 0.2744119 0.06907479 184930\n2 0.9761448 0.6145707 0.3615741 0.3312279 0.03034620 211987\n3 0.9786475 0.6559480 0.3226994 0.2912084 0.03149109 326378\n4 0.9695111 0.4306889 0.5388222 0.4908558 0.04796636 238021\n5 0.9826447 0.7499194 0.2327253 0.1850897 0.04763554 294549\n lymphocytes_count Monocytes Debris CD45_count\n1 652155 0.13801632 0.15703150 1017713\n2 314717 0.07480391 0.12281107 1447451\n3 544883 0.01512811 0.04439511 745037\n4 366784 0.01578611 0.18769586 589379\n5 663169 0.04243146 0.08655621 947858\n\n\nAlternatively, we could have set up the vector externally, and then provided it to filter()\n\nTheseConditions <- c(\"PPD\", \"SEB\")\nData |> filter(Condition %in% TheseConditions) |> head(5)\n\n bid timepoint Condition Date infant_sex ptype root singletsFSC\n1 INF0052 0 PPD 2025-07-26 Male HEU-hi 2363512 2136616\n2 INF0100 0 PPD 2025-07-26 Male HEU-lo 2049112 1821676\n3 INF0100 4 PPD 2025-07-26 Male HEU-lo 1063496 946587\n4 INF0100 9 PPD 2025-07-26 Male HEU-lo 788368 714198\n5 INF0179 0 PPD 2025-07-26 Male HU 1380336 1242311\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1875394 1732620 0.5873838 0.8619837 0.8429685 0.6408044\n2 1717636 1597085 0.9063081 0.9251961 0.8771889 0.2174284\n3 796056 767297 0.9709891 0.9848719 0.9556049 0.7313503\n4 626387 600011 0.9822803 0.9842139 0.8123041 0.6223228\n5 1047081 1000877 0.9470275 0.9575685 0.9134438 0.6996502\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9009254 0.20743228 0.6934931 0.2835676 0.007408209 0.9925918 0.01507057\n2 0.8929673 0.06181426 0.8311531 0.6735798 0.007137230 0.9928628 0.01671801\n3 0.8782307 0.20727202 0.6709587 0.5989873 0.005254643 0.9947454 0.01609790\n4 0.9566639 0.23164587 0.7250180 0.6489405 0.011935922 0.9880641 0.01855298\n5 0.8856898 0.33186111 0.5538287 0.4441538 0.004382972 0.9956170 0.01297237\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9775212 0.6340345 0.3434867 0.2744119 0.06907479 184930\n2 0.9761448 0.6145707 0.3615741 0.3312279 0.03034620 211987\n3 0.9786475 0.6559480 0.3226994 0.2912084 0.03149109 326378\n4 0.9695111 0.4306889 0.5388222 0.4908558 0.04796636 238021\n5 0.9826447 0.7499194 0.2327253 0.1850897 0.04763554 294549\n lymphocytes_count Monocytes Debris CD45_count\n1 652155 0.13801632 0.15703150 1017713\n2 314717 0.07480391 0.12281107 1447451\n3 544883 0.01512811 0.04439511 745037\n4 366784 0.01578611 0.18769586 589379\n5 663169 0.04243146 0.08655621 947858\n\n\nWhile this works when we have a limited number of variant condition values, what if had many more but only wanted to exclude one value? As we saw when learning about Conditionals, when we add a ! in front of a logical value, we get the opposite logical value returned\n\nIsThisASpectralInstrument <- TRUE\n\n!IsThisASpectralInstrument\n\n[1] FALSE\n\n\nIn the context of the dplyr package, we can use ! within the filter() to remove rows that contain a certain value\n\nSubset <- Data |> filter(!Condition %in% \"SEB\")\nSubset |> pull(Condition) |> unique()\n\n[1] \"Ctrl\" \"PPD\" \n\n\nLikewise, we can also use it with the select() to exclude columns we don’t want to include\n\nSubset <- Data |> select(!timepoint)\nSubset[1:3,]\n\n bid Condition Date infant_sex ptype root singletsFSC\n1 INF0052 Ctrl 2025-07-26 Male HEU-hi 2098368 1894070\n2 INF0100 Ctrl 2025-07-26 Male HEU-lo 2020184 1791890\n3 INF0100 Ctrl 2025-07-26 Male HEU-lo 1155040 1033320\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1666179 1537396 0.5952943 0.8820349 0.8627649 0.6420138\n2 1697083 1579098 0.9106762 0.9052256 0.8602660 0.2145848\n3 875465 845446 0.9705765 0.9845400 0.9578793 0.7403110\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9020581 0.21090996 0.6911482 0.2804264 0.008120361 0.9918796 0.01448070\n2 0.8908981 0.06252775 0.8283703 0.6748298 0.007265620 0.9927344 0.01577499\n3 0.8757665 0.20023803 0.6755285 0.6119129 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Monocytes Debris CD45_count\n1 587573 0.11796509 0.13723513 915203\n2 308583 0.09477437 0.13973396 1438047\n3 607477 0.01545999 0.04212072 820570", + "objectID": "course/03_InsideFCSFile/index.html#display", + "href": "course/03_InsideFCSFile/index.html#display", + "title": "03 - Inside an FCS File", + "section": "Display", + "text": "Display\nThen there is a stretch matching whether a particular detector needs to be displayed as linear (in the case of time and scatter) or as log (for individual detectors).\n\nDetectors <- DescriptionList[412:472]\nDetectors\n\n$P10DISPLAY\n[1] \"LOG\"\n\n$P11DISPLAY\n[1] \"LOG\"\n\n$P12DISPLAY\n[1] \"LOG\"\n\n$P13DISPLAY\n[1] \"LOG\"\n\n$P14DISPLAY\n[1] \"LOG\"\n\n$P15DISPLAY\n[1] \"LOG\"\n\n$P16DISPLAY\n[1] \"LOG\"\n\n$P17DISPLAY\n[1] \"LOG\"\n\n$P18DISPLAY\n[1] \"LIN\"\n\n$P19DISPLAY\n[1] \"LIN\"\n\n$P1DISPLAY\n[1] \"LOG\"\n\n$P20DISPLAY\n[1] \"LOG\"\n\n$P21DISPLAY\n[1] \"LOG\"\n\n$P22DISPLAY\n[1] \"LOG\"\n\n$P23DISPLAY\n[1] \"LOG\"\n\n$P24DISPLAY\n[1] \"LOG\"\n\n$P25DISPLAY\n[1] \"LOG\"\n\n$P26DISPLAY\n[1] \"LOG\"\n\n$P27DISPLAY\n[1] \"LOG\"\n\n$P28DISPLAY\n[1] \"LOG\"\n\n$P29DISPLAY\n[1] \"LOG\"\n\n$P2DISPLAY\n[1] \"LOG\"\n\n$P30DISPLAY\n[1] \"LOG\"\n\n$P31DISPLAY\n[1] \"LOG\"\n\n$P32DISPLAY\n[1] \"LOG\"\n\n$P33DISPLAY\n[1] \"LOG\"\n\n$P34DISPLAY\n[1] \"LOG\"\n\n$P35DISPLAY\n[1] \"LOG\"\n\n$P36DISPLAY\n[1] \"LIN\"\n\n$P37DISPLAY\n[1] \"LIN\"\n\n$P38DISPLAY\n[1] \"LIN\"\n\n$P39DISPLAY\n[1] \"LIN\"\n\n$P3DISPLAY\n[1] \"LOG\"\n\n$P40DISPLAY\n[1] \"LOG\"\n\n$P41DISPLAY\n[1] \"LOG\"\n\n$P42DISPLAY\n[1] \"LOG\"\n\n$P43DISPLAY\n[1] \"LOG\"\n\n$P44DISPLAY\n[1] \"LOG\"\n\n$P45DISPLAY\n[1] \"LOG\"\n\n$P46DISPLAY\n[1] \"LOG\"\n\n$P47DISPLAY\n[1] \"LOG\"\n\n$P48DISPLAY\n[1] \"LOG\"\n\n$P49DISPLAY\n[1] \"LOG\"\n\n$P4DISPLAY\n[1] \"LOG\"\n\n$P50DISPLAY\n[1] \"LOG\"\n\n$P51DISPLAY\n[1] \"LOG\"\n\n$P52DISPLAY\n[1] \"LOG\"\n\n$P53DISPLAY\n[1] \"LOG\"\n\n$P54DISPLAY\n[1] \"LOG\"\n\n$P55DISPLAY\n[1] \"LOG\"\n\n$P56DISPLAY\n[1] \"LOG\"\n\n$P57DISPLAY\n[1] \"LOG\"\n\n$P58DISPLAY\n[1] \"LOG\"\n\n$P59DISPLAY\n[1] \"LOG\"\n\n$P5DISPLAY\n[1] \"LOG\"\n\n$P60DISPLAY\n[1] \"LOG\"\n\n$P61DISPLAY\n[1] \"LOG\"\n\n$P6DISPLAY\n[1] \"LOG\"\n\n$P7DISPLAY\n[1] \"LOG\"\n\n$P8DISPLAY\n[1] \"LOG\"\n\n$P9DISPLAY\n[1] \"LOG\"\n\n\nAnd a few final keywords with threshold, window scaling and other user selected settings.\n\nDetectors <- DescriptionList[473:476]\nDetectors\n\n$THRESHOLD\n[1] \"(FSC,50000)\"\n\n$TUBENAME\n[1] \"05\"\n\n$USERSETTINGNAME\n[1] \"DTR_CellCounts\"\n\n$`WINDOW EXTENSION`\n[1] \"3\"", "crumbs": [ "About", "Intro to R", - "04 - Intro to Tidyverse" + "03 - Inside a .FCS file" ] }, { - "objectID": "course/04_IntroToTidyverse/index.html#mutate", - "href": "course/04_IntroToTidyverse/index.html#mutate", - "title": "04 - Introduction to Tidyverse", - "section": "mutate", - "text": "mutate\nAs we can see, with just these handful of functions, we have the building blocks to rearrange and subset a larger data.frame into a format that we prefer. But what if we wanted to alter the content of a column, or add new columns to an existing data.frame? This is where the mutate() function can be used.\nLet’s start by slimming down our current Data to a smaller workable example, highlighting the functions and pipes we learned about today\n\nTidyData <- Data |> filter(Condition %in% \"Ctrl\") |> filter(timepoint %in% \"0\") |>\n select(bid, timepoint, Condition, Date, Tcells_count, CD45_count) |>\n rename(specimen=bid, condition=Condition) |> relocate(Date, .after=specimen)\n\n\nTidyData\n\n specimen Date timepoint condition Tcells_count CD45_count\n1 INF0052 2025-07-26 0 Ctrl 164771 915203\n2 INF0100 2025-07-26 0 Ctrl 208241 1438047\n3 INF0179 2025-07-26 0 Ctrl 291777 940733\n4 INF0134 2025-07-29 0 Ctrl 127866 689676\n5 INF0148 2025-07-29 0 Ctrl 234335 1013985\n6 INF0191 2025-07-29 0 Ctrl 55780 715443\n7 INF0124 2025-07-31 0 Ctrl 70297 687720\n8 INF0149 2025-07-31 0 Ctrl 107900 857845\n9 INF0169 2025-07-31 0 Ctrl 75540 854594\n10 INF0019 2025-08-05 0 Ctrl 208055 873622\n11 INF0032 2025-08-05 0 Ctrl 361034 753064\n12 INF0180 2025-08-05 0 Ctrl 284958 1049663\n13 INF0155 2025-08-07 0 Ctrl 281626 1065048\n14 INF0158 2025-08-07 0 Ctrl 280913 1249338\n15 INF0159 2025-08-07 0 Ctrl 452551 1190219\n16 INF0013 2025-08-22 0 Ctrl 182751 836573\n17 INF0023 2025-08-22 0 Ctrl 218435 968035\n18 INF0030 2025-08-22 0 Ctrl 85521 732321\n19 INF0166 2025-08-28 0 Ctrl 225650 739495\n20 INF0199 2025-08-28 0 Ctrl 169736 1112176\n21 INF0207 2025-08-28 0 Ctrl 39055 905365\n22 INF0614 2025-08-30 0 Ctrl 224396 1569007\n23 INF0622 2025-08-30 0 Ctrl 161924 939307\n\n\nThe mutate() function can be used to modify existing columns, as well as to create new ones. For example, let’s derrive the proportion of T cells from the overall CD45 gate. To do so, within the parenthesis, we would specify a new column name, and then divide the original columns:\n\nTidyData <- TidyData |> mutate(Tcells_ProportionCD45 = Tcells_count / CD45_count)\nTidyData\n\n specimen Date timepoint condition Tcells_count CD45_count\n1 INF0052 2025-07-26 0 Ctrl 164771 915203\n2 INF0100 2025-07-26 0 Ctrl 208241 1438047\n3 INF0179 2025-07-26 0 Ctrl 291777 940733\n4 INF0134 2025-07-29 0 Ctrl 127866 689676\n5 INF0148 2025-07-29 0 Ctrl 234335 1013985\n6 INF0191 2025-07-29 0 Ctrl 55780 715443\n7 INF0124 2025-07-31 0 Ctrl 70297 687720\n8 INF0149 2025-07-31 0 Ctrl 107900 857845\n9 INF0169 2025-07-31 0 Ctrl 75540 854594\n10 INF0019 2025-08-05 0 Ctrl 208055 873622\n11 INF0032 2025-08-05 0 Ctrl 361034 753064\n12 INF0180 2025-08-05 0 Ctrl 284958 1049663\n13 INF0155 2025-08-07 0 Ctrl 281626 1065048\n14 INF0158 2025-08-07 0 Ctrl 280913 1249338\n15 INF0159 2025-08-07 0 Ctrl 452551 1190219\n16 INF0013 2025-08-22 0 Ctrl 182751 836573\n17 INF0023 2025-08-22 0 Ctrl 218435 968035\n18 INF0030 2025-08-22 0 Ctrl 85521 732321\n19 INF0166 2025-08-28 0 Ctrl 225650 739495\n20 INF0199 2025-08-28 0 Ctrl 169736 1112176\n21 INF0207 2025-08-28 0 Ctrl 39055 905365\n22 INF0614 2025-08-30 0 Ctrl 224396 1569007\n23 INF0622 2025-08-30 0 Ctrl 161924 939307\n Tcells_ProportionCD45\n1 0.18003765\n2 0.14480820\n3 0.31015921\n4 0.18540010\n5 0.23110302\n6 0.07796568\n7 0.10221747\n8 0.12578030\n9 0.08839285\n10 0.23815220\n11 0.47942008\n12 0.27147570\n13 0.26442564\n14 0.22484948\n15 0.38022498\n16 0.21845195\n17 0.22564783\n18 0.11678076\n19 0.30514067\n20 0.15261613\n21 0.04313730\n22 0.14301785\n23 0.17238666\n\n\nWe can see that we have many significant digits being returned. Let’s round this new column to 2 significant digits by applying the round() function\n\nTidyData <- TidyData |> mutate(TcellsRounded = round(Tcells_ProportionCD45, 2))\nTidyData \n\n specimen Date timepoint condition Tcells_count CD45_count\n1 INF0052 2025-07-26 0 Ctrl 164771 915203\n2 INF0100 2025-07-26 0 Ctrl 208241 1438047\n3 INF0179 2025-07-26 0 Ctrl 291777 940733\n4 INF0134 2025-07-29 0 Ctrl 127866 689676\n5 INF0148 2025-07-29 0 Ctrl 234335 1013985\n6 INF0191 2025-07-29 0 Ctrl 55780 715443\n7 INF0124 2025-07-31 0 Ctrl 70297 687720\n8 INF0149 2025-07-31 0 Ctrl 107900 857845\n9 INF0169 2025-07-31 0 Ctrl 75540 854594\n10 INF0019 2025-08-05 0 Ctrl 208055 873622\n11 INF0032 2025-08-05 0 Ctrl 361034 753064\n12 INF0180 2025-08-05 0 Ctrl 284958 1049663\n13 INF0155 2025-08-07 0 Ctrl 281626 1065048\n14 INF0158 2025-08-07 0 Ctrl 280913 1249338\n15 INF0159 2025-08-07 0 Ctrl 452551 1190219\n16 INF0013 2025-08-22 0 Ctrl 182751 836573\n17 INF0023 2025-08-22 0 Ctrl 218435 968035\n18 INF0030 2025-08-22 0 Ctrl 85521 732321\n19 INF0166 2025-08-28 0 Ctrl 225650 739495\n20 INF0199 2025-08-28 0 Ctrl 169736 1112176\n21 INF0207 2025-08-28 0 Ctrl 39055 905365\n22 INF0614 2025-08-30 0 Ctrl 224396 1569007\n23 INF0622 2025-08-30 0 Ctrl 161924 939307\n Tcells_ProportionCD45 TcellsRounded\n1 0.18003765 0.18\n2 0.14480820 0.14\n3 0.31015921 0.31\n4 0.18540010 0.19\n5 0.23110302 0.23\n6 0.07796568 0.08\n7 0.10221747 0.10\n8 0.12578030 0.13\n9 0.08839285 0.09\n10 0.23815220 0.24\n11 0.47942008 0.48\n12 0.27147570 0.27\n13 0.26442564 0.26\n14 0.22484948 0.22\n15 0.38022498 0.38\n16 0.21845195 0.22\n17 0.22564783 0.23\n18 0.11678076 0.12\n19 0.30514067 0.31\n20 0.15261613 0.15\n21 0.04313730 0.04\n22 0.14301785 0.14\n23 0.17238666 0.17", + "objectID": "course/03_InsideFCSFile/index.html#flowcore-parameters", + "href": "course/03_InsideFCSFile/index.html#flowcore-parameters", + "title": "03 - Inside an FCS File", + "section": "flowCore Parameters", + "text": "flowCore Parameters\nDepending on the arguments selected during read.FCS(), we might also encounter additional keywords that are added in by flowCore. For example, we do not see these keywords when “transformation” is set to FALSE.\n\nflowCoreCheck <- read.FCS(filename=firstfile,\n transformation = FALSE, truncate_max_range = FALSE)\n\nflowCoreCheck\n\nflowFrame object 'CellCounts4L_AB_05-ND050-05.fcs'\nwith 100 cells and 61 observables:\n name desc range minRange maxRange\n$P1 Time NA 272140 0 272139\n$P2 UV1-A NA 4194304 -111 4194303\n$P3 UV2-A NA 4194304 -111 4194303\n$P4 UV3-A NA 4194304 -111 4194303\n$P5 UV4-A NA 4194304 -111 4194303\n... ... ... ... ... ...\n$P57 R4-A NA 4194304 -111 4194303\n$P58 R5-A NA 4194304 -111 4194303\n$P59 R6-A NA 4194304 -111 4194303\n$P60 R7-A NA 4194304 -111 4194303\n$P61 R8-A NA 4194304 -111 4194303\n476 keywords are stored in the 'description' slot\n\n\n\nNoChange <- keyword(flowCoreCheck)\nDetectors <- NoChange [476:500]\nDetectors\n\n$`WINDOW EXTENSION`\n[1] \"3\"\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n\nBy contrast, if we had set “transformation” to TRUE:\n\nflowCoreCheck <- read.FCS(filename=firstfile,\n transformation = TRUE, truncate_max_range = FALSE)\n\nflowCoreCheck\n\nflowFrame object 'CellCounts4L_AB_05-ND050-05.fcs'\nwith 100 cells and 61 observables:\n name desc range minRange maxRange\n$P1 Time NA 272140 0 272139\n$P2 UV1-A NA 4194304 -111 4194303\n$P3 UV2-A NA 4194304 -111 4194303\n$P4 UV3-A NA 4194304 -111 4194303\n$P5 UV4-A NA 4194304 -111 4194303\n... ... ... ... ... ...\n$P57 R4-A NA 4194304 -111 4194303\n$P58 R5-A NA 4194304 -111 4194303\n$P59 R6-A NA 4194304 -111 4194303\n$P60 R7-A NA 4194304 -111 4194303\n$P61 R8-A NA 4194304 -111 4194303\n599 keywords are stored in the 'description' slot\n\n\n\nYesChange <- keyword(flowCoreCheck)\nDetectors <- YesChange [476:500]\nDetectors\n\n$`WINDOW EXTENSION`\n[1] \"3\"\n\n$transformation\n[1] \"applied\"\n\n$`flowCore_$P1Rmax`\n[1] \"272140\"\n\n$`flowCore_$P1Rmin`\n[1] \"0\"\n\n$`flowCore_$P2Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P2Rmin`\n[1] \"-111\"\n\n$`flowCore_$P3Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P3Rmin`\n[1] \"-111\"\n\n$`flowCore_$P4Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P4Rmin`\n[1] \"-111\"\n\n$`flowCore_$P5Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P5Rmin`\n[1] \"-111\"\n\n$`flowCore_$P6Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P6Rmin`\n[1] \"-111\"\n\n$`flowCore_$P7Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P7Rmin`\n[1] \"-111\"\n\n$`flowCore_$P8Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P8Rmin`\n[1] \"-26.3464946746826\"\n\n$`flowCore_$P9Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P9Rmin`\n[1] \"-111\"\n\n$`flowCore_$P10Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P10Rmin`\n[1] \"0\"\n\n$`flowCore_$P11Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P11Rmin`\n[1] \"-111\"\n\n$`flowCore_$P12Rmax`\n[1] \"4194304\"\n\n\n\n\nFor some flow cytometry R packages, you will notice when opening their exported .fcs outputs in commercial software that these flowCore keywords have ended up integrated. It is likely somewhere in the package code the author forgot to add set transformation to FALSE, which is why we are seeing these flowCore keywords after the fact.", "crumbs": [ "About", "Intro to R", - "04 - Intro to Tidyverse" + "03 - Inside a .FCS file" ] }, { - "objectID": "course/04_IntroToTidyverse/index.html#arrange", - "href": "course/04_IntroToTidyverse/index.html#arrange", - "title": "04 - Introduction to Tidyverse", - "section": "arrange", - "text": "arrange\nAnd while we are here, let’s rearrange the rows so that they are descending based on the Tcell proportion. We can use this by using the desc() and arrange() functions from dplyr:\n\nTidyData <- TidyData |> arrange(desc(TcellsRounded))\n\nAnd let’s go ahead and filter() and identify the specimens that had more than 30% T cells as part of the overall CD45 gate (context, these samples were Cord Blood):\n\nTidyData |> filter(TcellsRounded > 0.3)\n\n specimen Date timepoint condition Tcells_count CD45_count\n1 INF0032 2025-08-05 0 Ctrl 361034 753064\n2 INF0159 2025-08-07 0 Ctrl 452551 1190219\n3 INF0179 2025-07-26 0 Ctrl 291777 940733\n4 INF0166 2025-08-28 0 Ctrl 225650 739495\n Tcells_ProportionCD45 TcellsRounded\n1 0.4794201 0.48\n2 0.3802250 0.38\n3 0.3101592 0.31\n4 0.3051407 0.31\n\n\nWhich is we had wanted to just retrieve the specimen IDs, we could add pull() after a new pipe argument.\n\nTidyData |> filter(TcellsRounded > 0.3) |> pull(specimen)\n\n[1] \"INF0032\" \"INF0159\" \"INF0179\" \"INF0166\"\n\n\nAnd finally, since I may want to send the data to a supervisor, let’s go ahead and export this “tidyed” version of our data.frame out to it’s own .csv file. Working within our project folder, this would look like this:\n\nNewName <- paste0(\"MyNewDataset\", \".csv\")\nStorageLocation <- file.path(\"data\", NewName)\nStorageLocation\n\n[1] \"data/MyNewDataset.csv\"\n\n\n\nwrite.csv(TidyData, StorageLocation, row.names=FALSE)", + "objectID": "course/02_FilePaths/index.html", + "href": "course/02_FilePaths/index.html", + "title": "02 - File Paths", + "section": "", + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here\nWelcome to the second week of Cytometry in R! This week we will learn about file.path, namely, how to communicate to our computer (and R) where various files are stored.", "crumbs": [ "About", "Intro to R", - "04 - Intro to Tidyverse" + "02 - File Paths" ] }, { - "objectID": "course/04_IntroToTidyverse/slides.html#read.csv", - "href": "course/04_IntroToTidyverse/slides.html#read.csv", - "title": "04 - Introduction to Tidyverse", - "section": "read.csv", - "text": "read.csv\n\n\n\n\n\n\n\n\n.\n\n\nWe will start by first loading in our copied over dataset (Dataset.csv) from it’s location in the project folder. If you are following the organization scheme we have been using throughout the course, your file path will look something like this:\n\n\n\n\n\n\n\n\n\n\nthefilepath <- file.path(\"data\", \"Dataset.csv\")\n\nthefilepath\n\n[1] \"data/Dataset.csv\"" - }, - { - "objectID": "course/04_IntroToTidyverse/slides.html#data.frame", - "href": "course/04_IntroToTidyverse/slides.html#data.frame", - "title": "04 - Introduction to Tidyverse", - "section": "data.frame", - "text": "data.frame\n\n\n\n\n\n\n\n\n.\n\n\nOr alternatively using the new-to-us glimpse() function\n\n\n\n\n\n\n\nglimpse(Data)\n\nError in `glimpse()`:\n! could not find function \"glimpse\"" + "objectID": "course/02_FilePaths/index.html#set-up", + "href": "course/02_FilePaths/index.html#set-up", + "title": "02 - File Paths", + "section": "Set Up", + "text": "Set Up\nBefore we begin, let’s make sure you get the data needed for today transferred to your local computer, and then get the .fcs files copied over from there to your own working project folder. This is the process you will repeat each week throughout the course.\n\nNew Repository\nFirst off, login to your GitHub account. Once there, you will select the options to create a new repository (similar to what you did during Using GitHub)\n\n\n\nFor this week, let’s set this new repository up as a private repository, and call it Week2. This will keep things consistent with the file.paths we will be showing in the examples.\n\n\n\nOnce the new repository has been created, copy the URL.\n\n\n\nNext, open up Positron, set the interpreter to use R, and then select the option to bring in a “New Folder from Git”.\n\n\n\nPaste in your new repository’s url. Additionally, if you want to match file.paths shown in the examples, set your storage location to your local Documents folder (please note the start of the file.path will look differently depending on whether you are on Windows, MacOS, or Linux).\n\n\n\nYour new repository will then be imported from GitHub. Once this is done, create two subfolders (data and images) and a new .qmd file (naming it filepaths.qmd).\n\n\n\n\n\nSync\nWith this done, return to GitHub and open your forked version of the CytometryInR course folder. If you haven’t yet done so, click on sync to bring in this week’s code and datasets.\n\n\n\nReturning to Positron, you will need to switch Project Folders, switching from Week2 over to CytometryInR.\n\n\n\n\n\nPull\nOnce CytometryInR project folder has opened, you will need to pull in the new data from GitHub to your local computer.\n\n\n\n\n\nCopy Files to Week2\nOnce this is done, you will see within the course folder, containing this weeks folder (02_FilePaths). Within it there is a data folder with .fcs files. To avoid causing conflicts when bringing in next week’s materials, you will want to manually copy over these .fcs files (via your File Explorer) to the data folder within your “Week2” Project Folder.\n\n\n\n\n\nCommit and Push\nWhen you reopen your Week2 project folder in Positron, you should now be able to see the .fcs files within the data folder. Next, from the action bar on the far left, select the Source Control tab. Stage all the changes (as was done in Using Git), and write a short commit message.\n\n\n\nWith these files now being tracked by version control, push (ie. send) your changes to GitHub so that they are remotely backed up.\n\n\n\nAnd with this setup complete, you are now ready to proceed. Remember, run code and write notes in your working project folder (Week2 or otherwise named) to avoid conflicts next week in the CytometryInR folder when you are trying to bring in the Week #3 code and datasets.", + "crumbs": [ + "About", + "Intro to R", + "02 - File Paths" + ] }, { - "objectID": "course/04_IntroToTidyverse/slides.html#column-value-type", - "href": "course/04_IntroToTidyverse/slides.html#column-value-type", - "title": "04 - Introduction to Tidyverse", - "section": "Column value type", - "text": "Column value type\n\n\n\n\n\n\n\n\n.\n\n\nAs we saw last week, functions often need values that match a certain type (the paintbrush needing paint analogy). As we inspect the columns of Data, we can notice some of the columns contain values within that are character (ie. “char”) values. Others appear to contain numeric values (which are subtyped as either double (“ie. dbl”) or integer (ie. “int”)). At first glance, we do not appear to have any logical (ie. TRUE or FALSE) columns in this dataset." + "objectID": "course/02_FilePaths/index.html#working-directory", + "href": "course/02_FilePaths/index.html#working-directory", + "title": "02 - File Paths", + "section": "Working Directory", + "text": "Working Directory\nNow that we are back in our Week2 folder, let’s start by seeing our current location similarly to how our computer perceives it.\nWe will use getwd() function (ie. get working directory) to return the location of the folder we are currently inside of. For example, when getwd() is run within my Week2 project folder, I see the following location\n\ngetwd()\n\n\nThis returns a file path. The final location (Week2 in this case) is the Working Directory. Your computer when working in R will be descern other locations in relation to this directory.", + "crumbs": [ + "About", + "Intro to R", + "02 - File Paths" + ] }, { - "objectID": "course/04_IntroToTidyverse/slides.html#select-columns", - "href": "course/04_IntroToTidyverse/slides.html#select-columns", - "title": "04 - Introduction to Tidyverse", - "section": "select (Columns)", - "text": "select (Columns)\n\n\n\n\n\n\n\n\n.\n\n\nNow that we have read in our data, and have a general picture of the structure and contents, lets start learning the main dplyr functions we will be using throughout the course. To do this, lets go ahead and attach dplyr to our local environment via the library() call.\n\n\n\n\n\n\n\nlibrary(dplyr)" - }, - { - "objectID": "course/04_IntroToTidyverse/slides.html#relocate", - "href": "course/04_IntroToTidyverse/slides.html#relocate", - "title": "04 - Introduction to Tidyverse", - "section": "relocate", - "text": "relocate\n\n\n\n\n\n\n\n\n.\n\n\nAlternatively, we occasionally want to move one column. While we could respecify the location using select(), specifying the names of all the other columns out in a line of code to just to rearrange one does not sound like a good use of time. For this reason, the second dplyr function we will be learning is the relocate() function." - }, - { - "objectID": "course/04_IntroToTidyverse/slides.html#rename", - "href": "course/04_IntroToTidyverse/slides.html#rename", - "title": "04 - Introduction to Tidyverse", - "section": "rename", - "text": "rename\n\n\n\n\n\n\n\n\n.\n\n\nAt this point, we are able to both move and select particular columns, allowing us to rearrange and subset a larger data.frame object however we want it to appear. However, as we encountered, some of the names contain special characters and spaces, requiring use of tick marks (``) to avoid issues. How can we change a column name?" - }, - { - "objectID": "course/04_IntroToTidyverse/slides.html#pull", - "href": "course/04_IntroToTidyverse/slides.html#pull", - "title": "04 - Introduction to Tidyverse", - "section": "pull", - "text": "pull\n\n\n\n\n\n\n\n\n.\n\n\nSometimes, we may want to retrieve individual values present in a column, to use within either a vector or a list. We can do this using the pull() function, which will retrieve the column contents and strip the column formatting\n\n\n\n\n\n\n\nData |> pull(Date) |> head(10)\n\n [1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [6] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"" - }, - { - "objectID": "course/04_IntroToTidyverse/slides.html#filter-rows", - "href": "course/04_IntroToTidyverse/slides.html#filter-rows", - "title": "04 - Introduction to Tidyverse", - "section": "filter (Rows)", - "text": "filter (Rows)\n\n\n\n\n\n\n\n\n.\n\n\nSo far, we have been working with dplyr functions primarily used when working with and subsetting columns (including select(), pull(), rename() and relocate()). What if we wanted to work with rows of a data.frame? This is where the filter() function is used." - }, - { - "objectID": "course/04_IntroToTidyverse/slides.html#mutate", - "href": "course/04_IntroToTidyverse/slides.html#mutate", - "title": "04 - Introduction to Tidyverse", - "section": "mutate", - "text": "mutate\n\n\n\n\n\n\n\n\n.\n\n\nAs we can see, with just these handful of functions, we have the building blocks to rearrange and subset a larger data.frame into a format that we prefer. But what if we wanted to alter the content of a column, or add new columns to an existing data.frame? This is where the mutate() function can be used." - }, - { - "objectID": "course/04_IntroToTidyverse/slides.html#arrange", - "href": "course/04_IntroToTidyverse/slides.html#arrange", - "title": "04 - Introduction to Tidyverse", - "section": "arrange", - "text": "arrange\n\n\n\n\n\n\n\n\n.\n\n\nAnd while we are here, let’s rearrange the rows so that they are descending based on the Tcell proportion. We can use this by using the desc() and arrange() functions from dplyr:\n\n\n\n\n\n\n\nTidyData <- TidyData |> arrange(desc(TcellsRounded))" - }, - { - "objectID": "course/03_InsideFCSFile/slides.html#getting-set-up", - "href": "course/03_InsideFCSFile/slides.html#getting-set-up", - "title": "03 - Inside an FCS File", - "section": "Getting Set Up", - "text": "Getting Set Up" - }, - { - "objectID": "course/03_InsideFCSFile/slides.html#flowcore", - "href": "course/03_InsideFCSFile/slides.html#flowcore", - "title": "03 - Inside an FCS File", - "section": "flowCore", - "text": "flowCore\n\n\n\n\n\n\n\n\n.\n\n\nWe will be using the flowCore package, which is the oldest and most-frequently downloaded flow cytometry package on Bioconductor." - }, - { - "objectID": "course/03_InsideFCSFile/slides.html#flowframe", - "href": "course/03_InsideFCSFile/slides.html#flowframe", - "title": "03 - Inside an FCS File", - "section": "flowFrame", - "text": "flowFrame\n\n\n\n\n\n\n\n\n.\n\n\nFor read.FCS(), it accepts several arguments. The argument “filename” is where we provide our file.path to .fcs file that we wish to load into R. Let’s go ahead and do so\n\n\n\n\n\n\n\nread.FCS(filename=firstfile)" - }, - { - "objectID": "course/03_InsideFCSFile/slides.html#early-metadata", - "href": "course/03_InsideFCSFile/slides.html#early-metadata", - "title": "03 - Inside an FCS File", - "section": "Early Metadata", - "text": "Early Metadata\n\n\n\n\n\n\n\n\n.\n\n\nWithin the initial portion, we are getting back metadata keywords related to where and how the particular file was acquired. Keywords of potential interest include:\n\n\n\n\n\n\n\n\n\n\n\n\n\nStart Time\n\n\nWhat time was the .fcs file acquired\n\n\n\n\n\n\n\nDescriptionList$`$BTIM`\n\n[1] \"13:55:29.85\"" - }, - { - "objectID": "course/03_InsideFCSFile/slides.html#detector-values", - "href": "course/03_InsideFCSFile/slides.html#detector-values", - "title": "03 - Inside an FCS File", - "section": "Detector Values", - "text": "Detector Values\n\n\n\n\n\n\n\n\n.\n\n\nThe next major stretch of keywords encode parameter values associated with the individual detectors for at the time of acquisition.\n\n\n\n\n\n\n\nDetectors <- DescriptionList[20:384]\nDetectors\n\n$`$P10B`\n[1] \"32\"\n\n$`$P10E`\n[1] \"0,0\"\n\n$`$P10N`\n[1] \"UV9-A\"\n\n$`$P10R`\n[1] \"4194304\"\n\n$`$P10TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P10V`\n[1] \"710\"\n\n$`$P11B`\n[1] \"32\"\n\n$`$P11E`\n[1] \"0,0\"\n\n$`$P11N`\n[1] \"UV10-A\"\n\n$`$P11R`\n[1] \"4194304\"\n\n$`$P11TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P11V`\n[1] \"377\"\n\n$`$P12B`\n[1] \"32\"\n\n$`$P12E`\n[1] \"0,0\"\n\n$`$P12N`\n[1] \"UV11-A\"\n\n$`$P12R`\n[1] \"4194304\"\n\n$`$P12TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P12V`\n[1] \"469\"\n\n$`$P13B`\n[1] \"32\"\n\n$`$P13E`\n[1] \"0,0\"\n\n$`$P13N`\n[1] \"UV12-A\"\n\n$`$P13R`\n[1] \"4194304\"\n\n$`$P13TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P13V`\n[1] \"434\"\n\n$`$P14B`\n[1] \"32\"\n\n$`$P14E`\n[1] \"0,0\"\n\n$`$P14N`\n[1] \"UV13-A\"\n\n$`$P14R`\n[1] \"4194304\"\n\n$`$P14TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P14V`\n[1] \"564\"\n\n$`$P15B`\n[1] \"32\"\n\n$`$P15E`\n[1] \"0,0\"\n\n$`$P15N`\n[1] \"UV14-A\"\n\n$`$P15R`\n[1] \"4194304\"\n\n$`$P15TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P15V`\n[1] \"975\"\n\n$`$P16B`\n[1] \"32\"\n\n$`$P16E`\n[1] \"0,0\"\n\n$`$P16N`\n[1] \"UV15-A\"\n\n$`$P16R`\n[1] \"4194304\"\n\n$`$P16TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P16V`\n[1] \"737\"\n\n$`$P17B`\n[1] \"32\"\n\n$`$P17E`\n[1] \"0,0\"\n\n$`$P17N`\n[1] \"UV16-A\"\n\n$`$P17R`\n[1] \"4194304\"\n\n$`$P17TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P17V`\n[1] \"1069\"\n\n$`$P18B`\n[1] \"32\"\n\n$`$P18E`\n[1] \"0,0\"\n\n$`$P18N`\n[1] \"SSC-H\"\n\n$`$P18R`\n[1] \"4194304\"\n\n$`$P18TYPE`\n[1] \"Side_Scatter\"\n\n$`$P18V`\n[1] \"334\"\n\n$`$P19B`\n[1] \"32\"\n\n$`$P19E`\n[1] \"0,0\"\n\n$`$P19N`\n[1] \"SSC-A\"\n\n$`$P19R`\n[1] \"4194304\"\n\n$`$P19TYPE`\n[1] \"Side_Scatter\"\n\n$`$P19V`\n[1] \"334\"\n\n$`$P1B`\n[1] \"32\"\n\n$`$P1E`\n[1] \"0,0\"\n\n$`$P1N`\n[1] \"Time\"\n\n$`$P1R`\n[1] \"272140\"\n\n$`$P1TYPE`\n[1] \"Time\"\n\n$`$P20B`\n[1] \"32\"\n\n$`$P20E`\n[1] \"0,0\"\n\n$`$P20N`\n[1] \"V1-A\"\n\n$`$P20R`\n[1] \"4194304\"\n\n$`$P20TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P20V`\n[1] \"352\"\n\n$`$P21B`\n[1] \"32\"\n\n$`$P21E`\n[1] \"0,0\"\n\n$`$P21N`\n[1] \"V2-A\"\n\n$`$P21R`\n[1] \"4194304\"\n\n$`$P21TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P21V`\n[1] \"412\"\n\n$`$P22B`\n[1] \"32\"\n\n$`$P22E`\n[1] \"0,0\"\n\n$`$P22N`\n[1] \"V3-A\"\n\n$`$P22R`\n[1] \"4194304\"\n\n$`$P22TYPE`\n[1] 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\"4194304\"\n\n$`$P5TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P5V`\n[1] \"1022\"\n\n$`$P60B`\n[1] \"32\"\n\n$`$P60E`\n[1] \"0,0\"\n\n$`$P60N`\n[1] \"R7-A\"\n\n$`$P60R`\n[1] \"4194304\"\n\n$`$P60TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P60V`\n[1] \"524\"\n\n$`$P61B`\n[1] \"32\"\n\n$`$P61E`\n[1] \"0,0\"\n\n$`$P61N`\n[1] \"R8-A\"\n\n$`$P61R`\n[1] \"4194304\"\n\n$`$P61TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P61V`\n[1] \"243\"\n\n$`$P6B`\n[1] \"32\"\n\n$`$P6E`\n[1] \"0,0\"\n\n$`$P6N`\n[1] \"UV5-A\"\n\n$`$P6R`\n[1] \"4194304\"\n\n$`$P6TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P6V`\n[1] \"616\"\n\n$`$P7B`\n[1] \"32\"\n\n$`$P7E`\n[1] \"0,0\"\n\n$`$P7N`\n[1] \"UV6-A\"\n\n$`$P7R`\n[1] \"4194304\"\n\n$`$P7TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P7V`\n[1] \"506\"\n\n$`$P8B`\n[1] \"32\"\n\n$`$P8E`\n[1] \"0,0\"\n\n$`$P8N`\n[1] \"UV7-A\"\n\n$`$P8R`\n[1] \"4194304\"\n\n$`$P8TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P8V`\n[1] \"661\"\n\n$`$P9B`\n[1] \"32\"\n\n$`$P9E`\n[1] \"0,0\"\n\n$`$P9N`\n[1] \"UV8-A\"\n\n$`$P9R`\n[1] \"4194304\"\n\n$`$P9TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P9V`\n[1] \"514\"" - }, - { - "objectID": "course/03_InsideFCSFile/slides.html#middle-metadata", - "href": "course/03_InsideFCSFile/slides.html#middle-metadata", - "title": "03 - Inside an FCS File", - "section": "Middle Metadata", - "text": "Middle Metadata\n\n\n\n\n\n\n\n\n.\n\n\nOnce we are out of the detector keywords, we find the last of the $Metadata associated keywords.\n\n\n\n\n\n\n\nDetectors <- DescriptionList[385:398]\nDetectors\n\n$`$PAR`\n[1] \"61\"\n\n$`$PROJ`\n[1] \"CellCounts4L_AB_05\"\n\n$`$SPILLOVER`\n UV1-A UV2-A UV3-A UV4-A UV5-A UV6-A UV7-A UV8-A UV9-A UV10-A UV11-A\n [1,] 1e+00 0 0 0 0 0 0 0 0 0 0\n [2,] 1e-06 1 0 0 0 0 0 0 0 0 0\n [3,] 0e+00 0 1 0 0 0 0 0 0 0 0\n [4,] 0e+00 0 0 1 0 0 0 0 0 0 0\n [5,] 0e+00 0 0 0 1 0 0 0 0 0 0\n [6,] 0e+00 0 0 0 0 1 0 0 0 0 0\n [7,] 0e+00 0 0 0 0 0 1 0 0 0 0\n [8,] 0e+00 0 0 0 0 0 0 1 0 0 0\n [9,] 0e+00 0 0 0 0 0 0 0 1 0 0\n[10,] 0e+00 0 0 0 0 0 0 0 0 1 0\n[11,] 0e+00 0 0 0 0 0 0 0 0 0 1\n[12,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[13,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[14,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[15,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[16,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[17,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[18,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[19,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[20,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[21,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[22,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[23,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[24,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[25,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[26,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[27,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[28,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[29,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[30,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[31,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[32,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[33,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[34,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[35,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[36,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[37,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[38,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[39,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[40,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[41,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[42,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[43,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[44,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[45,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[46,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[47,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[48,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[49,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[50,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[51,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[52,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[53,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[54,] 0e+00 0 0 0 0 0 0 0 0 0 0\n UV12-A UV13-A UV14-A UV15-A UV16-A V1-A V2-A V3-A V4-A V5-A V6-A V7-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 1 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 1 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 1 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 1 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 1 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 1 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 1 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 1 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 1 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 1 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 1 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 1\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0\n V8-A V9-A V10-A V11-A V12-A V13-A V14-A V15-A V16-A B1-A B2-A B3-A B4-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n B5-A B6-A B7-A B8-A B9-A B10-A B11-A B12-A B13-A B14-A R1-A R2-A R3-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n R4-A R5-A R6-A R7-A R8-A\n [1,] 0 0 0 0 0\n [2,] 0 0 0 0 0\n [3,] 0 0 0 0 0\n [4,] 0 0 0 0 0\n [5,] 0 0 0 0 0\n [6,] 0 0 0 0 0\n [7,] 0 0 0 0 0\n [8,] 0 0 0 0 0\n [9,] 0 0 0 0 0\n[10,] 0 0 0 0 0\n[11,] 0 0 0 0 0\n[12,] 0 0 0 0 0\n[13,] 0 0 0 0 0\n[14,] 0 0 0 0 0\n[15,] 0 0 0 0 0\n[16,] 0 0 0 0 0\n[17,] 0 0 0 0 0\n[18,] 0 0 0 0 0\n[19,] 0 0 0 0 0\n[20,] 0 0 0 0 0\n[21,] 0 0 0 0 0\n[22,] 0 0 0 0 0\n[23,] 0 0 0 0 0\n[24,] 0 0 0 0 0\n[25,] 0 0 0 0 0\n[26,] 0 0 0 0 0\n[27,] 0 0 0 0 0\n[28,] 0 0 0 0 0\n[29,] 0 0 0 0 0\n[30,] 0 0 0 0 0\n[31,] 0 0 0 0 0\n[32,] 0 0 0 0 0\n[33,] 0 0 0 0 0\n[34,] 0 0 0 0 0\n[35,] 0 0 0 0 0\n[36,] 0 0 0 0 0\n[37,] 0 0 0 0 0\n[38,] 0 0 0 0 0\n[39,] 0 0 0 0 0\n[40,] 0 0 0 0 0\n[41,] 0 0 0 0 0\n[42,] 0 0 0 0 0\n[43,] 0 0 0 0 0\n[44,] 0 0 0 0 0\n[45,] 0 0 0 0 0\n[46,] 0 0 0 0 0\n[47,] 0 0 0 0 0\n[48,] 0 0 0 0 0\n[49,] 0 0 0 0 0\n[50,] 1 0 0 0 0\n[51,] 0 1 0 0 0\n[52,] 0 0 1 0 0\n[53,] 0 0 0 1 0\n[54,] 0 0 0 0 1\n\n$`$TIMESTEP`\n[1] \"0.0001\"\n\n$`$TOT`\n[1] \"100\"\n\n$`$VOL`\n[1] \"30.31\"\n\n$`APPLY COMPENSATION`\n[1] \"FALSE\"\n\n$CHARSET\n[1] \"utf-8\"\n\n$CREATOR\n[1] \"SpectroFlo 3.3.0\"\n\n$FCSversion\n[1] \"3\"\n\n$FILENAME\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n$`FSC ASF`\n[1] \"1.21\"\n\n$GROUPNAME\n[1] \"ND050\"\n\n$GUID\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"" - }, - { - "objectID": "course/03_InsideFCSFile/slides.html#laser-metadata", - "href": "course/03_InsideFCSFile/slides.html#laser-metadata", - "title": "03 - Inside an FCS File", - "section": "Laser Metadata", - "text": "Laser Metadata\n\n\n\n\n\n\n\n\n.\n\n\nNext up, there is a small stretch of keywords containing the values associated with the individual lasers as far as delays and area scaling factors for a particular day (also useful when plotted).\n\n\n\n\n\n\n\nDetectors <- DescriptionList[399:410]\nDetectors\n\n$LASER1ASF\n[1] \"1.09\"\n\n$LASER1DELAY\n[1] \"-19.525\"\n\n$LASER1NAME\n[1] \"Violet\"\n\n$LASER2ASF\n[1] \"1.14\"\n\n$LASER2DELAY\n[1] \"0\"\n\n$LASER2NAME\n[1] \"Blue\"\n\n$LASER3ASF\n[1] \"1.02\"\n\n$LASER3DELAY\n[1] \"20.15\"\n\n$LASER3NAME\n[1] \"Red\"\n\n$LASER4ASF\n[1] \"0.92\"\n\n$LASER4DELAY\n[1] \"40.725\"\n\n$LASER4NAME\n[1] \"UV\"" - }, - { - "objectID": "course/03_InsideFCSFile/slides.html#display", - "href": "course/03_InsideFCSFile/slides.html#display", - "title": "03 - Inside an FCS File", - "section": "Display", - "text": "Display\n\n\n\n\n\n\n\n\n.\n\n\nThen there is a stretch matching whether a particular detector needs to be displayed as linear (in the case of time and scatter) or as log (for individual detectors).\n\n\n\n\n\n\n\nDetectors <- DescriptionList[412:472]\nDetectors\n\n$P10DISPLAY\n[1] \"LOG\"\n\n$P11DISPLAY\n[1] \"LOG\"\n\n$P12DISPLAY\n[1] \"LOG\"\n\n$P13DISPLAY\n[1] \"LOG\"\n\n$P14DISPLAY\n[1] \"LOG\"\n\n$P15DISPLAY\n[1] \"LOG\"\n\n$P16DISPLAY\n[1] \"LOG\"\n\n$P17DISPLAY\n[1] \"LOG\"\n\n$P18DISPLAY\n[1] \"LIN\"\n\n$P19DISPLAY\n[1] \"LIN\"\n\n$P1DISPLAY\n[1] \"LOG\"\n\n$P20DISPLAY\n[1] \"LOG\"\n\n$P21DISPLAY\n[1] \"LOG\"\n\n$P22DISPLAY\n[1] \"LOG\"\n\n$P23DISPLAY\n[1] \"LOG\"\n\n$P24DISPLAY\n[1] \"LOG\"\n\n$P25DISPLAY\n[1] \"LOG\"\n\n$P26DISPLAY\n[1] \"LOG\"\n\n$P27DISPLAY\n[1] \"LOG\"\n\n$P28DISPLAY\n[1] \"LOG\"\n\n$P29DISPLAY\n[1] \"LOG\"\n\n$P2DISPLAY\n[1] \"LOG\"\n\n$P30DISPLAY\n[1] \"LOG\"\n\n$P31DISPLAY\n[1] \"LOG\"\n\n$P32DISPLAY\n[1] \"LOG\"\n\n$P33DISPLAY\n[1] \"LOG\"\n\n$P34DISPLAY\n[1] \"LOG\"\n\n$P35DISPLAY\n[1] \"LOG\"\n\n$P36DISPLAY\n[1] \"LIN\"\n\n$P37DISPLAY\n[1] \"LIN\"\n\n$P38DISPLAY\n[1] \"LIN\"\n\n$P39DISPLAY\n[1] \"LIN\"\n\n$P3DISPLAY\n[1] \"LOG\"\n\n$P40DISPLAY\n[1] \"LOG\"\n\n$P41DISPLAY\n[1] \"LOG\"\n\n$P42DISPLAY\n[1] \"LOG\"\n\n$P43DISPLAY\n[1] \"LOG\"\n\n$P44DISPLAY\n[1] \"LOG\"\n\n$P45DISPLAY\n[1] \"LOG\"\n\n$P46DISPLAY\n[1] \"LOG\"\n\n$P47DISPLAY\n[1] \"LOG\"\n\n$P48DISPLAY\n[1] \"LOG\"\n\n$P49DISPLAY\n[1] \"LOG\"\n\n$P4DISPLAY\n[1] \"LOG\"\n\n$P50DISPLAY\n[1] \"LOG\"\n\n$P51DISPLAY\n[1] \"LOG\"\n\n$P52DISPLAY\n[1] \"LOG\"\n\n$P53DISPLAY\n[1] \"LOG\"\n\n$P54DISPLAY\n[1] \"LOG\"\n\n$P55DISPLAY\n[1] \"LOG\"\n\n$P56DISPLAY\n[1] \"LOG\"\n\n$P57DISPLAY\n[1] \"LOG\"\n\n$P58DISPLAY\n[1] \"LOG\"\n\n$P59DISPLAY\n[1] \"LOG\"\n\n$P5DISPLAY\n[1] \"LOG\"\n\n$P60DISPLAY\n[1] \"LOG\"\n\n$P61DISPLAY\n[1] \"LOG\"\n\n$P6DISPLAY\n[1] \"LOG\"\n\n$P7DISPLAY\n[1] \"LOG\"\n\n$P8DISPLAY\n[1] \"LOG\"\n\n$P9DISPLAY\n[1] \"LOG\"" - }, - { - "objectID": "course/03_InsideFCSFile/slides.html#flowcore-parameters", - "href": "course/03_InsideFCSFile/slides.html#flowcore-parameters", - "title": "03 - Inside an FCS File", - "section": "flowCore Parameters", - "text": "flowCore Parameters\n\n\n\n\n\n\n\n\n.\n\n\nDepending on the arguments selected during read.FCS(), we might also encounter additional keywords that are added in by flowCore. For example, we do not see these keywords when “transformation” is set to FALSE.\n\n\n\n\n\n\n\nflowCoreCheck <- read.FCS(filename=firstfile,\n transformation = FALSE, truncate_max_range = FALSE)\n\nflowCoreCheck\n\nflowFrame object 'CellCounts4L_AB_05-ND050-05.fcs'\nwith 100 cells and 61 observables:\n name desc range minRange maxRange\n$P1 Time NA 272140 0 272139\n$P2 UV1-A NA 4194304 -111 4194303\n$P3 UV2-A NA 4194304 -111 4194303\n$P4 UV3-A NA 4194304 -111 4194303\n$P5 UV4-A NA 4194304 -111 4194303\n... ... ... ... ... ...\n$P57 R4-A NA 4194304 -111 4194303\n$P58 R5-A NA 4194304 -111 4194303\n$P59 R6-A NA 4194304 -111 4194303\n$P60 R7-A NA 4194304 -111 4194303\n$P61 R8-A NA 4194304 -111 4194303\n476 keywords are stored in the 'description' slot" - }, - { - "objectID": "course/02_FilePaths/Downsampler.html", - "href": "course/02_FilePaths/Downsampler.html", - "title": "Downsampling", - "section": "", - "text": "Due to trying to keep the overall file size down, I am downsampling to 100 events. For anyone interested in how I did this, this Quarto Markdown Document contains the code needed to repeat the process." - }, - { - "objectID": "course/02_FilePaths/Downsampler.html#specify-file.path-and-identify-files", - "href": "course/02_FilePaths/Downsampler.html#specify-file.path-and-identify-files", - "title": "Downsampling", - "section": "Specify file.path and identify files", - "text": "Specify file.path and identify files\nDue to the counts being conducter on two separate instruments, the number of columns differs, so they will need to be loaded into separate GatingSet objects.\n\nStorageLocation <- file.path(\"course\", \"02_FilePaths\", \"data\")\nExisting <- list.files(StorageLocation, pattern=\".fcs\", full.names=TRUE)\nList1 <- Existing[1:2] # 3L Aurora\nList2 <- Existing[3:8] # 4L Aurora" + "objectID": "course/02_FilePaths/index.html#directories", + "href": "course/02_FilePaths/index.html#directories", + "title": "02 - File Paths", + "section": "Directories", + "text": "Directories\nWithin this working directory, we have a variety of project folders and files related to the course. We can see the folders that are present using the list.dirs() function.\n\nlist.dirs(path=\".\", full.names=FALSE, recursive=FALSE)\n\n\nWithin this list.dirs() function, we are specifying two arguments with which we will be working with later today, full.names and recursive. For now, lets set their arguments to FALSE, which means they conditions they implement are inactive (turned off).\n\n\nThe path argument is currently set to “.”, which is a stand-in for the present directory. In R, if an argument is not specified directly, it is inferred based on an order of expected arguments. Thus, if not present, we could still get the same output as seen before.\n\nlist.dirs(full.names=FALSE, recursive=FALSE)\n\n\n\n\nWithin Positron, in addition to visible folders, we also have hidden folders (denoted by the “.” in front of the folder name when using list.dirs()). In the case of one of our course website folders, we can see a “.quarto” folder shown in a lighter gray . The “.git” folder we saw from list.dirs() is typically hidden when viewing from Positron.\n\nIn the case of Week2, the two not-hidden folders we created are listed. We will see how to navigate these in a second.", + "crumbs": [ + "About", + "Intro to R", + "02 - File Paths" + ] }, { - "objectID": "course/02_FilePaths/Downsampler.html#load-.fcs-files-into-a-gatingset", - "href": "course/02_FilePaths/Downsampler.html#load-.fcs-files-into-a-gatingset", - "title": "Downsampling", - "section": "Load .fcs files into a GatingSet", - "text": "Load .fcs files into a GatingSet\nLoad in files to their respective GatingSet objects\n\ncs1 <- load_cytoset_from_fcs(List1, truncate_max_range = FALSE, transformation = FALSE)\ngs1 <- GatingSet(cs1)\n\ncs2 <- load_cytoset_from_fcs(List2, truncate_max_range = FALSE, transformation = FALSE)\ngs2 <- GatingSet(cs2)" + "objectID": "course/02_FilePaths/index.html#variables", + "href": "course/02_FilePaths/index.html#variables", + "title": "02 - File Paths", + "section": "Variables", + "text": "Variables\nBefore exploring file paths, we need to have some basic R code knowledge that we can use to work with them. Within R, we have the ability to assign particular values (be they character strings, numbers or logicals) to objects (ie. variables) that can be used when called upon later.\nFor example:\n\nWhatDayDidIWriteThis <- \"Saturday\"\n\nIn this case, the variable name is what the assignment arrow (“<-”) is pointing at. In this case, WhatDayDidIWriteThis\n\n\nWhen we run this, we create a variable, that will appear within the right-sidebar.\n\nWhatDayDidIWriteThis <- \"Saturday\"\n\n\n\n\nThese variables can subsequently be retrieved by printing (ie. running) the name of the variable\n\nWhatDayDidIWriteThis \n\n[1] \"Saturday\"\n\n\n\n\nYou can create variables with almost any name you can think of\n\nTopSecretMeetingDay <- \"Saturday\"\n\n\n\nWith a few exceptions. R doesn’t play well with spaces:\n\nTop Secret Meeting Day <- \"Saturday\"\n\nError in parse(text = input): <text>:1:5: unexpected symbol\n1: Top Secret\n ^\n\n\n\n\nBut does play well with underscores:\n\nTop_Secret_Meeting_Day <- \"Saturday\"\n\n\n\nThe above (with individual words separated by _) is collectively known as snake case. The alternate way to help delineate variable names is “camelCase”, with first letter of each word being capitalized (seen in the previous example).\n\n\n\n\nTopSecretMeetingDay\n\n[1] \"Saturday\"\n\n\n\n\nYou can overwrite a Variable name by assigning a different value to it:\n\nTopSecretMeetingDay <- \"Monday\"\n\n\nTopSecretMeetingDay\n\n[1] \"Monday\"\n\n\n\n\nYou can also remove individual variables via the rm function\n\nrm(Top_Secret_Meeting_Day)\n\n\n\nOr if trying to remove all, via the right sidebar\n\n\n\nIn the prior case, we are creating a variable that is a “string” of character values, due to our use of “” around the word. We can see this when we use the str() function.\n\nFluorophores <- \"FITC\"\nstr(Fluorophores)\n\n chr \"FITC\"\n\n\nThe “chr” in front denotating that Fluorophores contains a character string.\n\n\nThis could also be retrieved using the class() function.\n\nclass(Fluorophores)\n\n[1] \"character\"\n\n\n\n\nAlternatively, we could assign a numeric value to a variable\n\nFluorophores <- 29\nstr(Fluorophores)\n\n num 29\n\n\nWhich returns “num”, ie. numeric.\n\n\nWe can also specify a logical (ie. True or FALSE) to a particular object\n\nIsPerCPCy5AGoodFluorophore <- FALSE\nstr(IsPerCPCy5AGoodFluorophore)\n\n logi FALSE\n\n\nWhich returns logi in front, denoting this variable contains a logical value.\n\n\nLast week, when we were installing dplyr, the reason that installation failed was install.packages() expects a character string. However, when we left off the ““, it looked within our local environments created variables for the dplyr variable, couldn’t find it, and thus failed.\nWe could of course, have assigned a character value to a variable name, and then used that variable name, which would have worked.\n\nPackageToInstall <- \"dplyr\"\n\ninstall.packages(PackageToInstall)", + "crumbs": [ + "About", + "Intro to R", + "02 - File Paths" + ] }, { - "objectID": "course/01_InstallingRPackages/index.html", - "href": "course/01_InstallingRPackages/index.html", - "title": "01 - Installing R Packages", - "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here\nWelcome to the first week of Cytometry in R! This week we will be diving into how R packages work, and the how to go about installing them.\nBefore getting started, please make sure you have completed the creating a GitHub and Workstation Setup walk-throughs, since we will begin where they left off once the required software was successfully installed.", + "objectID": "course/02_FilePaths/index.html#indexing", + "href": "course/02_FilePaths/index.html#indexing", + "title": "02 - File Paths", + "section": "Indexing", + "text": "Indexing\nNot all variables contain single objects.\nFor example, we can modify Fluorophores and add additional entries:\n\nFluorophores <- c(\"BV421\", \"FITC\", \"PE\", \"APC\")\nstr(Fluorophores)\n\n chr [1:4] \"BV421\" \"FITC\" \"PE\" \"APC\"\n\n\nThe c stands for concatenate. It concatenates the objects into a larger object, known as a vector.\nIn this case, you notice in addition to the specification the values are characters, we get a [1:4], denoting four objects are present.\n\n\nWe can similarly retrieve this information using the length() function\n\nlength(Fluorophores)\n\n[1] 4\n\n\n\n\nWhen multiple objects are present, we can specify them individidually by providing their index number within square brackets [].\n\nFluorophores[1]\n\n[1] \"BV421\"\n\n\n\n\n\nFluorophores[3]\n\n[1] \"PE\"\n\n\n\n\nOr specify in sequence using a colon (:)\n\nFluorophores[3:4]\n\n[1] \"PE\" \"APC\"\n\n\n\n\nOr if not adjacent, reusing c within the square brackets\n\nFluorophores[c(1,4)]\n\n[1] \"BV421\" \"APC\" \n\n\n\n\nWe will revisit these concepts throughout the course, with what we have covered today, this will help us create file.paths and select fcs files that we want to work with via index number.", "crumbs": [ "About", - "Intro to R" + "Intro to R", + "02 - File Paths" ] }, { - "objectID": "course/01_InstallingRPackages/index.html#set-up", - "href": "course/01_InstallingRPackages/index.html#set-up", - "title": "01 - Installing R Packages", - "section": "Set Up", - "text": "Set Up\nAlright, with the background out of the way, let’s get started!\n\n\n\n\n\n\nImportant\n\n\n\nPlease make sure to sync your forked version of the CytometryInR repository, and pull any changes to your local computer’s CytometryInR project folder so that you have the most recent version of the code and data available.\n\n\n\n\n\n\n\n\nWarning\n\n\n\nPlease remember to always copy over the new material from your local CytometryInR folder to a separate Project Folder that you created and named (ex. “Week_01” or “MyLearningFolder”, etc.). This will ensure any edits you make to the files do not affect your ability to bring in next week’s materials to the CytometryInR folder\n\n\n\n\nAfter pulling the new data and code locally, open CytometryInR, open the course folder, and open the 01_InstallingRPackages folder. From here, copy the index.qmd file to your own working Project Folder (ex. Week_01) where you can work on it without causing any conflicts. Then return to Positron and open up your working project folder (ex. Week_01).\n\n\n\nNext up, within Positron, let’s make sure to select R as the coding language being used for this session.\n\n\n\nNow that R is running within Positron, the console (lower portion of the screenn) is now able to run (ie. execute) any R code that is sent to it.", + "objectID": "course/02_FilePaths/index.html#listing-files", + "href": "course/02_FilePaths/index.html#listing-files", + "title": "02 - File Paths", + "section": "Listing Files", + "text": "Listing Files\nAfter this detour into variables and indexing, let’s return our focus to how to use these in context of file paths. Working from within our Week2 project folder, let’s see what directories (folders) are present\n\nlist.dirs(path=\".\", full.names=FALSE, recursive=FALSE)\n\n\n\n\nWe can also list any files that are present within our working directory using the list.files() function.\n\nlist.files()\n\n\nIn this case, in addition to our filepaths.qmd file, we can see the LICENSE and README files created when we set up the repository.\n\n\nWe can also specify a particular folder we want to show items present within by changing the path argument. For example, if we wanted to see the contents of the “data” folder\n\nlist.files(path=\"data\", full.names=FALSE, recursive=FALSE)\n\n\nWhich in this case returns the fcs files we copied over at the start of this lesson.\n\n\nIn this case, there are no folders under “data”. Let’s go ahead and create a new one, calling it target.", "crumbs": [ "About", - "Intro to R" + "Intro to R", + "02 - File Paths" ] }, { - "objectID": "course/01_InstallingRPackages/index.html#checking-for-loaded-packages", - "href": "course/01_InstallingRPackages/index.html#checking-for-loaded-packages", - "title": "01 - Installing R Packages", - "section": "Checking for Loaded Packages", - "text": "Checking for Loaded Packages\nFor the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active.\n\n\n\nAccessing Help Documentation\nWithin your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following sessionInfo() function:\n\nsessionInfo()\n\n\n\nIf you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over.\n\n\n\nIn this case, we can see the help documentation corresponding for sessionInfo(). Beyond hovering over the function, this can also be accessed by adding a ? directly in front of the function, and then running that line of code.\n\n?sessionInfo()\n\n\n\n\nWhen executed, the function’s help file documentation will open up within the Help tab in the secondary side bar on the right-side of the screen. Glancing at the top of the page we can see the name of the package that contains the sessionInfo() function ({utils}). Scrolling down the help page past all the documentation, we can see a link to the index page.\n\n\n\nAfter clicking, the Help tab switches from viewing the documentation for the sessionInfo() function, to showing all the functions within the utils package. Most R packages contain help documentation, so this process can be adapted to find out additional information about what a function does, and what arguments are needed to produce customized outputs.\n\n\n\n\n\nsessionInfo()\nWithin your .qmd file, let’s go ahead and run the following code-block:\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] BiocStyle_2.38.0\n\nloaded via a namespace (and not attached):\n [1] htmlwidgets_1.6.4 BiocManager_1.30.27 compiler_4.5.2 \n [4] fastmap_1.2.0 cli_3.6.5 tools_4.5.2 \n [7] htmltools_0.5.9 otel_0.2.0 yaml_2.3.12 \n[10] rmarkdown_2.30 knitr_1.51 jsonlite_2.0.0 \n[13] xfun_0.56 digest_0.6.39 rlang_1.1.7 \n[16] evaluate_1.0.5 \n\n\n\n\nThe outputs that get returned by sessionInfo() will vary a bit depending on your computer’s operating system, and the version of R you have installed.\nFor today, let’s focus on the last two elements of the output:\n\n\n\nThe R software itself is made up of several base R packages, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages.\nAs we install additional R packages and load them using the library() function throughout this session, sporadically re-run sessionInfo() to see how this list of R packages changes.", + "objectID": "course/02_FilePaths/index.html#creating-directories", + "href": "course/02_FilePaths/index.html#creating-directories", + "title": "02 - File Paths", + "section": "Creating directories", + "text": "Creating directories\nAlternatively, we can also create a folder via R using the dir.create() function. Since we want it within data, we would modify the path accordingly\n\nNewFolderLocation <- file.path(\"data\", \"target2\")\n\ndir.create(path=NewFolderLocation)\n\n\n\n\nBefore continuing, let’s copy the first two .fcs files into both target and target2.\n\n\n\nGiven our working directory is set the top-level of the Week2 project folder, we can’t just check inside nested target folders directly. If we attempt to:\n\nlist.files(path=\"target\", full.names=FALSE, recursive=FALSE)\n\ncharacter(0)\n\n\n\n\nNo files are returned (ie, character(0)), since from our computers perspective, “target” doesn’t exist within the active working directory.\n\nfile.exists(\"target\")\n\n[1] FALSE\n\n\n\n\nOn the other hand, within it’s view, it knows that the data folder exist\n\nfile.exists(\"data\")\n\n\nSo here we encounter the first challenge when communicating to our computer where to search for and find files. We need to provide a file.path that incorporates the path of folders between where the computer is currently at (ie. the working directory) and the target file itself.", "crumbs": [ "About", - "Intro to R" + "Intro to R", + "02 - File Paths" ] }, { - "objectID": "course/01_InstallingRPackages/index.html#installing-from-cran", - "href": "course/01_InstallingRPackages/index.html#installing-from-cran", - "title": "01 - Installing R Packages", - "section": "Installing from CRAN", - "text": "Installing from CRAN\nWe will start by installing R packages that are part of the CRAN repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository.\nThese include the tidyverse packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today.\n\n\n\ndplyr\nOur first R package we will install during this session is the dplyr package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function install.packages().\n\n?install.packages()\n\n\n\n\nFor the install.packages() function, we place within the () the name of the R package from CRAN that we wish to install.\n\ninstall.packages(\"dplyr\")\n\n\n\n\n\n\n\n\n\nTip\n\n\n\nA usual struggle point for beginners is that install.packages() requires ” ” to be placed around the package name. Forgetting them results in the error that we see below.\n\n\n\ninstall.packages(dplyr)\n\nError:\n! object 'dplyr' not found\n\n\n\n\n\ninstall.packages(\"dplyr\")\n\nGo ahead and click on “Run Cell” next to your code-block, to install the dplyr R package.\n\n\nWhen a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system).\n\n\n\nWithin this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN.\nIf the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder.\n\n\n\nThe final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the “Done” line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder).\n\n\n\n\nAttaching packages via library()\nIf an R package has been installed successfully, we are now able to load it (ie. make it’s functions available) to our local environment using the library() function.\n\n?library()\n\n\n\nUnlike install.packages(), where we needed “” around the package name, the library() function does not require “” around the package name. Let’s go ahead and load in dplyr, making its respective functions to our local environment.\n\nlibrary(dplyr)\n\n\nAttaching package: 'dplyr'\n\n\nThe following objects are masked from 'package:stats':\n\n filter, lag\n\n\nThe following objects are masked from 'package:base':\n\n intersect, setdiff, setequal, union\n\n\n\n\nFrom the output, we can see that dplyr has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages.\nWith dplyr now loaded via the library() call, let’s check sessionInfo() to see what has changed.\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] dplyr_1.2.0 BiocStyle_2.38.0\n\nloaded via a namespace (and not attached):\n [1] digest_0.6.39 R6_2.6.1 fastmap_1.2.0 \n [4] tidyselect_1.2.1 xfun_0.56 magrittr_2.0.4 \n [7] glue_1.8.0 tibble_3.3.1 knitr_1.51 \n[10] pkgconfig_2.0.3 htmltools_0.5.9 generics_0.1.4 \n[13] rmarkdown_2.30 lifecycle_1.0.5 cli_3.6.5 \n[16] vctrs_0.7.1 compiler_4.5.2 tools_4.5.2 \n[19] evaluate_1.0.5 pillar_1.11.1 yaml_2.3.12 \n[22] otel_0.2.0 BiocManager_1.30.27 rlang_1.1.7 \n[25] jsonlite_2.0.0 htmlwidgets_1.6.4 \n\n\n\n\nSimilar to what was seen for the base R packages, dplyr is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the dplyr packages select() function and it’s respective help page.\n\n?select\n\n\n\n\nSince its parent package has been attached to our local environment (via the library() call), we can see dplyr functions appear as suggestions as we begin to type.\nBy contrast, is we check for the ggplot() function from the ggplot2 package (which we haven’t yet installed or attached via library()), no suggestions will pop up.\n\n?ggplot\n\nNo documentation for 'ggplot' in specified packages and libraries:\nyou could try '??ggplot'\n\n\n\n\nBeyond individual functions, some R packages also have help landing pages, that can be similarly accessed by adding a ? in front of the package name:\n\n\n\n\n\nUnattaching\nSo far, we have installed an R package, and then attached it (via library()). How would we reverse these steps?\nWell, to unload it from the local environment, there are a couple options. You could of course simply shut down Positron. The local environment only exist in context of when you open and close the session, which closing the program will do. All previously loaded R packages will be unattached, which is why when you start a new session you will need to load in all packages you plan on using via library().\nAlternatively, although less used, you could detach() it via your console:\n\ndetach(\"package:dplyr\", unload=TRUE)\n\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] BiocStyle_2.38.0\n\nloaded via a namespace (and not attached):\n [1] digest_0.6.39 R6_2.6.1 fastmap_1.2.0 \n [4] tidyselect_1.2.1 xfun_0.56 magrittr_2.0.4 \n [7] glue_1.8.0 tibble_3.3.1 knitr_1.51 \n[10] pkgconfig_2.0.3 htmltools_0.5.9 generics_0.1.4 \n[13] rmarkdown_2.30 lifecycle_1.0.5 cli_3.6.5 \n[16] vctrs_0.7.1 compiler_4.5.2 tools_4.5.2 \n[19] evaluate_1.0.5 pillar_1.11.1 yaml_2.3.12 \n[22] otel_0.2.0 BiocManager_1.30.27 rlang_1.1.7 \n[25] jsonlite_2.0.0 htmlwidgets_1.6.4 \n\n\n\n\nLooking at the sessionInfo() output, dplyr is no longer attached to the local environment. Consequently, if we try to once again look for the documentation, no information will be retrieved.\n\n?dplyr\n\nNo documentation for 'dplyr' in specified packages and libraries:\nyou could try '??dplyr'\n\n\n\n\nThere is a workaround however, if we want to access functions from an unloaded R package. We can specify the R package’s name, followed by two :, and then the function name. The :: conveys the context to your computer that the package is present, but may not be attached.\n\n?dplyr::select()\n\nThis particular use case can be useful if we want to run a particular function, but not load in all a packages functions (which may have identical function names to other R packages we are using and cause some conflicts).\n\n\n\n\nRemoving Packages\nJust as we can install an R package, we can also uninstall an R package (although doing so is rare, most often when encountering package dependency conflict). To do so, we would use the remove.packages() function.\n\n?remove.packages()\n\n\nremove.packages(\"dplyr\")\n\nThis results in the package being removed entirely from our computer. We would then need to reinstall it if needed in the future.\n\n\n\n\nCommon Issues\nAs previously mentioned, CRAN is the main repository for R packages. But what if we tried to install an R package that is only found on Bioconductor or via GitHub using the install.packages() function?\nTo see what occurs, let’s try installing the PeacoQC package (which is found on Bioconductor).\n\ninstall.packages(\"PeacoQC\")\n\nInstalling package into '/home/david/R/x86_64-pc-linux-gnu-library/4.5'\n(as 'lib' is unspecified)\n\n\nWarning: package 'PeacoQC' is not available for this version of R\n\nA version of this package for your version of R might be available elsewhere,\nsee the ideas at\nhttps://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages\n\n\n\n\nAs you can see, the initial warning message suggest that PeacoQC is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn’t figure out what was going on.\nThis is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN.", + "objectID": "course/02_FilePaths/index.html#file-paths", + "href": "course/02_FilePaths/index.html#file-paths", + "title": "02 - File Paths", + "section": "File Paths", + "text": "File Paths\nOne way we can do this is through a file.path argument. We could potentially provide this by adding either a / or a  into the path argument, depending on your computers operating system.\n\nlist.files(path=\"data/target\", full.names=FALSE, recursive=FALSE)\n\n\n\nWhile this works in your particular context, if you are sharing the code with others who have a different operating system, these hard-coded “/” or “\" will cause the code for them to error out at these particular steps.\n\nFor that reason, it is better to assemble a file.path using the file.path() function. This function takes into account the operating system, removing your need to have to worry about this particular computing nuance, and write code that is reproducible and replicable for everyone.\n\nFolderLocation <- file.path(\"data\", \"target\")\nFolderLocation\n\n[1] \"data/target\"\n\n\n\nlist.files(path=FolderLocation, full.names=FALSE, recursive=FALSE)\n\n\n\n\nWe can also append additional locations to existing file paths, by including the variable name within the file.path() we are creating.\n\nFolderLocation <- \"data\"\nScreenshotFolder <- file.path(FolderLocation, \"target\")\nScreenshotFolder\n\n[1] \"data/target\"\n\n\n\nlist.files(path=ScreenshotFolder, full.names=FALSE, recursive=FALSE)\n\n\n\n\nAdditionally, list.files() has the ability to filter for files that contain a particular character string. This can be useful is we are searching for “.fcs” or “.csv” files, but also for files that contain a particular word. In the case of the ScreenshotFolders\n\nlist.files(path=ScreenshotFolder, pattern=\"ND050\", full.names=FALSE, recursive=FALSE)\n\n\nYou will notice, the index numbers are in the context of what is filtered, not all the folder contents.", "crumbs": [ "About", - "Intro to R" + "Intro to R", + "02 - File Paths" ] }, { - "objectID": "course/01_InstallingRPackages/index.html#installing-from-bioconductor", - "href": "course/01_InstallingRPackages/index.html#installing-from-bioconductor", - "title": "01 - Installing R Packages", - "section": "Installing from Bioconductor", - "text": "Installing from Bioconductor\nBioconductor is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this link you can find it’s current flow and mass cytometry R packages.\nBioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different standards for acceptance than CRAN. They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems.\n\n\nTo install an R package that is located on Bioconductor, we first need to install the BiocManager package from CRAN. This package will allow us to install Bioconductor packages from their respective repository.\n\ninstall.packages(\"BiocManager\")\n\n\n\nOnce BiocManager is installed, we can attach it to our local environment using the library() function\n\nlibrary(BiocManager)\n\n\n\nWhen loaded, you will see an output showing the current Bioconductor and R versions.\nWe can then use BiocManager’s install() function to go back and install PeacoQC().\n\n\n\n\n\n\nTip\n\n\n\nAs always, don’t forget the “” when running an install() command.\n\n\n\n?install()\n\n\ninstall(\"PeacoQC\")\n\n\n\nWe see a similar opening sequence of installation steps as what we saw when installing the dplyr package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation.\n\n\n\n\n\n\nNote\n\n\n\nBehind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process\n\n\n\n\n\nWithin the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with dplyr, with a “Done (packagename)” being printed upon successful installation.\n\n\n\nThis process continues for each dependency being installed.\n\n\n\nAnd finally, once all the dependencies are installed, PeacoQC starts to install.\n\n\n\nOccasionally, during installation, you will see a pop-up windown like this one in the console. This let’s you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n].\n\n\n\nAlternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter.\n\n\n\nGenerally, it’s okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn’t cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option.\n\n\n\nWith PeacoQC has been installed, we can load it via the library() call\n\n\n\n\n\n\nTip\n\n\n\nRemeber, library() doesn’t require ” ”\n\n\n\nlibrary(PeacoQC)\n\n\n\nAnd we can check to see if it has been attached to the local environment\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] PeacoQC_1.20.0 BiocManager_1.30.27 BiocStyle_2.38.0 \n\nloaded via a namespace (and not attached):\n [1] generics_0.1.4 shape_1.4.6.1 digest_0.6.39 \n [4] magrittr_2.0.4 evaluate_1.0.5 grid_4.5.2 \n [7] RColorBrewer_1.1-3 iterators_1.0.14 circlize_0.4.17 \n[10] fastmap_1.2.0 foreach_1.5.2 doParallel_1.0.17 \n[13] jsonlite_2.0.0 graph_1.88.1 GlobalOptions_0.1.3 \n[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1 scales_1.4.0 \n[19] XML_3.99-0.20 Rgraphviz_2.54.0 codetools_0.2-20 \n[22] cli_3.6.5 RProtoBufLib_2.22.0 rlang_1.1.7 \n[25] crayon_1.5.3 Biobase_2.70.0 yaml_2.3.12 \n[28] otel_0.2.0 cytolib_2.22.0 ncdfFlow_2.56.0 \n[31] tools_4.5.2 parallel_4.5.2 dplyr_1.2.0 \n[34] colorspace_2.1-2 ggplot2_4.0.2 GetoptLong_1.1.0 \n[37] BiocGenerics_0.56.0 vctrs_0.7.1 R6_2.6.1 \n[40] png_0.1-8 matrixStats_1.5.0 stats4_4.5.2 \n[43] lifecycle_1.0.5 flowCore_2.22.1 S4Vectors_0.48.0 \n[46] htmlwidgets_1.6.4 IRanges_2.44.0 clue_0.3-66 \n[49] cluster_2.1.8.1 pkgconfig_2.0.3 pillar_1.11.1 \n[52] gtable_0.3.6 data.table_1.18.2.1 glue_1.8.0 \n[55] xfun_0.56 tibble_3.3.1 tidyselect_1.2.1 \n[58] knitr_1.51 farver_2.1.2 rjson_0.2.23 \n[61] htmltools_0.5.9 rmarkdown_2.30 compiler_4.5.2 \n[64] S7_0.2.1 \n\n\n\n\nAs you may have noticed, the section of loaded via namespace (but not attached) packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment.\n\n\n\nTo see what packages are installed (but not yet loaded), we can use the installed.packages() function to return a list of R packages for your computer.\n\ninstalled.packages()", + "objectID": "course/02_FilePaths/index.html#selecting-for-patterns", + "href": "course/02_FilePaths/index.html#selecting-for-patterns", + "title": "02 - File Paths", + "section": "Selecting for Patterns", + "text": "Selecting for Patterns\nIf we currently listed the files within data, we get a return that looks like this:\n\nlist.files(\"data\", full.names=FALSE, recursive=FALSE)\n\n\n\n\nAs you can see, we are getting back both folders and individual .fcs files. We could consequently change the pattern to provide a character string that will only return the .fcs files. We will go ahead and assign this list to a variable named files, for later retrieval.\n\nfiles <- list.files(\"data\", pattern=\".fcs\", full.names=FALSE, recursive=FALSE)\nfiles\n\n\n\n\nOne of the R packages we will be using througout the course is the stringr package. It contains two functions that can be useful when identifying more complicated character strings. In this case, if we run the str_detect() function to identify which of the .fcs files within the files variable contains the “INF” character string, we get a vector of logical (ie. True or FALSE) outputs corresponding to each file.\n\n# install.packages(\"stringr\") # CRAN\nlibrary(stringr)\n\n\nstr_detect(files, \"INF\")\n\n\n\n\nSimilar to how we indexed the Fluorophore list (ex. Fluorophore[1:2]) which returned a subset, we can similarly use this logical vector to subset files that returned as TRUE for containing the pattern “INF”\n\nfiles[str_detect(files, \"INF\")]\n\n\n\n\nLet’s go ahead and save these subsetted file names to a new variable, called Infants.\n\nInfants <- files[str_detect(files, \"INF\")]", "crumbs": [ "About", - "Intro to R" + "Intro to R", + "02 - File Paths" ] }, { - "objectID": "course/01_InstallingRPackages/index.html#install-from-github", - "href": "course/01_InstallingRPackages/index.html#install-from-github", - "title": "01 - Installing R Packages", - "section": "Install from GitHub", - "text": "Install from GitHub\nIn addition to the CRAN and Bioconductor repositories, individual R packages can also be found on GitHub hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to CRAN or Bioconductor) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all.\n\n\nWhile many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to deprecation since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it’s useful to check the commits and issues pages to see when the last contribution occurred. We will take a closer look at how to do so later on.\n\n\nTo install packages from GitHub, you will need the remotes package, which can be found on CRAN.\n\n\n\n\n\n\nSpot Check #1\n\n\n\nTo install a package from CRAN, what function would you use? Click on the code-fold arrow below to reveal the answer.\n\n\n\n\nCode\ninstall.packages(\"remotes\")\n\n\n\n\nWith the remotes package now installed, we can attach it to our local environment.\n\n\n\n\n\n\nSpot Check #2\n\n\n\nWhat function would be used to do so?\n\n\n\n\nCode\nlibrary(remotes)\n\n\n\n\nAnd finally, we can use the install_github() function to download R packages from the invidual developers GitHub account.\n\n\n\n\n\n\nSpot Check #3\n\n\n\nHow would you look up the help documentation for this function?\n\n\n\n\nCode\n# Either by hovering over it within Positron or via\n\n?install_github()\n\n\n\n\nWe will be installing a small R package flowSpectrum for this example. It’s one of the packages created by Christopher Hall, whose small series of Flow Cytometry Data Analysis in R tutorials were immensely useful when I was first getting started learning R. flowSpectrum can be used to generate spectrum-style plots for spectral flow cytometry data.\n\n\n\nTo install an R package from GitHub, we first need the GitHub username (so hally166 in this case), which is followed by a “/”, and then the name of the package repository (so flowSpectrum in this case). Our code should consequently be:\n\ninstall_github(\"hally166/flowSpectrum\")\n\n\n\nWhen installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding.\nThis process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating R packages.", + "objectID": "course/02_FilePaths/index.html#conditionals", + "href": "course/02_FilePaths/index.html#conditionals", + "title": "02 - File Paths", + "section": "Conditionals", + "text": "Conditionals\nOne useful thing is that within R, we can set conditions on whether something is carried out. The most typical conditional you will encounter are the “If” statements. They typically take a form that resembles the following.\n\nNeedCoffee <- TRUE\n\nif (NeedCoffee){\n print(\"Take a break\")\n}\n\n\n\nIn this case of the above, if the variable within the () is equal to true, the code within the {} will be executed.\n\nNeedCoffee <- TRUE\n\nif (NeedCoffee){\n print(\"Take a break\")\n}\n\n[1] \"Take a break\"\n\n\n\n\nBy contrast, when the variable within the () is equal to false, the code within the {} will not be executed.\n\nNeedCoffee <- FALSE\n\nif (NeedCoffee){\n print(\"Take a break\")\n}\n\n\n\nThese “If” statements will trigger as long as the specified condition within the () is TRUE. For a different example:\n\nRowNumber <- 299\n2 + RowNumber > 300\n\n[1] TRUE\n\n\n\nif (2 + RowNumber > 3){\n print(\"Stop Iterating\")\n}\n\n[1] \"Stop Iterating\"\n\n\n\n\nWhen you add an ! in front a conditional, it flips the expected outcome.\n\nItsRaining <- TRUE\n\nif (ItsRaining){print(\"Bring an Umbrella\")}\n\n[1] \"Bring an Umbrella\"\n\n\n\n!ItsRaining\n\n[1] FALSE\n\n\n\nif (!ItsRaining){print(\"Bring an Umbrella\")}\n\n\nItsRaining <- TRUE\n\nif (!ItsRaining){print(\"Bring Sunglasses\")}\n\n\n\nWe will explore more complicated conditionals throughout the course, but for now, let’s implement a couple simple ones in the context of copying over the .fcs files in Infants over to a new target3 folder.", "crumbs": [ "About", - "Intro to R" + "Intro to R", + "02 - File Paths" ] }, { - "objectID": "course/01_InstallingRPackages/index.html#troubleshooting-install-errors", - "href": "course/01_InstallingRPackages/index.html#troubleshooting-install-errors", - "title": "01 - Installing R Packages", - "section": "Troubleshooting Install Errors", - "text": "Troubleshooting Install Errors\nWe have now installed three R packages, dplyr, PeacoQC, and flowSpectrum. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies.\nWhen encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below.\n\n\n\nIf you encounter an installation error this week, please take screenshots of the error message and post them to this Discussion. This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future.", + "objectID": "course/02_FilePaths/index.html#conditionals-in-practice", + "href": "course/02_FilePaths/index.html#conditionals-in-practice", + "title": "02 - File Paths", + "section": "Conditionals in practice", + "text": "Conditionals in practice\nFirst off, let’s write a conditional to check if there is a target3 folder within data.\n\nfiles_present <- list.files(\"data\", full.names=FALSE, recursive=FALSE)\nfiles_present\n\n\n\n\n\nFolderTarget3 <- file.path(\"data\", \"target3\")\ndir.exists(FolderTarget3)\n\n\n\n\nWe can write a conditional to create a folder if one does not yet exist.\n\nif (!dir.exists(FolderTarget3)){\n dir.create(FolderTarget3)\n}", "crumbs": [ "About", - "Intro to R" + "Intro to R", + "02 - File Paths" ] }, { - "objectID": "course/01_InstallingRPackages/index.html#installing-specific-package-versions", - "href": "course/01_InstallingRPackages/index.html#installing-specific-package-versions", - "title": "01 - Installing R Packages", - "section": "Installing Specific-Package Versions", - "text": "Installing Specific-Package Versions\nWhile we may be tempted to think of R packages as static, they change quite often, as their develipers add new features, fix bugs, etc. To help keep track of these changes (essential for reproducibility and replicability), R packages have version numbers.\nWhen we run sessionInfo(), we can see an example of this, with the version number appearing after the package name.\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] PeacoQC_1.20.0 BiocManager_1.30.27 BiocStyle_2.38.0 \n\nloaded via a namespace (and not attached):\n [1] generics_0.1.4 shape_1.4.6.1 digest_0.6.39 \n [4] magrittr_2.0.4 evaluate_1.0.5 grid_4.5.2 \n [7] RColorBrewer_1.1-3 iterators_1.0.14 circlize_0.4.17 \n[10] fastmap_1.2.0 foreach_1.5.2 doParallel_1.0.17 \n[13] jsonlite_2.0.0 graph_1.88.1 GlobalOptions_0.1.3 \n[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1 scales_1.4.0 \n[19] XML_3.99-0.20 Rgraphviz_2.54.0 codetools_0.2-20 \n[22] cli_3.6.5 RProtoBufLib_2.22.0 rlang_1.1.7 \n[25] crayon_1.5.3 Biobase_2.70.0 yaml_2.3.12 \n[28] otel_0.2.0 cytolib_2.22.0 ncdfFlow_2.56.0 \n[31] tools_4.5.2 parallel_4.5.2 dplyr_1.2.0 \n[34] colorspace_2.1-2 ggplot2_4.0.2 GetoptLong_1.1.0 \n[37] BiocGenerics_0.56.0 vctrs_0.7.1 R6_2.6.1 \n[40] png_0.1-8 matrixStats_1.5.0 stats4_4.5.2 \n[43] lifecycle_1.0.5 flowCore_2.22.1 S4Vectors_0.48.0 \n[46] htmlwidgets_1.6.4 IRanges_2.44.0 clue_0.3-66 \n[49] cluster_2.1.8.1 pkgconfig_2.0.3 pillar_1.11.1 \n[52] gtable_0.3.6 data.table_1.18.2.1 glue_1.8.0 \n[55] xfun_0.56 tibble_3.3.1 tidyselect_1.2.1 \n[58] knitr_1.51 farver_2.1.2 rjson_0.2.23 \n[61] htmltools_0.5.9 rmarkdown_2.30 compiler_4.5.2 \n[64] S7_0.2.1 \n\n\n\n\nAlternatively, we can retrieve the same information for the individual packages via the packageVersion() function\n\npackageVersion(\"PeacoQC\")\n\n[1] '1.20.0'\n\n\n\n\nAs well as from the citation() function.\n\ncitation(\"PeacoQC\")\n\nTo cite package 'PeacoQC' in publications use:\n\n Emmaneel A (2025). _PeacoQC: Peak-based selection of high quality\n cytometry data_. doi:10.18129/B9.bioc.PeacoQC\n <https://doi.org/10.18129/B9.bioc.PeacoQC>, R package version 1.20.0,\n <https://bioconductor.org/packages/PeacoQC>.\n\nA BibTeX entry for LaTeX users is\n\n @Manual{,\n title = {PeacoQC: Peak-based selection of high quality cytometry data},\n author = {Annelies Emmaneel},\n year = {2025},\n note = {R package version 1.20.0},\n url = {https://bioconductor.org/packages/PeacoQC},\n doi = {10.18129/B9.bioc.PeacoQC},\n }\n\n\n\n\nHow does a version number work? Lets say we have the following version number: 1.20.0\nThe first number of the version (1. in this case) denotes major changes, primarily those where after the version change the package may not be compatible with the code used in the prior version. As a consequence, this number changes rarely.\nThe second number (.20. in this case) is the minor version. Minor changes typically consist of new features that are added, that don’t affect the overall package function. These will change more frequently, especially for Bioconductor packages with fixed release cycles.\nThe final number (.0 in this case) is often used to denote small changes occuring within a minor release period, often bug-fixes or fixing typos within the documentation.\n\n\nWe may in the future need to install specific package versions (but wont be doing so today). As expected, which repository contains the R package influences how we would go about doing this.\nFor CRAN packages, we can use the remotes packages install_version() function. This allows us to provide the version number, and designate the repository location (the CRAN url in this case).\n\nremotes::install_version(\"ggplot2\", version = \"3.5.2\", repos = \"https://cloud.r-project.org\")\n\nFor GitHub-based R packages, the package versioning schema is not as strict as that of CRAN or Bioconductor. Typically, changes in R packagaes are put out by their developers as releases. When trying to install a particular release, we can add an additional argument to the install_github() function, specifying the release version’s tag number. For example:\n\nremotes::install_github(\"DavidRach/Luciernaga\", ref = \"v0.99.7\")\n\nAlternatively, if the developer doesn’t implement releases, you can provide the hash number of a particular commit.\n\nremotes::install_github(\"DavidRach/Luciernaga\", ref = \"8d1d694\")", + "objectID": "course/02_FilePaths/index.html#copying-files", + "href": "course/02_FilePaths/index.html#copying-files", + "title": "02 - File Paths", + "section": "Copying Files", + "text": "Copying Files\nTo copy files to another folder location, we use the file.copy() function. It has two arguments that we will be working with, from being the .fcs files, and to being the folder location we wish to transfer them to. If we tried using them as we currently have them:\n\n# Variable Infants containing 4 .fcs file names\n\nfile.copy(from=Infants, to=FolderTarget3)\n\n\n\n\nThe reason for this error is we are only working with a partial file path, as viewed from our Working directory. In this case, what is needed is the full file.path, so the file.path should also include the upstream folders from your current working directory.\n\ngetwd()\n\n\n\n\nIn this case, we can update the .fcs files location by switching the full.names argument within list.files() from FALSE, to TRUE.\n\nfiles_present <- list.files(\"data\", full.names=TRUE, recursive=FALSE)\nfiles_present\n\n\nAnd filter for those containing “INF” again\n\nInfants <- files_present[str_detect(files_present, \"INF\")]\n\nAnd then try again:\n\n# Variable Infants containing 4 .fcs file names\n\nfile.copy(from=Infants, to=FolderTarget3)", "crumbs": [ "About", - "Intro to R" + "Intro to R", + "02 - File Paths" ] }, { - "objectID": "course/01_InstallingRPackages/index.html#documentation-and-websites", - "href": "course/01_InstallingRPackages/index.html#documentation-and-websites", - "title": "01 - Installing R Packages", - "section": "Documentation and Websites", - "text": "Documentation and Websites\nWe have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package.\nFor CRAN-based packages, we can start off by searching for the package name. So, in the case of dplyr:\n\n\n\nTwo main suggestions pop up. One is the package’s CRAN page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible.\n\n\n\nBecause of this, many CRAN-based R packages (especially those part of the tidyverse) use pkgdown-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr’s pkgdown-style website\n\n\n\nWe can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab.\n\n\n\nGitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository’s ReadMe.\n\n\n\nFor Bioconductor-based packages, on the package’s page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with PeacoQC:\n\n\n\nAdditionally, package vignettes can also be reached via the packages help index page. These will usually appear under User guides, package vignettes, and other documentation.", + "objectID": "course/02_FilePaths/index.html#removing-files.", + "href": "course/02_FilePaths/index.html#removing-files.", + "title": "02 - File Paths", + "section": "Removing files.", + "text": "Removing files.\nJust like we can add files via R, we can also remove them. However, when we remove them via this route, they are removed permanently, not sent to the recycle bin. We will revisit how later on in the course after you have gained additional experience with file.paths.\n\n?unlink()", "crumbs": [ "About", - "Intro to R" + "Intro to R", + "02 - File Paths" ] }, { - "objectID": "course/01_InstallingRPackages/slides.html#set-up", - "href": "course/01_InstallingRPackages/slides.html#set-up", - "title": "01 - Installing R Packages", - "section": "Set Up", - "text": "Set Up\nAlright, with the background out of the way, let’s get started!\n\n\n\n\n\n\n\nImportant\n\n\nPlease make sure to sync your forked version of the CytometryInR repository, and pull any changes to your local computer’s CytometryInR project folder so that you have the most recent version of the code and data available.\n\n\n\n\n\n\n\n\n\n\n\nWarning\n\n\nPlease remember to always copy over the new material from your local CytometryInR folder to a separate Project Folder that you created and named (ex. “Week_01” or “MyLearningFolder”, etc.). This will ensure any edits you make to the files do not affect your ability to bring in next week’s materials to the CytometryInR folder" + "objectID": "course/02_FilePaths/index.html#basename", + "href": "course/02_FilePaths/index.html#basename", + "title": "02 - File Paths", + "section": "Basename", + "text": "Basename\nIf we look at Infants with the full.names=TRUE, we see the additional pathing folder has been added, allowing us to successfully copy over the files.\n\nInfants\n\n\n\n\nIf we were trying to retrieve just the local file names from the full.names, we could do so with basename() function. We will use this in combination with additional arguments later in the course\n\nbasename(Infants)", + "crumbs": [ + "About", + "Intro to R", + "02 - File Paths" + ] }, { - "objectID": "course/01_InstallingRPackages/slides.html#checking-for-loaded-packages", - "href": "course/01_InstallingRPackages/slides.html#checking-for-loaded-packages", + "objectID": "course/02_FilePaths/index.html#recursive", + "href": "course/02_FilePaths/index.html#recursive", + "title": "02 - File Paths", + "section": "Recursive", + "text": "Recursive\nAnd finally that we have created additional nested folders and populated them with fcs files, let’s see what setting list.files() recursive argument to TRUE\n\nall_files_present <- list.files(full.names=TRUE, recursive=TRUE)\nall_files_present \n\n\n\n\nIn this case, all files in all folders within the working directory are shown. This can be useful when exploring folder contents, but if there are a lot of files present within the folder, it will take a while to return the list.", + "crumbs": [ + "About", + "Intro to R", + "02 - File Paths" + ] + }, + { + "objectID": "course/02_FilePaths/index.html#saving-changes-to-version-control", + "href": "course/02_FilePaths/index.html#saving-changes-to-version-control", + "title": "02 - File Paths", + "section": "Saving changes to Version Control", + "text": "Saving changes to Version Control\nAnd as is good practice, to maintain version control, let’s stage all the files and folders we created today within the Week2 Project Folder, write a commit message, and send these files back to GitHub until they are needed again next time.", + "crumbs": [ + "About", + "Intro to R", + "02 - File Paths" + ] + }, + { + "objectID": "course/02_FilePaths/slides.html#set-up", + "href": "course/02_FilePaths/slides.html#set-up", + "title": "02 - File Paths", + "section": "Set Up", + "text": "Set Up\n\n\n\n\n\n\n\n\n.\n\n\nBefore we begin, let’s make sure you get the data needed for today transferred to your local computer, and then get the .fcs files copied over from there to your own working project folder. This is the process you will repeat each week throughout the course." + }, + { + "objectID": "course/02_FilePaths/slides.html#working-directory", + "href": "course/02_FilePaths/slides.html#working-directory", + "title": "02 - File Paths", + "section": "Working Directory", + "text": "Working Directory\n\n\n\n\n\n\n\n\n.\n\n\nNow that we are back in our Week2 folder, let’s start by seeing our current location similarly to how our computer perceives it.\nWe will use getwd() function (ie. get working directory) to return the location of the folder we are currently inside of. For example, when getwd() is run within my Week2 project folder, I see the following location" + }, + { + "objectID": "course/02_FilePaths/slides.html#directories", + "href": "course/02_FilePaths/slides.html#directories", + "title": "02 - File Paths", + "section": "Directories", + "text": "Directories\n\n\n\n\n\n\n\n\n.\n\n\nWithin this working directory, we have a variety of project folders and files related to the course. We can see the folders that are present using the list.dirs() function.\n\n\n\n\n\n\n\n\n\n\nlist.dirs(path=\".\", full.names=FALSE, recursive=FALSE)" + }, + { + "objectID": "course/02_FilePaths/slides.html#variables", + "href": "course/02_FilePaths/slides.html#variables", + "title": "02 - File Paths", + "section": "Variables", + "text": "Variables\n\n\n\n\n\n\n\n\n.\n\n\nBefore exploring file paths, we need to have some basic R code knowledge that we can use to work with them. Within R, we have the ability to assign particular values (be they character strings, numbers or logicals) to objects (ie. variables) that can be used when called upon later.\nFor example:\n\n\n\n\n\n\n\nWhatDayDidIWriteThis <- \"Saturday\"\n\n\n\n\n\n\n\n\n\n\n.\n\n\nIn this case, the variable name is what the assignment arrow (“<-”) is pointing at. In this case, WhatDayDidIWriteThis" + }, + { + "objectID": "course/02_FilePaths/slides.html#indexing", + "href": "course/02_FilePaths/slides.html#indexing", + "title": "02 - File Paths", + "section": "Indexing", + "text": "Indexing\n\n\n\n\n\n\n\n\n.\n\n\nNot all variables contain single objects.\nFor example, we can modify Fluorophores and add additional entries:\n\n\n\n\n\n\n\nFluorophores <- c(\"BV421\", \"FITC\", \"PE\", \"APC\")\nstr(Fluorophores)\n\n chr [1:4] \"BV421\" \"FITC\" \"PE\" \"APC\"\n\n\n\n\n\n\n\n\n\n\n\n.\n\n\nThe c stands for concatenate. It concatenates the objects into a larger object, known as a vector.\nIn this case, you notice in addition to the specification the values are characters, we get a [1:4], denoting four objects are present." + }, + { + "objectID": "course/02_FilePaths/slides.html#listing-files", + "href": "course/02_FilePaths/slides.html#listing-files", + "title": "02 - File Paths", + "section": "Listing Files", + "text": "Listing Files\n\n\n\n\n\n\n\n\n.\n\n\nAfter this detour into variables and indexing, let’s return our focus to how to use these in context of file paths. Working from within our Week2 project folder, let’s see what directories (folders) are present\n\n\n\n\n\n\n\nlist.dirs(path=\".\", full.names=FALSE, recursive=FALSE)" + }, + { + "objectID": "course/02_FilePaths/slides.html#creating-directories", + "href": "course/02_FilePaths/slides.html#creating-directories", + "title": "02 - File Paths", + "section": "Creating directories", + "text": "Creating directories\n\n\n\n\n\n\n\n\n.\n\n\nAlternatively, we can also create a folder via R using the dir.create() function. Since we want it within data, we would modify the path accordingly\n\n\n\n\n\n\n\nNewFolderLocation <- file.path(\"data\", \"target2\")\n\ndir.create(path=NewFolderLocation)" + }, + { + "objectID": "course/02_FilePaths/slides.html#file-paths", + "href": "course/02_FilePaths/slides.html#file-paths", + "title": "02 - File Paths", + "section": "File Paths", + "text": "File Paths\n\n\n\n\n\n\n\n\n.\n\n\nOne way we can do this is through a file.path argument. We could potentially provide this by adding either a “/” or a “\" into the path argument, depending on your computers operating system.\n\n\n\n\n\n\n\nlist.files(path=\"data/target\", full.names=FALSE, recursive=FALSE)" + }, + { + "objectID": "course/02_FilePaths/slides.html#selecting-for-patterns", + "href": "course/02_FilePaths/slides.html#selecting-for-patterns", + "title": "02 - File Paths", + "section": "Selecting for Patterns", + "text": "Selecting for Patterns\n\n\n\n\n\n\n\n\n.\n\n\nIf we currently listed the files within data, we get a return that looks like this:\n\n\n\n\n\n\n\nlist.files(\"data\", full.names=FALSE, recursive=FALSE)" + }, + { + "objectID": "course/02_FilePaths/slides.html#conditionals", + "href": "course/02_FilePaths/slides.html#conditionals", + "title": "02 - File Paths", + "section": "Conditionals", + "text": "Conditionals\n\n\n\n\n\n\n\n\n.\n\n\nOne useful thing is that within R, we can set conditions on whether something is carried out. The most typical conditional you will encounter are the “If” statements. They typically take a form that resembles the following.\n\n\n\n\n\n\n\nNeedCoffee <- TRUE\n\nif (NeedCoffee){\n print(\"Take a break\")\n}" + }, + { + "objectID": "course/02_FilePaths/slides.html#conditionals-in-practice", + "href": "course/02_FilePaths/slides.html#conditionals-in-practice", + "title": "02 - File Paths", + "section": "Conditionals in practice", + "text": "Conditionals in practice\n\n\n\n\n\n\n\n\n.\n\n\nFirst off, let’s write a conditional to check if there is a target3 folder within data.\n\n\n\n\n\n\n\nfiles_present <- list.files(\"data\", full.names=FALSE, recursive=FALSE)\nfiles_present" + }, + { + "objectID": "course/02_FilePaths/slides.html#copying-files", + "href": "course/02_FilePaths/slides.html#copying-files", + "title": "02 - File Paths", + "section": "Copying Files", + "text": "Copying Files\n\n\n\n\n\n\n\n\n.\n\n\nTo copy files to another folder location, we use the file.copy() function. It has two arguments that we will be working with, from being the .fcs files, and to being the folder location we wish to transfer them to. If we tried using them as we currently have them:\n\n\n\n\n\n\n\n# Variable Infants containing 4 .fcs file names\n\nfile.copy(from=Infants, to=FolderTarget3)" + }, + { + "objectID": "course/02_FilePaths/slides.html#removing-files.", + "href": "course/02_FilePaths/slides.html#removing-files.", + "title": "02 - File Paths", + "section": "Removing files.", + "text": "Removing files.\n\n\n\n\n\n\n\n\n.\n\n\nJust like we can add files via R, we can also remove them. However, when we remove them via this route, they are removed permanently, not sent to the recycle bin. We will revisit how later on in the course after you have gained additional experience with file.paths.\n\n\n\n\n\n\n\n?unlink()" + }, + { + "objectID": "course/02_FilePaths/slides.html#basename", + "href": "course/02_FilePaths/slides.html#basename", + "title": "02 - File Paths", + "section": "Basename", + "text": "Basename\n\n\n\n\n\n\n\n\n.\n\n\nIf we look at Infants with the full.names=TRUE, we see the additional pathing folder has been added, allowing us to successfully copy over the files.\n\n\n\n\n\n\n\nInfants" + }, + { + "objectID": "course/02_FilePaths/slides.html#recursive", + "href": "course/02_FilePaths/slides.html#recursive", + "title": "02 - File Paths", + "section": "Recursive", + "text": "Recursive\n\n\n\n\n\n\n\n\n.\n\n\nAnd finally that we have created additional nested folders and populated them with fcs files, let’s see what setting list.files() recursive argument to TRUE\n\n\n\n\n\n\n\nall_files_present <- list.files(full.names=TRUE, recursive=TRUE)\nall_files_present" + }, + { + "objectID": "course/02_FilePaths/slides.html#saving-changes-to-version-control", + "href": "course/02_FilePaths/slides.html#saving-changes-to-version-control", + "title": "02 - File Paths", + "section": "Saving changes to Version Control", + "text": "Saving changes to Version Control\n\n\n\n\n\n\n\n\n.\n\n\nAnd as is good practice, to maintain version control, let’s stage all the files and folders we created today within the Week2 Project Folder, write a commit message, and send these files back to GitHub until they are needed again next time." + }, + { + "objectID": "course/01_InstallingRPackages/slides_inperson.html#checking-for-loaded-packages", + "href": "course/01_InstallingRPackages/slides_inperson.html#checking-for-loaded-packages", "title": "01 - Installing R Packages", "section": "Checking for Loaded Packages", "text": "Checking for Loaded Packages\n\n\n\n\n\n\n\n\n.\n\n\nFor the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active." }, { - "objectID": "course/01_InstallingRPackages/slides.html#installing-from-cran", - "href": "course/01_InstallingRPackages/slides.html#installing-from-cran", + "objectID": "course/01_InstallingRPackages/slides_inperson.html#installing-from-cran", + "href": "course/01_InstallingRPackages/slides_inperson.html#installing-from-cran", "title": "01 - Installing R Packages", "section": "Installing from CRAN", "text": "Installing from CRAN\n\n\n\n\n\n\n\n\n.\n\n\nWe will start by installing R packages that are part of the CRAN repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository.\nThese include the tidyverse packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today." }, { - "objectID": "course/01_InstallingRPackages/slides.html#installing-from-bioconductor", - "href": "course/01_InstallingRPackages/slides.html#installing-from-bioconductor", + "objectID": "course/01_InstallingRPackages/slides_inperson.html#installing-from-bioconductor", + "href": "course/01_InstallingRPackages/slides_inperson.html#installing-from-bioconductor", "title": "01 - Installing R Packages", "section": "Installing from Bioconductor", "text": "Installing from Bioconductor\n\n\n\n\n\n\n\n\n.\n\n\nBioconductor is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this link you can find it’s current flow and mass cytometry R packages.\nBioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different standards for acceptance than CRAN. They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems." }, { - "objectID": "course/01_InstallingRPackages/slides.html#install-from-github", - "href": "course/01_InstallingRPackages/slides.html#install-from-github", + "objectID": "course/01_InstallingRPackages/slides_inperson.html#install-from-github", + "href": "course/01_InstallingRPackages/slides_inperson.html#install-from-github", "title": "01 - Installing R Packages", "section": "Install from GitHub", "text": "Install from GitHub\n\n\n\n\n\n\n\n\n.\n\n\nIn addition to the CRAN and Bioconductor repositories, individual R packages can also be found on GitHub hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to CRAN or Bioconductor) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all." }, { - "objectID": "course/01_InstallingRPackages/slides.html#troubleshooting-install-errors", - "href": "course/01_InstallingRPackages/slides.html#troubleshooting-install-errors", + "objectID": "course/01_InstallingRPackages/slides_inperson.html#troubleshooting-install-errors", + "href": "course/01_InstallingRPackages/slides_inperson.html#troubleshooting-install-errors", "title": "01 - Installing R Packages", "section": "Troubleshooting Install Errors", "text": "Troubleshooting Install Errors\n\n\n\n\n\n\n\n\n.\n\n\nWe have now installed three R packages, dplyr, PeacoQC, and flowSpectrum. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies.\nWhen encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below." }, { - "objectID": "course/01_InstallingRPackages/slides.html#installing-specific-package-versions", - "href": "course/01_InstallingRPackages/slides.html#installing-specific-package-versions", - "title": "01 - Installing R Packages", - "section": "Installing Specific-Package Versions", - "text": "Installing Specific-Package Versions\n\n\n\n\n\n\n\n\n.\n\n\nWhile we may be tempted to think of R packages as static, they change quite often, as their develipers add new features, fix bugs, etc. To help keep track of these changes (essential for reproducibility and replicability), R packages have version numbers.\nWhen we run sessionInfo(), we can see an example of this, with the version number appearing after the package name.\n\n\n\n\n\n\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] PeacoQC_1.20.0 BiocManager_1.30.27\n\nloaded via a namespace (and not attached):\n [1] generics_0.1.4 shape_1.4.6.1 digest_0.6.39 \n [4] magrittr_2.0.4 evaluate_1.0.5 grid_4.5.2 \n [7] RColorBrewer_1.1-3 iterators_1.0.14 circlize_0.4.17 \n[10] fastmap_1.2.0 foreach_1.5.2 doParallel_1.0.17 \n[13] jsonlite_2.0.0 graph_1.88.1 GlobalOptions_0.1.3 \n[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1 scales_1.4.0 \n[19] XML_3.99-0.20 Rgraphviz_2.54.0 codetools_0.2-20 \n[22] cli_3.6.5 RProtoBufLib_2.22.0 rlang_1.1.7 \n[25] crayon_1.5.3 Biobase_2.70.0 yaml_2.3.12 \n[28] otel_0.2.0 cytolib_2.22.0 ncdfFlow_2.56.0 \n[31] tools_4.5.2 parallel_4.5.2 dplyr_1.2.0 \n[34] colorspace_2.1-2 ggplot2_4.0.2 GetoptLong_1.1.0 \n[37] BiocGenerics_0.56.0 vctrs_0.7.1 R6_2.6.1 \n[40] png_0.1-8 matrixStats_1.5.0 stats4_4.5.2 \n[43] lifecycle_1.0.5 flowCore_2.22.1 S4Vectors_0.48.0 \n[46] IRanges_2.44.0 clue_0.3-66 cluster_2.1.8.1 \n[49] pkgconfig_2.0.3 pillar_1.11.1 gtable_0.3.6 \n[52] data.table_1.18.2.1 glue_1.8.0 xfun_0.56 \n[55] tibble_3.3.1 tidyselect_1.2.1 knitr_1.51 \n[58] farver_2.1.2 rjson_0.2.23 htmltools_0.5.9 \n[61] rmarkdown_2.30 compiler_4.5.2 S7_0.2.1" - }, - { - "objectID": "course/01_InstallingRPackages/slides.html#documentation-and-websites", - "href": "course/01_InstallingRPackages/slides.html#documentation-and-websites", + "objectID": "course/01_InstallingRPackages/slides_inperson.html#documentation-and-websites", + "href": "course/01_InstallingRPackages/slides_inperson.html#documentation-and-websites", "title": "01 - Installing R Packages", "section": "Documentation and Websites", "text": "Documentation and Websites\n\n\n\n\n\n\n\n\n.\n\n\nWe have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package.\nFor CRAN-based packages, we can start off by searching for the package name. So, in the case of dplyr" }, { - "objectID": "course/00_WorkstationSetup/Windows.html", - "href": "course/00_WorkstationSetup/Windows.html", - "title": "Installing Software on Windows", - "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shots slides, click here\nThis is the software installation walkthrough for those whose computers are running Windows. Based on our pre-course interest form, you make up the majority of course participants." + "objectID": "course/00_WorkstationSetup/MacOSSlides.html#installing-r", + "href": "course/00_WorkstationSetup/MacOSSlides.html#installing-r", + "title": "Installing Software on MacOS", + "section": "Installing R", + "text": "Installing R\n\n\n\n\n\n\n\n\n.\n\n\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page." }, { - "objectID": "course/00_WorkstationSetup/Windows.html#installing-r", - "href": "course/00_WorkstationSetup/Windows.html#installing-r", - "title": "Installing Software on Windows", - "section": "Installing R", - "text": "Installing R\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.\n\n\n\nOn the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.\n\n\n\nYou will then select your Operating System, in this case, Windows.\n\n\n\nAnd go ahead and select the Install R for the first time link.\n\n\n\nNext, you will select the download the current version option at the top of the page.\n\n\n\nThe popup window will then ask where you want to save the installer (.exe) file. We generally save this to either Downloads or Desktop to make finding it easier.\n\n\n\nAfter the download is complete, double click on the installer’s .exe file. This will open a popup asking you to select your preferred language.\n\n\n\nYou will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course).\n\n\n\nOn Windows, R will normally save it’s software folder under Program Files.\n\n\n\nNext, please accept the defaults.\n\n\n\n\n\n\n\n\n\n\n\n\nWith the defaults accepted, the installation will commence. Feel free to go have a coffee/tea/beverage-of-your choice break while you wait.\n\n\n\nAnd if all goes well, the installation will complete without any issues." + "objectID": "course/00_WorkstationSetup/MacOSSlides.html#xcode-command-line-tools", + "href": "course/00_WorkstationSetup/MacOSSlides.html#xcode-command-line-tools", + "title": "Installing Software on MacOS", + "section": "Xcode Command Line Tools", + "text": "Xcode Command Line Tools\n\n\n\n\n\n\n\n\n.\n\n\nDepending on your version of macOS, you may or may not already have Git installed on your computer. The reason is that it comes bundled within the Xcode Command Line Tools.\nIf this is not your first foray into coding, you may have previously seen an installation pop-up along the lines of “XYZ requires command line developer tools. Would you like to install the tools now?” when installing an IDE (like Positron, Rstudio or Visual Studio Code)." }, { - "objectID": "course/00_WorkstationSetup/Windows.html#installing-rtools", - "href": "course/00_WorkstationSetup/Windows.html#installing-rtools", - "title": "Installing Software on Windows", - "section": "Installing RTools", - "text": "Installing RTools\nWe will now work on installing Rtools. This software is needed when building R packages from source, which we will need throughout the course for R packages hosted on GitHub.\nTo get started, we will return to the R installation page we visited previously and instead click on the Rtools option.\n\n\n\nNext, select the most recent version of Rtools to Download.\n\n\n\nYou will then select for your architecture. For the vast majority of Windows users, your computer will likely be be using a x86 chip architecture, so you would select the Rtools45 installer option.\nIf your computer however uses the ARM chip architecture, you would select the 64-bit ARM Rtools45 installer instead. If you are unsure, see the following.\n\n\n\nNext, you will select the location to save the Rtools installer to. We generally save this to either Downloads or Desktop to make finding it easier.\n\n\n\nOnce downloaded, double click on the .exe to launch the Rtools installer.\n\n\n\nSimilar to what we did when installing R, go ahead and keep the defaults.\n\n\n\nAnd click install to proceed with the installation.\n\n\n\nAnd wait while the installation wraps up.\n\n\n\nIf all goes well, you should see the following installation success page." + "objectID": "course/00_WorkstationSetup/MacOSSlides.html#install-positron", + "href": "course/00_WorkstationSetup/MacOSSlides.html#install-positron", + "title": "Installing Software on MacOS", + "section": "Install Positron", + "text": "Install Positron\n\n\n\n\n\n\n\n\n.\n\n\nFinally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right." }, { - "objectID": "course/00_WorkstationSetup/Windows.html#installing-git", - "href": "course/00_WorkstationSetup/Windows.html#installing-git", - "title": "Installing Software on Windows", + "objectID": "course/00_WorkstationSetup/LinuxSlides.html#debian-based-distros", + "href": "course/00_WorkstationSetup/LinuxSlides.html#debian-based-distros", + "title": "Installing Software on Linux", + "section": "Debian-based Distros", + "text": "Debian-based Distros\nInstalling R\n\n\n\n\n\n\n\n\n.\n\n\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page." + }, + { + "objectID": "course/00_WorkstationSetup/LinuxSlides.html#installing-git", + "href": "course/00_WorkstationSetup/LinuxSlides.html#installing-git", + "title": "Installing Software on Linux", "section": "Installing Git", - "text": "Installing Git\nGit is a version control software widely used among software developers and bioinformaticians. We will use it extensively throughout the course, both locally on our computers (to keep track of changes to our files), as well as in combination with GitHub(to maintain online backups of our files).\nWe will first navigate to the website and select the download from Windows option.\n\n\n\n\n\n\n\n\n\nWe will then proceed and select install 64-bit Git for Windows Setup option\n\n\n\n\n\n\n\nAs was the case with our installation of R and Rtools, a pop-up will appear asking for a location to save the installer to.\nOnce downloaded, double-click and proceed with the installation.\nYou will be asked to accept the Git License (which is the free copyleft GPL2 license, which we will learn about later in the course).\n\n\n\nThen you will be asked to select the folder to save to software to (usually your Programs folder)\n\n\n\nAt this point, the Git installer will ask a series of increasingly niche questions. It is best to just accept all the default options, to avoid wandering too far down a “What is Vim?!?” rabbit-hole.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nHaving made it through all the niche customization screens, we finally reach the install button.\n\n\n\nWe then can wait for the install to complete.\n\n\n\nAnd success, we have now installed Git." + "text": "Installing Git\n\n# sudo apt install git" }, { - "objectID": "course/00_WorkstationSetup/Windows.html#installing-positron", - "href": "course/00_WorkstationSetup/Windows.html#installing-positron", - "title": "Installing Software on Windows", + "objectID": "course/00_WorkstationSetup/LinuxSlides.html#installing-positron", + "href": "course/00_WorkstationSetup/LinuxSlides.html#installing-positron", + "title": "Installing Software on Linux", "section": "Installing Positron", - "text": "Installing Positron\nFinally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right.\n\n\n\nYou will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).\nWith the license accepted, you will be able to select your operating system. In this case, we will select Windows, specifally the user level install.\n\n\n\nPlease note, if you are using a Windows computer with an ARM based chip (like is the case with Snapdragons), you will need to download the installed from the Positron’s GitHub Release Page, as they are still testing some features.\n\n\nYou will then be prompted to select the location you want to save the installer to. We will generally save this to either Downloads or Desktop to make finding it easier.\n\n\n\nOnce the download is complete, double click on the installer, and again accept the license agreement.\n\n\n\nGenerally, Positron will be store its software folder under Program Files.\n\n\n\nNext up, accept the default options for the following screens\n\n\n\n\n\n\nAnd finally, click Install.\n\n\n\n \n\nIf all goes well, you should then see the installation success page." + "text": "Installing Positron\n\n\n\n\n\n\n\n\n.\n\n\nFinally, you will need to install Positron. It will be the integrated development environment (IDE) we will be using for the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right." }, { - "objectID": "course/00_WorkstationSetup/index.html", - "href": "course/00_WorkstationSetup/index.html", - "title": "Workstation Setup", + "objectID": "course/00_WorkstationSetup/Linux.html", + "href": "course/00_WorkstationSetup/Linux.html", + "title": "Installing Software on Linux", "section": "", - "text": "In the previous section, we first set up your GitHub account. Then we modified your GitHub profile and added a README section. Finally, we forked the CytometryInR repository so that you can easily retrieve the new course materials each week.\nIt is now time to install the required software on your computer, which will get your work-station set up with everything needed for this course. Depending on your computers operating system, the installation requirements may differ a bit. In general, you will need to install the following software:\nR website : The programming language we will be using throughout the course.\nPositron : The integrated development environment (IDE) in which we will open, modify and run our code.\nGit : The version control software that will allow us to track changes to our files.\nAdditionally, Windows users will need to install:\nRTools : Used to build R packages from source code.\nYou can find the operating system specific installation walkthroughs below. Once you have completed your specific walkthrough, return to this page and proceed to the next section.\nPlease note: For those using university or company administered computers, please be aware that you may not have the necessary permissions to install these directly, and may need to reach out to your IT department to help get the software installed and running correctly.\nIf you are using your own computer, congratulations, you are your system administrator, and should already have the necessary permissions.", - "crumbs": [ - "About", - "Getting Started", - "00 - Workstation Setup" - ] - }, - { - "objectID": "course/00_WorkstationSetup/index.html#windows", - "href": "course/00_WorkstationSetup/index.html#windows", - "title": "Workstation Setup", - "section": "Windows", - "text": "Windows\n\nInstallation walkthrough for Windows", - "crumbs": [ - "About", - "Getting Started", - "00 - Workstation Setup" - ] + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here\nThis is the software installation walkthrough for those whose computers are running Linux. First off, welcome! Based on our pre-course interest form, there was a suprising number of you daily-drivers out there! However, a CytometryInR interest form is unlikely to be representative of the general population, so please stash all Year of the Linux desktop banners until further notice." }, { - "objectID": "course/00_WorkstationSetup/index.html#macos", - "href": "course/00_WorkstationSetup/index.html#macos", - "title": "Workstation Setup", - "section": "MacOS", - "text": "MacOS\n\nInstallation walkthrough for MacOS", - "crumbs": [ - "About", - "Getting Started", - "00 - Workstation Setup" - ] + "objectID": "course/00_WorkstationSetup/Linux.html#debian-based-distros", + "href": "course/00_WorkstationSetup/Linux.html#debian-based-distros", + "title": "Installing Software on Linux", + "section": "Debian-based Distros", + "text": "Debian-based Distros\n\nInstalling R\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.\n\n\n\nOn the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.\n\n\n\nOnce this is done, select your Linux Distro (or one that shares your package managers format).\n\n\n\nOn the landing page, you will find a bunch of relevant installation information, which is worthwhile giving a read-through when you have time.\n\n\n\nThe process to successfully install R can be summarized as follows:\nUpdate apt/sources.list to include the CRAN repository (allowing access to R packages)\n\n\n\nSince we are running on Debian stable (Trixie), we would add the following line to sources.list\n\n\n\nSo in practice, open sources.list:\n\n\n\nPaste the line, and “Ctrl + O”; “Enter”; “Ctrl + X” to save the changes.\n\n\n\nNext, we will need to retrieve the keyID used to sign. This can be fetched from Ubuntu via the terminal.\n\n\n\n\n\n\nThen we need to export and write it\n\n\n\nWhich if successful, will display the public key.\n\n\n\nWith the above set up, we can proceed via our apt package manager to install both r-base and r-base-dev (which contains the equivalent of Rtools for Windows, or Xcode Command Line Tools for macOS).\n\n\n\n\n\n\n\n\n\nAnd if all goes well, R should now be installed." }, { - "objectID": "course/00_WorkstationSetup/index.html#linux-debian", - "href": "course/00_WorkstationSetup/index.html#linux-debian", - "title": "Workstation Setup", - "section": "Linux (Debian)", - "text": "Linux (Debian)\n\nInstallation walkthrough for Linux", - "crumbs": [ - "About", - "Getting Started", - "00 - Workstation Setup" - ] + "objectID": "course/00_WorkstationSetup/Linux.html#installing-git", + "href": "course/00_WorkstationSetup/Linux.html#installing-git", + "title": "Installing Software on Linux", + "section": "Installing Git", + "text": "Installing Git\n\n# sudo apt install git" }, { - "objectID": "course/00_WorkstationSetup/MacOS.html", - "href": "course/00_WorkstationSetup/MacOS.html", - "title": "Installing Software on MacOS", - "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here\nThis is the software installation walkthrough for those whose computers are running MacOS. Based on our pre-course interest form, you make up a solid proportion of the course participants." + "objectID": "course/00_WorkstationSetup/Linux.html#installing-positron", + "href": "course/00_WorkstationSetup/Linux.html#installing-positron", + "title": "Installing Software on Linux", + "section": "Installing Positron", + "text": "Installing Positron\nFinally, you will need to install Positron. It will be the integrated development environment (IDE) we will be using for the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right.\n\n\n\nYou will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).\n\n\n\nWith the license accepted, you will be able to select distribution and architecture.\n\n\n\nOnce the Download completes, proceed to install the .deb package as you would nornally. GUI example via Discover below.\n\n\n\nDepending on your configurations, you may be asked to exert your sudo powers.\n\n\n\nOnce this completes, you should now be able to launch the software for the first time." }, { - "objectID": "course/00_WorkstationSetup/MacOS.html#installing-r", - "href": "course/00_WorkstationSetup/MacOS.html#installing-r", - "title": "Installing Software on MacOS", + "objectID": "course/00_WorkstationSetup/WindowsSlides.html#installing-r", + "href": "course/00_WorkstationSetup/WindowsSlides.html#installing-r", + "title": "Installing Software on Windows", "section": "Installing R", - "text": "Installing R\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.\n\n\n\nOn the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.\n\n\n\nYou will then select your Operating System, in this case, macOS\n\n\n\nNext, you will need to select the appropiate download based on your computers architecture. On newer Macs (containing M1+ chips) this would the arm64 option on the center left of the screen. For the older Intel (pre-2020) Macs, you would select the x86_64 option. If you are unsure, check your About This Mac tab\n\n\n\nAfter the download has completed, launch the installer\n\n\n\nProceed through the Read Me\n\n\n\nYou will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course).\n\n\n\n\n\n\nNext, you will need to navigate through several pages, keeping the defaults.\n\n\n\nAnd with any luck, you should see that the installation was successful." + "text": "Installing R\n\n\n\n\n\n\n\n\n.\n\n\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page." }, { - "objectID": "course/00_WorkstationSetup/MacOS.html#xcode-command-line-tools", - "href": "course/00_WorkstationSetup/MacOS.html#xcode-command-line-tools", - "title": "Installing Software on MacOS", - "section": "Xcode Command Line Tools", - "text": "Xcode Command Line Tools\nDepending on your version of macOS, you may or may not already have Git installed on your computer. The reason is that it comes bundled within the Xcode Command Line Tools.\nIf this is not your first foray into coding, you may have previously seen an installation pop-up along the lines of “XYZ requires command line developer tools. Would you like to install the tools now?” when installing an IDE (like Positron, Rstudio or Visual Studio Code).\n\n\n\nSince these command line developer tools contain both Git, and also the equivalent of Rtools for Windows, we will need to install them for this course. To get started, first open your terminal.\n\n\n\nNext run the following code:\n\nxcode-select --install\n\n\n\n\nYou will then have the pop-up asking whether you want to install the command line tools (which contain Git). Select Install.\n\n\n\nYou will then be asked to accept the license\n\n\n\nYour installation will then proceed\n\n\n\nAnd if all goes well, the software will finish installing.\n\n\n\nAfter you complete Positron installation (next section), if you check the version control tab on the action bar on the far left side of the screen, you should see the following if Git was installed correctly.\n\n\n\nAlternatively, if you see this, you will need to reattempt the installation." + "objectID": "course/00_WorkstationSetup/WindowsSlides.html#installing-rtools", + "href": "course/00_WorkstationSetup/WindowsSlides.html#installing-rtools", + "title": "Installing Software on Windows", + "section": "Installing RTools", + "text": "Installing RTools\n\n\n\n\n\n\n\n\n.\n\n\nWe will now work on installing Rtools. This software is needed when building R packages from source, which we will need throughout the course for R packages hosted on GitHub.\nTo get started, we will return to the R installation page we visited previously and instead click on the Rtools option." }, { - "objectID": "course/00_WorkstationSetup/MacOS.html#install-positron", - "href": "course/00_WorkstationSetup/MacOS.html#install-positron", - "title": "Installing Software on MacOS", - "section": "Install Positron", - "text": "Install Positron\nFinally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right.\n\n\n\nYou will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).\nWith the license accepted, you will be able to select your operating system and the relevant installer depending on whether you are on an M1+ (ARM) or older Intel (x86) Mac.\n\n\nOnce the Download completes, proceed to install the package as you normally would for any other program." + "objectID": "course/00_WorkstationSetup/WindowsSlides.html#installing-git", + "href": "course/00_WorkstationSetup/WindowsSlides.html#installing-git", + "title": "Installing Software on Windows", + "section": "Installing Git", + "text": "Installing Git\n\n\n\n\n\n\n\n\n.\n\n\nGit is a version control software widely used among software developers and bioinformaticians. We will use it extensively throughout the course, both locally on our computers (to keep track of changes to our files), as well as in combination with GitHub(to maintain online backups of our files).\nWe will first navigate to the website and select the download from Windows option." }, { - "objectID": "course/00_Quarto/index.html", - "href": "course/00_Quarto/index.html", - "title": "Introduction to Quarto", - "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", - "crumbs": [ - "About", - "Getting Started", - "00 - Quarto" - ] + "objectID": "course/00_WorkstationSetup/WindowsSlides.html#installing-positron", + "href": "course/00_WorkstationSetup/WindowsSlides.html#installing-positron", + "title": "Installing Software on Windows", + "section": "Installing Positron", + "text": "Installing Positron\n\n\n\n\n\n\n\n\n.\n\n\nFinally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right." }, { - "objectID": "course/00_Quarto/index.html#renderpreview", - "href": "course/00_Quarto/index.html#renderpreview", + "objectID": "course/00_Quarto/slides.html#renderpreview", + "href": "course/00_Quarto/slides.html#renderpreview", "title": "Introduction to Quarto", "section": "Render/Preview", - "text": "Render/Preview\nThe preview button, at the upper-left end of the Editor, is used to render/knit a quarto document. This triggers the process by which code-chunks are run, and then the outputs are cobbled together into the file format type designated by the YAML header.\n\n\n\n\nHTML\nIn this case, the YAML header’s format argument is set to html. After clicking preview, we can see the various rendering steps appear in the console below. Since no errors occured, the html document was formed succesfully and appears as a file in the left side-bar. Additional, a preview of the document appears in the View tab of the right side-bar, allowing for quick visual inspection.\n\n\n\nAlternatively, we can render a document via the terminal, by entering “quarto render”, followed by the name of the document.\n\n\n\nThis results similar process as what we saw with the preview button\n\n\n\nWe can also open the .html document via our File Explorer, which will open it within our web browser.\n\n\n\nQuarto documents can be rendered (previewed) in other formats besides html. These include pdf, Word documents (docx), and slides (revealjs). This is set by the format argument within the YAML header.\n\n\nPDF\nBy switching the format argument from html to pdf, we can render the document as a pdf\n\n\n\nWe can see the pdf is now listed in the list of files, with a preview shown on the right side-bar.\n\n\n\n\n\nDocx\nWe can also generate Word documents (.docx) as well.\n\n\n\nIn this case, we can see that a Word document file was created, but nothing appears in the View tab. This is because the format is not yet supported for the View tab. We can however open and view the Word document via our File explorer.\n\n\n\nWhich shows a Word Document style output.", - "crumbs": [ - "About", - "Getting Started", - "00 - Quarto" - ] + "text": "Render/Preview\n\n\n\n\n\n\n\n\n.\n\n\nThe preview button, at the upper-left end of the Editor, is used to render/knit a quarto document. This triggers the process by which code-chunks are run, and then the outputs are cobbled together into the file format type designated by the YAML header." }, { - "objectID": "course/00_Quarto/index.html#yaml", - "href": "course/00_Quarto/index.html#yaml", + "objectID": "course/00_Quarto/slides.html#yaml", + "href": "course/00_Quarto/slides.html#yaml", "title": "Introduction to Quarto", "section": "YAML", - "text": "YAML\nWe can additionally provide additional custom inputs to the YAML header. A couple examples include providing the document author and date.\n\n\n\nWhich we can see are updated after we preview/render.", - "crumbs": [ - "About", - "Getting Started", - "00 - Quarto" - ] + "text": "YAML\n\n\n\n\n\n\n\n\n.\n\n\nWe can additionally provide additional custom inputs to the YAML header. A couple examples include providing the document author and date." }, { - "objectID": "course/00_Quarto/index.html#table-of-contents", - "href": "course/00_Quarto/index.html#table-of-contents", + "objectID": "course/00_Quarto/slides.html#table-of-contents", + "href": "course/00_Quarto/slides.html#table-of-contents", "title": "Introduction to Quarto", "section": "Table of Contents", - "text": "Table of Contents\nIn the previous section, we saw that we could provide headings and subheadings to our .qmd file by placing a # at the start of a line in the text portion of the document. A subheading was designated by a ##, with additional hierarchy being designated by appending an additional #.\n\n\n\nWe can use the heading information to generate a table of contents for our document. To do this, we add a toc argument to the yaml header, and set it to TRUE. After rendering, it appears on the upper-right side of the document.\n\n\n\nNotice, that the subheaders do not appear currently within the TOC.\n\n\n\nWe can fix this by setting a toc-expand argument in the YAML to true.", - "crumbs": [ - "About", - "Getting Started", - "00 - Quarto" - ] + "text": "Table of Contents\n\n\n\n\n\n\n\n\n.\n\n\nIn the previous section, we saw that we could provide headings and subheadings to our .qmd file by placing a # at the start of a line in the text portion of the document. A subheading was designated by a ##, with additional hierarchy being designated by appending an additional #." }, { - "objectID": "course/00_Quarto/index.html#code-chunk-arguments", - "href": "course/00_Quarto/index.html#code-chunk-arguments", + "objectID": "course/00_Quarto/slides.html#code-chunk-arguments", + "href": "course/00_Quarto/slides.html#code-chunk-arguments", "title": "Introduction to Quarto", "section": "Code Chunk Arguments", - "text": "Code Chunk Arguments\nAs we briefly touched on in the last section, code-chunks can be modified by including arguments, which affect whether a particular code chunk gets evaluated. In that example, we included a “#| eval: FALSE” to the install commands since we did not want them to be re-run subsequently. We will take a closer look at the other arguments in this section.\n\nEval\nThe code-chunk argument, “Eval”, is used to determine when a code-chunk get’s evaluated. When set to true (or by default if no eval argument is included), the code-chunks contents will be run/executed, and the output will appear. We can see this in the html output, as below the code block, we get back the address of my working directory.\n\n\n\nWhen we switch the Eval argument to FALSE, and then render the document, we can see that the code block remains, but we do not get any output for the code contained within.\nIn every-day practice, we will “use eval: FALSE” arguments when we want to keep the code for later use, but want to manually run the code contained within ourselves.\n\n\n\n\n\nEcho\nThe code-block argument “echo” dictates whether the code within the code-block is displayed within the document. So in the case when “echo: true”, we get both the code displayed, as well as the output that gets returned by the code.\n\n\n\nBy contrast, when “echo: FALSE”, we do not have the code displayed, but do get the output of that code being run.\nIn daily-practice, “echo: FALSE” gets often used when generating plots that we want to include in the report, without the code that generated them being displayed.\n\n\n\n\n\nInclude\nThe next code-chunk argument is include. Unlike echo, which focuses on whether the code is displayed, but still returns the output, include dictates behavior of both the code-block and it’s output. Unlike eval however, it will still run the code, which allows it to be available for the next code-chunk that might need it. When we set “include: false”, no trace of that code-chunk is present in the document. This is useful when making reports where we do not want to include the code used to generate a particular figure.\n\n\n\nBy contrast, when we set “include: true”, the code block and it’s output is once again included within the rendered document.\n\n\n\n\n\nCode-Fold\nOne of my favorites is “code-fold”. When we set it as “code-fold: show”, it displays the code, but provides a drop-down arrow that can be closed to compress the code.\n\n\n\nIn contrast, if we want to make the code-available for those that are interested, but not directly visible, we can set as “code-fold: true”\n\n\n\n\n\nWarnings\nWithin R, when code is executed, in addition to returning the output, R is capable of returning warnings (when something is not as expected, but not sufficient to elicit an error with a complete stop) or a message (text output that gets displayed, often telling about progress). While these are useful when running code yourself, it can be annoying when generating a report and the 2nd page is a bunch of warning text being displayed.\nFor example, when the R package ggcyto is loaded via the library call, it will automatically load several other packages, which typically results in these messages being outputted:\n\n\n\nWe can therefore set that code-chunk’s warning/message arguments to FALSE, therefore silencing the message outputs that would otherwise clutter up our report.", - "crumbs": [ - "About", - "Getting Started", - "00 - Quarto" - ] + "text": "Code Chunk Arguments\n\n\n\n\n\n\n\n\n.\n\n\nAs we briefly touched on in the last section, code-chunks can be modified by including arguments, which affect whether a particular code chunk gets evaluated. In that example, we included a “#| eval: FALSE” to the install commands since we did not want them to be re-run subsequently. We will take a closer look at the other arguments in this section.\n\n\n\n\n\nEval\n\n\n\n\n\n\n\n\n.\n\n\nThe code-chunk argument, “Eval”, is used to determine when a code-chunk get’s evaluated. When set to true (or by default if no eval argument is included), the code-chunks contents will be run/executed, and the output will appear. We can see this in the html output, as below the code block, we get back the address of my working directory." }, { - "objectID": "course/00_Quarto/index.html#text-styles", - "href": "course/00_Quarto/index.html#text-styles", + "objectID": "course/00_Quarto/slides.html#text-styles", + "href": "course/00_Quarto/slides.html#text-styles", "title": "Introduction to Quarto", "section": "Text Styles", - "text": "Text Styles\nQuarto primarily uses Markdown for text styling. Consequently, markdown arguments can be used within the text to change how various text appears.\n\n\n\nFor a regular text, This single asterisk on each side of a word will italicize.\n\n\n\nWhen the number of asterisk is doubled, This word is bolded.\n\n\n\nWhen three asterisk are used, both are applied.\n\n\n\nFor an underscore, the word of interest is surrounded by square brackets “[]”, with “{.underline}” adjacent.", - "crumbs": [ - "About", - "Getting Started", - "00 - Quarto" - ] + "text": "Text Styles\n\n\n\n\n\n\n\n\n.\n\n\nQuarto primarily uses Markdown for text styling. Consequently, markdown arguments can be used within the text to change how various text appears." }, { - "objectID": "course/00_Quarto/index.html#hyperlinks", - "href": "course/00_Quarto/index.html#hyperlinks", + "objectID": "course/00_Quarto/slides.html#hyperlinks", + "href": "course/00_Quarto/slides.html#hyperlinks", "title": "Introduction to Quarto", "section": "Hyperlinks", - "text": "Hyperlinks\nYou can link to a website by surrounding word of interest in [] and placing the url within () adjacent to it.", - "crumbs": [ - "About", - "Getting Started", - "00 - Quarto" - ] + "text": "Hyperlinks\n\n\n\n\n\n\n\n\n.\n\n\nYou can link to a website by surrounding word of interest in [] and placing the url within () adjacent to it." }, { - "objectID": "course/00_Quarto/index.html#images", - "href": "course/00_Quarto/index.html#images", + "objectID": "course/00_Quarto/slides.html#images", + "href": "course/00_Quarto/slides.html#images", "title": "Introduction to Quarto", "section": "Images", - "text": "Images\nYou can place images by adding the following, as long as the file.path to the image is correctly formatted. In my case, this is why I include images folders within my folders to simplify the copy and paste.", - "crumbs": [ - "About", - "Getting Started", - "00 - Quarto" - ] - }, - { - "objectID": "course/00_Positron/index.html", - "href": "course/00_Positron/index.html", - "title": "Using Positron", - "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", - "crumbs": [ - "About", - "Getting Started", - "00 - Positron" - ] + "text": "Images\n\n\n\n\n\n\n\n\n.\n\n\nYou can place images by adding the following, as long as the file.path to the image is correctly formatted. In my case, this is why I include images folders within my folders to simplify the copy and paste." }, { - "objectID": "course/00_Positron/index.html#console", - "href": "course/00_Positron/index.html#console", + "objectID": "course/00_Positron/slides.html#console", + "href": "course/00_Positron/slides.html#console", "title": "Using Positron", "section": "Console", - "text": "Console\nAt the bottom of the sceen, you will first see the Console Tab. This is the tab where your lines of code when executed (run) will appear, as well as any messages, warnings or errors that get returned. On the right side of the console, you can find several buttons, among them restart R and delete session (for when you need a fresh start), and clear console (which keeps all previously run outputs and objects, but clears away the displayed text within the console).", - "crumbs": [ - "About", - "Getting Started", - "00 - Positron" - ] + "text": "Console\n\n\n\n\n\n\n\n\n.\n\n\nAt the bottom of the sceen, you will first see the Console Tab. This is the tab where your lines of code when executed (run) will appear, as well as any messages, warnings or errors that get returned. On the right side of the console, you can find several buttons, among them restart R and delete session (for when you need a fresh start), and clear console (which keeps all previously run outputs and objects, but clears away the displayed text within the console)." }, { - "objectID": "course/00_Positron/index.html#terminal", - "href": "course/00_Positron/index.html#terminal", + "objectID": "course/00_Positron/slides.html#terminal", + "href": "course/00_Positron/slides.html#terminal", "title": "Using Positron", "section": "Terminal", - "text": "Terminal\nRight next to the Console tab is your Terminal tab. While the console tab is primarily used to run R code within Positron, the terminal is the interface where code containing system commands directed at at your computer is entered. We will use this less frequently, primarily in two context: 1) rendering Quarto documents, and 2) commiting changes to version control. Among the buttons on the right-side of the terminal to make note of are the + button to add a new terminal, and the trash/garbage can button to kill (stop) the terminal.\n\n\n\nThe other tabs (Problems, Output, Ports, Debug Console) are used less frequently. I usually will Problems and Debug when something goes wrong with the code, as various warning and error messages will end up being displayed there.", - "crumbs": [ - "About", - "Getting Started", - "00 - Positron" - ] + "text": "Terminal\n\n\n\n\n\n\n\n\n.\n\n\nRight next to the Console tab is your Terminal tab. While the console tab is primarily used to run R code within Positron, the terminal is the interface where code containing system commands directed at at your computer is entered. We will use this less frequently, primarily in two context: 1) rendering Quarto documents, and 2) commiting changes to version control. Among the buttons on the right-side of the terminal to make note of are the + button to add a new terminal, and the trash/garbage can button to kill (stop) the terminal." }, { - "objectID": "course/00_Positron/index.html#help", - "href": "course/00_Positron/index.html#help", + "objectID": "course/00_Positron/slides.html#help", + "href": "course/00_Positron/slides.html#help", "title": "Using Positron", "section": "Help", - "text": "Help\nWhen trying to evaluate how a particular function is working in R, you can hover over it and positron will open up the documentation for that particular function if available, alternatively, you can enter ?theParticularFunctionsName in the console and hit enter to similarly view what is occuring.", - "crumbs": [ - "About", - "Getting Started", - "00 - Positron" - ] + "text": "Help\n\n\n\n\n\n\n\n\n.\n\n\nWhen trying to evaluate how a particular function is working in R, you can hover over it and positron will open up the documentation for that particular function if available, alternatively, you can enter ?theParticularFunctionsName in the console and hit enter to similarly view what is occuring." }, { - "objectID": "course/00_Positron/index.html#variables", - "href": "course/00_Positron/index.html#variables", + "objectID": "course/00_Positron/slides.html#variables", + "href": "course/00_Positron/slides.html#variables", "title": "Using Positron", "section": "Variables", - "text": "Variables\nOn the upper-portion of the Secondary Side Bar, we can find the Session window, containing the Variables tab. As you run (execute) lines of code, and different variables, objects and functions are created, these become visible under the variables tab on the upper right.\n\n\n\nFor some types of objects (generally data.frames and other matrix-like objects), you can click on their listing under variables to expand to see additional details about the object (column names, etc.) as well as view a larger version which will appear within the Editor window.", - "crumbs": [ - "About", - "Getting Started", - "00 - Positron" - ] + "text": "Variables\n\n\n\n\n\n\n\n\n.\n\n\nOn the upper-portion of the Secondary Side Bar, we can find the Session window, containing the Variables tab. As you run (execute) lines of code, and different variables, objects and functions are created, these become visible under the variables tab on the upper right." }, { - "objectID": "course/00_Positron/index.html#plots", - "href": "course/00_Positron/index.html#plots", + "objectID": "course/00_Positron/slides.html#plots", + "href": "course/00_Positron/slides.html#plots", "title": "Using Positron", "section": "Plots", - "text": "Plots\nSimilarly, any generated Plots or Documents will appear within the Secondary Side Bar, either under Plots (bottom) or Viewer (top) tabs.", - "crumbs": [ - "About", - "Getting Started", - "00 - Positron" - ] + "text": "Plots\n\n\n\n\n\n\n\n\n.\n\n\nSimilarly, any generated Plots or Documents will appear within the Secondary Side Bar, either under Plots (bottom) or Viewer (top) tabs." }, { - "objectID": "course/00_Positron/index.html#view", - "href": "course/00_Positron/index.html#view", + "objectID": "course/00_Positron/slides.html#view", + "href": "course/00_Positron/slides.html#view", "title": "Using Positron", "section": "View", - "text": "View\nOn the upper bar multiple tabs can be found, which we will explore in due time. Most useful to point out is the View tab. If you accidentally close your console, session or plots window, and are trying to get them to reapper, you would need to reselect them from this tab.", - "crumbs": [ - "About", - "Getting Started", - "00 - Positron" - ] + "text": "View\n\n\n\n\n\n\n\n\n.\n\n\nOn the upper bar multiple tabs can be found, which we will explore in due time. Most useful to point out is the View tab. If you accidentally close your console, session or plots window, and are trying to get them to reapper, you would need to reselect them from this tab." }, { - "objectID": "course/00_Positron/index.html#pages", - "href": "course/00_Positron/index.html#pages", + "objectID": "course/00_Positron/slides.html#pages", + "href": "course/00_Positron/slides.html#pages", "title": "Using Positron", "section": "Pages", - "text": "Pages\nThe pages tab and the left-side bar show you everything that is currently within your project folder, including all the folders, and files. Once version control with Git is initiated, new files are relected showing up as green text and a dot, while modified tracked files are reflected by light brown text and a dot.\n\n\n\nThe dropdown arrows can be used to open and close specific folders to allow for better organization. There is also a scrollbar on the right-side of the side-bar to scroll through the entire folders contents.", - "crumbs": [ - "About", - "Getting Started", - "00 - Positron" - ] + "text": "Pages\n\n\n\n\n\n\n\n\n.\n\n\nThe pages tab and the left-side bar show you everything that is currently within your project folder, including all the folders, and files. Once version control with Git is initiated, new files are relected showing up as green text and a dot, while modified tracked files are reflected by light brown text and a dot." }, { - "objectID": "course/00_Positron/index.html#search", - "href": "course/00_Positron/index.html#search", + "objectID": "course/00_Positron/slides.html#search", + "href": "course/00_Positron/slides.html#search", "title": "Using Positron", "section": "Search", - "text": "Search\nThe search tab on the left side bar is something that I use routinely.\n\n\n\nIt can help locate code that you had been working on, but have since forgotten where it is at. Here is an example of finding the files where I had used a function that needed modifying within a local project folder’s files.\n\n\n\nSimilarly, if you need to replace a particular character string with another, the replace with field below can help simplify the task without having to track down and change 20 lines across 5 files.", - "crumbs": [ - "About", - "Getting Started", - "00 - Positron" - ] + "text": "Search\n\n\n\n\n\n\n\n\n.\n\n\nThe search tab on the left side bar is something that I use routinely." }, { - "objectID": "course/00_Positron/index.html#extensions", - "href": "course/00_Positron/index.html#extensions", + "objectID": "course/00_Positron/slides.html#extensions", + "href": "course/00_Positron/slides.html#extensions", "title": "Using Positron", "section": "Extensions", - "text": "Extensions\nOn the far-left side we can find the Activity bar, which contains several tabs. Which tab you have selected will then dictate the contents of your left side-bar.\nOccupying the left side bar are several tabs. One of these is Extensions, which shows “Plugins” (or the VScode equivalent) that extend the functionality of Positron further. The ones you have installed may vary, but the main ones in context of this course are Air (provides color and highlights syntax for R code to make interpretation easier) as well as Quarto (for rendering the various document types).", - "crumbs": [ - "About", - "Getting Started", - "00 - Positron" - ] + "text": "Extensions\n\n\n\n\n\n\n\n\n.\n\n\nOn the far-left side we can find the Activity bar, which contains several tabs. Which tab you have selected will then dictate the contents of your left side-bar.\nOccupying the left side bar are several tabs. One of these is Extensions, which shows “Plugins” (or the VScode equivalent) that extend the functionality of Positron further. The ones you have installed may vary, but the main ones in context of this course are Air (provides color and highlights syntax for R code to make interpretation easier) as well as Quarto (for rendering the various document types)." }, { - "objectID": "course/00_Positron/index.html#git", - "href": "course/00_Positron/index.html#git", + "objectID": "course/00_Positron/slides.html#git", + "href": "course/00_Positron/slides.html#git", "title": "Using Positron", "section": "Git", - "text": "Git\nThe Git tab on the left side bar is where once version control is initiated for the project folder, we can see changes that have occurred to the individual files since the last commit. These changes can be added to a new commit by clicking on the + sign. This will be covered more extensively in the next section\n\n\n\nSimilarly, if you want to discard a change that has occured, the circular arrow will revert to the last commited version. Selecting and pressing the delete button will similarly work.\n\n\n\nSelecting the … options will highlight all the various git functions, some of which we will cover more extensively in the next section and throughout the course.", - "crumbs": [ - "About", - "Getting Started", - "00 - Positron" - ] - }, - { - "objectID": "course/00_Homeworks/index.html", - "href": "course/00_Homeworks/index.html", - "title": "Getting Help", - "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", - "crumbs": [ - "About", - "Getting Started", - "00 - Getting Help" - ] + "text": "Git\n\n\n\n\n\n\n\n\n.\n\n\nThe Git tab on the left side bar is where once version control is initiated for the project folder, we can see changes that have occurred to the individual files since the last commit. These changes can be added to a new commit by clicking on the + sign. This will be covered more extensively in the next section" }, { - "objectID": "course/00_Homeworks/index.html#discussions-forum", - "href": "course/00_Homeworks/index.html#discussions-forum", + "objectID": "course/00_Homeworks/slides.html#discussions-forum", + "href": "course/00_Homeworks/slides.html#discussions-forum", "title": "Getting Help", "section": "Discussions Forum", - "text": "Discussions Forum\nOn the course’s GitHub repository, we have opened up a Discussions page that we plan to use as a community forum. We hope that it will serve multiple functions, from providing a better sense of community for the online participants, to facilitating asking and receiving help on something that is not clear, provide feedback about something that it not working out, as well as a place to celebrate and show off your coding wins.\n\nTo keep the Discussions forum semi-organized, we have set up several categories, please select the appropiate category when opening a new discussion!\n\n\n\nCode of Conduct\n\nWe ask that all course participants read and adhere to the spirit of our Code of Conduct. We are all human, at different points in our learning journeys, so what may be obvious to you at your point of your learning journey may have necessarily be obvious to someone just getting started. This course is our giving back to those in the community, but is on a voluntary basis in addition to our regular workload. While we try to reply quickly, sometimes our cell sorters fully melt down sending everything into chaos. We will reply when we can.\n\n\n\n\nAnnouncements\n\nWhen we send out an email to all participants, we will also repost it as an announcement. This ensures that even if you are not on our mailing list, you will still be able to have access to important information and course updates.\n\n\n\n\n\n\n\nGeneral\n\nThis section category can be used for any discussions that you think are worth having, that don’t fall under any of the other category. Good examples are continuing a discussion that was held during one of the livestreams; wanting to discuss and dive further into a given week’s topic; or bringing in additional resources that you found useful to understandingn something that didn’t click initially. This space is for the community to shape as they see best.\n\n\n\n\n\n\n\nIdeas\n\nHave an idea for a new topic or a way to improve the course? We would love to hear them. Provide as many details, and ideally, an example, and if it is doable, we will try to implement them.\n\n\n\n\n\n\n\nIntroductions\n\nOnline courses can be odd in terms of replicating in-person dynamics. Fortunately, we have gathered the largest cohort of “cytometrist with no-to-little flow experience trying to learn R at the same time” that the world has ever seen, so best to take advantage of this while we can. Treat this section as if we had just met at a conference, tell us about yourself, what brings you here, and what you want to hopefully be able to do after the course ends.", - "crumbs": [ - "About", - "Getting Started", - "00 - Getting Help" - ] + "text": "Discussions Forum\n\n\n\n\n\n\n\n\n.\n\n\nOn the course’s GitHub repository, we have opened up a Discussions page that we plan to use as a community forum. We hope that it will serve multiple functions, from providing a better sense of community for the online participants, to facilitating asking and receiving help on something that is not clear, provide feedback about something that it not working out, as well as a place to celebrate and show off your coding wins." }, { - "objectID": "course/00_Homeworks/index.html#polls", - "href": "course/00_Homeworks/index.html#polls", + "objectID": "course/00_Homeworks/slides.html#polls", + "href": "course/00_Homeworks/slides.html#polls", "title": "Getting Help", "section": "Polls", - "text": "Polls\n\nOccasionally, we will need to gather community feedback on what is working and what is not working. We will sporadically post Polls for this purpose.\n\n\n\n\n\n\nQ&A\n\nThe Questions and Answers (Q&A) section is where you go if something is not clear, not working, and you are trying to troubleshoot your way through it. First thing before posting, search! to see if someone has already asked the question. If you don’t find anything, go ahead and open a new discussion.\nSince we are not at your computer, and don’t have your dataset, when troubleshooting it is best to include a minimal reproducible example of the issuen you are encountering, slimming down the number of files needed to be transferred, and generalizing down the code so that other course participants and instructors can follow along. If this is not doable, or if the problem requires added context (and larger files), create a new repository on your GitHub, make it public, and share the links to it in your post. The goal would be to download the folder and be able to replicate the issue that you are encountering.\n\n\n\n\n\n\n\n\n\n\nShow and Tell\n\nWhere Q&A section is for getting help on code that is frustratingly not working, Show and Tell is where to go and celebrate when you finally get things to work. Share your wins, show us the extra pretty graphs, bizarre autofluorescence signatures, or odd outputs that just make you laugh.", - "crumbs": [ - "About", - "Getting Started", - "00 - Getting Help" - ] + "text": "Polls\n\n\n\n\n\n\n\n\n\n.\n\n\nOccasionally, we will need to gather community feedback on what is working and what is not working. We will sporadically post Polls for this purpose." }, { - "objectID": "course/00_Homeworks/index.html#issues", - "href": "course/00_Homeworks/index.html#issues", + "objectID": "course/00_Homeworks/slides.html#issues", + "href": "course/00_Homeworks/slides.html#issues", "title": "Getting Help", "section": "Issues", - "text": "Issues\nMost of the time, if you are having trouble getting you code to run, you should first stop after some initial troubleshooting should be to open a new Discussion under the Q&A category. Here you will be able to get both community and instructor help and suggestions to hopefully resolve whatever is going on.\n\nThe Issues page is primarily meant for course-specific problems that require the course instructor intervention to fix. For example, we release a new week of material, and while it runs fine for both Windows and Linux, the code fails to run for all MacOS users. While you may be able to find workarounds on your own, it’s ultimately our responsibility to help provide a solution so that everyone can move forward. This is the situation where opening an Issue is appropiate.\n\n\n\nSimilarly, if our code contains a wrong argument, is returning a deprecation warning, etc. open an issue to let us know. While we may not be able to fix something that is not directly related to our code, we can redirect it to the package maintainers so that they can fix the issue.\nAnd likewise, if you find multiple typos in the documentation, you can open an issue and propose carrying out a pull-request to fix them.", - "crumbs": [ - "About", - "Getting Started", - "00 - Getting Help" - ] + "text": "Issues" }, { - "objectID": "course/00_Homeworks/index.html#submitting-take-home-problems", - "href": "course/00_Homeworks/index.html#submitting-take-home-problems", + "objectID": "course/00_Homeworks/slides.html#submitting-take-home-problems", + "href": "course/00_Homeworks/slides.html#submitting-take-home-problems", "title": "Getting Help", "section": "Submitting Take-Home Problems", - "text": "Submitting Take-Home Problems\nEach week, during the course, we introduce and cover the main concepts for the particular concept. Our goal is to provide you with the necessary code and enough code to be able to get the jist. However, to become comfortable and be able to apply what you have learned, you will need to explore beyond our examples, try it with your own datasets, encounter things that don’t work, and troubleshoot your way through them. It’s this cycle of venturing into the unknown that develops strong coding skills that are needed to overcome any barrier you encounter. The goal of the take-home questions is to provide some less curated problems that will take a little longer to answer to help get you started on your own exploration of the topic.\nAs previously mentioned, these take-home problems are completely optional. If you are in the middle of solving them and want to seek feedback from then community and course instructors, open a Discussion under the general category is the way to go.\nHowever, if you have completed them, and want course instructor feedback, you can submit them to us in the form of a pull-request to the CytometryInR repo’s homework branch. We will take a look, offer constructive suggestions, and when ready merge the solution. This will also result in GitHub listing you as a contributor to the course.\nWe will outline the basic steps of how to set up and open a pull-request, to help simplify the process.\n\nSync your Fork\nFirst off, make sure to Sync your fork of the Cytometry in R project. That makes sure that all the commits present are up-to-date and simplifies the process of having the pull-request being merged.\n\n\n\n\n\n\n\n\n\n\n\nPull to Local\nHaving Synced your branch on GitHub, return to your computer, open the CytometryInR repository and pull in the changes locally.\n\n\n\n\nCreate own Folder under Homeworks\nUnder the course folder, you will find folders for each week. Within these folders find the homework folder. This will appear empty except for a README file with ionstructions. It is within this folder you will need to create your own folder.\nTo ensure there are no conflicts on the pull-request merge, please use your GitHub username as the folder name.\n\n\n\nOnce you have your folder inside homework, go ahead and copy anything you are turning in from their respective working project folders. Remember, the goal is minimal reproducible example is the goal. Rendered Quarto Documents are preferred, but we will also accept scripts and small data files and images. a README.MD file with anything you want me to know,\n\n\n\n\n\n\n\n\nSign off Commit\nNow that everything is present, Sign Off and Commit the change.\n\n\n\n\n\nPush Branch to GitHub.\nProceed to push the branch to GitHub.\n\n\n\n\n\nRe-sync if necessary\nIf additional changes have occured to the parent CytometryInR repository, go ahead and update your branch. As long as your edits occurred within your folder inside homework folders, they should still be able to merge.\n\n\n\n\n\n\n\n\nOpen a pull-request\nTo start a pull request, click to see how your commit is ahead by\n\n\n\nNext, switch from the parent CytometryInR main branch (used for the website and course) to the homework branch for that respective week (used for the take-home problems).\n\n\n\nOnce this is done, select Pull request\n\n\n\nMake sure to triple check it’s bound for the homeworks branch. If you see that it is not capable of merging, verify that your commit only contains files within your respective homework username folder. Fill in the required fields of the pull request.\n\n\n\nAnd when ready, create the pull request.\n\n\n\n\nWait for Feedback\nOn our end, once you have created a pull request, we will review your work, offer constructive suggestions, etc. If I ask for revisions, all you would need to do is update your files, commit again on your side of the local forked repository.\n\n\n\n\n\nFinal Review and Merge\nIf all is good, we will merge the pull request and your solution to the take-home problems will now be available on the homework branch.\n\n\n\n\n\nAfter course\nAfter the course completes, we will merge homework branch with the main branch, making the community solutions to the take-home problems additional coding examples that can be used by others following along after the course concludes.", - "crumbs": [ - "About", - "Getting Started", - "00 - Getting Help" - ] - }, - { - "objectID": "course/00_GitHub/index.html", - "href": "course/00_GitHub/index.html", - "title": "Using GitHub", - "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", - "crumbs": [ - "About", - "Getting Started", - "00 - GitHub" - ] + "text": "Submitting Take-Home Problems\n\n\n\n\n\n\n\n\n.\n\n\nEach week, during the course, we introduce and cover the main concepts for the particular concept. Our goal is to provide you with the necessary code and enough code to be able to get the jist. However, to become comfortable and be able to apply what you have learned, you will need to explore beyond our examples, try it with your own datasets, encounter things that don’t work, and troubleshoot your way through them. It’s this cycle of venturing into the unknown that develops strong coding skills that are needed to overcome any barrier you encounter. The goal of the take-home questions is to provide some less curated problems that will take a little longer to answer to help get you started on your own exploration of the topic." }, { - "objectID": "course/00_GitHub/index.html#creating-an-account", - "href": "course/00_GitHub/index.html#creating-an-account", + "objectID": "course/00_GitHub/slides.html#creating-an-account", + "href": "course/00_GitHub/slides.html#creating-an-account", "title": "Using GitHub", "section": "Creating an Account", - "text": "Creating an Account\nWe will first navigate to the GitHub homepage. If you haven’t previously created an account, click on the button to sign up for an account.\n\n\n\nOn the sign-up page, you will fill in various details needed to create an account. Please remember that GitHub usernames are visible to others. Additionally, if you end up sharing code with others as part of a manuscript, or use GitHub to create a personal portfolio website in the future, your username will appear as part of the URL.\nFor example, in my case, my user name is DavidRach, so my GitHub profile ends up as: https://github.com/DavidRach. For our course, the core’s GitHub user name is UMGCCCFCSR, so the github profile ends up as https://github.com/UMGCCCFCSR, while the course website ends up as https://umgcccfcsr.github.io/CytometryInR/\n\n\n\nOnce you have entered your new account information, you will need your account creation by entering the code sent to the email address that you provided.\n\n\n\nOnce account creation has been confirmed, please proceed to login to GitHub for the first time.", - "crumbs": [ - "About", - "Getting Started", - "00 - GitHub" - ] + "text": "Creating an Account\n\n\n\n\n\n\n\n\n.\n\n\nWe will first navigate to the GitHub homepage. If you haven’t previously created an account, click on the button to sign up for an account." }, { - "objectID": "course/00_GitHub/index.html#github-profile", - "href": "course/00_GitHub/index.html#github-profile", + "objectID": "course/00_GitHub/slides.html#github-profile", + "href": "course/00_GitHub/slides.html#github-profile", "title": "Using GitHub", "section": "GitHub Profile", - "text": "GitHub Profile\nUpon creating a brand new account, your GitHub homepage will initially look rather empty, and can be intimidating to navigate for the first time.\nFor now, on the upper right, go ahead and click on the default profile picture icon…\n\n\n\nAnd then select Profile…\n\n\n\nYou are now on your public GitHub profile page. For a newly created account, it will look something like this:\n\n\n\nFor a more established account, this page will look a little different, and can be customized to highlight various projects that you are working on.\nFor this course, we will have you set up a basic GitHub profile page for now, although you are free to customize and personalize it as much as you may want to in the future!\nTo start, first select the edit profile button on the left below the default profile icon.\n\n\n\nYou can then proceed to fill in any details that you feel are relevant and are comfortable sharing.\n\n\n\nWith the quick access details filled in, it is now time to navigate to the Settings tab. You will return to the previous menu dropdown on the upper right, and instead of selecting Profile, click on the Settings option.\n\n\n\nYou should now end up within your Public Profile Settings page.\nFeel free to edit the default profile picture, and any other fields that you feel are relevant. Once done, continue to scroll down the page past ORCID ID.\n\n\n\nWhen you reach Contributions and Activity, go ahead and select the option to include private repositories in the activity summary graphic. Then scroll down and click save. You will now be returned to your GitHub profile page.\n\n\n\nAt the top of the profile, you will see a “Your contributions” calendar graph. For a new account, it will look like this:\n\n\n\nIf you are just starting out, this chart will be mostly empty, but will fill in as you work on projects, see here as an example.\nEvery time you save your code (ie. make a commit), the activity will be reflected in this chart. By clicking the option in settings, code made within a private repository will remain private, but will count toward your contribution chart. As you progress through the course, this will provide a nice visual reminder of the progress you have made, and the obstacles that you have overcome.", - "crumbs": [ - "About", - "Getting Started", - "00 - GitHub" - ] + "text": "GitHub Profile\n\n\n\n\n\n\n\n\n.\n\n\nUpon creating a brand new account, your GitHub homepage will initially look rather empty, and can be intimidating to navigate for the first time.\nFor now, on the upper right, go ahead and click on the default profile picture icon…" }, { - "objectID": "course/00_GitHub/index.html#github-readme", - "href": "course/00_GitHub/index.html#github-readme", + "objectID": "course/00_GitHub/slides.html#github-readme", + "href": "course/00_GitHub/slides.html#github-readme", "title": "Using GitHub", "section": "GitHub ReadMe", - "text": "GitHub ReadMe\nWith this done, we modify your GitHub profile by adding one customized element, a ReadMe page. This will be used for a couple projects during the course, and can be personalized further in the future.\nTo create a ReadMe page for your profile, we will navigate to the upper right of the screen and click on the + sign.\n\n\n\nWe will then select the Create New Repository option.\n\n\n\nYou will next create a repository (folder), naming it exactly the same as your username. This will be recognized by GitHub as being a special type of repository corresponding to the ReadMe section of your profile.\nFor options, leave the visibility as Public, and Add README set to On. And proceed to Create Repository.\n\n\n\nHaving created the repository (folder), you will see it has been populated by a few default files. For now, you will be editing the README.md file. On a new repository, the easiest way to access it is by clicking the green option on the right side of your screen.\n\n\n\nWith the README.md file now opened, you will be able to see generic filler text that is suggested by GitHub.\nFor this course, I will ask you to add a couple elements for now. You are free to return and further personalize it later if you wish to do so.\n\n\n\nThe type of file that we are working with is a Markdown file, which can allow for a bunch of customizations which we will cover throughout the course.\nFor now, please add and customize the following questions:\nCytometry In R\nLocation: Baltimore, Maryland, USA\nMy Favorite Fluorophore/Metal-Isotope: Spark Blue 550\nPrevious Coding Experience: Repeatedly Calling IT\nWhat I Hope to Get From This Course: A faster way to match FlowSOM clusters to their likely cell type.\n\n\n\nNext, to save you will select the green “Commit changes” button. We will cover the meaning of “Commit” more in-depth during the Git section.\nFor now, write a short summary of the change you made to the file in the “Commit message”, and any additional details within the “Extended description” field. When ready, click the green “Commit changes” button.\n\n\n\nYou will now be able to see the updated README.md file, as you can see in our example below. To make additional edits, you would select the pencil icon on the right-center side of the screen.\n\n\n\nNext, navigate back to your profile page (by clicking on either your username or the Overview option on the tabs).\nYou will see that the README file contents are now displayed on the upper portion of your GitHub profile. Feel free to circle back and customize this further to your liking.\nIn this last example, we created your first repository (folder). Since this is public, it is now shown below the README section of the profile under your repositories. You can also see that your commits made in the process of making the changes are now shown both in the Contributions graph, and under the Contributor Activity summary at the bottom of the page.", - "crumbs": [ - "About", - "Getting Started", - "00 - GitHub" - ] + "text": "GitHub ReadMe\n\n\n\n\n\n\n\n\n.\n\n\nWith this done, we modify your GitHub profile by adding one customized element, a ReadMe page. This will be used for a couple projects during the course, and can be personalized further in the future.\nTo create a ReadMe page for your profile, we will navigate to the upper right of the screen and click on the + sign." }, { - "objectID": "course/00_GitHub/index.html#github-repository", - "href": "course/00_GitHub/index.html#github-repository", + "objectID": "course/00_GitHub/slides.html#github-repository", + "href": "course/00_GitHub/slides.html#github-repository", "title": "Using GitHub", "section": "GitHub Repository", - "text": "GitHub Repository\nHaving set up your GitHub profile, it now is time to make sure you have access to our course materials. We will have you navigate to our course’s GitHub profile\nOn the profile page, you will be able to see our version of the README, our repositories, and the Contributions graph and Contribution activity sections.\nPlease click on the CytometryInR to navigate to its repository (folder)\n\n\n\nOn this page, you will see several elements that you will be circling back to throughout the course.\nFor our course, we will be extentsively ussing the Discussions page as a community forum. If you have any questions, are looking for feedback, or want to show off something that you worked on, this is the place for it. This will also help make sure\n\n\n\nThe Issues tab is where you will need to go to open an Issue if you encounter a bug (or major documentation typo), so that I can cicle back and correct them when I have the chance.\n\n\n\nTo submit the optional take-home problems, you would turn in these problems by going to the Pull Request tab, and initiating a pull request between your forked version of the project and our “homework” branch (more details on this later).\n\n\n\nOptionally, you can “Star” a repository. This is basically the GitHub equivalent of liking a project. In our case, we will often star a repository since it will be saved under the Stars tab of our profile, which makes finding it again significantly easier a few weeks later after forgetting the repository name.\n\n\n\nTo see projects that you have starred, you can select the Stars option from the same dropdown you used to get to Settings.\n\n\n\nOr from your GitHub profile, you can see these under Stars tab.", - "crumbs": [ - "About", - "Getting Started", - "00 - GitHub" - ] + "text": "GitHub Repository\n\n\n\n\n\n\n\n\n.\n\n\nHaving set up your GitHub profile, it now is time to make sure you have access to our course materials. We will have you navigate to our course’s GitHub profile\nOn the profile page, you will be able to see our version of the README, our repositories, and the Contributions graph and Contribution activity sections.\nPlease click on the CytometryInR to navigate to its repository (folder)" }, { - "objectID": "course/00_GitHub/index.html#forking-cytometryinr", - "href": "course/00_GitHub/index.html#forking-cytometryinr", + "objectID": "course/00_GitHub/slides.html#forking-cytometryinr", + "href": "course/00_GitHub/slides.html#forking-cytometryinr", "title": "Using GitHub", "section": "Forking CytometryInR", - "text": "Forking CytometryInR\nBefore we go further, we will need you to make your own copy of the course repository (ie. fork it). This will allow you to quickly retrieve all the new materials and code corrections by simply rereshing (ie. syncing) your forked version with our upstream parent branch once a week.\n\n\nTo fork the course repository, you will select the “Fork repository” option on the upper-center portion of your screen.\n\n\n\nBy “Fork-ing” a repository, you are basically copying the contents from that repository to a newly created repository on your own GitHub. Forked projects are still linked to the original (parent) fork, and can retrieve any updates via syncing, as well as return changes via a pull request.\nFor this course, when you create the fork, keep the existing repository name (“CytometryInR”). Importantly, select the copy main branch option. This will ensure you only get the code and data needed for the course copied over, and don’t end up with your entire hard-drive filled will website elements, or other people’s solutions to the take-home problems.\n\n\n\nOnce you have created the fork, you will see your copy of the forked repository under your own username. Seeing as you have just now forked the project, you will see the notification that you are up to date with the existing version of the CytometryInR course repository.\nAs we go through the course, and new material is released each week on Sunday at 2200 EST (Monday 0300 GMT+0), you will see this changed to behind the main branch by a number of commits, and have the option to sync in the changes to your fork to gain access to that week’s material.\n\n\n\nIf you remember, previously under your GitHub profile, the Repositories tab only contained the repository corresponding to your ReadMe section.\n\n\n\nYou should however now be able to see your fork of the CytometryInR repository. As you add project specific repositories throughout the course, they will also appear here.", - "crumbs": [ - "About", - "Getting Started", - "00 - GitHub" - ] - }, - { - "objectID": "course/00_Git/index.html", - "href": "course/00_Git/index.html", - "title": "Version Control with Git", - "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", - "crumbs": [ - "About", - "Getting Started", - "00 - Git" - ] + "text": "Forking CytometryInR\n\n\n\n\n\n\n\n\n.\n\n\nBefore we go further, we will need you to make your own copy of the course repository (ie. fork it). This will allow you to quickly retrieve all the new materials and code corrections by simply rereshing (ie. syncing) your forked version with our upstream parent branch once a week." }, { - "objectID": "course/00_Git/index.html#new-folder-from-template", - "href": "course/00_Git/index.html#new-folder-from-template", + "objectID": "course/00_Git/slides.html#new-folder-from-template", + "href": "course/00_Git/slides.html#new-folder-from-template", "title": "Version Control with Git", "section": "New Folder from Template", - "text": "New Folder from Template\nSince Positron can use multiple programming languages, when we select “New Folder from Template” we will be asked what kind of folder template we want to use. Since we are working in R, we will select the “R Project” option.\n\n\n\nWe will next be asked to name the new project folder and a storage location.\nOne thing I would like to remind everyone who is just starting to code is that it is best to avoid using special characters (ex. @ $ # ^ ! ; : ,) in any folder or file name. This is because when coding, these can be misinterpreted as commands.\nWhile spaces are generally okay, it is often to best stick to to stick to hyphens (-), underscores (_). We will explore naming conventions in more depth at a later time.\n\n\n\nAnother useful thing to know when getting started with version control, it is best to save your files within your local computer, avoid using OneDrive or other cloud storage options for the time reason. The reason behind is that permissions to write/save to the cloud locations can sometimes be quite finicky, and some autosave/indexing behaviors can cause issues. akes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder.\nHaving named our new Project Folder, and designated a storage location, go ahead and check the Initialize Git Repository option. This will indicate to version control to monitor content and changes to files within this folder.\n\n\n\nThe next setup screen will verify which version of R you wish to use. Since we are just getting started, your most recent version of R (usually system) should work. We will also leave the “renv” (reproducible environment setup) option unchecked for the time being (we will revisit the concept later in the course).\n\n\n\nAnd if all goes well, we should see the “New Folder Created” popup.", - "crumbs": [ - "About", - "Getting Started", - "00 - Git" - ] + "text": "New Folder from Template\n\n\n\n\n\n\n\n\n.\n\n\nSince Positron can use multiple programming languages, when we select “New Folder from Template” we will be asked what kind of folder template we want to use. Since we are working in R, we will select the “R Project” option." }, { - "objectID": "course/00_Git/index.html#creating-subfolders", - "href": "course/00_Git/index.html#creating-subfolders", + "objectID": "course/00_Git/slides.html#creating-subfolders", + "href": "course/00_Git/slides.html#creating-subfolders", "title": "Version Control with Git", "section": "Creating SubFolders", - "text": "Creating SubFolders\nOnce your new project folder has opened, you should be seeing the main layout elements that we briefly covered in the Positron walk-through.\nFor this section, we will primarily be focused on what is happening within the primary side bar on the left, where changes to the individual files within the folder since the last save/commit will be reflected by colored text.\nFor my own projects, there are some elements of organization that I go ahead and add for each new folder. These include both a data and an images subfolders to help keep things a little more organized.\nTo create these folders, we would click on the respective add folder (+) button on the side bar. Files and Folders can be clicked and dragged within the primary side bar to move things to new folder locations.", - "crumbs": [ - "About", - "Getting Started", - "00 - Git" - ] + "text": "Creating SubFolders\n\n\n\n\n\n\n\n\n.\n\n\nOnce your new project folder has opened, you should be seeing the main layout elements that we briefly covered in the Positron walk-through.\nFor this section, we will primarily be focused on what is happening within the primary side bar on the left, where changes to the individual files within the folder since the last save/commit will be reflected by colored text.\nFor my own projects, there are some elements of organization that I go ahead and add for each new folder. These include both a data and an images subfolders to help keep things a little more organized.\nTo create these folders, we would click on the respective add folder (+) button on the side bar. Files and Folders can be clicked and dragged within the primary side bar to move things to new folder locations." }, { - "objectID": "course/00_Git/index.html#creating-files", - "href": "course/00_Git/index.html#creating-files", + "objectID": "course/00_Git/slides.html#creating-files", + "href": "course/00_Git/slides.html#creating-files", "title": "Version Control with Git", "section": "Creating Files", - "text": "Creating Files\nIn context of this course, we will primarily be working with two types of files when coding:\n\nR Scripts: These files end in .R. These contain only code (with occasional # comment line). These are often used for self-contained code that once we get them working we rarely need to modify.\nQuarto Markdowns: These files end in .qmd. They contain a .yaml header, followed by a mix of regular written text (often explanations or other documentation), and sections (ie. chunks) that contain code. These are used when we are still getting the code to work, when we need to modify inputs frequently, or simply when we need to document what and why we are doing something to make life easier for our future-self two months from now.\n\n\n\nIn this example, I will go ahead and select the new file icon\n\n\n\nThenn I will name the file, and designate it as a Quarto Markdown file by adding the .qmd at the end of the name to denote the file type.", - "crumbs": [ - "About", - "Getting Started", - "00 - Git" - ] + "text": "Creating Files\n\n\n\n\n\n\n\n\n.\n\n\nIn context of this course, we will primarily be working with two types of files when coding:\n\nR Scripts: These files end in .R. These contain only code (with occasional # comment line). These are often used for self-contained code that once we get them working we rarely need to modify.\nQuarto Markdowns: These files end in .qmd. They contain a .yaml header, followed by a mix of regular written text (often explanations or other documentation), and sections (ie. chunks) that contain code. These are used when we are still getting the code to work, when we need to modify inputs frequently, or simply when we need to document what and why we are doing something to make life easier for our future-self two months from now." }, { - "objectID": "course/00_Git/index.html#qmd-files", - "href": "course/00_Git/index.html#qmd-files", + "objectID": "course/00_Git/slides.html#qmd-files", + "href": "course/00_Git/slides.html#qmd-files", "title": "Version Control with Git", "section": "QMD Files", - "text": "QMD Files\nOnce this is done, we can now see we have a new .qmd file (“Example.qmd” in this case).\n\nYAML\nAs previously mentioned, the start of a Quarto Markdown file containg a YAML code chunk that is used to set formatting choices (we will explore this in-depth during the next section)\nWhat designates the location of the YAML block are three hyphens at the start, and three hyphens at the end. For this example, we will also provide a “title:” and “format:” field for the time being (see additional options here).\n\n\n\n\n\nText\nWith a basic YAML formatting block now in place, we can build out other elements of our Quarto Markdown document. Unless otherwise specified, everything else in the document is assumed to be text, so I will go ahead and provide an initial text description of what I am trying to do.\n\n\n\n\n\nCode-Chunks\nHaving provided some initial text for documentation, we can then add code-block chunks to start writing some code.\nThe easiest way to do do this is to click the respective option on the upper-right of the Editor screen. Since Positron can handle multiple programming languages, so the chunk is inserted, we will need to select the language we use to be used within the code chunk (R in this case).\n\n\n\nYou will notice, that the inserted code block starts off with three backticks (`) and then “{r}”. The end of the code block is denoted by an additional three backticks.\nWe can also add new code blocks by simply typing these elements into the location we want to place a code chunk (as long as we are careful to add 3 backticks also at the end).\n\n\n\n\n\n\n\n\nRunning Code\nNow that we have two code-chunks written, we can write lines of code within them. For this example, I will use two beginner friendly functions, print(“Hello”), which will print the contents contained between the ” ” to the console, and getwd() which will return the location of the folder you are working within (ie. the working directory).\nTo run/execute these lines of code, we have a couple options. We can click on the Run Cell option that appears on the upper-left side of the code chunk. Additionally, it has a companion option that will run all code chunks above it.\n\n\n\nWhen a code block is successfully run, you will see within the console (lower bottom of the screen) the line of code be run, with any returned outputs appear directly after.\n\n\n\nAn alternative to clicking the Run Cell button is to click on the line of code you are interested in running, then press (Ctrl + Enter)/(Command + Enter). This will execute the line of code that you have clicked on. This can be useful in scenarios where you want to run a specific line, and not the entire code-chunk.\n\n\n\nUsing this approach, you can see the location (ie. file path) of the current working directory was returned to the Console.", - "crumbs": [ - "About", - "Getting Started", - "00 - Git" - ] + "text": "QMD Files\n\n\n\n\n\n\n\n\n.\n\n\nOnce this is done, we can now see we have a new .qmd file (“Example.qmd” in this case).\n\n\n\n\n\nYAML\n\n\n\n\n\n\n\n\n.\n\n\nAs previously mentioned, the start of a Quarto Markdown file containg a YAML code chunk that is used to set formatting choices (we will explore this in-depth during the next section)\nWhat designates the location of the YAML block are three hyphens at the start, and three hyphens at the end. For this example, we will also provide a “title:” and “format:” field for the time being (see additional options here)." }, { - "objectID": "course/00_Git/index.html#local-version-control", - "href": "course/00_Git/index.html#local-version-control", + "objectID": "course/00_Git/slides.html#local-version-control", + "href": "course/00_Git/slides.html#local-version-control", "title": "Version Control with Git", "section": "Local Version Control", - "text": "Local Version Control\nHaving introduced the main elements of a Quarto Markdown file, let’s turn our attention to the tab within the editor showing our newly created .qmd file.\nWe can see there is a solid circle next to the file name, and it is appearing as green. The circle denotes unsaved changes, which we can correct by clicking on the Save Button to save the changes to our file.\n\n\n\n\nUntracked\nIf we turn our attention to the left primary sidebar, we can see that within our GitPractie folder there are three files, our Example.qmd, and the default README.md and .gitignore files. These all show up in green text with U’s to the right of the file names.\nThis denotes that the version control tracking software Git is currently considering them as “Untracked” files. While saving the document via the Save button means we will still have our changes when we reopen Positron, we won’t have any history of changes that we can use to revert back to the way all the files appeared at this exact point in time should something go wrong.\nWe will next go the address bar on the very far left, and select the Git tab.\n\n\n\nOn the Git tab, we can see that each of the three files are shown underneath a “Changes” drop-down. This contains the files that have undergone changes since the last commit. In our case, since we haven’t updated the save-state yet, this last commit would be the initial creation of the project folder.\n\n\n\nTo have version control track these individual files going forward, we can do so in two separate ways. We can add them individually by clicking the + symbol next to the individual names.\n\n\n\n\n\nStaged\nThis will result in the files being moved to the “Staged” dropdown. This denotes files being tracked with the intention of being recorded as the next save-state or waypoint (ie. a commit).\n\n\n\n\n\nCommit\nTo create a new commit (save-state or waypoint), once we have the files we want to track staged, we will write a commit message, and then press commit.\nA commit message is a brief description of the changes that have occurred to the files between this commit and the previous one. Make this short description informative enough that if you need to revert back in the future, you can quickly identify the commit you need to fall back to (more about this later).\n\n\n\nIf this your first time using version control, you will likely encounter the following pop-up asking that you provide a user.name and user.email. This is used to designate the author of the changes.If you get this popup, go ahead and select “Open Git Log”\n\n\n\n\n\nUserName and UserEmail\nThe Output tab at the bottom of the screen will open, showing the messages that led to the popup.\nThe important part to note is the commands that will be needed to provide your user name and email to the computer for authoring the commit. Typically, your email will be the same one you used for your GitHub account.\n\n\n\nFrom the displayed message, go ahead and copy\n“git config –global user.email”you@example.com””\nThen click on the adjacent terminal tab. You will paste the command in, but do not hit enter just yet.\nWindows users, please note, depending on your settings, if trying to paste from the keyboard into the terminal, you may need to press “Ctrl + Shift + V” instead of the usual “Ctrl + V”.\n\n\n\nWith the command now pasted (or typed), use your keyboard arrows to navigate to the email portion, and replace the generic email with your email address used for your GitHub account.\nMake sure that the quotation marks (“) around the email address remain present, as they help the computer identify where your email address starts and ends. Once satisfied that your email address is correct, press enter.\n\n\n\nNext up, repeat the process, this time copying over the command needed to set your user name to the terminal. Repeat the editing process to provide your name between the “” marks. Then press enter.\n\n\n\n\n\n\n\n\nFirst Commit\nNow that your user.name and email address have been provided, Git should be able to provide an author to the commit message. Reattempt to press commit button.\nIf this is successful, you will see your initial commit appear on the bottom half of the left primary side bar, under the Graph dropdown. Congrats! Your files are now being tracked by version control.\n\n\n\nIf you hover with your mouse arrow just over the commit, you can see the longer commit message and additional details appear.\nIf you click on the commit tab, a new display will open in the editor, displaying the changes that occured in that commit compared to the previous one. In this case, since we added everything since the previous commit, nothing appears on the left side, while the entire documents contents appear highlighted in green on the right.\nGreen highlighting is used to show additions, while red highlighting is used to show deletions.\n\n\n\nHaving completed this initial commit, for this example, let’s imitate a typical workflow and make some additional changes to the file before we make a second commit. Within text portions of the .qmd file, use of # denotes a section header in markdown, so let’s add a header for Introduction and click save.\n\n\n\n\n\nModified\nWithin the left primary sidebar, we can see that the Git tracking has updated. Examples.qmd is visible once again. However, becuase it is now a tracked file, instead of showing up with the “U/Untracked” green highlight, it now appears as a brownish-red with a “M/Modified”.\nLet’s make an additional change to the .qmd file by adding another section (# Setup) and a code block with a commented out line (denoted by the # at the line start), before pressing Save.\n\n\n\nIf we were now to click on the Example.qmd file in the left primary sidebar, it will open the same kind of tracking display we saw previously. This time, we can see changes since our last commit. These appear as the green highlights along the scroll-bar, corresponding to the # Introduction and # Setup headers that we have added in since the last commit.\n\n\n\nFor a larger document, we can scroll down to see the various highlighted regions.\n\n\n\nWe could now repeat the steps showed above, staging the file, writing a commit message, and commiting again by clicking on the designated buttons.\nAn important question is how often should we commit, vs. just hit save? Well… it depends :D Let’s think about this in context of a video game. If you made commits at regular intervals throughout the day (or more frequently when doing something particularly risky), you are more likely to be close enough to a particular commit (waypoint/save-state) that you can quickly revert back to without loosing any progress. Alternatively, if your last commit was last week, you will not have any intermediate versions to fall back to.\n\n\nCommit via Terminal\nHaving demonstrated how to commit changes to Git via the left primary side-bar, for this second commit, let’s do it the alternate way via the terminal (tab on the panel at the bottom of your screen).\n\n\n\nAfter clicking on the terminal tab, click on blinking command line.\nThe command to stage a file is “git add”, followed by the name of the file you want to stage.\nIn this case, you would enter “git add Example.qmd” and press Enter. \n\n\nYou will see after pressing enter a new blank terminal line appear. If you glance at the left-sidebar, you can see that Example.qmd now appears under the Staged Changes dropdown.\n\n\n\nNext up, let’s write the git commit via the terminal. In this case, the command would be “git commit -m” (-m denoting message). The commit text is then surrounded by “” marks.\nFor example: “git commit -m”Added section headers to my QMD file””\nPress enter to save the commit.\n\n\n\nAnd you should see your second commit now appear in the left primary sidebar underneath the graphs dropdown.", - "crumbs": [ - "About", - "Getting Started", - "00 - Git" - ] + "text": "Local Version Control\n\n\n\n\n\n\n\n\n.\n\n\nHaving introduced the main elements of a Quarto Markdown file, let’s turn our attention to the tab within the editor showing our newly created .qmd file.\nWe can see there is a solid circle next to the file name, and it is appearing as green. The circle denotes unsaved changes, which we can correct by clicking on the Save Button to save the changes to our file." }, { - "objectID": "course/00_Git/index.html#remote-version-control", - "href": "course/00_Git/index.html#remote-version-control", + "objectID": "course/00_Git/slides.html#remote-version-control", + "href": "course/00_Git/slides.html#remote-version-control", "title": "Version Control with Git", "section": "Remote Version Control", - "text": "Remote Version Control\n\nCopying Project Folder to GitHub\nWhile having local version control in place is helpful when you need to revert back after encountering issues, where Git shines is the ability to pass your changes to your online GitHub repository.\nNot only does this allow you to switch between computers, but should something disastrous happen to your main computer, you still have all your hard work backed up and readily assessible.\nFor this subsection, first, double check that Positron is still connected to your GitHub account by checking the user tab on the bottom-left. If not, repeat the connection setup.\n\n\n\nSince our project was created using the “New Folder from Template” option, it currently only exist locally. What we want to do next is to copy it to our GitHub account, creating a new repository in the process.\nTo do this, we will first need to install the usethis R package. Within your console, you would run the following line of code:\n\ninstall.packages(\"usethis\")\n\nDepending on what R packages you already have installed on your computer, you may get a prompt asking if you want to update/install additional dependencies. Go ahead and type the number corresponding to Update All, and press enter.\nThe package and all it’s dependencies should then install. If an error message appears, read through it, and follow provided instructions. Go to Discussions if need help.\n\n\nOnce the usethis package is installed, we need to activate it within R by calling it with the library command. This makes all the tools (ie. functions) within an R package available for use within Positron.\nIn your console, you would type:\n\nlibrary(usethis)\n\n\n\n\nWith library called, you now have access to the functions (tools) within the usethis R package. One of these is the use_github() function.\nIn Positron, if you hover over a function, it will pull up the associated help file which will provide you information about the arguments the function expects to receive, and what they do.\nFor use_github(), the main thing to remember for now is since this is a personal project being used for testing, we don’t necessarily want to share it with the entire world, so we should set the “private” argument equal to TRUE when creating a new repository.\n\n\n\nTaking this information that we have now gathered, we can now within our Quarto Markdown create a code chunk, write out the line of code calling the function, and providing the Private=TRUE argument within the ().\nWithin a code chunk, adding a # in front of a line of code, will comment it out, resulting in that line of code not being run. Since we have already installed the usethis package, and we don’t want to reinstall it every single time, let’s go ahead and comment out that line. Go ahead and press Enter.\n\n\n\nWe will see a message pop-up in the console. In this case, we had not saved before pressing enter, so there are uncommitted changes within the folder. The pop-up is asking whether you want to save these as well before sending the Folder to GitHub.\nIn this case I will chose to ignore the uncommitted changes by entering 3 (for Definitely) in the console and hitting enter on my keyboard.\n\n\n\nThe usethis R package will then execute the series of git commands that are needed to set up a GitHub repository (ie. the messages being displayed in the console window), and when finished will open a pop-up asking whether you want to see your new repository in your default Web Browser. I will go ahead and select yes in this case.\n\n\n\nAfter the browser opens, you can see that the elements I had staged and committed within Positron are now present within the GitHub repository. Since I had only staged Example.qmd, it is the only file that was backed up. We can also see the commit history online by clicking on the commit clock.\n\n\n\nAs we would expect, we only see our two commit messages. One important thing to note is the commit hash numbers, that denote a particular commit. If we decided to revert/fall back to a prior commit in the future, this would be the number we would need to provide to Git to return to that previous commit/save-state\n\n\n\nSimilarly, on GitHub, we have an option to Browse a Repository at a particular point in time. This will be quite useful later in the future when troubleshooting what major changes occurred between versions of an R package.\n\n\n\n\n\nCode Chunk Arguments\nHaving successfully connected our local Project Folder to a remote GitHub repository, let’s return to Positron.\nBefore continuing, if we left the code chunk that created the GitHub repository as is, every time we ran all code chunks in the document, it would try to recreate the GitHub repository. We don’t want this to happen, as the setup was a one-time operation.\nWhile we could add # in front of every line of code (or delete the code chunk entirely) it is often useful to have these set-up code chunks around to remind us what arguments we need to provide next time we need to a similar setup and are mind blanking on what to do.\nFortunately, Quarto allows us to set conditions on whether a chunk is run (ie. evaluated). We will discuss the conditiona arguments in more depth in the next section, but for now, we can modify the code chunk as follows.\nOn the next line after the {r}, we will add a hashtag (#), then a pipe (|), followed by a space. This is the setup for a code-chunk specific argument. We will then add “eval: FALSE”, which signals that the particular code-chunk should not be evaluated (ie, should not be run).\n\n\n\n\n\nREADME\nNow that we have connected our local Project Folder to GitHub, and have gotten a basic introduction to the “git add”, “git commit” arguments, let’s turn our focus to the other files currently listed as untracked by Git within our folder, the README.md and the .gitignore files.\nWhen setting up our GitHub account, we encounted an example of a README.md file. This file often provides a brief description of the project, and an outline of what the other files in the folder are for. As you may have gathered, even software developers are forgetful/under-caffenaited, and having notes to catch back up to speed is important.\n\n\n\n\n\n.gitignore\nWe additionally have a .gitignore file. Within a project, there are often some files that we will never want version control to track. These could be files that are too large for GitHub (ex. really large .fcs files), or files containing sensitive information (passwords, history, credentials, etc.).\nWhen the names of these file (or the file type shothand) are added to the .gitignore file, they are ignored by version control, and no longer appear on the primary left side bar.\n\n\n\nLet’s proceed and stage both the README.md and .gitignore file, so that changes to these files will be tracked. We can of course select both from the primary left side bar and write a short commit message.\n\n\n\n\n\n\nOr alternatively, if we want to stage all uncommitted files present in a single step, we could in the terminal use the “git add .”\nWe can then write our git commit using “git commit -m”.\nBoth approaches work, and you may switch between them based on preferrence.\n\n\n\nYou will notice after having committed, that if you look at the Graph dropdown on the bottom half of the primary left side-bar that something has changed.\nThere are now separate icons denoted as main and origin/main. These correspond to the last commit present locally (main), and the last commit on remote (ie. GitHub, origin/main).\nLocal is ahead since you just made the commit with the changes inactivating the code-chunk, and you have not passed these changes up to GitHub yet.\n\n\n\n\n\nPull\nBefore sending (ie. pushing up) our updated commit to GitHub, especially if you are working on a project from multiple computers (or as part of a team) to bring in (ie. pull down) any changes that might be on GitHub that are not present locally.\nThis ensures that everything is up to date, and you don’t end up with mismatched commits that are incompatible with each other and trigger an error message.\nTo pull in changes from GitHub, at the top of the primary left side-bar, you can select the … button to open a drop-down menu of Git options. You would then select “Pull”.\nAlternatively, you could do the same thing via the terminal by running the “git pull” command.\n\n\n\n\n\nPush\nIn our case, there was no new material present on our GitHub repository that were not already present locally, so all that is returned is the “Already up to date” message.\nWe are now good to proceed to push (ie. send) the updated commit up to our GitHub repository.\nWe can do this by either pressing the Sync changes button, or via the terminal entering the “git push” command.\n\n\n\nAnd now, if you glance down at left side-bar’s graph section, you will see that both the main and origin/main icons are now present for the most recent commit.\n\n\n\nIf we switch to our Web browser, we can see that this is also now the case for our GitHub repository that now also has the most recent changes.\n\n\n\n\n\nReverting to Prior Commit\nFor most daily-workflows, you will only need the git commands that we have introduced above (git add, commit, pull, push). The next two areas (reverting to a prior commit, and branches) are more specialized, and will be covered in greater depth later in the course. We are briefly covering them here. If you are at the point where your last remaining neuron has disconnected, and you feel you need to take a break from version control, feel free to skip to the next section and we will revisit these topics later in the course.\n\n–\nIn most cases, if your code stops working, you can identify the issue and fix it in the existing version, never needing to resort to reverting to a previous commit (save-state). The times you would need to revert would be if you deleted important files, or the new files are hopeless mess that is not worth trying to sort through. In those cases, reverting back might be better approach.\nTo imitate a falling back scenario, lets create and additional file, stage and commit it to end up a commit ahead of where we are currently at within the Project Folder.\n\n\n\nNow being one (or several) commits ahead, if we wanted to revert back, we would first need to identify the commit we want to revert back to and copy the commit hash number.\n\n\n\nThen, opening the terminal, we can enter “git reset” and paste the hash afterwards. We can then press enter.\n\n\n\nYou will notice our additional commit has been removed, although the newer files we were working on subsequent last commit are still present.\n\n\n\nIf however, we had wanted to return to the exact same state as the previous commit (removing all subsequent created files), we could do so by adding in the –hard argument. Before starting, save any newer files you want to keep in a completely different folder, because they will be permanently removed.\nThen, enter “git reset –hard thecommithashnumber” into the terminal, which would result in a “hard” return to the previous commits save-state. You may need to close and reopen Positron to see the changes reflected.\n\n\nBranches\nBranches are an useful Git feature that we will start using extensively later in the course. Branching allows you to create a parallel/carbon-copy of your existing repository, which you can then edit without affecting the main branch. This is particularly useful for projects that may get messy or drawn out. By isolating these edits to a parallel branch, if they don’t work, your main branch remains safe. Alternatively, if you like the changes that occurred in the branch, you can pull these changes from the branch back to main, bringing the timelines back together.\n\n\nWithin the terminal, entering “git branch” will show the existing branches. In this case, only main is present since we haven’t yet created a new branch.\n\n\n\nWe can create a new branch in the terminal by entering “git branch” followed by the name of our desired branch. In this case, we are creating a branch called Week1\n\n\n\nNow, when we check “git branch” again in the terminal, which returns the two branches, Week1 and main. The * is located next to main, indicating that we are currently within the main branch.\n\n\n\nBesides the terminal, we can also create a new branch via Positron. To do so, we first click on the Git tab in the Actions Bar.\nOnce the left-side bar displays the version control display, we can click on the … button (to the right of changes)to gain access to the Git options drop-down.\nFrom here, we click on Branch, and then select Create Branch.\n\n\n\nUsing Git branch, we saw that we were still within the main branch. In the terminal, we can switch over to the Week1 branch by using the “git checkout” command, followed by the branch we wish to switch to.\n\n\n\nThis results in us switching over to the Week1 branch.\n\n\n\nHaving switched (ie. checkout) to the Week 1 branch, let’s create the file BranchTest.qmd, which will exist within this branch, but not yet in the main branch.\n\n\n\nHaving created the file, let’s stage and then commit it. This will put the Week1 branch ahead of the main branch by a single commit.\n\n\n\nWith our changes staged and committed, if we look at the left side-bar’s graph section, our Week1 branch is now ahead of the origin/main branch by one commit.\n\n\n\nIf we were to check on GitHub, we can see that no new files are present on the main branch, but can see the notification listing recent changes to Week1 branch.\n\n\n\nUsing the drop-down, we can switch from displaying the main branch to the Week1 branch, where we can see the new file.\n\n\n\nIf we click the green compare and pull request button, we end up on this screen. This compares how the two branches are different from each other.\n\n\n\nWe will delve into branches again at a later point. For now, remember that by creating and prunning parallel branches, you can develop knowing that even if something goes wrong, your main branch remains safe.", - "crumbs": [ - "About", - "Getting Started", - "00 - Git" - ] - }, - { - "objectID": "course/00_Floreada/index.html", - "href": "course/00_Floreada/index.html", - "title": "Using Floreada", - "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", - "crumbs": [ - "About", - "Getting Started", - "00 - Floreada" - ] + "text": "Remote Version Control\nCopying Project Folder to GitHub\n\n\n\n\n\n\n\n\n.\n\n\nWhile having local version control in place is helpful when you need to revert back after encountering issues, where Git shines is the ability to pass your changes to your online GitHub repository.\nNot only does this allow you to switch between computers, but should something disastrous happen to your main computer, you still have all your hard work backed up and readily assessible.\nFor this subsection, first, double check that Positron is still connected to your GitHub account by checking the user tab on the bottom-left. If not, repeat the connection setup." }, { - "objectID": "course/00_Floreada/index.html#floreada", - "href": "course/00_Floreada/index.html#floreada", + "objectID": "course/00_Floreada/slides.html#floreada", + "href": "course/00_Floreada/slides.html#floreada", "title": "Using Floreada", "section": "Floreada", - "text": "Floreada\n\nLoading Dataset\nFirst, open your web browser and navigate to the website\nClick on Start to proceed to the next page.\n\n\n\n\n\n\nOnce that is done, select the File tab on the upper navigation bar. Then click on Open File(s).\n\n\n\n\n\n\n\nFrom there, select your .fcs files of interest, and click Open.\n\n\n\nThe .fcs files will now load in, and you should see a view similar to the one below. On the left side-bar, you have your gating options (Rectangle, Polygon, Range, Elipse, Quad, etc). Next to these on the right you have the FCS files that are loaded into the workspace. Then on the right, you have the visual display for your selected specimen.\n\n\n\n\n\nSwitching Axis Markers\nIf you left click on the axis name (SSC-H or FSC-H in this case), you will be able to select other markers by which to gate your specimen. For the provided example, we were using a raw spectral flow cytometry .fcs file, so the names of the detectors are present.\n\n\n\nFor now, I plan to start off by gating for singlets. I switch the y-axis to FSC-H, and then proceed to switch the x-axis to FSC-A.\n\n\n\n\n\nCreating Gates\nWith this done, I can now select the Poly gate tab on the upper left.\n\n\n\nThen manually click on the locations on the plot to add the individual gate nodes.\n\n\n\nTo complete the gate, I click back to the original node point. At this point, the popup will allow you to name the gate.\n\n\n\nTo adjust the polygon gate, you can click on a node and drag it to expand or contract in a particular direction\n\n\n\nTo move the entire gate, first click on a node to select the gate, then click in the center of the gate to adjust its location.\n\n\n\n\n\nAdditional Gates\nUnfortunately for those with the force-of-habit from using other softwares, double-clicking within the gate doesn’t do anything. To continue gating on the selected cells, you will need to click on the newly created gate name on the left. This will result in visualizing the isolated cells.\n\n\n\nOnce this is done, you can repeat the previous steps to change the axis markers and create a second gate. For this example, we went with a “Cells” gate to exclude debris from this particular sample.\n\n\n\nHaving created the “Cells” gate, we will be switching gating based on FSC and SSC to using the detector parameters.\nThe samples in this example were acquired to derive the cell counts and concentration of various cell populations within cryopreserved cord and peripheral blood mononuclear cells (CBMC and PBMC) specimens after thawing.\nThey were stained with CD19 BV421, CD45 PE, and CD14 APC on a 5-Laser Cytek Aurora, before unmixing, this would correspond respectively to V1, YG1/B4, R1/YG4 peaks respectively.\n\n\n\n\nScaling/Transformation\nWhen we switch the axis, we can see that the scaling/transformation is not ideal, as the staining and not-staining populations are scrunched up together in the center of the plot.\n\n\n\nTo change the scaling/transformation, we need to click directly on the axis.\n\n\n\nFrom there, when we click on the drop-down, we see the various transformation options. We will select Logicle, given we are working with spectral flow cytometry files.\n\n\n\nThis y-axis values are subsequently visualized with the logicle transformation applied, increasing our resolution between the positive and negative population.\n\n\n\nWe can then repeat this for the x-axis, adjusting the fine-tune options for the scaling as needed.\n\n\n\n\n\nNavigating Gating Hierarchy\nWith this done, let’s first draw a rectangle gate for the CD45+ (B4-A) cells.\n\n\n\nAnd then selecting that population by clicking on the gate name, let’s proceed and gate the CD19+ cells (V2-A).\n\n\n\nAs you can see, we now have the various gates present in the gating hierarchy for the respective .fcs file. To return to a previous gated population, we would click on the parent population above it.\n\n\n\nWe can subsequently add an additional gate at this gating level for the likely debris population (the threshold setting was suboptimal for this experimental run).\n\n\n\n\n\nCopying Gates\nThis was the process for gating for a single specimen. To copy gates over to the other specimens, we have two options. First, holding down your Ctrl (or equivalent) button, you can click on the individual gate names.\n\n\n\nFrom there, you can drag them down to the next specimen and apply them.\n\n\n\nAlternatively, you can drag down the highlighted gated to the Pipelines Tab, and apply to All Files. This will result in the gates being copied to all specimens in the experiment.\n\n\n\n\n\n\nAdjustments within Pipelines will carry over to all other respective unmodified specimens that share it’s gates.\n\n\n\nOnce this is done, I recommend cycling through the gates for each specimen, just to ensure that the gates were positioned correctly before saving the workspace.\n\n\n\n\n\nSaving Workspace\nWith everyone now “correctly” gated, we can proceed to save the workspace so that we can reopen it later from another browser.\nTo do this we open the File tab from the upper navigation bar, and select Save Workspace.\n\n\n\nFrom there we have a couple options, for now let’s select Floreada Workspace. Where it is saved at will depend on your individual browser settings, so watch for a popup.\n\n\n\nAlternatively (and crucially for the CytoML pipeline) we can also choose to save it as a FlowJo v10 .wsp file.\n\n\n\nIn both cases, you will end up with Workspace files that can be used later to access your created gates\n\n\n\n\n\nReopening Workspace\nTo reopen the Floreada workspace within the browser, reopen the website, and select the Open File(s) option.\n\n\n\nFrom there, select both the Floreada Workspace file as well as the .fcs files\n\n\n\nAt which point you will now be back to the point you last saved at.", - "crumbs": [ - "About", - "Getting Started", - "00 - Floreada" - ] + "text": "Floreada\nLoading Dataset\n\n\n\n\n\n\n\n\n.\n\n\nFirst, open your web browser and navigate to the website\nClick on Start to proceed to the next page." }, { - "objectID": "course/00_Floreada/index.html#cytoml", - "href": "course/00_Floreada/index.html#cytoml", + "objectID": "course/00_Floreada/slides.html#cytoml", + "href": "course/00_Floreada/slides.html#cytoml", "title": "Using Floreada", "section": "CytoML", - "text": "CytoML\nDue to a unknown formatting bug, the Floreada produced FlowJo v10 .wsp is not directly accessible by CytoML at the time of this course. However, the issue is resolved as soon as the file is opened the first time within FlowJo v10, regardless of whether you have a log in or not. Strange? Yes, but we will take the workaround.\nSo, for anyone on Windows or MacOS, download FlowJo v10. Once installed, open the software, and close the login popups. Once there, open the Floreada created FlowJo.wsp file. Since you haven’t logged in, it won’t show any events. But it will correct the formatting bug. Close the software, and return to R. Your Floreada sourced .WSP file should now be readable by CytoML.\nOdd? For sure. Fixable? Likely, I will set a reminder to work with the Floreada and CytoML devs to see if we can cut out the need for this workaround.", - "crumbs": [ - "About", - "Getting Started", - "00 - Floreada" - ] - }, - { - "objectID": "course/00_BonusContent/index.html", - "href": "course/00_BonusContent/index.html", - "title": "Bonus Content", - "section": "", - "text": "This is a miscellaneous page to host walk-throughs of topics that come up via the Discussion Page. Rather than re-explain how to in the comments, I want to have a place to post short-walkthroughs to solve these issues, while avoiding incorporating it into the existing walk-throughs at this point in time. I hope you find it useful, and pardon the organized chaos of miscellaneous topics." - }, - { - "objectID": "course/00_BonusContent/index.html#windows-arm", - "href": "course/00_BonusContent/index.html#windows-arm", - "title": "Bonus Content", - "section": "Windows Arm", - "text": "Windows Arm\n\nPositron\nOn the main Positron installation page, only the installers for Windows Computers with x86 chips are currently shown. There is a beta (experimental) version of Positron for Windows ARM (ex. Snapdragons), but it needs to be installed from Positron’s GitHub releases page.\n\nPlease note, you should download the most recent version that is available to you, as they continue to update it and fix bugs. As of February 04, 2026, you would also need to install Quarto separately.\nTo install Quarto, first navigate to their website. Quarto for Windows ARM was implemented in 2023, so the regular installer should work.\n\nAlso, you would need a Python arm64 installation installed if you decide you want to venture into using Python at any point." - }, - { - "objectID": "course/00_BonusContent/index.html#visual-mode", - "href": "course/00_BonusContent/index.html#visual-mode", - "title": "Bonus Content", - "section": "Visual Mode", - "text": "Visual Mode\nWithin Positron, there exist a toggle button to switch between source and visual mode on Quarto documents. But what do you do when you can’t find it?\n\nTuns out…. Visual Mode is currently broken, so the developers removed it about two weeks ago.\nThe current way to switch to it is via right-click, then select edit visual mode.\n\nVice versa, once there, you can revert by right-clicking and selecting Edit Source Mode\n\nThe process of figuring what is going on highlights how to use a GitHub Discussion Page. This is Positrons when I searched for visual button. I then found that a similar question was asked 3 days ago that led me to the linked thread above." - }, - { - "objectID": "course/00_BonusContent/index.html#not-detecting-git", - "href": "course/00_BonusContent/index.html#not-detecting-git", - "title": "Bonus Content", - "section": "Not Detecting Git", - "text": "Not Detecting Git\nIf you leave the “Initialize Git Repository” option unclicked when setting up a New Folder from Template, Git will not be active within your project folder.\n\nAs a result, when you try to use the usethis packages use_github(private=true) function, you will get an error that resembles the one below\n\nTo initiate a Git repository after the fact, you will need to go to the Version Control tab in the action bar, and select the option.\n\nThen, you will need to stage the files you want to work with, and commit them.\n\nuse_github(private=TRUE) should now be functional at that point. However, you can also choose to continue via Positron’s interface instead by selecting Publish.\n\nIt will then ask you whether you want to save it as either a Public or a Private repository.\n\nAnd if all goes well, you will see the “Successs” pop-up in the lower-right" - }, - { - "objectID": "course/00_BonusContent/PullConflicts/index.html", - "href": "course/00_BonusContent/PullConflicts/index.html", - "title": "Take-Home Problems - Pull Fix Resolution", - "section": "", - "text": "Background\nFor those who have turned in the homework to the Cytometry in R - homework branches, many report having encountered merge issues pulling in the next week’s data if the pull request hasn’t been resolved yet. Creating a parallel branch, and submitting homework from there to the homework branch might solve the issue? But we will need to test that out. For now, here are the steps we used to resolve the issue locally without needing to delete and re-download.\n\n\nGetting Started\nStart off checking your GitHub forked version of the CytometryInR, notice how many commits behind you are.\n\n\nIf you haven’t submitted the optional Take-Home problems via a pull-request, proceed to do so.\n\n\nThis was an example of the page you see when submitting the pull request. Upon submission, your branch may show merge conflicts due to difference in rendered docs. This is okay, we will resolve it on our end.\n\n\nWhat we will end up doing is ignore the changes and accept the current version. This issue is likely due to the weekly updating of the data resulting in new sidebar links. We will then mark these issues as resolved\n\nWe will then mark the issues as resolved.\n\n\nOn return to the homework, we will be able to merge the branch once again. We will likely make our suggestions at this point for this branch.\n\n\nHowever, after pull request has been merged, you will see your branch is way ahead (due to everyone elses homework commits). This is the area we will need to address via the new branch method.\n\n\nFor now, proceed to discard the changes (you don’t need the other participants homeworks cluttering your folder)\n\n\nYou will then appear as caught up with the main branch.\n\n\nOn return to Positron, attempt to pull\n\n\nHowever, since your homework commit is still present, you will receive a pop-up asking you to see the GitLog. If you scroll up the problem log, it will give you several options.\n\n\nYou will need to enter the following code into your terminal tab:\n\ngit config pull.rebase TRUE\n\n\n\nThis will result in a branched appearance, and the button asking you to sync the changes.\n\n\nUpon doing so you will have a restored status vs. the main cytometry in R project folder.\n\n\n\nTake Away\nWe have encountered a first growing pain for the course, in that the pull-request method we have been using still causes merge conflicts. We will be going to a homework branch to homework branch pull-request approach going forward, I will send out additional instructions on how to do so shortly.\nThanks for your patience!\nDavid\n\n\nAdditional Resources" - }, - { - "objectID": "course/index.html", - "href": "course/index.html", - "title": "Cytometry in R", - "section": "", - "text": "Cytometry in R is a free virtual mini-course being organized by the Flow Cytometry Shared Resource Core at the University of Maryland’s Greenebaum Comprehensive Cancer Center. This course is a passion project arising from our desire to contribute back to the community.\nWe are excited that so many individuals worldwide have chosen to take part, and we look forward to helping you get started on your own learning journeys." - }, - { - "objectID": "course/index.html#resources", - "href": "course/index.html#resources", - "title": "Cytometry in R", - "section": "Resources", - "text": "Resources\nCourse materials can be found here. The livestream recordings are available via YouTube" - }, - { - "objectID": "course/index.html#in-person-baltimore", - "href": "course/index.html#in-person-baltimore", - "title": "Cytometry in R", - "section": "In-Person (Baltimore)", - "text": "In-Person (Baltimore)\nFor those joining us in person, the class is being offered on Thursday from 4-5 pm EST in Bressler Research Building Room 7-035. Monitors to plug your laptops in will be available on a first come, first served basis. These in-person sessions will not be recorded, but with the smaller class size you will have our undivided attention should you have any questions." - }, - { - "objectID": "course/index.html#virtual-worldwide", - "href": "course/index.html#virtual-worldwide", - "title": "Cytometry in R", - "section": "Virtual (Worldwide)", - "text": "Virtual (Worldwide)\nFor those joining us virtually, we will have three separate livestreams throughout the week on YouTube. These will be offered on:\n\nTuesday 2200 EST (Wednesday 0300 GMT+0)\nWednesday 1600 EST (Wednesday 2100 GMT+0)\nThursday 1000 EST (Thursday 1500 GMT+0)\n\nAll three livestreams will be recorded and available on YouTube immediately afterwards." - }, - { - "objectID": "course/index.html#discussion-forum", - "href": "course/index.html#discussion-forum", - "title": "Cytometry in R", - "section": "Discussion Forum", - "text": "Discussion Forum\nWe will be using the Cytometry in R Discussions page as a community forum, and a place to ask questions, celebrate wins, and provide feedback. After creating a a GitHub account, pleae go introduce yourself." - }, - { - "objectID": "ExistingResources.html", - "href": "ExistingResources.html", - "title": "Existing Resources", - "section": "", - "text": "We are not the first “Cytometry in R” course, nor will we be the last. This page is linking to the already existant online Cytometry in R resources that we have encountered and benefited from during our own learning journey. May they prove useful to you as you progress your way through yours!\n\n\n\nChristopher Hall - Flow Cytometry Data Analysis in R\nCytometry-R-Scripts: R scripts to help with your flow cytometry analysis\nR_flowcytometry_course: The files and presentation from the Cytometry Core Facility flow cytometry data analysis course in R\n\nInstallation and Loading Data\n(1) Flow Cytometry Data Analysis in R - Installation and Loading Data\n\n\n\n\nCompensation, Cleaning, Transformation, Visualization\n(2) Flow Cytometry Data Analysis in R: compensation, cleaning, transformation, visualization\n\n\n\n\nGating with flowWorkspace\n(3) Flow Cytometry Data Analysis in R: gating with flowWorkspace\n\n\n\n\nVisualization\n(4) Flow Cytometry Data Analysis in R: Visualisation\n\n\n\n\n\n\n\nOzette Technologies - BioC 2023 Workshop\nWorkshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew McDavid.\nWorkshop: Reproducible and programmatic analysis of flow cytometry experiments with the cytoverse\n\n\n\n\n\n\nPritam Kumar Panda - Flow Cytometry Data Analysis & Visualization in R using CytoExploreR\nFlow-Cytometry-analysis-in-R\nCytoExploreR-Interactive-visualization\n\nComplete Guide\nFlow Cytometry Data Analysis & Visualization in R using CytoExploreR: Complete Guide\n\n\n\n\n\n\n\nBioinformatics DotCa - Introduction to Flow Cytometry in R\n\nIntroduction to Flow Cytometry in R\nIntroduction to Flow Cytometry in R\n\n\n\n\nExploring FCM Data in R\nExploring FCM Data in R\n\n\n\n\nProcessing and Quality Assurance of FCM Data\nProcessing and Quality Assurance of FCM Data\n\n\n\n\n1D Dynamic Gating\n1D Dynamic Gating\n\n\n\n\nClustering and Additional FCM Tools\nClustering and Additional FCM Tools\n\n\n\n\n\nTulika Rai - Learn Innovatively With Me\n\nflowAI Flow Cytometry Data Cleaning using R\nflowAI Flow Cytometry Data Cleaning using R: A Step-by-step Tutorial\n\n\n\n\ntSNE UMAP TRIMAP colorization or Transformation using R script\ntSNE UMAP TRIMAP colorization or Transformation using R script\n\n\n\n\n\n\n\nGivanna Putri - Introduction to Cytometry Data Analysis in R workshop\nACS 2021 Workshops - Introduction to Cytometry Data Analysis in R workshop\n\n\n\n\n\n\nTimothy Keyes -\n{tidytof}: Predicting Patient Outcomes from Single-cell Data using Tidy Data Principles\n\n\n\n\n\n\nRyan Duggan - Cytometry on Air\nCytometry on Air: Analyzing Flow Cytometry Data in R Presentation by TJ Chen and Greg Finak,\n\n\n\n\n\n\nGuillaume Beyrend - Learn Cytometry\nLearn Cytometry Originally appeared to have been paywalled, doesn’t currently appear to be the case.\n\n\n\n\nHong Qin - flow analysis in R\n\nFlow Analysis in R\nflow analysis in R, bio125, Spring 2015\n\n\n\n\nFlow Cytometer Data Analysis\nBIO233 demo, flow cytometer data analysis, simple example\n\n\n\n\n\n\n\nSwayam Prabha - Flow cytometry data analysis in R/Bioconductor\nLecture 15 : Flow cytometry data analysis in R/Bioconductor" + "text": "CytoML\n\n\n\n\n\n\n\n\n.\n\n\nDue to a unknown formatting bug, the Floreada produced FlowJo v10 .wsp is not directly accessible by CytoML at the time of this course. However, the issue is resolved as soon as the file is opened the first time within FlowJo v10, regardless of whether you have a log in or not. Strange? Yes, but we will take the workaround.\nSo, for anyone on Windows or MacOS, download FlowJo v10. Once installed, open the software, and close the login popups. Once there, open the Floreada created FlowJo.wsp file. Since you haven’t logged in, it won’t show any events. But it will correct the formatting bug. Close the software, and return to R. Your Floreada sourced .WSP file should now be readable by CytoML.\nOdd? For sure. Fixable? Likely, I will set a reminder to work with the Floreada and CytoML devs to see if we can cut out the need for this workaround." }, { - "objectID": "index.html", - "href": "index.html", - "title": "About", + "objectID": "course/00_BonusContent/PullConflicts/UpdatedPullRequest.html", + "href": "course/00_BonusContent/PullConflicts/UpdatedPullRequest.html", + "title": "Updated Pull Request Protocol", "section": "", - "text": "Cytometry in R is a free weekly mini-course being offered both in-person and online by the Flow Cytometry Shared Resource staff at the University of Maryland Greenebaum Comprehensive Cancer Center. Its primary audience is for those with prior flow cytometry knowledge, who have limited previous experience with the programming language R. However, we welcome everyone regardless of their existing  flow cytometry  or coding experience.\nThis course is a passion project arising from our desire to contribute back to the community. We are excited that so many of you have chosen to sign up, and look forward to helping you get started on your own learning journeys.\nFor more information on topics-covered, please see our schedule. Course materials can be found here or via the Course tab in the navigation bar. The livestream recordings are available via YouTube\n\n\nAbout\n\n\nMotivation\nWhile many cytometry enthusiast express an interest in learning how to carry out flow cytometry analyses in R, they often do not know where to start. Additionally, many of the limited existing resources are focused towards users with intermediate bioinformatic skills, contributing to a greater barrier for entry for those just starting out. Our motivation in offering this mini-course tailored towards beginners is to make the learning journey smoother than the one we ourselves experienced.\n\nWhile designing the course, we kept the following concepts in mind:\n\nBeginning coders benefit both by having detailed examples that they can initially work through on their own time, as well as less defined problems that through troubleshooting enable the acquisition of the thought-process and skills needed for coding.\nSome topics will take individuals a longer time to fully grasp. Providing a format and resources that enable being able to revisit the material multiple times is incredibly helpful. Likewise, life is busy, and missing a workshop session is highly probable. If this happens, it shouldn’t make or break the ability of the individual to understanding the rest of the course.\nConsistency is key, and being able to apply what you are learning to your own datasets, files, and questions of interest helps achieve this.\n\n\n\n\n\nCourse Details\n\nEach week, the mini-course will cover a particular topic for an hour. This individual class is offered on multiple days, at different times, both in-person and online. We invite you to attend the one that best fits your schedule each week. If life gets busy and you can’t make regular day, the online livestream recordings will be available on YouTube.\n \n\nCourse Materials\n\nWe will release the course materials for the upcoming week on Monday 1700 EST (Monday 2200 GMT+0) via our course website and GitHub. These materials will normally be Quarto Markdown documents containing code, explanation, and other resources needed for that week. If you have your own data, you can use your own data! If you don’t have any data, we will make sure to provide some of our own available data for each lesson so that you can use it and be able to follow along.\nIn our commitment to open-source and open-science, all teaching materials are freely offered under a CC-BY-SA license, while all code examples are offered under the AGPL3-0 copyleft license.\n \n\n\nIn-Person (Baltimore)\n\nFor those who are local and attending in person, the class will be offered on Thursday from 4-5 pm EST in Bressler Research Building Conference Room 7-035 (around the corner from the Flow Core).\nIf you have your own laptop, feel free to bring it. If you don’t have a laptop, please reach out, the Flow Core has 6 laptops running Linux that we can lend out to participants for use during the session.\nFor those who arrive early, we will have a limited number of second screens with provided mouse and keyboard that you can plug a laptop into via HDMI cable to set up a larger workstation. For those arriving later, the room has enough space (and electrical plugs) for up to 20 people, but you will need to balance a laptop on your lap.\n \n\n\nOnline (Worldwide)\n\nFor those joining us virtually, we will have three separate livestreams throughout the week on YouTube. These will be offered on:\n\nTuesday 2200 EST (Wednesday 0300 GMT+0)\nWednesday 1600 EST (Wednesday 2100 GMT+0)\nThursday 1000 EST (Thursday 1500 GMT+0)\n\n \n\n\nRecordings\n\nAll three livestreams will be recorded and available on YouTube immediately afterwards. Our plan is to eventually circle back after the course and properly edit them (ie. less minutes of random background noise, highlighting the relevant lines of code, time-stamps, subtitles, translations, etc.) later on as time allows, so that they can serve as a more permanent resource.  \n\n\nDiscussion Forum\n\nWe will be using our GitHub Discussions page as a community forum. This will allow us to answer questions, and benefit from insights from others in the community. One advantage of having so many people signed up for the course is that if you have a question, someone else likely does as well, so go start a post and ask it!\n \n\n\nOptional Take-Home Problems\n\nEach week, we will offer optional take-home problems. These are intended to allow you to work with your own data on similar problems, but in a not-so-structured manner. Challenges that you and overcome during the process will help grow your problem solving and debugging skills, and help solidify concepts covered during the course.\nTo get feedback on these problems, you can reach out to the community on the Discussions page, or once far enough open a pull request to the homework branch and we will provide additional feedback.\n \n\n\nCost\nIs there a cost to participate? No, it’s absolutely free! Is there a catch? Yes, you learn R, and may wind up with strong feelings about flowframes vs. cytoframes. This is also our first year offering this course, so we will sporadically ask you to fill out a feedback forms to help us improve.\n\n \n\n\nComputing Requirements\n\nFor those attending online, you will need a computer with internet access. Operating system shouldn’t matter, as we will be offering code examples for Windows, Mac and Linux. As with all things flow-cytometry software, having a faster CPU with multiple cores, more RAM and greater storage space is generally helpful, but not a deal breaker.\n\nYou will need to be able to install the required software (R, Rtools, Positron, Quarto, and Git) as well as install and compile R packages from the CRAN and Bioconductor repositories (as well as a few GitHub-based R packages). Installation walkthroughs for each computer operating system can be found here.\nFor those using university or company administered computers, please be aware that you may not have the necessary permissions to install these directly, and may need to reach out to your IT department to help get these initial requirements set up. If you are using your own computer, congratulations, you are your system administrator, and should already have the necessary permissions.\n\nFor those attending in-person, we have set up a pop-up computer lab in the conference room. For those who arrive early, we have a limited number of second screens with provided mouse and keyboard that you can plug a laptop into via HDMI cable to set up a workstation. For those arriving later, the room has enough space (and electrical plugs) for 20 people, but you will need to balance a laptop on your lap. If you have your own laptop, feel free to bring it. If you don’t have a laptop, the flow core has 6 loaner laptops running Linux that we can let participants use for that session.\n\n\n\n\nLicense\nIn our commitment to open-science and open-source, all teaching materials are freely offered under a CC-BY-SA license, while all code examples are offered under the AGPL3-0 copyleft license." + "text": "Background\nDue to an encountered issue pulling in new updates for CytometryInR when you have an optional take-home problem still waiting to be reviewed, we will be modifying the protocol for submitting a pull request. You will first create a local homework branch, and submit from your branch to our homework branch. That should hopefully prevent any incoming changes from main to main from becoming conflicted.\n\n\nGetting Started\nThe first step is to open Positron, and navigate through the dropdown options to the Create a Branch option\n\n\nAnd provide a name (since the homework was for Week 02, we set it as Week 02)\n\n\nNext, select the option to Publish the Branch\n\n\nFrom here, importantly, select the option to make it a branch of YOUR forked CytometryInR version (since you don’t have permissions for the main course repository)\n\n\nAt this point, your new branch will have been created. You can check by entering the following code in the terminal, and verifying the * is next to the Week02 branch\n\ngit branch\n\n\n\nOnce you have confirmed you are in your homework branch, go ahead and transfer in all the files you will be submitting for the optional take-home problems\n\n\nAnd once done, make a commit as you would normally\n\n\nAs you can see, you will now be ahead of the main branch by one commit. Go ahead and sync your branch to GitHub so the contents are available remotely for use in the pull-request.\n\n\nOnce synced, you will notice that your branch is now up to date with the remote (cloud) icon. Next, proceed to checkout to the main branch, either via the dropdown or via the terminal using\n\ngit checkout main\n\n\n\nReturning to GitHub, you will see that your homework branch has received the incoming changes. You are now safe to sync your fork to bring in changes from the main course CytometryInR repository.\n\n\nAnd confirm yes.\n\n\nReturning to Positron, once verified you are in your main branch, proceed to pull in changes\n\n\nIf you switch between branches, you will notice you have both the new changes to main, as well as your week specific side branch co-existing peacefully.\n\n\nYou are then safe to make a pullrequest from your homework branch, to our homework branch, without running into risk of an additional commit from our end (or delay in reviewing) causing issues.\n\n\n\n\nAdditional Resources\nThis method should hopefully avoid the previously encountered issues. Apologies once again to those who encountered the issue! Still learning how to use some of these aspects of Version control in a GitHub context." }, { - "objectID": "Schedule.html", - "href": "Schedule.html", - "title": "Cytometry in R", + "objectID": "course/00_BonusContent/Immport/images/index.html", + "href": "course/00_BonusContent/Immport/images/index.html", + "title": "ImmPort - Downloading Datasets", "section": "", - "text": "Cytometry in R: A Course for Beginners\nCytometry in R is a free virtual mini-course being organized by the Flow Cytometry Shared Resource core at the University of Maryland’s Greenebaum Comprehensive Cancer Center. This course is a passion project arising from our desire to contribute back to the community. We are excited that you have chosen to take part and look forward to helping you get started on your own learning journey.\nCourse materials can be found here or via the Course tab in the navigation bar. The livestream recordings are available via YouTube\n\n\n\nPre-Course Walkthroughs\n\nWeek 0: January 26, 2026 In these pre-course walk-throughs, we ensure that everyone creates a GitHub account, and has their computer properly set up with the required software (including R, Positron, and Git). We then start to build individual participants familiarity with the software infrastructure that they will be using throughout the rest of the course.\n \n\n\nInstalling R Packages\n\nWeek 1: February 2, 2026 During this first session, we learn how to install R packages from the various repositories (CRAN, Bioconductor, GitHub), and how to troubleshoot the more typical errors that occur during this process.\n \n\n\nFile Paths\n\nWeek 2: February 9, 2026 For this second session, we focus on how to programmatically tell your computer where to locate your experimental files, introducing the concept of file paths. We explore how the various operating systems (Linux, MacOS, Windows) specify their respective folders and files, and how to identify where you are currently within the directory. Our goal by the end of this session is to have walked you through how to figure out where an .fcs file of interest is stored, and convey to your computer where you want it copied/moved to, without encountering the common pitfalls.\n \n\n\nInside an .FCS file\n\nWeek 3: February 16, 2026 In the course of this third session we will slice into an .FCS file and find out what the individual components that make it up are. In the process, we will cover the concepts of main data structures within R (vectors, matrices, data.frames, list) and how to identify what we are working with. Additionally, we will explore how various cytometry softwares store their metadata variables under various keywords that can be useful to know about.\n \n\n\nIntroduction to the Tidyverse\n\nWeek 4: February 23, 2026 Within this fourth session, we explore how the various tidyverse packages can be utilized to reorganize rows and columns of data in ways that are useful for data analysis. We will primarily work with the MFI expression data we isolated from within the .fcs file in the previous session, identifying and isolating events that meet certain criterias. We introduce the concepts behind “tidy” data and how it can improve our workflows.\n \n\n\nGating Sets\n\nWeek 5: March 2, 2026 As part of this fifth session, we learn about the two main flow cytometry infrastructure packages in R we will be working with during the course, flowcore and flowWorkspace. Throughout the session, we will compare how they differ in naming, memory usage, and accessing .fcs file metadata. We additionally explore how to add keywords to their respective metadata for use in filtering specimens of interest from the larger set of .fcs files.\n \n\n\nVisualizing with ggplot2\n\nWeek 6: March 9, 2026 During this session we provide an introduction to the ggplot2 package. We will take the datasets we have collected from the previous sessions and see how in varying in different arguments at the respective plot layers we can produce and customize many different forms of plots, focusing on both cytometry and statistics plots. We close out providing links to additional helpful resources and highlight the TidyTuesday project.\n \n\n\nApplying Transformations and Compensation\n\nWeek 7: March 16, 2026 For this seventh session, we take a closer look at the raw values of the data within our .fcs files, and explore the various ways to transform (ie. scale) flow cytometry data in R to better visualize “positive” and “negative populations”. In the process, we visualize the differences resulting from applying different transformations commonly used by commercial software. Similarly, we learn how to apply and visualize compensation in context of conventional flow cytometry files.\n \n\n\nManual and Automated Gating\n\nWeek 8: March 23, 2026 Within this session, we explore various ways to implement gating for flow cytometry files in R. We will explore manual approaches utilizing flowGate, as well as automated options with openCyto and it’s gating templates. We additionally will explore how to provide gate constraints and various ways to visually screen and evaluate the outcomes within the context of our own projects.\n \n\n\nConference Break 1\nNo class week of March 30, 2026. If you are attending the ABRF conference, track me down at the Complex Data Analysis in Flow Cytometry: Navigating the Landscape talk on Monday, March 30th at 4:30 PM.\n \n\n\nIt’s Raining Functions!\n\nWeek 9: April 6, 2026 In the course of this ninth session, we tackle one of the harder but most useful concepts to learn for a beginner, namely functions. We explore what they are, how their individual arguments work, how they differ from for-loops, and how to create our own to do useful work, reduce the number times code gets copied and pasted. Additionally, some functional programming best practices will be introduced, as well as provide introduction to how to use the walk and map functions from the purrr package.\n \n\n\nDownsampling and Concatenation\n\nWeek 10: April 13, 2026 Within this session, we will expand on our growing understanding of GatingSets, functions and fcs file internals to write a script to downsample your fcs files to a desired number (or percentage) of cells for a given cell population. We will additionally learn how to concatenate these downsampled files together, and save them to a new .fcs file in ways that the metadata can be read by commercial software without the scaling being widely thrown off.\n \n\n\nRetrieving data for Statistics\n\nWeek 11: April 20, 2026 Leveraging the increased familiarity working with the various packages this far in the course, in this session we will retrieve summary statistics for the gates within our GatingSet, and programmatically derrive out tidy data.frames for use in statistical analyses typically used by many Immunologist. In the process, we add a couple additional plot types to our ggplot2 arsenal to hold in reserve should Prism prices go up again.\n \n\n\nSpectral Signatures\n\nWeek 12: April 27, 2026 As part of this session, we will explore how to extract fluorescent signatures from our raw spectral flow cytometry reference controls. Building on prior concepts, we will learn to isolate median signatures from positive and negative gates, and how to derrive and plot normalized signatures. We also introduce plotly package and it’s interactive plotting features, before showcasing various packages attempts at facilitating signature retrieval.\n \n\n\nSimilarities and Hotspots\n\nWeek 13: May 4, 2026 During this session, we will utilize the spectral signature matrix isolated from raw spectral flow cytometry controls and evaluate different ways of evaluating how similar different fluorescent signatures are to each other. In the process, we will gain better understanding of the metrics behind similarity (cosine), panel complexity (kappa), and unmixing-dependent spreading (collinearity).\n \n\n\nUnmixing in R\n\nWeek 14: May 11, 2026 In the course of this session, we will attempt a reach goal of many, namely carry out unmixing of raw .fcs files using the spectral signatures we have isolated from our unmixing controls, and write to new .fcs files. After evaluating the necessary internals, we will explore how various current cytometry R packages have implemented their own unmixing functions, and the various limitations that each approach has encountered.\n \n\n\nCleaning Algorithms\n\nWeek 15: May 18, 2026 In the span of this session, we will directly compare how various Bioconductor data cleanup algorithms (namely PeacoQC, FlowAI, FlowCut, and FlowClean) tackle distinguishing and removing bad quality events. We will see how they perform with previously identified good quality and horrific quality .fcs files. We will whether the implemented algorithmic decisions made sense, and how to customize them within our workflows to achieve our own desired goals.\n \n\n\nClustering Algorithms\n\nWeek 16: May 25, 2026 As part of this session, we venture away from supervised and semi-supervised analyses to explore unsupervised clustering approaches, namely FlowSOM and Phenograph. We will compare outcomes depending markers included, transformations applied, and panel used to gain a greater familiarity with how they work. We wrap up by investigating ways to visualize marker expression of cells ending up in each cluster, and how to backgate them to our manual gates.\n \n\n\nNormalization: Batch Effect or Real Biology\n\nWeek 17: June 1, 2026 During this session, we will dive into evaluating the performance of two commonly used normalization algorithms, CytoNorm and CyCombine. We will utilize our ggplot2 and functional programming toolkits to create a customized workflow to visualize the differences for our respective cell populations before and after normalization, to better evaluate how the respective parameter choices can affect the process.\n \n\n\nConference Break 2\nNo class week of June 8, 2026. If you are attending the Cyto conference, track me down at my talks (Open-Source automation on June 7, 10:30-11:30AM at Grand Ballroom; and Semi-supervised pipeline on June 9, 10:30-11:45AM atRoom 2DEF) or poster (grab some Cytometry in R course hex stickers!)\n \n\n\nDimensionality Visualization\n\nWeek 18: June 15, 2026 For this session, we explore how dimensionality visualization algorithms perform tSNE and UMAP in R using our raw and unmixed samples. In the process, we will explore how markers included, number of cells, and presence of bad quality events can impact the final visualizations. Finally, we will provide an overview of how to link to Python to additionally run PaCMAP and PHATE visualizations for use in R.\n \n\n\nAnnotating Unsupervised Clusters\n\nWeek 19: June 22, 2026 In the course of this session, we explore ways to scale our efficiency in figuring out what an unsupervised cluster of cells may be, by employing several annotation packages. We explore how these work under the hood in their decision making process, and how to link them to reference data from external repositories for additional evaluation.\n \n\n\nThe Art of GitHub Diving\n\nWeek 20: June 29, 2026 Within this session, we delve into the art of investigating a new-to-you GitHub repository. We discuss the overall structure of R packages stored as source files within GitHub repositories, and how to leverage this knowledge when troubleshooting errors thrown by underdocumented R packages. We discuss how to modify identified functions, evaluate them, and process to submit helpful bug reports back to the original project to help fix the issue.\n \n\n\nXML Files All The Way Down\n\nWeek 21: July 6, 2026 Breaking news alert, most of the experiment templates and worksheet layouts we work with as cytometrist are .xml files. In this session, we learn some additional coding tools to allow us to work with these types of files to extract useful data. In this session, we test out our new problem solving abilities to retrieve data from SpectroFlo and Diva .xml files to monitor how our core’s flow cytometers behaved for various users last week.\n \n\n\nUtilizing Bioconductor packages\n\nWeek 22: July 13, 2026 Many of the R packages for Flow Cytometry we have utilized in this course were packages from the Bioconductor project. We take a look at what makes Bioconductor packages unique compared to packages found on GitHub and CRAN, explore some of their specific infrastructure types for flow cytometry data, and highlight some useful packages for downstream analysis that we haven’t had time to properly explore.\n \n\n\nBuilding your First R package\n\nWeek 23: July 20, 2026 For most of the course, we have been working with R packages that other individuals built and maintained. In this session, we leverage all your hard work from the rest of the course and corral the unwieldly arsenal of functions you wrote into your first R package for easier use. We will discuss the individual pieces of an R package, the importance of a well-setup namespace file, and how to generate help page manuals to refer future-you back to what your individual function arguments actually do.\n \n\n\nEveryone Get’s a Quarto Website\n\nWeek 24: July 27, 2026 In this session, we will extend the knowledge of .R and .qmd files you have gained from the course and extend them to create your own website using Quarto. We discuss the additional files that are required, how to customize and render the website locally, and finally set up Quarto Pub or GitHub Pages website that we are to access online.\n \n\n\nReproducibility and Replicability\n\nWeek 25: August 3, 2026 Throughout the course, we emphasized the importance of making your workspaces and code reproducible and replicable. But what do we mean by these terms, and are there best practices we could add to our existing workflow to do this more efficiently? We explore a couple community-led efforts within the cytometry space and troubleshoot their implementation into a previously published pipeline.\n \n\n\nConference Break 3\nNo class week of August 10, 2026. If you are attending the BioC conference, track me down at my talk/poster.\n \n\n\nOpen Source Licenses\n\nWeek 26: August 17, 2026 For this course, we have relied extensively on open-source software to create our own data analysis pipelines. In the process, you may have some recollection of the various license names. But what impact do all these different names have in the end? We take a brief deep-dive into the ecosystem of free and open-source licenses, and evaluate what their respective license terms mean for us as individual users of the code, as well as potential developers extending existing codebases.\n \n\n\nValidating Algorthmic Tools\n\nWeek 27: August 24, 2026 We will be the first to admit, new implementations of algorithms as R packages are awesome! We appreciate the effort that went into them and making them available to the community at large. But what is the best way of evaluating whether they behave as promised, or work for our dataset? During this session, we share tips and tricks to gain better understanding of how a new R package works, and things to watch out for when evaluating complicated algortithms. We wrap with walkthrough of how to generate simulated datasets with known distributions for use in testing.\n \n\n\nDatabases and Repositories\n\nWeek 28: August 31, 2026 During this session, we will learn how to identify and retrieve .fcs files from databases. While many of us are accustomed to working with large datasets of our own making, many of us are increasingly encountering larger-than-memory datasets, as well as files stored in large repositories. In this session, we will explore several database focused R packages, before investigating how to identify and retrieve .fcs files and associated metadata of interest from repositories, namely ImmPort (and maybe FlowRepository if it can be pinged that afternoon).\n \n\n\nAssembling Web Data\n\nWeek 29: September 7, 2026 In this session, we briefly delve into the concepts of web-scraping and APIs in general. We highlight useful packages, namely httr2 and rvest, and best practices implemented to allow respectful retrieval of useful data without crashing someone’s server like some AI startup bot. We finish by providing a list of additional useful resources for those interested in learning more.\n \n\n\nFuture Directions\n\nWeek 30: September 14, 2026 In this final of the planned sessions, we revisit our solutions to the challenge problems set out during the beginning of the course. We also discuss potential future topics to visit in the future, and any additional resources that proved helpful throughout the course.", - "crumbs": [ - "About", - "Cytometry Core" - ] + "text": "To download data from the ImmPort Shared Data Repository, first navigate to the website\n\nFor help setting up Aspera Connect, see the following help documentation" }, { "objectID": "PackageWalkthroughs.html#flowcore", @@ -1804,861 +1631,1141 @@ "text": "flowMagic" }, { - "objectID": "course/00_BonusContent/Immport/images/index.html", - "href": "course/00_BonusContent/Immport/images/index.html", - "title": "ImmPort - Downloading Datasets", + "objectID": "Schedule.html", + "href": "Schedule.html", + "title": "Cytometry in R", "section": "", - "text": "To download data from the ImmPort Shared Data Repository, first navigate to the website\n\nFor help setting up Aspera Connect, see the following help documentation" + "text": "Cytometry in R: A Course for Beginners\nCytometry in R is a free virtual mini-course being organized by the Flow Cytometry Shared Resource core at the University of Maryland’s Greenebaum Comprehensive Cancer Center. This course is a passion project arising from our desire to contribute back to the community. We are excited that you have chosen to take part and look forward to helping you get started on your own learning journey.\nCourse materials can be found here or via the Course tab in the navigation bar. The livestream recordings are available via YouTube\n\n\n\nPre-Course Walkthroughs\n\nWeek 0: January 26, 2026 In these pre-course walk-throughs, we ensure that everyone creates a GitHub account, and has their computer properly set up with the required software (including R, Positron, and Git). We then start to build individual participants familiarity with the software infrastructure that they will be using throughout the rest of the course.\n \n\n\nInstalling R Packages\n\nWeek 1: February 2, 2026 During this first session, we learn how to install R packages from the various repositories (CRAN, Bioconductor, GitHub), and how to troubleshoot the more typical errors that occur during this process.\n \n\n\nFile Paths\n\nWeek 2: February 9, 2026 For this second session, we focus on how to programmatically tell your computer where to locate your experimental files, introducing the concept of file paths. We explore how the various operating systems (Linux, MacOS, Windows) specify their respective folders and files, and how to identify where you are currently within the directory. Our goal by the end of this session is to have walked you through how to figure out where an .fcs file of interest is stored, and convey to your computer where you want it copied/moved to, without encountering the common pitfalls.\n \n\n\nInside an .FCS file\n\nWeek 3: February 16, 2026 In the course of this third session we will slice into an .FCS file and find out what the individual components that make it up are. In the process, we will cover the concepts of main data structures within R (vectors, matrices, data.frames, list) and how to identify what we are working with. Additionally, we will explore how various cytometry softwares store their metadata variables under various keywords that can be useful to know about.\n \n\n\nIntroduction to the Tidyverse\n\nWeek 4: February 23, 2026 Within this fourth session, we explore how the various tidyverse packages can be utilized to reorganize rows and columns of data in ways that are useful for data analysis. We will primarily work with the MFI expression data we isolated from within the .fcs file in the previous session, identifying and isolating events that meet certain criterias. We introduce the concepts behind “tidy” data and how it can improve our workflows.\n \n\n\nGating Sets\n\nWeek 5: March 2, 2026 As part of this fifth session, we learn about the two main flow cytometry infrastructure packages in R we will be working with during the course, flowcore and flowWorkspace. Throughout the session, we will compare how they differ in naming, memory usage, and accessing .fcs file metadata. We additionally explore how to add keywords to their respective metadata for use in filtering specimens of interest from the larger set of .fcs files.\n \n\n\nVisualizing with ggplot2\n\nWeek 6: March 9, 2026 During this session we provide an introduction to the ggplot2 package. We will take the datasets we have collected from the previous sessions and see how in varying in different arguments at the respective plot layers we can produce and customize many different forms of plots, focusing on both cytometry and statistics plots. We close out providing links to additional helpful resources and highlight the TidyTuesday project.\n \n\n\nApplying Transformations and Compensation\n\nWeek 7: March 16, 2026 For this seventh session, we take a closer look at the raw values of the data within our .fcs files, and explore the various ways to transform (ie. scale) flow cytometry data in R to better visualize “positive” and “negative populations”. In the process, we visualize the differences resulting from applying different transformations commonly used by commercial software. Similarly, we learn how to apply and visualize compensation in context of conventional flow cytometry files.\n \n\n\nManual and Automated Gating\n\nWeek 8: March 23, 2026 Within this session, we explore various ways to implement gating for flow cytometry files in R. We will explore manual approaches utilizing flowGate, as well as automated options with openCyto and it’s gating templates. We additionally will explore how to provide gate constraints and various ways to visually screen and evaluate the outcomes within the context of our own projects.\n \n\n\nConference Break 1\nNo class week of March 30, 2026. If you are attending the ABRF conference, track me down at the Complex Data Analysis in Flow Cytometry: Navigating the Landscape talk on Monday, March 30th at 4:30 PM.\n \n\n\nIt’s Raining Functions!\n\nWeek 9: April 6, 2026 In the course of this ninth session, we tackle one of the harder but most useful concepts to learn for a beginner, namely functions. We explore what they are, how their individual arguments work, how they differ from for-loops, and how to create our own to do useful work, reduce the number times code gets copied and pasted. Additionally, some functional programming best practices will be introduced, as well as provide introduction to how to use the walk and map functions from the purrr package.\n \n\n\nDownsampling and Concatenation\n\nWeek 10: April 13, 2026 Within this session, we will expand on our growing understanding of GatingSets, functions and fcs file internals to write a script to downsample your fcs files to a desired number (or percentage) of cells for a given cell population. We will additionally learn how to concatenate these downsampled files together, and save them to a new .fcs file in ways that the metadata can be read by commercial software without the scaling being widely thrown off.\n \n\n\nRetrieving data for Statistics\n\nWeek 11: April 20, 2026 Leveraging the increased familiarity working with the various packages this far in the course, in this session we will retrieve summary statistics for the gates within our GatingSet, and programmatically derrive out tidy data.frames for use in statistical analyses typically used by many Immunologist. In the process, we add a couple additional plot types to our ggplot2 arsenal to hold in reserve should Prism prices go up again.\n \n\n\nSpectral Signatures\n\nWeek 12: April 27, 2026 As part of this session, we will explore how to extract fluorescent signatures from our raw spectral flow cytometry reference controls. Building on prior concepts, we will learn to isolate median signatures from positive and negative gates, and how to derrive and plot normalized signatures. We also introduce plotly package and it’s interactive plotting features, before showcasing various packages attempts at facilitating signature retrieval.\n \n\n\nSimilarities and Hotspots\n\nWeek 13: May 4, 2026 During this session, we will utilize the spectral signature matrix isolated from raw spectral flow cytometry controls and evaluate different ways of evaluating how similar different fluorescent signatures are to each other. In the process, we will gain better understanding of the metrics behind similarity (cosine), panel complexity (kappa), and unmixing-dependent spreading (collinearity).\n \n\n\nUnmixing in R\n\nWeek 14: May 11, 2026 In the course of this session, we will attempt a reach goal of many, namely carry out unmixing of raw .fcs files using the spectral signatures we have isolated from our unmixing controls, and write to new .fcs files. After evaluating the necessary internals, we will explore how various current cytometry R packages have implemented their own unmixing functions, and the various limitations that each approach has encountered.\n \n\n\nCleaning Algorithms\n\nWeek 15: May 18, 2026 In the span of this session, we will directly compare how various Bioconductor data cleanup algorithms (namely PeacoQC, FlowAI, FlowCut, and FlowClean) tackle distinguishing and removing bad quality events. We will see how they perform with previously identified good quality and horrific quality .fcs files. We will whether the implemented algorithmic decisions made sense, and how to customize them within our workflows to achieve our own desired goals.\n \n\n\nClustering Algorithms\n\nWeek 16: May 25, 2026 As part of this session, we venture away from supervised and semi-supervised analyses to explore unsupervised clustering approaches, namely FlowSOM and Phenograph. We will compare outcomes depending markers included, transformations applied, and panel used to gain a greater familiarity with how they work. We wrap up by investigating ways to visualize marker expression of cells ending up in each cluster, and how to backgate them to our manual gates.\n \n\n\nNormalization: Batch Effect or Real Biology\n\nWeek 17: June 1, 2026 During this session, we will dive into evaluating the performance of two commonly used normalization algorithms, CytoNorm and CyCombine. We will utilize our ggplot2 and functional programming toolkits to create a customized workflow to visualize the differences for our respective cell populations before and after normalization, to better evaluate how the respective parameter choices can affect the process.\n \n\n\nConference Break 2\nNo class week of June 8, 2026. If you are attending the Cyto conference, track me down at my talks (Open-Source automation on June 7, 10:30-11:30AM at Grand Ballroom; and Semi-supervised pipeline on June 9, 10:30-11:45AM atRoom 2DEF) or poster (grab some Cytometry in R course hex stickers!)\n \n\n\nDimensionality Visualization\n\nWeek 18: June 15, 2026 For this session, we explore how dimensionality visualization algorithms perform tSNE and UMAP in R using our raw and unmixed samples. In the process, we will explore how markers included, number of cells, and presence of bad quality events can impact the final visualizations. Finally, we will provide an overview of how to link to Python to additionally run PaCMAP and PHATE visualizations for use in R.\n \n\n\nAnnotating Unsupervised Clusters\n\nWeek 19: June 22, 2026 In the course of this session, we explore ways to scale our efficiency in figuring out what an unsupervised cluster of cells may be, by employing several annotation packages. We explore how these work under the hood in their decision making process, and how to link them to reference data from external repositories for additional evaluation.\n \n\n\nThe Art of GitHub Diving\n\nWeek 20: June 29, 2026 Within this session, we delve into the art of investigating a new-to-you GitHub repository. We discuss the overall structure of R packages stored as source files within GitHub repositories, and how to leverage this knowledge when troubleshooting errors thrown by underdocumented R packages. We discuss how to modify identified functions, evaluate them, and process to submit helpful bug reports back to the original project to help fix the issue.\n \n\n\nXML Files All The Way Down\n\nWeek 21: July 6, 2026 Breaking news alert, most of the experiment templates and worksheet layouts we work with as cytometrist are .xml files. In this session, we learn some additional coding tools to allow us to work with these types of files to extract useful data. In this session, we test out our new problem solving abilities to retrieve data from SpectroFlo and Diva .xml files to monitor how our core’s flow cytometers behaved for various users last week.\n \n\n\nUtilizing Bioconductor packages\n\nWeek 22: July 13, 2026 Many of the R packages for Flow Cytometry we have utilized in this course were packages from the Bioconductor project. We take a look at what makes Bioconductor packages unique compared to packages found on GitHub and CRAN, explore some of their specific infrastructure types for flow cytometry data, and highlight some useful packages for downstream analysis that we haven’t had time to properly explore.\n \n\n\nBuilding your First R package\n\nWeek 23: July 20, 2026 For most of the course, we have been working with R packages that other individuals built and maintained. In this session, we leverage all your hard work from the rest of the course and corral the unwieldly arsenal of functions you wrote into your first R package for easier use. We will discuss the individual pieces of an R package, the importance of a well-setup namespace file, and how to generate help page manuals to refer future-you back to what your individual function arguments actually do.\n \n\n\nEveryone Get’s a Quarto Website\n\nWeek 24: July 27, 2026 In this session, we will extend the knowledge of .R and .qmd files you have gained from the course and extend them to create your own website using Quarto. We discuss the additional files that are required, how to customize and render the website locally, and finally set up Quarto Pub or GitHub Pages website that we are to access online.\n \n\n\nReproducibility and Replicability\n\nWeek 25: August 3, 2026 Throughout the course, we emphasized the importance of making your workspaces and code reproducible and replicable. But what do we mean by these terms, and are there best practices we could add to our existing workflow to do this more efficiently? We explore a couple community-led efforts within the cytometry space and troubleshoot their implementation into a previously published pipeline.\n \n\n\nConference Break 3\nNo class week of August 10, 2026. If you are attending the BioC conference, track me down at my talk/poster.\n \n\n\nOpen Source Licenses\n\nWeek 26: August 17, 2026 For this course, we have relied extensively on open-source software to create our own data analysis pipelines. In the process, you may have some recollection of the various license names. But what impact do all these different names have in the end? We take a brief deep-dive into the ecosystem of free and open-source licenses, and evaluate what their respective license terms mean for us as individual users of the code, as well as potential developers extending existing codebases.\n \n\n\nValidating Algorthmic Tools\n\nWeek 27: August 24, 2026 We will be the first to admit, new implementations of algorithms as R packages are awesome! We appreciate the effort that went into them and making them available to the community at large. But what is the best way of evaluating whether they behave as promised, or work for our dataset? During this session, we share tips and tricks to gain better understanding of how a new R package works, and things to watch out for when evaluating complicated algortithms. We wrap with walkthrough of how to generate simulated datasets with known distributions for use in testing.\n \n\n\nDatabases and Repositories\n\nWeek 28: August 31, 2026 During this session, we will learn how to identify and retrieve .fcs files from databases. While many of us are accustomed to working with large datasets of our own making, many of us are increasingly encountering larger-than-memory datasets, as well as files stored in large repositories. In this session, we will explore several database focused R packages, before investigating how to identify and retrieve .fcs files and associated metadata of interest from repositories, namely ImmPort (and maybe FlowRepository if it can be pinged that afternoon).\n \n\n\nAssembling Web Data\n\nWeek 29: September 7, 2026 In this session, we briefly delve into the concepts of web-scraping and APIs in general. We highlight useful packages, namely httr2 and rvest, and best practices implemented to allow respectful retrieval of useful data without crashing someone’s server like some AI startup bot. We finish by providing a list of additional useful resources for those interested in learning more.\n \n\n\nFuture Directions\n\nWeek 30: September 14, 2026 In this final of the planned sessions, we revisit our solutions to the challenge problems set out during the beginning of the course. We also discuss potential future topics to visit in the future, and any additional resources that proved helpful throughout the course.", + "crumbs": [ + "About", + "Cytometry Core" + ] }, { - "objectID": "course/00_BonusContent/PullConflicts/UpdatedPullRequest.html", - "href": "course/00_BonusContent/PullConflicts/UpdatedPullRequest.html", - "title": "Updated Pull Request Protocol", + "objectID": "index.html", + "href": "index.html", + "title": "About", "section": "", - "text": "Background\nDue to an encountered issue pulling in new updates for CytometryInR when you have an optional take-home problem still waiting to be reviewed, we will be modifying the protocol for submitting a pull request. You will first create a local homework branch, and submit from your branch to our homework branch. That should hopefully prevent any incoming changes from main to main from becoming conflicted.\n\n\nGetting Started\nThe first step is to open Positron, and navigate through the dropdown options to the Create a Branch option\n\n\nAnd provide a name (since the homework was for Week 02, we set it as Week 02)\n\n\nNext, select the option to Publish the Branch\n\n\nFrom here, importantly, select the option to make it a branch of YOUR forked CytometryInR version (since you don’t have permissions for the main course repository)\n\n\nAt this point, your new branch will have been created. You can check by entering the following code in the terminal, and verifying the * is next to the Week02 branch\n\ngit branch\n\n\n\nOnce you have confirmed you are in your homework branch, go ahead and transfer in all the files you will be submitting for the optional take-home problems\n\n\nAnd once done, make a commit as you would normally\n\n\nAs you can see, you will now be ahead of the main branch by one commit. Go ahead and sync your branch to GitHub so the contents are available remotely for use in the pull-request.\n\n\nOnce synced, you will notice that your branch is now up to date with the remote (cloud) icon. Next, proceed to checkout to the main branch, either via the dropdown or via the terminal using\n\ngit checkout main\n\n\n\nReturning to GitHub, you will see that your homework branch has received the incoming changes. You are now safe to sync your fork to bring in changes from the main course CytometryInR repository.\n\n\nAnd confirm yes.\n\n\nReturning to Positron, once verified you are in your main branch, proceed to pull in changes\n\n\nIf you switch between branches, you will notice you have both the new changes to main, as well as your week specific side branch co-existing peacefully.\n\n\nYou are then safe to make a pullrequest from your homework branch, to our homework branch, without running into risk of an additional commit from our end (or delay in reviewing) causing issues.\n\n\n\n\nAdditional Resources\nThis method should hopefully avoid the previously encountered issues. Apologies once again to those who encountered the issue! Still learning how to use some of these aspects of Version control in a GitHub context." - }, - { - "objectID": "course/00_Floreada/slides.html#floreada", - "href": "course/00_Floreada/slides.html#floreada", - "title": "Using Floreada", - "section": "Floreada", - "text": "Floreada\nLoading Dataset\n\n\n\n\n\n\n\n\n.\n\n\nFirst, open your web browser and navigate to the website\nClick on Start to proceed to the next page." + "text": "Cytometry in R is a free weekly mini-course being offered both in-person and online by the Flow Cytometry Shared Resource staff at the University of Maryland Greenebaum Comprehensive Cancer Center. Its primary audience is for those with prior flow cytometry knowledge, who have limited previous experience with the programming language R. However, we welcome everyone regardless of their existing  flow cytometry  or coding experience.\nThis course is a passion project arising from our desire to contribute back to the community. We are excited that so many of you have chosen to sign up, and look forward to helping you get started on your own learning journeys.\nFor more information on topics-covered, please see our schedule. Course materials can be found here or via the Course tab in the navigation bar. The livestream recordings are available via YouTube\n\n\nAbout\n\n\nMotivation\nWhile many cytometry enthusiast express an interest in learning how to carry out flow cytometry analyses in R, they often do not know where to start. Additionally, many of the limited existing resources are focused towards users with intermediate bioinformatic skills, contributing to a greater barrier for entry for those just starting out. Our motivation in offering this mini-course tailored towards beginners is to make the learning journey smoother than the one we ourselves experienced.\n\nWhile designing the course, we kept the following concepts in mind:\n\nBeginning coders benefit both by having detailed examples that they can initially work through on their own time, as well as less defined problems that through troubleshooting enable the acquisition of the thought-process and skills needed for coding.\nSome topics will take individuals a longer time to fully grasp. Providing a format and resources that enable being able to revisit the material multiple times is incredibly helpful. Likewise, life is busy, and missing a workshop session is highly probable. If this happens, it shouldn’t make or break the ability of the individual to understanding the rest of the course.\nConsistency is key, and being able to apply what you are learning to your own datasets, files, and questions of interest helps achieve this.\n\n\n\n\n\nCourse Details\n\nEach week, the mini-course will cover a particular topic for an hour. This individual class is offered on multiple days, at different times, both in-person and online. We invite you to attend the one that best fits your schedule each week. If life gets busy and you can’t make regular day, the online livestream recordings will be available on YouTube.\n \n\nCourse Materials\n\nWe will release the course materials for the upcoming week on Monday 1700 EST (Monday 2200 GMT+0) via our course website and GitHub. These materials will normally be Quarto Markdown documents containing code, explanation, and other resources needed for that week. If you have your own data, you can use your own data! If you don’t have any data, we will make sure to provide some of our own available data for each lesson so that you can use it and be able to follow along.\nIn our commitment to open-source and open-science, all teaching materials are freely offered under a CC-BY-SA license, while all code examples are offered under the AGPL3-0 copyleft license.\n \n\n\nIn-Person (Baltimore)\n\nFor those who are local and attending in person, the class will be offered on Thursday from 4-5 pm EST in Bressler Research Building Conference Room 7-035 (around the corner from the Flow Core).\nIf you have your own laptop, feel free to bring it. If you don’t have a laptop, please reach out, the Flow Core has 6 laptops running Linux that we can lend out to participants for use during the session.\nFor those who arrive early, we will have a limited number of second screens with provided mouse and keyboard that you can plug a laptop into via HDMI cable to set up a larger workstation. For those arriving later, the room has enough space (and electrical plugs) for up to 20 people, but you will need to balance a laptop on your lap.\n \n\n\nOnline (Worldwide)\n\nFor those joining us virtually, we will have three separate livestreams throughout the week on YouTube. These will be offered on:\n\nTuesday 2200 EST (Wednesday 0300 GMT+0)\nWednesday 1600 EST (Wednesday 2100 GMT+0)\nThursday 1000 EST (Thursday 1500 GMT+0)\n\n \n\n\nRecordings\n\nAll three livestreams will be recorded and available on YouTube immediately afterwards. Our plan is to eventually circle back after the course and properly edit them (ie. less minutes of random background noise, highlighting the relevant lines of code, time-stamps, subtitles, translations, etc.) later on as time allows, so that they can serve as a more permanent resource.  \n\n\nDiscussion Forum\n\nWe will be using our GitHub Discussions page as a community forum. This will allow us to answer questions, and benefit from insights from others in the community. One advantage of having so many people signed up for the course is that if you have a question, someone else likely does as well, so go start a post and ask it!\n \n\n\nOptional Take-Home Problems\n\nEach week, we will offer optional take-home problems. These are intended to allow you to work with your own data on similar problems, but in a not-so-structured manner. Challenges that you and overcome during the process will help grow your problem solving and debugging skills, and help solidify concepts covered during the course.\nTo get feedback on these problems, you can reach out to the community on the Discussions page, or once far enough open a pull request to the homework branch and we will provide additional feedback.\n \n\n\nCost\nIs there a cost to participate? No, it’s absolutely free! Is there a catch? Yes, you learn R, and may wind up with strong feelings about flowframes vs. cytoframes. This is also our first year offering this course, so we will sporadically ask you to fill out a feedback forms to help us improve.\n\n \n\n\nComputing Requirements\n\nFor those attending online, you will need a computer with internet access. Operating system shouldn’t matter, as we will be offering code examples for Windows, Mac and Linux. As with all things flow-cytometry software, having a faster CPU with multiple cores, more RAM and greater storage space is generally helpful, but not a deal breaker.\n\nYou will need to be able to install the required software (R, Rtools, Positron, Quarto, and Git) as well as install and compile R packages from the CRAN and Bioconductor repositories (as well as a few GitHub-based R packages). Installation walkthroughs for each computer operating system can be found here.\nFor those using university or company administered computers, please be aware that you may not have the necessary permissions to install these directly, and may need to reach out to your IT department to help get these initial requirements set up. If you are using your own computer, congratulations, you are your system administrator, and should already have the necessary permissions.\n\nFor those attending in-person, we have set up a pop-up computer lab in the conference room. For those who arrive early, we have a limited number of second screens with provided mouse and keyboard that you can plug a laptop into via HDMI cable to set up a workstation. For those arriving later, the room has enough space (and electrical plugs) for 20 people, but you will need to balance a laptop on your lap. If you have your own laptop, feel free to bring it. If you don’t have a laptop, the flow core has 6 loaner laptops running Linux that we can let participants use for that session.\n\n\n\n\nLicense\nIn our commitment to open-science and open-source, all teaching materials are freely offered under a CC-BY-SA license, while all code examples are offered under the AGPL3-0 copyleft license." }, { - "objectID": "course/00_Floreada/slides.html#cytoml", - "href": "course/00_Floreada/slides.html#cytoml", - "title": "Using Floreada", - "section": "CytoML", - "text": "CytoML\n\n\n\n\n\n\n\n\n.\n\n\nDue to a unknown formatting bug, the Floreada produced FlowJo v10 .wsp is not directly accessible by CytoML at the time of this course. However, the issue is resolved as soon as the file is opened the first time within FlowJo v10, regardless of whether you have a log in or not. Strange? Yes, but we will take the workaround.\nSo, for anyone on Windows or MacOS, download FlowJo v10. Once installed, open the software, and close the login popups. Once there, open the Floreada created FlowJo.wsp file. Since you haven’t logged in, it won’t show any events. But it will correct the formatting bug. Close the software, and return to R. Your Floreada sourced .WSP file should now be readable by CytoML.\nOdd? For sure. Fixable? Likely, I will set a reminder to work with the Floreada and CytoML devs to see if we can cut out the need for this workaround." + "objectID": "ExistingResources.html", + "href": "ExistingResources.html", + "title": "Existing Resources", + "section": "", + "text": "We are not the first “Cytometry in R” course, nor will we be the last. This page is linking to the already existant online Cytometry in R resources that we have encountered and benefited from during our own learning journey. May they prove useful to you as you progress your way through yours!\n\n\n\nChristopher Hall - Flow Cytometry Data Analysis in R\nCytometry-R-Scripts: R scripts to help with your flow cytometry analysis\nR_flowcytometry_course: The files and presentation from the Cytometry Core Facility flow cytometry data analysis course in R\n\nInstallation and Loading Data\n(1) Flow Cytometry Data Analysis in R - Installation and Loading Data\n\n\n\n\nCompensation, Cleaning, Transformation, Visualization\n(2) Flow Cytometry Data Analysis in R: compensation, cleaning, transformation, visualization\n\n\n\n\nGating with flowWorkspace\n(3) Flow Cytometry Data Analysis in R: gating with flowWorkspace\n\n\n\n\nVisualization\n(4) Flow Cytometry Data Analysis in R: Visualisation\n\n\n\n\n\n\n\nOzette Technologies - BioC 2023 Workshop\nWorkshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew McDavid.\nWorkshop: Reproducible and programmatic analysis of flow cytometry experiments with the cytoverse\n\n\n\n\n\n\nPritam Kumar Panda - Flow Cytometry Data Analysis & Visualization in R using CytoExploreR\nFlow-Cytometry-analysis-in-R\nCytoExploreR-Interactive-visualization\n\nComplete Guide\nFlow Cytometry Data Analysis & Visualization in R using CytoExploreR: Complete Guide\n\n\n\n\n\n\n\nBioinformatics DotCa - Introduction to Flow Cytometry in R\n\nIntroduction to Flow Cytometry in R\nIntroduction to Flow Cytometry in R\n\n\n\n\nExploring FCM Data in R\nExploring FCM Data in R\n\n\n\n\nProcessing and Quality Assurance of FCM Data\nProcessing and Quality Assurance of FCM Data\n\n\n\n\n1D Dynamic Gating\n1D Dynamic Gating\n\n\n\n\nClustering and Additional FCM Tools\nClustering and Additional FCM Tools\n\n\n\n\n\nTulika Rai - Learn Innovatively With Me\n\nflowAI Flow Cytometry Data Cleaning using R\nflowAI Flow Cytometry Data Cleaning using R: A Step-by-step Tutorial\n\n\n\n\ntSNE UMAP TRIMAP colorization or Transformation using R script\ntSNE UMAP TRIMAP colorization or Transformation using R script\n\n\n\n\n\n\n\nGivanna Putri - Introduction to Cytometry Data Analysis in R workshop\nACS 2021 Workshops - Introduction to Cytometry Data Analysis in R workshop\n\n\n\n\n\n\nTimothy Keyes -\n{tidytof}: Predicting Patient Outcomes from Single-cell Data using Tidy Data Principles\n\n\n\n\n\n\nRyan Duggan - Cytometry on Air\nCytometry on Air: Analyzing Flow Cytometry Data in R Presentation by TJ Chen and Greg Finak,\n\n\n\n\n\n\nGuillaume Beyrend - Learn Cytometry\nLearn Cytometry Originally appeared to have been paywalled, doesn’t currently appear to be the case.\n\n\n\n\nHong Qin - flow analysis in R\n\nFlow Analysis in R\nflow analysis in R, bio125, Spring 2015\n\n\n\n\nFlow Cytometer Data Analysis\nBIO233 demo, flow cytometer data analysis, simple example\n\n\n\n\n\n\n\nSwayam Prabha - Flow cytometry data analysis in R/Bioconductor\nLecture 15 : Flow cytometry data analysis in R/Bioconductor" }, { - "objectID": "course/00_Git/slides.html#new-folder-from-template", - "href": "course/00_Git/slides.html#new-folder-from-template", - "title": "Version Control with Git", - "section": "New Folder from Template", - "text": "New Folder from Template\n\n\n\n\n\n\n\n\n.\n\n\nSince Positron can use multiple programming languages, when we select “New Folder from Template” we will be asked what kind of folder template we want to use. Since we are working in R, we will select the “R Project” option." + "objectID": "course/index.html", + "href": "course/index.html", + "title": "Cytometry in R", + "section": "", + "text": "Cytometry in R is a free virtual mini-course being organized by the Flow Cytometry Shared Resource Core at the University of Maryland’s Greenebaum Comprehensive Cancer Center. This course is a passion project arising from our desire to contribute back to the community.\nWe are excited that so many individuals worldwide have chosen to take part, and we look forward to helping you get started on your own learning journeys." }, { - "objectID": "course/00_Git/slides.html#creating-subfolders", - "href": "course/00_Git/slides.html#creating-subfolders", - "title": "Version Control with Git", - "section": "Creating SubFolders", - "text": "Creating SubFolders\n\n\n\n\n\n\n\n\n.\n\n\nOnce your new project folder has opened, you should be seeing the main layout elements that we briefly covered in the Positron walk-through.\nFor this section, we will primarily be focused on what is happening within the primary side bar on the left, where changes to the individual files within the folder since the last save/commit will be reflected by colored text.\nFor my own projects, there are some elements of organization that I go ahead and add for each new folder. These include both a data and an images subfolders to help keep things a little more organized.\nTo create these folders, we would click on the respective add folder (+) button on the side bar. Files and Folders can be clicked and dragged within the primary side bar to move things to new folder locations." + "objectID": "course/index.html#resources", + "href": "course/index.html#resources", + "title": "Cytometry in R", + "section": "Resources", + "text": "Resources\nCourse materials can be found here. The livestream recordings are available via YouTube" }, { - "objectID": "course/00_Git/slides.html#creating-files", - "href": "course/00_Git/slides.html#creating-files", - "title": "Version Control with Git", - "section": "Creating Files", - "text": "Creating Files\n\n\n\n\n\n\n\n\n.\n\n\nIn context of this course, we will primarily be working with two types of files when coding:\n\nR Scripts: These files end in .R. These contain only code (with occasional # comment line). These are often used for self-contained code that once we get them working we rarely need to modify.\nQuarto Markdowns: These files end in .qmd. They contain a .yaml header, followed by a mix of regular written text (often explanations or other documentation), and sections (ie. chunks) that contain code. These are used when we are still getting the code to work, when we need to modify inputs frequently, or simply when we need to document what and why we are doing something to make life easier for our future-self two months from now." + "objectID": "course/index.html#in-person-baltimore", + "href": "course/index.html#in-person-baltimore", + "title": "Cytometry in R", + "section": "In-Person (Baltimore)", + "text": "In-Person (Baltimore)\nFor those joining us in person, the class is being offered on Thursday from 4-5 pm EST in Bressler Research Building Room 7-035. Monitors to plug your laptops in will be available on a first come, first served basis. These in-person sessions will not be recorded, but with the smaller class size you will have our undivided attention should you have any questions." }, { - "objectID": "course/00_Git/slides.html#qmd-files", - "href": "course/00_Git/slides.html#qmd-files", - "title": "Version Control with Git", - "section": "QMD Files", - "text": "QMD Files\n\n\n\n\n\n\n\n\n.\n\n\nOnce this is done, we can now see we have a new .qmd file (“Example.qmd” in this case).\n\n\n\n\n\nYAML\n\n\n\n\n\n\n\n\n.\n\n\nAs previously mentioned, the start of a Quarto Markdown file containg a YAML code chunk that is used to set formatting choices (we will explore this in-depth during the next section)\nWhat designates the location of the YAML block are three hyphens at the start, and three hyphens at the end. For this example, we will also provide a “title:” and “format:” field for the time being (see additional options here)." + "objectID": "course/index.html#virtual-worldwide", + "href": "course/index.html#virtual-worldwide", + "title": "Cytometry in R", + "section": "Virtual (Worldwide)", + "text": "Virtual (Worldwide)\nFor those joining us virtually, we will have three separate livestreams throughout the week on YouTube. These will be offered on:\n\nTuesday 2200 EST (Wednesday 0300 GMT+0)\nWednesday 1600 EST (Wednesday 2100 GMT+0)\nThursday 1000 EST (Thursday 1500 GMT+0)\n\nAll three livestreams will be recorded and available on YouTube immediately afterwards." }, { - "objectID": "course/00_Git/slides.html#local-version-control", - "href": "course/00_Git/slides.html#local-version-control", - "title": "Version Control with Git", - "section": "Local Version Control", - "text": "Local Version Control\n\n\n\n\n\n\n\n\n.\n\n\nHaving introduced the main elements of a Quarto Markdown file, let’s turn our attention to the tab within the editor showing our newly created .qmd file.\nWe can see there is a solid circle next to the file name, and it is appearing as green. The circle denotes unsaved changes, which we can correct by clicking on the Save Button to save the changes to our file." + "objectID": "course/index.html#discussion-forum", + "href": "course/index.html#discussion-forum", + "title": "Cytometry in R", + "section": "Discussion Forum", + "text": "Discussion Forum\nWe will be using the Cytometry in R Discussions page as a community forum, and a place to ask questions, celebrate wins, and provide feedback. After creating a a GitHub account, pleae go introduce yourself." }, { - "objectID": "course/00_Git/slides.html#remote-version-control", - "href": "course/00_Git/slides.html#remote-version-control", - "title": "Version Control with Git", - "section": "Remote Version Control", - "text": "Remote Version Control\nCopying Project Folder to GitHub\n\n\n\n\n\n\n\n\n.\n\n\nWhile having local version control in place is helpful when you need to revert back after encountering issues, where Git shines is the ability to pass your changes to your online GitHub repository.\nNot only does this allow you to switch between computers, but should something disastrous happen to your main computer, you still have all your hard work backed up and readily assessible.\nFor this subsection, first, double check that Positron is still connected to your GitHub account by checking the user tab on the bottom-left. If not, repeat the connection setup." + "objectID": "course/00_BonusContent/PullConflicts/index.html", + "href": "course/00_BonusContent/PullConflicts/index.html", + "title": "Take-Home Problems - Pull Fix Resolution", + "section": "", + "text": "Background\nFor those who have turned in the homework to the Cytometry in R - homework branches, many report having encountered merge issues pulling in the next week’s data if the pull request hasn’t been resolved yet. Creating a parallel branch, and submitting homework from there to the homework branch might solve the issue? But we will need to test that out. For now, here are the steps we used to resolve the issue locally without needing to delete and re-download.\n\n\nGetting Started\nStart off checking your GitHub forked version of the CytometryInR, notice how many commits behind you are.\n\n\nIf you haven’t submitted the optional Take-Home problems via a pull-request, proceed to do so.\n\n\nThis was an example of the page you see when submitting the pull request. Upon submission, your branch may show merge conflicts due to difference in rendered docs. This is okay, we will resolve it on our end.\n\n\nWhat we will end up doing is ignore the changes and accept the current version. This issue is likely due to the weekly updating of the data resulting in new sidebar links. We will then mark these issues as resolved\n\nWe will then mark the issues as resolved.\n\n\nOn return to the homework, we will be able to merge the branch once again. We will likely make our suggestions at this point for this branch.\n\n\nHowever, after pull request has been merged, you will see your branch is way ahead (due to everyone elses homework commits). This is the area we will need to address via the new branch method.\n\n\nFor now, proceed to discard the changes (you don’t need the other participants homeworks cluttering your folder)\n\n\nYou will then appear as caught up with the main branch.\n\n\nOn return to Positron, attempt to pull\n\n\nHowever, since your homework commit is still present, you will receive a pop-up asking you to see the GitLog. If you scroll up the problem log, it will give you several options.\n\n\nYou will need to enter the following code into your terminal tab:\n\ngit config pull.rebase TRUE\n\n\n\nThis will result in a branched appearance, and the button asking you to sync the changes.\n\n\nUpon doing so you will have a restored status vs. the main cytometry in R project folder.\n\n\n\nTake Away\nWe have encountered a first growing pain for the course, in that the pull-request method we have been using still causes merge conflicts. We will be going to a homework branch to homework branch pull-request approach going forward, I will send out additional instructions on how to do so shortly.\nThanks for your patience!\nDavid\n\n\nAdditional Resources" }, { - "objectID": "course/00_GitHub/slides.html#creating-an-account", - "href": "course/00_GitHub/slides.html#creating-an-account", - "title": "Using GitHub", - "section": "Creating an Account", - "text": "Creating an Account\n\n\n\n\n\n\n\n\n.\n\n\nWe will first navigate to the GitHub homepage. If you haven’t previously created an account, click on the button to sign up for an account." + "objectID": "course/00_BonusContent/index.html", + "href": "course/00_BonusContent/index.html", + "title": "Bonus Content", + "section": "", + "text": "This is a miscellaneous page to host walk-throughs of topics that come up via the Discussion Page. Rather than re-explain how to in the comments, I want to have a place to post short-walkthroughs to solve these issues, while avoiding incorporating it into the existing walk-throughs at this point in time. I hope you find it useful, and pardon the organized chaos of miscellaneous topics." }, { - "objectID": "course/00_GitHub/slides.html#github-profile", - "href": "course/00_GitHub/slides.html#github-profile", - "title": "Using GitHub", - "section": "GitHub Profile", - "text": "GitHub Profile\n\n\n\n\n\n\n\n\n.\n\n\nUpon creating a brand new account, your GitHub homepage will initially look rather empty, and can be intimidating to navigate for the first time.\nFor now, on the upper right, go ahead and click on the default profile picture icon…" + "objectID": "course/00_BonusContent/index.html#windows-arm", + "href": "course/00_BonusContent/index.html#windows-arm", + "title": "Bonus Content", + "section": "Windows Arm", + "text": "Windows Arm\n\nPositron\nOn the main Positron installation page, only the installers for Windows Computers with x86 chips are currently shown. There is a beta (experimental) version of Positron for Windows ARM (ex. Snapdragons), but it needs to be installed from Positron’s GitHub releases page.\n\nPlease note, you should download the most recent version that is available to you, as they continue to update it and fix bugs. As of February 04, 2026, you would also need to install Quarto separately.\nTo install Quarto, first navigate to their website. Quarto for Windows ARM was implemented in 2023, so the regular installer should work.\n\nAlso, you would need a Python arm64 installation installed if you decide you want to venture into using Python at any point." }, { - "objectID": "course/00_GitHub/slides.html#github-readme", - "href": "course/00_GitHub/slides.html#github-readme", - "title": "Using GitHub", - "section": "GitHub ReadMe", - "text": "GitHub ReadMe\n\n\n\n\n\n\n\n\n.\n\n\nWith this done, we modify your GitHub profile by adding one customized element, a ReadMe page. This will be used for a couple projects during the course, and can be personalized further in the future.\nTo create a ReadMe page for your profile, we will navigate to the upper right of the screen and click on the + sign." + "objectID": "course/00_BonusContent/index.html#visual-mode", + "href": "course/00_BonusContent/index.html#visual-mode", + "title": "Bonus Content", + "section": "Visual Mode", + "text": "Visual Mode\nWithin Positron, there exist a toggle button to switch between source and visual mode on Quarto documents. But what do you do when you can’t find it?\n\nTuns out…. Visual Mode is currently broken, so the developers removed it about two weeks ago.\nThe current way to switch to it is via right-click, then select edit visual mode.\n\nVice versa, once there, you can revert by right-clicking and selecting Edit Source Mode\n\nThe process of figuring what is going on highlights how to use a GitHub Discussion Page. This is Positrons when I searched for visual button. I then found that a similar question was asked 3 days ago that led me to the linked thread above." }, { - "objectID": "course/00_GitHub/slides.html#github-repository", - "href": "course/00_GitHub/slides.html#github-repository", - "title": "Using GitHub", - "section": "GitHub Repository", - "text": "GitHub Repository\n\n\n\n\n\n\n\n\n.\n\n\nHaving set up your GitHub profile, it now is time to make sure you have access to our course materials. We will have you navigate to our course’s GitHub profile\nOn the profile page, you will be able to see our version of the README, our repositories, and the Contributions graph and Contribution activity sections.\nPlease click on the CytometryInR to navigate to its repository (folder)" + "objectID": "course/00_BonusContent/index.html#not-detecting-git", + "href": "course/00_BonusContent/index.html#not-detecting-git", + "title": "Bonus Content", + "section": "Not Detecting Git", + "text": "Not Detecting Git\nIf you leave the “Initialize Git Repository” option unclicked when setting up a New Folder from Template, Git will not be active within your project folder.\n\nAs a result, when you try to use the usethis packages use_github(private=true) function, you will get an error that resembles the one below\n\nTo initiate a Git repository after the fact, you will need to go to the Version Control tab in the action bar, and select the option.\n\nThen, you will need to stage the files you want to work with, and commit them.\n\nuse_github(private=TRUE) should now be functional at that point. However, you can also choose to continue via Positron’s interface instead by selecting Publish.\n\nIt will then ask you whether you want to save it as either a Public or a Private repository.\n\nAnd if all goes well, you will see the “Successs” pop-up in the lower-right" }, { - "objectID": "course/00_GitHub/slides.html#forking-cytometryinr", - "href": "course/00_GitHub/slides.html#forking-cytometryinr", - "title": "Using GitHub", - "section": "Forking CytometryInR", - "text": "Forking CytometryInR\n\n\n\n\n\n\n\n\n.\n\n\nBefore we go further, we will need you to make your own copy of the course repository (ie. fork it). This will allow you to quickly retrieve all the new materials and code corrections by simply rereshing (ie. syncing) your forked version with our upstream parent branch once a week." + "objectID": "course/00_Floreada/index.html", + "href": "course/00_Floreada/index.html", + "title": "Using Floreada", + "section": "", + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", + "crumbs": [ + "About", + "Getting Started", + "00 - Floreada" + ] }, { - "objectID": "course/00_Homeworks/slides.html#discussions-forum", - "href": "course/00_Homeworks/slides.html#discussions-forum", - "title": "Getting Help", + "objectID": "course/00_Floreada/index.html#floreada", + "href": "course/00_Floreada/index.html#floreada", + "title": "Using Floreada", + "section": "Floreada", + "text": "Floreada\n\nLoading Dataset\nFirst, open your web browser and navigate to the website\nClick on Start to proceed to the next page.\n\n\n\n\n\n\nOnce that is done, select the File tab on the upper navigation bar. Then click on Open File(s).\n\n\n\n\n\n\n\nFrom there, select your .fcs files of interest, and click Open.\n\n\n\nThe .fcs files will now load in, and you should see a view similar to the one below. On the left side-bar, you have your gating options (Rectangle, Polygon, Range, Elipse, Quad, etc). Next to these on the right you have the FCS files that are loaded into the workspace. Then on the right, you have the visual display for your selected specimen.\n\n\n\n\n\nSwitching Axis Markers\nIf you left click on the axis name (SSC-H or FSC-H in this case), you will be able to select other markers by which to gate your specimen. For the provided example, we were using a raw spectral flow cytometry .fcs file, so the names of the detectors are present.\n\n\n\nFor now, I plan to start off by gating for singlets. I switch the y-axis to FSC-H, and then proceed to switch the x-axis to FSC-A.\n\n\n\n\n\nCreating Gates\nWith this done, I can now select the Poly gate tab on the upper left.\n\n\n\nThen manually click on the locations on the plot to add the individual gate nodes.\n\n\n\nTo complete the gate, I click back to the original node point. At this point, the popup will allow you to name the gate.\n\n\n\nTo adjust the polygon gate, you can click on a node and drag it to expand or contract in a particular direction\n\n\n\nTo move the entire gate, first click on a node to select the gate, then click in the center of the gate to adjust its location.\n\n\n\n\n\nAdditional Gates\nUnfortunately for those with the force-of-habit from using other softwares, double-clicking within the gate doesn’t do anything. To continue gating on the selected cells, you will need to click on the newly created gate name on the left. This will result in visualizing the isolated cells.\n\n\n\nOnce this is done, you can repeat the previous steps to change the axis markers and create a second gate. For this example, we went with a “Cells” gate to exclude debris from this particular sample.\n\n\n\nHaving created the “Cells” gate, we will be switching gating based on FSC and SSC to using the detector parameters.\nThe samples in this example were acquired to derive the cell counts and concentration of various cell populations within cryopreserved cord and peripheral blood mononuclear cells (CBMC and PBMC) specimens after thawing.\nThey were stained with CD19 BV421, CD45 PE, and CD14 APC on a 5-Laser Cytek Aurora, before unmixing, this would correspond respectively to V1, YG1/B4, R1/YG4 peaks respectively.\n\n\n\n\nScaling/Transformation\nWhen we switch the axis, we can see that the scaling/transformation is not ideal, as the staining and not-staining populations are scrunched up together in the center of the plot.\n\n\n\nTo change the scaling/transformation, we need to click directly on the axis.\n\n\n\nFrom there, when we click on the drop-down, we see the various transformation options. We will select Logicle, given we are working with spectral flow cytometry files.\n\n\n\nThis y-axis values are subsequently visualized with the logicle transformation applied, increasing our resolution between the positive and negative population.\n\n\n\nWe can then repeat this for the x-axis, adjusting the fine-tune options for the scaling as needed.\n\n\n\n\n\nNavigating Gating Hierarchy\nWith this done, let’s first draw a rectangle gate for the CD45+ (B4-A) cells.\n\n\n\nAnd then selecting that population by clicking on the gate name, let’s proceed and gate the CD19+ cells (V2-A).\n\n\n\nAs you can see, we now have the various gates present in the gating hierarchy for the respective .fcs file. To return to a previous gated population, we would click on the parent population above it.\n\n\n\nWe can subsequently add an additional gate at this gating level for the likely debris population (the threshold setting was suboptimal for this experimental run).\n\n\n\n\n\nCopying Gates\nThis was the process for gating for a single specimen. To copy gates over to the other specimens, we have two options. First, holding down your Ctrl (or equivalent) button, you can click on the individual gate names.\n\n\n\nFrom there, you can drag them down to the next specimen and apply them.\n\n\n\nAlternatively, you can drag down the highlighted gated to the Pipelines Tab, and apply to All Files. This will result in the gates being copied to all specimens in the experiment.\n\n\n\n\n\n\nAdjustments within Pipelines will carry over to all other respective unmodified specimens that share it’s gates.\n\n\n\nOnce this is done, I recommend cycling through the gates for each specimen, just to ensure that the gates were positioned correctly before saving the workspace.\n\n\n\n\n\nSaving Workspace\nWith everyone now “correctly” gated, we can proceed to save the workspace so that we can reopen it later from another browser.\nTo do this we open the File tab from the upper navigation bar, and select Save Workspace.\n\n\n\nFrom there we have a couple options, for now let’s select Floreada Workspace. Where it is saved at will depend on your individual browser settings, so watch for a popup.\n\n\n\nAlternatively (and crucially for the CytoML pipeline) we can also choose to save it as a FlowJo v10 .wsp file.\n\n\n\nIn both cases, you will end up with Workspace files that can be used later to access your created gates\n\n\n\n\n\nReopening Workspace\nTo reopen the Floreada workspace within the browser, reopen the website, and select the Open File(s) option.\n\n\n\nFrom there, select both the Floreada Workspace file as well as the .fcs files\n\n\n\nAt which point you will now be back to the point you last saved at.", + "crumbs": [ + "About", + "Getting Started", + "00 - Floreada" + ] + }, + { + "objectID": "course/00_Floreada/index.html#cytoml", + "href": "course/00_Floreada/index.html#cytoml", + "title": "Using Floreada", + "section": "CytoML", + "text": "CytoML\nDue to a unknown formatting bug, the Floreada produced FlowJo v10 .wsp is not directly accessible by CytoML at the time of this course. However, the issue is resolved as soon as the file is opened the first time within FlowJo v10, regardless of whether you have a log in or not. Strange? Yes, but we will take the workaround.\nSo, for anyone on Windows or MacOS, download FlowJo v10. Once installed, open the software, and close the login popups. Once there, open the Floreada created FlowJo.wsp file. Since you haven’t logged in, it won’t show any events. But it will correct the formatting bug. Close the software, and return to R. Your Floreada sourced .WSP file should now be readable by CytoML.\nOdd? For sure. Fixable? Likely, I will set a reminder to work with the Floreada and CytoML devs to see if we can cut out the need for this workaround.", + "crumbs": [ + "About", + "Getting Started", + "00 - Floreada" + ] + }, + { + "objectID": "course/00_Git/index.html", + "href": "course/00_Git/index.html", + "title": "Version Control with Git", + "section": "", + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", + "crumbs": [ + "About", + "Getting Started", + "00 - Git" + ] + }, + { + "objectID": "course/00_Git/index.html#new-folder-from-template", + "href": "course/00_Git/index.html#new-folder-from-template", + "title": "Version Control with Git", + "section": "New Folder from Template", + "text": "New Folder from Template\nSince Positron can use multiple programming languages, when we select “New Folder from Template” we will be asked what kind of folder template we want to use. Since we are working in R, we will select the “R Project” option.\n\n\n\nWe will next be asked to name the new project folder and a storage location.\nOne thing I would like to remind everyone who is just starting to code is that it is best to avoid using special characters (ex. @ $ # ^ ! ; : ,) in any folder or file name. This is because when coding, these can be misinterpreted as commands.\nWhile spaces are generally okay, it is often to best stick to to stick to hyphens (-), underscores (_). We will explore naming conventions in more depth at a later time.\n\n\n\nAnother useful thing to know when getting started with version control, it is best to save your files within your local computer, avoid using OneDrive or other cloud storage options for the time reason. The reason behind is that permissions to write/save to the cloud locations can sometimes be quite finicky, and some autosave/indexing behaviors can cause issues. akes things easier to save or modify without running into permission issues. For most of our course examples, we will be saving our Project Folders under the Documents Folder.\nHaving named our new Project Folder, and designated a storage location, go ahead and check the Initialize Git Repository option. This will indicate to version control to monitor content and changes to files within this folder.\n\n\n\nThe next setup screen will verify which version of R you wish to use. Since we are just getting started, your most recent version of R (usually system) should work. We will also leave the “renv” (reproducible environment setup) option unchecked for the time being (we will revisit the concept later in the course).\n\n\n\nAnd if all goes well, we should see the “New Folder Created” popup.", + "crumbs": [ + "About", + "Getting Started", + "00 - Git" + ] + }, + { + "objectID": "course/00_Git/index.html#creating-subfolders", + "href": "course/00_Git/index.html#creating-subfolders", + "title": "Version Control with Git", + "section": "Creating SubFolders", + "text": "Creating SubFolders\nOnce your new project folder has opened, you should be seeing the main layout elements that we briefly covered in the Positron walk-through.\nFor this section, we will primarily be focused on what is happening within the primary side bar on the left, where changes to the individual files within the folder since the last save/commit will be reflected by colored text.\nFor my own projects, there are some elements of organization that I go ahead and add for each new folder. These include both a data and an images subfolders to help keep things a little more organized.\nTo create these folders, we would click on the respective add folder (+) button on the side bar. Files and Folders can be clicked and dragged within the primary side bar to move things to new folder locations.", + "crumbs": [ + "About", + "Getting Started", + "00 - Git" + ] + }, + { + "objectID": "course/00_Git/index.html#creating-files", + "href": "course/00_Git/index.html#creating-files", + "title": "Version Control with Git", + "section": "Creating Files", + "text": "Creating Files\nIn context of this course, we will primarily be working with two types of files when coding:\n\nR Scripts: These files end in .R. These contain only code (with occasional # comment line). These are often used for self-contained code that once we get them working we rarely need to modify.\nQuarto Markdowns: These files end in .qmd. They contain a .yaml header, followed by a mix of regular written text (often explanations or other documentation), and sections (ie. chunks) that contain code. These are used when we are still getting the code to work, when we need to modify inputs frequently, or simply when we need to document what and why we are doing something to make life easier for our future-self two months from now.\n\n\n\nIn this example, I will go ahead and select the new file icon\n\n\n\nThenn I will name the file, and designate it as a Quarto Markdown file by adding the .qmd at the end of the name to denote the file type.", + "crumbs": [ + "About", + "Getting Started", + "00 - Git" + ] + }, + { + "objectID": "course/00_Git/index.html#qmd-files", + "href": "course/00_Git/index.html#qmd-files", + "title": "Version Control with Git", + "section": "QMD Files", + "text": "QMD Files\nOnce this is done, we can now see we have a new .qmd file (“Example.qmd” in this case).\n\nYAML\nAs previously mentioned, the start of a Quarto Markdown file containg a YAML code chunk that is used to set formatting choices (we will explore this in-depth during the next section)\nWhat designates the location of the YAML block are three hyphens at the start, and three hyphens at the end. For this example, we will also provide a “title:” and “format:” field for the time being (see additional options here).\n\n\n\n\n\nText\nWith a basic YAML formatting block now in place, we can build out other elements of our Quarto Markdown document. Unless otherwise specified, everything else in the document is assumed to be text, so I will go ahead and provide an initial text description of what I am trying to do.\n\n\n\n\n\nCode-Chunks\nHaving provided some initial text for documentation, we can then add code-block chunks to start writing some code.\nThe easiest way to do do this is to click the respective option on the upper-right of the Editor screen. Since Positron can handle multiple programming languages, so the chunk is inserted, we will need to select the language we use to be used within the code chunk (R in this case).\n\n\n\nYou will notice, that the inserted code block starts off with three backticks (`) and then “{r}”. The end of the code block is denoted by an additional three backticks.\nWe can also add new code blocks by simply typing these elements into the location we want to place a code chunk (as long as we are careful to add 3 backticks also at the end).\n\n\n\n\n\n\n\n\nRunning Code\nNow that we have two code-chunks written, we can write lines of code within them. For this example, I will use two beginner friendly functions, print(“Hello”), which will print the contents contained between the ” ” to the console, and getwd() which will return the location of the folder you are working within (ie. the working directory).\nTo run/execute these lines of code, we have a couple options. We can click on the Run Cell option that appears on the upper-left side of the code chunk. Additionally, it has a companion option that will run all code chunks above it.\n\n\n\nWhen a code block is successfully run, you will see within the console (lower bottom of the screen) the line of code be run, with any returned outputs appear directly after.\n\n\n\nAn alternative to clicking the Run Cell button is to click on the line of code you are interested in running, then press (Ctrl + Enter)/(Command + Enter). This will execute the line of code that you have clicked on. This can be useful in scenarios where you want to run a specific line, and not the entire code-chunk.\n\n\n\nUsing this approach, you can see the location (ie. file path) of the current working directory was returned to the Console.", + "crumbs": [ + "About", + "Getting Started", + "00 - Git" + ] + }, + { + "objectID": "course/00_Git/index.html#local-version-control", + "href": "course/00_Git/index.html#local-version-control", + "title": "Version Control with Git", + "section": "Local Version Control", + "text": "Local Version Control\nHaving introduced the main elements of a Quarto Markdown file, let’s turn our attention to the tab within the editor showing our newly created .qmd file.\nWe can see there is a solid circle next to the file name, and it is appearing as green. The circle denotes unsaved changes, which we can correct by clicking on the Save Button to save the changes to our file.\n\n\n\n\nUntracked\nIf we turn our attention to the left primary sidebar, we can see that within our GitPractie folder there are three files, our Example.qmd, and the default README.md and .gitignore files. These all show up in green text with U’s to the right of the file names.\nThis denotes that the version control tracking software Git is currently considering them as “Untracked” files. While saving the document via the Save button means we will still have our changes when we reopen Positron, we won’t have any history of changes that we can use to revert back to the way all the files appeared at this exact point in time should something go wrong.\nWe will next go the address bar on the very far left, and select the Git tab.\n\n\n\nOn the Git tab, we can see that each of the three files are shown underneath a “Changes” drop-down. This contains the files that have undergone changes since the last commit. In our case, since we haven’t updated the save-state yet, this last commit would be the initial creation of the project folder.\n\n\n\nTo have version control track these individual files going forward, we can do so in two separate ways. We can add them individually by clicking the + symbol next to the individual names.\n\n\n\n\n\nStaged\nThis will result in the files being moved to the “Staged” dropdown. This denotes files being tracked with the intention of being recorded as the next save-state or waypoint (ie. a commit).\n\n\n\n\n\nCommit\nTo create a new commit (save-state or waypoint), once we have the files we want to track staged, we will write a commit message, and then press commit.\nA commit message is a brief description of the changes that have occurred to the files between this commit and the previous one. Make this short description informative enough that if you need to revert back in the future, you can quickly identify the commit you need to fall back to (more about this later).\n\n\n\nIf this your first time using version control, you will likely encounter the following pop-up asking that you provide a user.name and user.email. This is used to designate the author of the changes.If you get this popup, go ahead and select “Open Git Log”\n\n\n\n\n\nUserName and UserEmail\nThe Output tab at the bottom of the screen will open, showing the messages that led to the popup.\nThe important part to note is the commands that will be needed to provide your user name and email to the computer for authoring the commit. Typically, your email will be the same one you used for your GitHub account.\n\n\n\nFrom the displayed message, go ahead and copy\n“git config –global user.email”you@example.com””\nThen click on the adjacent terminal tab. You will paste the command in, but do not hit enter just yet.\nWindows users, please note, depending on your settings, if trying to paste from the keyboard into the terminal, you may need to press “Ctrl + Shift + V” instead of the usual “Ctrl + V”.\n\n\n\nWith the command now pasted (or typed), use your keyboard arrows to navigate to the email portion, and replace the generic email with your email address used for your GitHub account.\nMake sure that the quotation marks (“) around the email address remain present, as they help the computer identify where your email address starts and ends. Once satisfied that your email address is correct, press enter.\n\n\n\nNext up, repeat the process, this time copying over the command needed to set your user name to the terminal. Repeat the editing process to provide your name between the “” marks. Then press enter.\n\n\n\n\n\n\n\n\nFirst Commit\nNow that your user.name and email address have been provided, Git should be able to provide an author to the commit message. Reattempt to press commit button.\nIf this is successful, you will see your initial commit appear on the bottom half of the left primary side bar, under the Graph dropdown. Congrats! Your files are now being tracked by version control.\n\n\n\nIf you hover with your mouse arrow just over the commit, you can see the longer commit message and additional details appear.\nIf you click on the commit tab, a new display will open in the editor, displaying the changes that occured in that commit compared to the previous one. In this case, since we added everything since the previous commit, nothing appears on the left side, while the entire documents contents appear highlighted in green on the right.\nGreen highlighting is used to show additions, while red highlighting is used to show deletions.\n\n\n\nHaving completed this initial commit, for this example, let’s imitate a typical workflow and make some additional changes to the file before we make a second commit. Within text portions of the .qmd file, use of # denotes a section header in markdown, so let’s add a header for Introduction and click save.\n\n\n\n\n\nModified\nWithin the left primary sidebar, we can see that the Git tracking has updated. Examples.qmd is visible once again. However, becuase it is now a tracked file, instead of showing up with the “U/Untracked” green highlight, it now appears as a brownish-red with a “M/Modified”.\nLet’s make an additional change to the .qmd file by adding another section (# Setup) and a code block with a commented out line (denoted by the # at the line start), before pressing Save.\n\n\n\nIf we were now to click on the Example.qmd file in the left primary sidebar, it will open the same kind of tracking display we saw previously. This time, we can see changes since our last commit. These appear as the green highlights along the scroll-bar, corresponding to the # Introduction and # Setup headers that we have added in since the last commit.\n\n\n\nFor a larger document, we can scroll down to see the various highlighted regions.\n\n\n\nWe could now repeat the steps showed above, staging the file, writing a commit message, and commiting again by clicking on the designated buttons.\nAn important question is how often should we commit, vs. just hit save? Well… it depends :D Let’s think about this in context of a video game. If you made commits at regular intervals throughout the day (or more frequently when doing something particularly risky), you are more likely to be close enough to a particular commit (waypoint/save-state) that you can quickly revert back to without loosing any progress. Alternatively, if your last commit was last week, you will not have any intermediate versions to fall back to.\n\n\nCommit via Terminal\nHaving demonstrated how to commit changes to Git via the left primary side-bar, for this second commit, let’s do it the alternate way via the terminal (tab on the panel at the bottom of your screen).\n\n\n\nAfter clicking on the terminal tab, click on blinking command line.\nThe command to stage a file is “git add”, followed by the name of the file you want to stage.\nIn this case, you would enter “git add Example.qmd” and press Enter. \n\n\nYou will see after pressing enter a new blank terminal line appear. If you glance at the left-sidebar, you can see that Example.qmd now appears under the Staged Changes dropdown.\n\n\n\nNext up, let’s write the git commit via the terminal. In this case, the command would be “git commit -m” (-m denoting message). The commit text is then surrounded by “” marks.\nFor example: “git commit -m”Added section headers to my QMD file””\nPress enter to save the commit.\n\n\n\nAnd you should see your second commit now appear in the left primary sidebar underneath the graphs dropdown.", + "crumbs": [ + "About", + "Getting Started", + "00 - Git" + ] + }, + { + "objectID": "course/00_Git/index.html#remote-version-control", + "href": "course/00_Git/index.html#remote-version-control", + "title": "Version Control with Git", + "section": "Remote Version Control", + "text": "Remote Version Control\n\nCopying Project Folder to GitHub\nWhile having local version control in place is helpful when you need to revert back after encountering issues, where Git shines is the ability to pass your changes to your online GitHub repository.\nNot only does this allow you to switch between computers, but should something disastrous happen to your main computer, you still have all your hard work backed up and readily assessible.\nFor this subsection, first, double check that Positron is still connected to your GitHub account by checking the user tab on the bottom-left. If not, repeat the connection setup.\n\n\n\nSince our project was created using the “New Folder from Template” option, it currently only exist locally. What we want to do next is to copy it to our GitHub account, creating a new repository in the process.\nTo do this, we will first need to install the usethis R package. Within your console, you would run the following line of code:\n\ninstall.packages(\"usethis\")\n\nDepending on what R packages you already have installed on your computer, you may get a prompt asking if you want to update/install additional dependencies. Go ahead and type the number corresponding to Update All, and press enter.\nThe package and all it’s dependencies should then install. If an error message appears, read through it, and follow provided instructions. Go to Discussions if need help.\n\n\nOnce the usethis package is installed, we need to activate it within R by calling it with the library command. This makes all the tools (ie. functions) within an R package available for use within Positron.\nIn your console, you would type:\n\nlibrary(usethis)\n\n\n\n\nWith library called, you now have access to the functions (tools) within the usethis R package. One of these is the use_github() function.\nIn Positron, if you hover over a function, it will pull up the associated help file which will provide you information about the arguments the function expects to receive, and what they do.\nFor use_github(), the main thing to remember for now is since this is a personal project being used for testing, we don’t necessarily want to share it with the entire world, so we should set the “private” argument equal to TRUE when creating a new repository.\n\n\n\nTaking this information that we have now gathered, we can now within our Quarto Markdown create a code chunk, write out the line of code calling the function, and providing the Private=TRUE argument within the ().\nWithin a code chunk, adding a # in front of a line of code, will comment it out, resulting in that line of code not being run. Since we have already installed the usethis package, and we don’t want to reinstall it every single time, let’s go ahead and comment out that line. Go ahead and press Enter.\n\n\n\nWe will see a message pop-up in the console. In this case, we had not saved before pressing enter, so there are uncommitted changes within the folder. The pop-up is asking whether you want to save these as well before sending the Folder to GitHub.\nIn this case I will chose to ignore the uncommitted changes by entering 3 (for Definitely) in the console and hitting enter on my keyboard.\n\n\n\nThe usethis R package will then execute the series of git commands that are needed to set up a GitHub repository (ie. the messages being displayed in the console window), and when finished will open a pop-up asking whether you want to see your new repository in your default Web Browser. I will go ahead and select yes in this case.\n\n\n\nAfter the browser opens, you can see that the elements I had staged and committed within Positron are now present within the GitHub repository. Since I had only staged Example.qmd, it is the only file that was backed up. We can also see the commit history online by clicking on the commit clock.\n\n\n\nAs we would expect, we only see our two commit messages. One important thing to note is the commit hash numbers, that denote a particular commit. If we decided to revert/fall back to a prior commit in the future, this would be the number we would need to provide to Git to return to that previous commit/save-state\n\n\n\nSimilarly, on GitHub, we have an option to Browse a Repository at a particular point in time. This will be quite useful later in the future when troubleshooting what major changes occurred between versions of an R package.\n\n\n\n\n\nCode Chunk Arguments\nHaving successfully connected our local Project Folder to a remote GitHub repository, let’s return to Positron.\nBefore continuing, if we left the code chunk that created the GitHub repository as is, every time we ran all code chunks in the document, it would try to recreate the GitHub repository. We don’t want this to happen, as the setup was a one-time operation.\nWhile we could add # in front of every line of code (or delete the code chunk entirely) it is often useful to have these set-up code chunks around to remind us what arguments we need to provide next time we need to a similar setup and are mind blanking on what to do.\nFortunately, Quarto allows us to set conditions on whether a chunk is run (ie. evaluated). We will discuss the conditiona arguments in more depth in the next section, but for now, we can modify the code chunk as follows.\nOn the next line after the {r}, we will add a hashtag (#), then a pipe (|), followed by a space. This is the setup for a code-chunk specific argument. We will then add “eval: FALSE”, which signals that the particular code-chunk should not be evaluated (ie, should not be run).\n\n\n\n\n\nREADME\nNow that we have connected our local Project Folder to GitHub, and have gotten a basic introduction to the “git add”, “git commit” arguments, let’s turn our focus to the other files currently listed as untracked by Git within our folder, the README.md and the .gitignore files.\nWhen setting up our GitHub account, we encounted an example of a README.md file. This file often provides a brief description of the project, and an outline of what the other files in the folder are for. As you may have gathered, even software developers are forgetful/under-caffenaited, and having notes to catch back up to speed is important.\n\n\n\n\n\n.gitignore\nWe additionally have a .gitignore file. Within a project, there are often some files that we will never want version control to track. These could be files that are too large for GitHub (ex. really large .fcs files), or files containing sensitive information (passwords, history, credentials, etc.).\nWhen the names of these file (or the file type shothand) are added to the .gitignore file, they are ignored by version control, and no longer appear on the primary left side bar.\n\n\n\nLet’s proceed and stage both the README.md and .gitignore file, so that changes to these files will be tracked. We can of course select both from the primary left side bar and write a short commit message.\n\n\n\n\n\n\nOr alternatively, if we want to stage all uncommitted files present in a single step, we could in the terminal use the “git add .”\nWe can then write our git commit using “git commit -m”.\nBoth approaches work, and you may switch between them based on preferrence.\n\n\n\nYou will notice after having committed, that if you look at the Graph dropdown on the bottom half of the primary left side-bar that something has changed.\nThere are now separate icons denoted as main and origin/main. These correspond to the last commit present locally (main), and the last commit on remote (ie. GitHub, origin/main).\nLocal is ahead since you just made the commit with the changes inactivating the code-chunk, and you have not passed these changes up to GitHub yet.\n\n\n\n\n\nPull\nBefore sending (ie. pushing up) our updated commit to GitHub, especially if you are working on a project from multiple computers (or as part of a team) to bring in (ie. pull down) any changes that might be on GitHub that are not present locally.\nThis ensures that everything is up to date, and you don’t end up with mismatched commits that are incompatible with each other and trigger an error message.\nTo pull in changes from GitHub, at the top of the primary left side-bar, you can select the … button to open a drop-down menu of Git options. You would then select “Pull”.\nAlternatively, you could do the same thing via the terminal by running the “git pull” command.\n\n\n\n\n\nPush\nIn our case, there was no new material present on our GitHub repository that were not already present locally, so all that is returned is the “Already up to date” message.\nWe are now good to proceed to push (ie. send) the updated commit up to our GitHub repository.\nWe can do this by either pressing the Sync changes button, or via the terminal entering the “git push” command.\n\n\n\nAnd now, if you glance down at left side-bar’s graph section, you will see that both the main and origin/main icons are now present for the most recent commit.\n\n\n\nIf we switch to our Web browser, we can see that this is also now the case for our GitHub repository that now also has the most recent changes.\n\n\n\n\n\nReverting to Prior Commit\nFor most daily-workflows, you will only need the git commands that we have introduced above (git add, commit, pull, push). The next two areas (reverting to a prior commit, and branches) are more specialized, and will be covered in greater depth later in the course. We are briefly covering them here. If you are at the point where your last remaining neuron has disconnected, and you feel you need to take a break from version control, feel free to skip to the next section and we will revisit these topics later in the course.\n\n–\nIn most cases, if your code stops working, you can identify the issue and fix it in the existing version, never needing to resort to reverting to a previous commit (save-state). The times you would need to revert would be if you deleted important files, or the new files are hopeless mess that is not worth trying to sort through. In those cases, reverting back might be better approach.\nTo imitate a falling back scenario, lets create and additional file, stage and commit it to end up a commit ahead of where we are currently at within the Project Folder.\n\n\n\nNow being one (or several) commits ahead, if we wanted to revert back, we would first need to identify the commit we want to revert back to and copy the commit hash number.\n\n\n\nThen, opening the terminal, we can enter “git reset” and paste the hash afterwards. We can then press enter.\n\n\n\nYou will notice our additional commit has been removed, although the newer files we were working on subsequent last commit are still present.\n\n\n\nIf however, we had wanted to return to the exact same state as the previous commit (removing all subsequent created files), we could do so by adding in the –hard argument. Before starting, save any newer files you want to keep in a completely different folder, because they will be permanently removed.\nThen, enter “git reset –hard thecommithashnumber” into the terminal, which would result in a “hard” return to the previous commits save-state. You may need to close and reopen Positron to see the changes reflected.\n\n\nBranches\nBranches are an useful Git feature that we will start using extensively later in the course. Branching allows you to create a parallel/carbon-copy of your existing repository, which you can then edit without affecting the main branch. This is particularly useful for projects that may get messy or drawn out. By isolating these edits to a parallel branch, if they don’t work, your main branch remains safe. Alternatively, if you like the changes that occurred in the branch, you can pull these changes from the branch back to main, bringing the timelines back together.\n\n\nWithin the terminal, entering “git branch” will show the existing branches. In this case, only main is present since we haven’t yet created a new branch.\n\n\n\nWe can create a new branch in the terminal by entering “git branch” followed by the name of our desired branch. In this case, we are creating a branch called Week1\n\n\n\nNow, when we check “git branch” again in the terminal, which returns the two branches, Week1 and main. The * is located next to main, indicating that we are currently within the main branch.\n\n\n\nBesides the terminal, we can also create a new branch via Positron. To do so, we first click on the Git tab in the Actions Bar.\nOnce the left-side bar displays the version control display, we can click on the … button (to the right of changes)to gain access to the Git options drop-down.\nFrom here, we click on Branch, and then select Create Branch.\n\n\n\nUsing Git branch, we saw that we were still within the main branch. In the terminal, we can switch over to the Week1 branch by using the “git checkout” command, followed by the branch we wish to switch to.\n\n\n\nThis results in us switching over to the Week1 branch.\n\n\n\nHaving switched (ie. checkout) to the Week 1 branch, let’s create the file BranchTest.qmd, which will exist within this branch, but not yet in the main branch.\n\n\n\nHaving created the file, let’s stage and then commit it. This will put the Week1 branch ahead of the main branch by a single commit.\n\n\n\nWith our changes staged and committed, if we look at the left side-bar’s graph section, our Week1 branch is now ahead of the origin/main branch by one commit.\n\n\n\nIf we were to check on GitHub, we can see that no new files are present on the main branch, but can see the notification listing recent changes to Week1 branch.\n\n\n\nUsing the drop-down, we can switch from displaying the main branch to the Week1 branch, where we can see the new file.\n\n\n\nIf we click the green compare and pull request button, we end up on this screen. This compares how the two branches are different from each other.\n\n\n\nWe will delve into branches again at a later point. For now, remember that by creating and prunning parallel branches, you can develop knowing that even if something goes wrong, your main branch remains safe.", + "crumbs": [ + "About", + "Getting Started", + "00 - Git" + ] + }, + { + "objectID": "course/00_GitHub/index.html", + "href": "course/00_GitHub/index.html", + "title": "Using GitHub", + "section": "", + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", + "crumbs": [ + "About", + "Getting Started", + "00 - GitHub" + ] + }, + { + "objectID": "course/00_GitHub/index.html#creating-an-account", + "href": "course/00_GitHub/index.html#creating-an-account", + "title": "Using GitHub", + "section": "Creating an Account", + "text": "Creating an Account\nWe will first navigate to the GitHub homepage. If you haven’t previously created an account, click on the button to sign up for an account.\n\n\n\nOn the sign-up page, you will fill in various details needed to create an account. Please remember that GitHub usernames are visible to others. Additionally, if you end up sharing code with others as part of a manuscript, or use GitHub to create a personal portfolio website in the future, your username will appear as part of the URL.\nFor example, in my case, my user name is DavidRach, so my GitHub profile ends up as: https://github.com/DavidRach. For our course, the core’s GitHub user name is UMGCCCFCSR, so the github profile ends up as https://github.com/UMGCCCFCSR, while the course website ends up as https://umgcccfcsr.github.io/CytometryInR/\n\n\n\nOnce you have entered your new account information, you will need your account creation by entering the code sent to the email address that you provided.\n\n\n\nOnce account creation has been confirmed, please proceed to login to GitHub for the first time.", + "crumbs": [ + "About", + "Getting Started", + "00 - GitHub" + ] + }, + { + "objectID": "course/00_GitHub/index.html#github-profile", + "href": "course/00_GitHub/index.html#github-profile", + "title": "Using GitHub", + "section": "GitHub Profile", + "text": "GitHub Profile\nUpon creating a brand new account, your GitHub homepage will initially look rather empty, and can be intimidating to navigate for the first time.\nFor now, on the upper right, go ahead and click on the default profile picture icon…\n\n\n\nAnd then select Profile…\n\n\n\nYou are now on your public GitHub profile page. For a newly created account, it will look something like this:\n\n\n\nFor a more established account, this page will look a little different, and can be customized to highlight various projects that you are working on.\nFor this course, we will have you set up a basic GitHub profile page for now, although you are free to customize and personalize it as much as you may want to in the future!\nTo start, first select the edit profile button on the left below the default profile icon.\n\n\n\nYou can then proceed to fill in any details that you feel are relevant and are comfortable sharing.\n\n\n\nWith the quick access details filled in, it is now time to navigate to the Settings tab. You will return to the previous menu dropdown on the upper right, and instead of selecting Profile, click on the Settings option.\n\n\n\nYou should now end up within your Public Profile Settings page.\nFeel free to edit the default profile picture, and any other fields that you feel are relevant. Once done, continue to scroll down the page past ORCID ID.\n\n\n\nWhen you reach Contributions and Activity, go ahead and select the option to include private repositories in the activity summary graphic. Then scroll down and click save. You will now be returned to your GitHub profile page.\n\n\n\nAt the top of the profile, you will see a “Your contributions” calendar graph. For a new account, it will look like this:\n\n\n\nIf you are just starting out, this chart will be mostly empty, but will fill in as you work on projects, see here as an example.\nEvery time you save your code (ie. make a commit), the activity will be reflected in this chart. By clicking the option in settings, code made within a private repository will remain private, but will count toward your contribution chart. As you progress through the course, this will provide a nice visual reminder of the progress you have made, and the obstacles that you have overcome.", + "crumbs": [ + "About", + "Getting Started", + "00 - GitHub" + ] + }, + { + "objectID": "course/00_GitHub/index.html#github-readme", + "href": "course/00_GitHub/index.html#github-readme", + "title": "Using GitHub", + "section": "GitHub ReadMe", + "text": "GitHub ReadMe\nWith this done, we modify your GitHub profile by adding one customized element, a ReadMe page. This will be used for a couple projects during the course, and can be personalized further in the future.\nTo create a ReadMe page for your profile, we will navigate to the upper right of the screen and click on the + sign.\n\n\n\nWe will then select the Create New Repository option.\n\n\n\nYou will next create a repository (folder), naming it exactly the same as your username. This will be recognized by GitHub as being a special type of repository corresponding to the ReadMe section of your profile.\nFor options, leave the visibility as Public, and Add README set to On. And proceed to Create Repository.\n\n\n\nHaving created the repository (folder), you will see it has been populated by a few default files. For now, you will be editing the README.md file. On a new repository, the easiest way to access it is by clicking the green option on the right side of your screen.\n\n\n\nWith the README.md file now opened, you will be able to see generic filler text that is suggested by GitHub.\nFor this course, I will ask you to add a couple elements for now. You are free to return and further personalize it later if you wish to do so.\n\n\n\nThe type of file that we are working with is a Markdown file, which can allow for a bunch of customizations which we will cover throughout the course.\nFor now, please add and customize the following questions:\nCytometry In R\nLocation: Baltimore, Maryland, USA\nMy Favorite Fluorophore/Metal-Isotope: Spark Blue 550\nPrevious Coding Experience: Repeatedly Calling IT\nWhat I Hope to Get From This Course: A faster way to match FlowSOM clusters to their likely cell type.\n\n\n\nNext, to save you will select the green “Commit changes” button. We will cover the meaning of “Commit” more in-depth during the Git section.\nFor now, write a short summary of the change you made to the file in the “Commit message”, and any additional details within the “Extended description” field. When ready, click the green “Commit changes” button.\n\n\n\nYou will now be able to see the updated README.md file, as you can see in our example below. To make additional edits, you would select the pencil icon on the right-center side of the screen.\n\n\n\nNext, navigate back to your profile page (by clicking on either your username or the Overview option on the tabs).\nYou will see that the README file contents are now displayed on the upper portion of your GitHub profile. Feel free to circle back and customize this further to your liking.\nIn this last example, we created your first repository (folder). Since this is public, it is now shown below the README section of the profile under your repositories. You can also see that your commits made in the process of making the changes are now shown both in the Contributions graph, and under the Contributor Activity summary at the bottom of the page.", + "crumbs": [ + "About", + "Getting Started", + "00 - GitHub" + ] + }, + { + "objectID": "course/00_GitHub/index.html#github-repository", + "href": "course/00_GitHub/index.html#github-repository", + "title": "Using GitHub", + "section": "GitHub Repository", + "text": "GitHub Repository\nHaving set up your GitHub profile, it now is time to make sure you have access to our course materials. We will have you navigate to our course’s GitHub profile\nOn the profile page, you will be able to see our version of the README, our repositories, and the Contributions graph and Contribution activity sections.\nPlease click on the CytometryInR to navigate to its repository (folder)\n\n\n\nOn this page, you will see several elements that you will be circling back to throughout the course.\nFor our course, we will be extentsively ussing the Discussions page as a community forum. If you have any questions, are looking for feedback, or want to show off something that you worked on, this is the place for it. This will also help make sure\n\n\n\nThe Issues tab is where you will need to go to open an Issue if you encounter a bug (or major documentation typo), so that I can cicle back and correct them when I have the chance.\n\n\n\nTo submit the optional take-home problems, you would turn in these problems by going to the Pull Request tab, and initiating a pull request between your forked version of the project and our “homework” branch (more details on this later).\n\n\n\nOptionally, you can “Star” a repository. This is basically the GitHub equivalent of liking a project. In our case, we will often star a repository since it will be saved under the Stars tab of our profile, which makes finding it again significantly easier a few weeks later after forgetting the repository name.\n\n\n\nTo see projects that you have starred, you can select the Stars option from the same dropdown you used to get to Settings.\n\n\n\nOr from your GitHub profile, you can see these under Stars tab.", + "crumbs": [ + "About", + "Getting Started", + "00 - GitHub" + ] + }, + { + "objectID": "course/00_GitHub/index.html#forking-cytometryinr", + "href": "course/00_GitHub/index.html#forking-cytometryinr", + "title": "Using GitHub", + "section": "Forking CytometryInR", + "text": "Forking CytometryInR\nBefore we go further, we will need you to make your own copy of the course repository (ie. fork it). This will allow you to quickly retrieve all the new materials and code corrections by simply rereshing (ie. syncing) your forked version with our upstream parent branch once a week.\n\n\nTo fork the course repository, you will select the “Fork repository” option on the upper-center portion of your screen.\n\n\n\nBy “Fork-ing” a repository, you are basically copying the contents from that repository to a newly created repository on your own GitHub. Forked projects are still linked to the original (parent) fork, and can retrieve any updates via syncing, as well as return changes via a pull request.\nFor this course, when you create the fork, keep the existing repository name (“CytometryInR”). Importantly, select the copy main branch option. This will ensure you only get the code and data needed for the course copied over, and don’t end up with your entire hard-drive filled will website elements, or other people’s solutions to the take-home problems.\n\n\n\nOnce you have created the fork, you will see your copy of the forked repository under your own username. Seeing as you have just now forked the project, you will see the notification that you are up to date with the existing version of the CytometryInR course repository.\nAs we go through the course, and new material is released each week on Sunday at 2200 EST (Monday 0300 GMT+0), you will see this changed to behind the main branch by a number of commits, and have the option to sync in the changes to your fork to gain access to that week’s material.\n\n\n\nIf you remember, previously under your GitHub profile, the Repositories tab only contained the repository corresponding to your ReadMe section.\n\n\n\nYou should however now be able to see your fork of the CytometryInR repository. As you add project specific repositories throughout the course, they will also appear here.", + "crumbs": [ + "About", + "Getting Started", + "00 - GitHub" + ] + }, + { + "objectID": "course/00_Homeworks/index.html", + "href": "course/00_Homeworks/index.html", + "title": "Getting Help", + "section": "", + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", + "crumbs": [ + "About", + "Getting Started", + "00 - Getting Help" + ] + }, + { + "objectID": "course/00_Homeworks/index.html#discussions-forum", + "href": "course/00_Homeworks/index.html#discussions-forum", + "title": "Getting Help", "section": "Discussions Forum", - "text": "Discussions Forum\n\n\n\n\n\n\n\n\n.\n\n\nOn the course’s GitHub repository, we have opened up a Discussions page that we plan to use as a community forum. We hope that it will serve multiple functions, from providing a better sense of community for the online participants, to facilitating asking and receiving help on something that is not clear, provide feedback about something that it not working out, as well as a place to celebrate and show off your coding wins." + "text": "Discussions Forum\nOn the course’s GitHub repository, we have opened up a Discussions page that we plan to use as a community forum. We hope that it will serve multiple functions, from providing a better sense of community for the online participants, to facilitating asking and receiving help on something that is not clear, provide feedback about something that it not working out, as well as a place to celebrate and show off your coding wins.\n\nTo keep the Discussions forum semi-organized, we have set up several categories, please select the appropiate category when opening a new discussion!\n\n\n\nCode of Conduct\n\nWe ask that all course participants read and adhere to the spirit of our Code of Conduct. We are all human, at different points in our learning journeys, so what may be obvious to you at your point of your learning journey may have necessarily be obvious to someone just getting started. This course is our giving back to those in the community, but is on a voluntary basis in addition to our regular workload. While we try to reply quickly, sometimes our cell sorters fully melt down sending everything into chaos. We will reply when we can.\n\n\n\n\nAnnouncements\n\nWhen we send out an email to all participants, we will also repost it as an announcement. This ensures that even if you are not on our mailing list, you will still be able to have access to important information and course updates.\n\n\n\n\n\n\n\nGeneral\n\nThis section category can be used for any discussions that you think are worth having, that don’t fall under any of the other category. Good examples are continuing a discussion that was held during one of the livestreams; wanting to discuss and dive further into a given week’s topic; or bringing in additional resources that you found useful to understandingn something that didn’t click initially. This space is for the community to shape as they see best.\n\n\n\n\n\n\n\nIdeas\n\nHave an idea for a new topic or a way to improve the course? We would love to hear them. Provide as many details, and ideally, an example, and if it is doable, we will try to implement them.\n\n\n\n\n\n\n\nIntroductions\n\nOnline courses can be odd in terms of replicating in-person dynamics. Fortunately, we have gathered the largest cohort of “cytometrist with no-to-little flow experience trying to learn R at the same time” that the world has ever seen, so best to take advantage of this while we can. Treat this section as if we had just met at a conference, tell us about yourself, what brings you here, and what you want to hopefully be able to do after the course ends.", + "crumbs": [ + "About", + "Getting Started", + "00 - Getting Help" + ] }, { - "objectID": "course/00_Homeworks/slides.html#polls", - "href": "course/00_Homeworks/slides.html#polls", + "objectID": "course/00_Homeworks/index.html#polls", + "href": "course/00_Homeworks/index.html#polls", "title": "Getting Help", "section": "Polls", - "text": "Polls\n\n\n\n\n\n\n\n\n\n.\n\n\nOccasionally, we will need to gather community feedback on what is working and what is not working. We will sporadically post Polls for this purpose." + "text": "Polls\n\nOccasionally, we will need to gather community feedback on what is working and what is not working. We will sporadically post Polls for this purpose.\n\n\n\n\n\n\nQ&A\n\nThe Questions and Answers (Q&A) section is where you go if something is not clear, not working, and you are trying to troubleshoot your way through it. First thing before posting, search! to see if someone has already asked the question. If you don’t find anything, go ahead and open a new discussion.\nSince we are not at your computer, and don’t have your dataset, when troubleshooting it is best to include a minimal reproducible example of the issuen you are encountering, slimming down the number of files needed to be transferred, and generalizing down the code so that other course participants and instructors can follow along. If this is not doable, or if the problem requires added context (and larger files), create a new repository on your GitHub, make it public, and share the links to it in your post. The goal would be to download the folder and be able to replicate the issue that you are encountering.\n\n\n\n\n\n\n\n\n\n\nShow and Tell\n\nWhere Q&A section is for getting help on code that is frustratingly not working, Show and Tell is where to go and celebrate when you finally get things to work. Share your wins, show us the extra pretty graphs, bizarre autofluorescence signatures, or odd outputs that just make you laugh.", + "crumbs": [ + "About", + "Getting Started", + "00 - Getting Help" + ] }, { - "objectID": "course/00_Homeworks/slides.html#issues", - "href": "course/00_Homeworks/slides.html#issues", + "objectID": "course/00_Homeworks/index.html#issues", + "href": "course/00_Homeworks/index.html#issues", "title": "Getting Help", "section": "Issues", - "text": "Issues" + "text": "Issues\nMost of the time, if you are having trouble getting you code to run, you should first stop after some initial troubleshooting should be to open a new Discussion under the Q&A category. Here you will be able to get both community and instructor help and suggestions to hopefully resolve whatever is going on.\n\nThe Issues page is primarily meant for course-specific problems that require the course instructor intervention to fix. For example, we release a new week of material, and while it runs fine for both Windows and Linux, the code fails to run for all MacOS users. While you may be able to find workarounds on your own, it’s ultimately our responsibility to help provide a solution so that everyone can move forward. This is the situation where opening an Issue is appropiate.\n\n\n\nSimilarly, if our code contains a wrong argument, is returning a deprecation warning, etc. open an issue to let us know. While we may not be able to fix something that is not directly related to our code, we can redirect it to the package maintainers so that they can fix the issue.\nAnd likewise, if you find multiple typos in the documentation, you can open an issue and propose carrying out a pull-request to fix them.", + "crumbs": [ + "About", + "Getting Started", + "00 - Getting Help" + ] }, { - "objectID": "course/00_Homeworks/slides.html#submitting-take-home-problems", - "href": "course/00_Homeworks/slides.html#submitting-take-home-problems", + "objectID": "course/00_Homeworks/index.html#submitting-take-home-problems", + "href": "course/00_Homeworks/index.html#submitting-take-home-problems", "title": "Getting Help", "section": "Submitting Take-Home Problems", - "text": "Submitting Take-Home Problems\n\n\n\n\n\n\n\n\n.\n\n\nEach week, during the course, we introduce and cover the main concepts for the particular concept. Our goal is to provide you with the necessary code and enough code to be able to get the jist. However, to become comfortable and be able to apply what you have learned, you will need to explore beyond our examples, try it with your own datasets, encounter things that don’t work, and troubleshoot your way through them. It’s this cycle of venturing into the unknown that develops strong coding skills that are needed to overcome any barrier you encounter. The goal of the take-home questions is to provide some less curated problems that will take a little longer to answer to help get you started on your own exploration of the topic." + "text": "Submitting Take-Home Problems\nEach week, during the course, we introduce and cover the main concepts for the particular concept. Our goal is to provide you with the necessary code and enough code to be able to get the jist. However, to become comfortable and be able to apply what you have learned, you will need to explore beyond our examples, try it with your own datasets, encounter things that don’t work, and troubleshoot your way through them. It’s this cycle of venturing into the unknown that develops strong coding skills that are needed to overcome any barrier you encounter. The goal of the take-home questions is to provide some less curated problems that will take a little longer to answer to help get you started on your own exploration of the topic.\nAs previously mentioned, these take-home problems are completely optional. If you are in the middle of solving them and want to seek feedback from then community and course instructors, open a Discussion under the general category is the way to go.\nHowever, if you have completed them, and want course instructor feedback, you can submit them to us in the form of a pull-request to the CytometryInR repo’s homework branch. We will take a look, offer constructive suggestions, and when ready merge the solution. This will also result in GitHub listing you as a contributor to the course.\nWe will outline the basic steps of how to set up and open a pull-request, to help simplify the process.\n\nSync your Fork\nFirst off, make sure to Sync your fork of the Cytometry in R project. That makes sure that all the commits present are up-to-date and simplifies the process of having the pull-request being merged.\n\n\n\n\n\n\n\n\n\n\n\nPull to Local\nHaving Synced your branch on GitHub, return to your computer, open the CytometryInR repository and pull in the changes locally.\n\n\n\n\nCreate own Folder under Homeworks\nUnder the course folder, you will find folders for each week. Within these folders find the homework folder. This will appear empty except for a README file with ionstructions. It is within this folder you will need to create your own folder.\nTo ensure there are no conflicts on the pull-request merge, please use your GitHub username as the folder name.\n\n\n\nOnce you have your folder inside homework, go ahead and copy anything you are turning in from their respective working project folders. Remember, the goal is minimal reproducible example is the goal. Rendered Quarto Documents are preferred, but we will also accept scripts and small data files and images. a README.MD file with anything you want me to know,\n\n\n\n\n\n\n\n\nSign off Commit\nNow that everything is present, Sign Off and Commit the change.\n\n\n\n\n\nPush Branch to GitHub.\nProceed to push the branch to GitHub.\n\n\n\n\n\nRe-sync if necessary\nIf additional changes have occured to the parent CytometryInR repository, go ahead and update your branch. As long as your edits occurred within your folder inside homework folders, they should still be able to merge.\n\n\n\n\n\n\n\n\nOpen a pull-request\nTo start a pull request, click to see how your commit is ahead by\n\n\n\nNext, switch from the parent CytometryInR main branch (used for the website and course) to the homework branch for that respective week (used for the take-home problems).\n\n\n\nOnce this is done, select Pull request\n\n\n\nMake sure to triple check it’s bound for the homeworks branch. If you see that it is not capable of merging, verify that your commit only contains files within your respective homework username folder. Fill in the required fields of the pull request.\n\n\n\nAnd when ready, create the pull request.\n\n\n\n\nWait for Feedback\nOn our end, once you have created a pull request, we will review your work, offer constructive suggestions, etc. If I ask for revisions, all you would need to do is update your files, commit again on your side of the local forked repository.\n\n\n\n\n\nFinal Review and Merge\nIf all is good, we will merge the pull request and your solution to the take-home problems will now be available on the homework branch.\n\n\n\n\n\nAfter course\nAfter the course completes, we will merge homework branch with the main branch, making the community solutions to the take-home problems additional coding examples that can be used by others following along after the course concludes.", + "crumbs": [ + "About", + "Getting Started", + "00 - Getting Help" + ] }, { - "objectID": "course/00_Positron/slides.html#console", - "href": "course/00_Positron/slides.html#console", + "objectID": "course/00_Positron/index.html", + "href": "course/00_Positron/index.html", + "title": "Using Positron", + "section": "", + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", + "crumbs": [ + "About", + "Getting Started", + "00 - Positron" + ] + }, + { + "objectID": "course/00_Positron/index.html#console", + "href": "course/00_Positron/index.html#console", "title": "Using Positron", "section": "Console", - "text": "Console\n\n\n\n\n\n\n\n\n.\n\n\nAt the bottom of the sceen, you will first see the Console Tab. This is the tab where your lines of code when executed (run) will appear, as well as any messages, warnings or errors that get returned. On the right side of the console, you can find several buttons, among them restart R and delete session (for when you need a fresh start), and clear console (which keeps all previously run outputs and objects, but clears away the displayed text within the console)." + "text": "Console\nAt the bottom of the sceen, you will first see the Console Tab. This is the tab where your lines of code when executed (run) will appear, as well as any messages, warnings or errors that get returned. On the right side of the console, you can find several buttons, among them restart R and delete session (for when you need a fresh start), and clear console (which keeps all previously run outputs and objects, but clears away the displayed text within the console).", + "crumbs": [ + "About", + "Getting Started", + "00 - Positron" + ] }, { - "objectID": "course/00_Positron/slides.html#terminal", - "href": "course/00_Positron/slides.html#terminal", + "objectID": "course/00_Positron/index.html#terminal", + "href": "course/00_Positron/index.html#terminal", "title": "Using Positron", "section": "Terminal", - "text": "Terminal\n\n\n\n\n\n\n\n\n.\n\n\nRight next to the Console tab is your Terminal tab. While the console tab is primarily used to run R code within Positron, the terminal is the interface where code containing system commands directed at at your computer is entered. We will use this less frequently, primarily in two context: 1) rendering Quarto documents, and 2) commiting changes to version control. Among the buttons on the right-side of the terminal to make note of are the + button to add a new terminal, and the trash/garbage can button to kill (stop) the terminal." + "text": "Terminal\nRight next to the Console tab is your Terminal tab. While the console tab is primarily used to run R code within Positron, the terminal is the interface where code containing system commands directed at at your computer is entered. We will use this less frequently, primarily in two context: 1) rendering Quarto documents, and 2) commiting changes to version control. Among the buttons on the right-side of the terminal to make note of are the + button to add a new terminal, and the trash/garbage can button to kill (stop) the terminal.\n\n\n\nThe other tabs (Problems, Output, Ports, Debug Console) are used less frequently. I usually will Problems and Debug when something goes wrong with the code, as various warning and error messages will end up being displayed there.", + "crumbs": [ + "About", + "Getting Started", + "00 - Positron" + ] }, { - "objectID": "course/00_Positron/slides.html#help", - "href": "course/00_Positron/slides.html#help", + "objectID": "course/00_Positron/index.html#help", + "href": "course/00_Positron/index.html#help", "title": "Using Positron", "section": "Help", - "text": "Help\n\n\n\n\n\n\n\n\n.\n\n\nWhen trying to evaluate how a particular function is working in R, you can hover over it and positron will open up the documentation for that particular function if available, alternatively, you can enter ?theParticularFunctionsName in the console and hit enter to similarly view what is occuring." + "text": "Help\nWhen trying to evaluate how a particular function is working in R, you can hover over it and positron will open up the documentation for that particular function if available, alternatively, you can enter ?theParticularFunctionsName in the console and hit enter to similarly view what is occuring.", + "crumbs": [ + "About", + "Getting Started", + "00 - Positron" + ] }, { - "objectID": "course/00_Positron/slides.html#variables", - "href": "course/00_Positron/slides.html#variables", + "objectID": "course/00_Positron/index.html#variables", + "href": "course/00_Positron/index.html#variables", "title": "Using Positron", "section": "Variables", - "text": "Variables\n\n\n\n\n\n\n\n\n.\n\n\nOn the upper-portion of the Secondary Side Bar, we can find the Session window, containing the Variables tab. As you run (execute) lines of code, and different variables, objects and functions are created, these become visible under the variables tab on the upper right." + "text": "Variables\nOn the upper-portion of the Secondary Side Bar, we can find the Session window, containing the Variables tab. As you run (execute) lines of code, and different variables, objects and functions are created, these become visible under the variables tab on the upper right.\n\n\n\nFor some types of objects (generally data.frames and other matrix-like objects), you can click on their listing under variables to expand to see additional details about the object (column names, etc.) as well as view a larger version which will appear within the Editor window.", + "crumbs": [ + "About", + "Getting Started", + "00 - Positron" + ] }, { - "objectID": "course/00_Positron/slides.html#plots", - "href": "course/00_Positron/slides.html#plots", + "objectID": "course/00_Positron/index.html#plots", + "href": "course/00_Positron/index.html#plots", "title": "Using Positron", "section": "Plots", - "text": "Plots\n\n\n\n\n\n\n\n\n.\n\n\nSimilarly, any generated Plots or Documents will appear within the Secondary Side Bar, either under Plots (bottom) or Viewer (top) tabs." + "text": "Plots\nSimilarly, any generated Plots or Documents will appear within the Secondary Side Bar, either under Plots (bottom) or Viewer (top) tabs.", + "crumbs": [ + "About", + "Getting Started", + "00 - Positron" + ] }, { - "objectID": "course/00_Positron/slides.html#view", - "href": "course/00_Positron/slides.html#view", + "objectID": "course/00_Positron/index.html#view", + "href": "course/00_Positron/index.html#view", "title": "Using Positron", "section": "View", - "text": "View\n\n\n\n\n\n\n\n\n.\n\n\nOn the upper bar multiple tabs can be found, which we will explore in due time. Most useful to point out is the View tab. If you accidentally close your console, session or plots window, and are trying to get them to reapper, you would need to reselect them from this tab." + "text": "View\nOn the upper bar multiple tabs can be found, which we will explore in due time. Most useful to point out is the View tab. If you accidentally close your console, session or plots window, and are trying to get them to reapper, you would need to reselect them from this tab.", + "crumbs": [ + "About", + "Getting Started", + "00 - Positron" + ] }, { - "objectID": "course/00_Positron/slides.html#pages", - "href": "course/00_Positron/slides.html#pages", + "objectID": "course/00_Positron/index.html#pages", + "href": "course/00_Positron/index.html#pages", "title": "Using Positron", "section": "Pages", - "text": "Pages\n\n\n\n\n\n\n\n\n.\n\n\nThe pages tab and the left-side bar show you everything that is currently within your project folder, including all the folders, and files. Once version control with Git is initiated, new files are relected showing up as green text and a dot, while modified tracked files are reflected by light brown text and a dot." + "text": "Pages\nThe pages tab and the left-side bar show you everything that is currently within your project folder, including all the folders, and files. Once version control with Git is initiated, new files are relected showing up as green text and a dot, while modified tracked files are reflected by light brown text and a dot.\n\n\n\nThe dropdown arrows can be used to open and close specific folders to allow for better organization. There is also a scrollbar on the right-side of the side-bar to scroll through the entire folders contents.", + "crumbs": [ + "About", + "Getting Started", + "00 - Positron" + ] }, { - "objectID": "course/00_Positron/slides.html#search", - "href": "course/00_Positron/slides.html#search", + "objectID": "course/00_Positron/index.html#search", + "href": "course/00_Positron/index.html#search", "title": "Using Positron", "section": "Search", - "text": "Search\n\n\n\n\n\n\n\n\n.\n\n\nThe search tab on the left side bar is something that I use routinely." + "text": "Search\nThe search tab on the left side bar is something that I use routinely.\n\n\n\nIt can help locate code that you had been working on, but have since forgotten where it is at. Here is an example of finding the files where I had used a function that needed modifying within a local project folder’s files.\n\n\n\nSimilarly, if you need to replace a particular character string with another, the replace with field below can help simplify the task without having to track down and change 20 lines across 5 files.", + "crumbs": [ + "About", + "Getting Started", + "00 - Positron" + ] }, { - "objectID": "course/00_Positron/slides.html#extensions", - "href": "course/00_Positron/slides.html#extensions", + "objectID": "course/00_Positron/index.html#extensions", + "href": "course/00_Positron/index.html#extensions", "title": "Using Positron", "section": "Extensions", - "text": "Extensions\n\n\n\n\n\n\n\n\n.\n\n\nOn the far-left side we can find the Activity bar, which contains several tabs. Which tab you have selected will then dictate the contents of your left side-bar.\nOccupying the left side bar are several tabs. One of these is Extensions, which shows “Plugins” (or the VScode equivalent) that extend the functionality of Positron further. The ones you have installed may vary, but the main ones in context of this course are Air (provides color and highlights syntax for R code to make interpretation easier) as well as Quarto (for rendering the various document types)." + "text": "Extensions\nOn the far-left side we can find the Activity bar, which contains several tabs. Which tab you have selected will then dictate the contents of your left side-bar.\nOccupying the left side bar are several tabs. One of these is Extensions, which shows “Plugins” (or the VScode equivalent) that extend the functionality of Positron further. The ones you have installed may vary, but the main ones in context of this course are Air (provides color and highlights syntax for R code to make interpretation easier) as well as Quarto (for rendering the various document types).", + "crumbs": [ + "About", + "Getting Started", + "00 - Positron" + ] }, { - "objectID": "course/00_Positron/slides.html#git", - "href": "course/00_Positron/slides.html#git", + "objectID": "course/00_Positron/index.html#git", + "href": "course/00_Positron/index.html#git", "title": "Using Positron", "section": "Git", - "text": "Git\n\n\n\n\n\n\n\n\n.\n\n\nThe Git tab on the left side bar is where once version control is initiated for the project folder, we can see changes that have occurred to the individual files since the last commit. These changes can be added to a new commit by clicking on the + sign. This will be covered more extensively in the next section" + "text": "Git\nThe Git tab on the left side bar is where once version control is initiated for the project folder, we can see changes that have occurred to the individual files since the last commit. These changes can be added to a new commit by clicking on the + sign. This will be covered more extensively in the next section\n\n\n\nSimilarly, if you want to discard a change that has occured, the circular arrow will revert to the last commited version. Selecting and pressing the delete button will similarly work.\n\n\n\nSelecting the … options will highlight all the various git functions, some of which we will cover more extensively in the next section and throughout the course.", + "crumbs": [ + "About", + "Getting Started", + "00 - Positron" + ] }, { - "objectID": "course/00_Quarto/slides.html#renderpreview", - "href": "course/00_Quarto/slides.html#renderpreview", + "objectID": "course/00_Quarto/index.html", + "href": "course/00_Quarto/index.html", + "title": "Introduction to Quarto", + "section": "", + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", + "crumbs": [ + "About", + "Getting Started", + "00 - Quarto" + ] + }, + { + "objectID": "course/00_Quarto/index.html#renderpreview", + "href": "course/00_Quarto/index.html#renderpreview", "title": "Introduction to Quarto", "section": "Render/Preview", - "text": "Render/Preview\n\n\n\n\n\n\n\n\n.\n\n\nThe preview button, at the upper-left end of the Editor, is used to render/knit a quarto document. This triggers the process by which code-chunks are run, and then the outputs are cobbled together into the file format type designated by the YAML header." + "text": "Render/Preview\nThe preview button, at the upper-left end of the Editor, is used to render/knit a quarto document. This triggers the process by which code-chunks are run, and then the outputs are cobbled together into the file format type designated by the YAML header.\n\n\n\n\nHTML\nIn this case, the YAML header’s format argument is set to html. After clicking preview, we can see the various rendering steps appear in the console below. Since no errors occured, the html document was formed succesfully and appears as a file in the left side-bar. Additional, a preview of the document appears in the View tab of the right side-bar, allowing for quick visual inspection.\n\n\n\nAlternatively, we can render a document via the terminal, by entering “quarto render”, followed by the name of the document.\n\n\n\nThis results similar process as what we saw with the preview button\n\n\n\nWe can also open the .html document via our File Explorer, which will open it within our web browser.\n\n\n\nQuarto documents can be rendered (previewed) in other formats besides html. These include pdf, Word documents (docx), and slides (revealjs). This is set by the format argument within the YAML header.\n\n\nPDF\nBy switching the format argument from html to pdf, we can render the document as a pdf\n\n\n\nWe can see the pdf is now listed in the list of files, with a preview shown on the right side-bar.\n\n\n\n\n\nDocx\nWe can also generate Word documents (.docx) as well.\n\n\n\nIn this case, we can see that a Word document file was created, but nothing appears in the View tab. This is because the format is not yet supported for the View tab. We can however open and view the Word document via our File explorer.\n\n\n\nWhich shows a Word Document style output.", + "crumbs": [ + "About", + "Getting Started", + "00 - Quarto" + ] }, { - "objectID": "course/00_Quarto/slides.html#yaml", - "href": "course/00_Quarto/slides.html#yaml", + "objectID": "course/00_Quarto/index.html#yaml", + "href": "course/00_Quarto/index.html#yaml", "title": "Introduction to Quarto", "section": "YAML", - "text": "YAML\n\n\n\n\n\n\n\n\n.\n\n\nWe can additionally provide additional custom inputs to the YAML header. A couple examples include providing the document author and date." + "text": "YAML\nWe can additionally provide additional custom inputs to the YAML header. A couple examples include providing the document author and date.\n\n\n\nWhich we can see are updated after we preview/render.", + "crumbs": [ + "About", + "Getting Started", + "00 - Quarto" + ] }, { - "objectID": "course/00_Quarto/slides.html#table-of-contents", - "href": "course/00_Quarto/slides.html#table-of-contents", + "objectID": "course/00_Quarto/index.html#table-of-contents", + "href": "course/00_Quarto/index.html#table-of-contents", "title": "Introduction to Quarto", "section": "Table of Contents", - "text": "Table of Contents\n\n\n\n\n\n\n\n\n.\n\n\nIn the previous section, we saw that we could provide headings and subheadings to our .qmd file by placing a # at the start of a line in the text portion of the document. A subheading was designated by a ##, with additional hierarchy being designated by appending an additional #." + "text": "Table of Contents\nIn the previous section, we saw that we could provide headings and subheadings to our .qmd file by placing a # at the start of a line in the text portion of the document. A subheading was designated by a ##, with additional hierarchy being designated by appending an additional #.\n\n\n\nWe can use the heading information to generate a table of contents for our document. To do this, we add a toc argument to the yaml header, and set it to TRUE. After rendering, it appears on the upper-right side of the document.\n\n\n\nNotice, that the subheaders do not appear currently within the TOC.\n\n\n\nWe can fix this by setting a toc-expand argument in the YAML to true.", + "crumbs": [ + "About", + "Getting Started", + "00 - Quarto" + ] }, { - "objectID": "course/00_Quarto/slides.html#code-chunk-arguments", - "href": "course/00_Quarto/slides.html#code-chunk-arguments", + "objectID": "course/00_Quarto/index.html#code-chunk-arguments", + "href": "course/00_Quarto/index.html#code-chunk-arguments", "title": "Introduction to Quarto", "section": "Code Chunk Arguments", - "text": "Code Chunk Arguments\n\n\n\n\n\n\n\n\n.\n\n\nAs we briefly touched on in the last section, code-chunks can be modified by including arguments, which affect whether a particular code chunk gets evaluated. In that example, we included a “#| eval: FALSE” to the install commands since we did not want them to be re-run subsequently. We will take a closer look at the other arguments in this section.\n\n\n\n\n\nEval\n\n\n\n\n\n\n\n\n.\n\n\nThe code-chunk argument, “Eval”, is used to determine when a code-chunk get’s evaluated. When set to true (or by default if no eval argument is included), the code-chunks contents will be run/executed, and the output will appear. We can see this in the html output, as below the code block, we get back the address of my working directory." - }, - { - "objectID": "course/00_Quarto/slides.html#text-styles", - "href": "course/00_Quarto/slides.html#text-styles", - "title": "Introduction to Quarto", - "section": "Text Styles", - "text": "Text Styles\n\n\n\n\n\n\n\n\n.\n\n\nQuarto primarily uses Markdown for text styling. Consequently, markdown arguments can be used within the text to change how various text appears." - }, - { - "objectID": "course/00_Quarto/slides.html#hyperlinks", - "href": "course/00_Quarto/slides.html#hyperlinks", - "title": "Introduction to Quarto", - "section": "Hyperlinks", - "text": "Hyperlinks\n\n\n\n\n\n\n\n\n.\n\n\nYou can link to a website by surrounding word of interest in [] and placing the url within () adjacent to it." - }, - { - "objectID": "course/00_Quarto/slides.html#images", - "href": "course/00_Quarto/slides.html#images", - "title": "Introduction to Quarto", - "section": "Images", - "text": "Images\n\n\n\n\n\n\n\n\n.\n\n\nYou can place images by adding the following, as long as the file.path to the image is correctly formatted. In my case, this is why I include images folders within my folders to simplify the copy and paste." - }, - { - "objectID": "course/00_WorkstationSetup/WindowsSlides.html#installing-r", - "href": "course/00_WorkstationSetup/WindowsSlides.html#installing-r", - "title": "Installing Software on Windows", - "section": "Installing R", - "text": "Installing R\n\n\n\n\n\n\n\n\n.\n\n\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page." - }, - { - "objectID": "course/00_WorkstationSetup/WindowsSlides.html#installing-rtools", - "href": "course/00_WorkstationSetup/WindowsSlides.html#installing-rtools", - "title": "Installing Software on Windows", - "section": "Installing RTools", - "text": "Installing RTools\n\n\n\n\n\n\n\n\n.\n\n\nWe will now work on installing Rtools. This software is needed when building R packages from source, which we will need throughout the course for R packages hosted on GitHub.\nTo get started, we will return to the R installation page we visited previously and instead click on the Rtools option." - }, - { - "objectID": "course/00_WorkstationSetup/WindowsSlides.html#installing-git", - "href": "course/00_WorkstationSetup/WindowsSlides.html#installing-git", - "title": "Installing Software on Windows", - "section": "Installing Git", - "text": "Installing Git\n\n\n\n\n\n\n\n\n.\n\n\nGit is a version control software widely used among software developers and bioinformaticians. We will use it extensively throughout the course, both locally on our computers (to keep track of changes to our files), as well as in combination with GitHub(to maintain online backups of our files).\nWe will first navigate to the website and select the download from Windows option." - }, - { - "objectID": "course/00_WorkstationSetup/WindowsSlides.html#installing-positron", - "href": "course/00_WorkstationSetup/WindowsSlides.html#installing-positron", - "title": "Installing Software on Windows", - "section": "Installing Positron", - "text": "Installing Positron\n\n\n\n\n\n\n\n\n.\n\n\nFinally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right." - }, - { - "objectID": "course/00_WorkstationSetup/Linux.html", - "href": "course/00_WorkstationSetup/Linux.html", - "title": "Installing Software on Linux", - "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here\nThis is the software installation walkthrough for those whose computers are running Linux. First off, welcome! Based on our pre-course interest form, there was a suprising number of you daily-drivers out there! However, a CytometryInR interest form is unlikely to be representative of the general population, so please stash all Year of the Linux desktop banners until further notice." - }, - { - "objectID": "course/00_WorkstationSetup/Linux.html#debian-based-distros", - "href": "course/00_WorkstationSetup/Linux.html#debian-based-distros", - "title": "Installing Software on Linux", - "section": "Debian-based Distros", - "text": "Debian-based Distros\n\nInstalling R\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.\n\n\n\nOn the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.\n\n\n\nOnce this is done, select your Linux Distro (or one that shares your package managers format).\n\n\n\nOn the landing page, you will find a bunch of relevant installation information, which is worthwhile giving a read-through when you have time.\n\n\n\nThe process to successfully install R can be summarized as follows:\nUpdate apt/sources.list to include the CRAN repository (allowing access to R packages)\n\n\n\nSince we are running on Debian stable (Trixie), we would add the following line to sources.list\n\n\n\nSo in practice, open sources.list:\n\n\n\nPaste the line, and “Ctrl + O”; “Enter”; “Ctrl + X” to save the changes.\n\n\n\nNext, we will need to retrieve the keyID used to sign. This can be fetched from Ubuntu via the terminal.\n\n\n\n\n\n\nThen we need to export and write it\n\n\n\nWhich if successful, will display the public key.\n\n\n\nWith the above set up, we can proceed via our apt package manager to install both r-base and r-base-dev (which contains the equivalent of Rtools for Windows, or Xcode Command Line Tools for macOS).\n\n\n\n\n\n\n\n\n\nAnd if all goes well, R should now be installed." - }, - { - "objectID": "course/00_WorkstationSetup/Linux.html#installing-git", - "href": "course/00_WorkstationSetup/Linux.html#installing-git", - "title": "Installing Software on Linux", - "section": "Installing Git", - "text": "Installing Git\n\n# sudo apt install git" + "text": "Code Chunk Arguments\nAs we briefly touched on in the last section, code-chunks can be modified by including arguments, which affect whether a particular code chunk gets evaluated. In that example, we included a “#| eval: FALSE” to the install commands since we did not want them to be re-run subsequently. We will take a closer look at the other arguments in this section.\n\nEval\nThe code-chunk argument, “Eval”, is used to determine when a code-chunk get’s evaluated. When set to true (or by default if no eval argument is included), the code-chunks contents will be run/executed, and the output will appear. We can see this in the html output, as below the code block, we get back the address of my working directory.\n\n\n\nWhen we switch the Eval argument to FALSE, and then render the document, we can see that the code block remains, but we do not get any output for the code contained within.\nIn every-day practice, we will “use eval: FALSE” arguments when we want to keep the code for later use, but want to manually run the code contained within ourselves.\n\n\n\n\n\nEcho\nThe code-block argument “echo” dictates whether the code within the code-block is displayed within the document. So in the case when “echo: true”, we get both the code displayed, as well as the output that gets returned by the code.\n\n\n\nBy contrast, when “echo: FALSE”, we do not have the code displayed, but do get the output of that code being run.\nIn daily-practice, “echo: FALSE” gets often used when generating plots that we want to include in the report, without the code that generated them being displayed.\n\n\n\n\n\nInclude\nThe next code-chunk argument is include. Unlike echo, which focuses on whether the code is displayed, but still returns the output, include dictates behavior of both the code-block and it’s output. Unlike eval however, it will still run the code, which allows it to be available for the next code-chunk that might need it. When we set “include: false”, no trace of that code-chunk is present in the document. This is useful when making reports where we do not want to include the code used to generate a particular figure.\n\n\n\nBy contrast, when we set “include: true”, the code block and it’s output is once again included within the rendered document.\n\n\n\n\n\nCode-Fold\nOne of my favorites is “code-fold”. When we set it as “code-fold: show”, it displays the code, but provides a drop-down arrow that can be closed to compress the code.\n\n\n\nIn contrast, if we want to make the code-available for those that are interested, but not directly visible, we can set as “code-fold: true”\n\n\n\n\n\nWarnings\nWithin R, when code is executed, in addition to returning the output, R is capable of returning warnings (when something is not as expected, but not sufficient to elicit an error with a complete stop) or a message (text output that gets displayed, often telling about progress). While these are useful when running code yourself, it can be annoying when generating a report and the 2nd page is a bunch of warning text being displayed.\nFor example, when the R package ggcyto is loaded via the library call, it will automatically load several other packages, which typically results in these messages being outputted:\n\n\n\nWe can therefore set that code-chunk’s warning/message arguments to FALSE, therefore silencing the message outputs that would otherwise clutter up our report.", + "crumbs": [ + "About", + "Getting Started", + "00 - Quarto" + ] }, { - "objectID": "course/00_WorkstationSetup/Linux.html#installing-positron", - "href": "course/00_WorkstationSetup/Linux.html#installing-positron", - "title": "Installing Software on Linux", - "section": "Installing Positron", - "text": "Installing Positron\nFinally, you will need to install Positron. It will be the integrated development environment (IDE) we will be using for the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right.\n\n\n\nYou will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).\n\n\n\nWith the license accepted, you will be able to select distribution and architecture.\n\n\n\nOnce the Download completes, proceed to install the .deb package as you would nornally. GUI example via Discover below.\n\n\n\nDepending on your configurations, you may be asked to exert your sudo powers.\n\n\n\nOnce this completes, you should now be able to launch the software for the first time." + "objectID": "course/00_Quarto/index.html#text-styles", + "href": "course/00_Quarto/index.html#text-styles", + "title": "Introduction to Quarto", + "section": "Text Styles", + "text": "Text Styles\nQuarto primarily uses Markdown for text styling. Consequently, markdown arguments can be used within the text to change how various text appears.\n\n\n\nFor a regular text, This single asterisk on each side of a word will italicize.\n\n\n\nWhen the number of asterisk is doubled, This word is bolded.\n\n\n\nWhen three asterisk are used, both are applied.\n\n\n\nFor an underscore, the word of interest is surrounded by square brackets “[]”, with “{.underline}” adjacent.", + "crumbs": [ + "About", + "Getting Started", + "00 - Quarto" + ] }, { - "objectID": "course/00_WorkstationSetup/LinuxSlides.html#debian-based-distros", - "href": "course/00_WorkstationSetup/LinuxSlides.html#debian-based-distros", - "title": "Installing Software on Linux", - "section": "Debian-based Distros", - "text": "Debian-based Distros\nInstalling R\n\n\n\n\n\n\n\n\n.\n\n\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page." + "objectID": "course/00_Quarto/index.html#hyperlinks", + "href": "course/00_Quarto/index.html#hyperlinks", + "title": "Introduction to Quarto", + "section": "Hyperlinks", + "text": "Hyperlinks\nYou can link to a website by surrounding word of interest in [] and placing the url within () adjacent to it.", + "crumbs": [ + "About", + "Getting Started", + "00 - Quarto" + ] }, { - "objectID": "course/00_WorkstationSetup/LinuxSlides.html#installing-git", - "href": "course/00_WorkstationSetup/LinuxSlides.html#installing-git", - "title": "Installing Software on Linux", - "section": "Installing Git", - "text": "Installing Git\n\n# sudo apt install git" + "objectID": "course/00_Quarto/index.html#images", + "href": "course/00_Quarto/index.html#images", + "title": "Introduction to Quarto", + "section": "Images", + "text": "Images\nYou can place images by adding the following, as long as the file.path to the image is correctly formatted. In my case, this is why I include images folders within my folders to simplify the copy and paste.", + "crumbs": [ + "About", + "Getting Started", + "00 - Quarto" + ] }, { - "objectID": "course/00_WorkstationSetup/LinuxSlides.html#installing-positron", - "href": "course/00_WorkstationSetup/LinuxSlides.html#installing-positron", - "title": "Installing Software on Linux", - "section": "Installing Positron", - "text": "Installing Positron\n\n\n\n\n\n\n\n\n.\n\n\nFinally, you will need to install Positron. It will be the integrated development environment (IDE) we will be using for the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right." + "objectID": "course/00_WorkstationSetup/MacOS.html", + "href": "course/00_WorkstationSetup/MacOS.html", + "title": "Installing Software on MacOS", + "section": "", + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here\nThis is the software installation walkthrough for those whose computers are running MacOS. Based on our pre-course interest form, you make up a solid proportion of the course participants." }, { - "objectID": "course/00_WorkstationSetup/MacOSSlides.html#installing-r", - "href": "course/00_WorkstationSetup/MacOSSlides.html#installing-r", + "objectID": "course/00_WorkstationSetup/MacOS.html#installing-r", + "href": "course/00_WorkstationSetup/MacOS.html#installing-r", "title": "Installing Software on MacOS", "section": "Installing R", - "text": "Installing R\n\n\n\n\n\n\n\n\n.\n\n\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page." + "text": "Installing R\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.\n\n\n\nOn the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.\n\n\n\nYou will then select your Operating System, in this case, macOS\n\n\n\nNext, you will need to select the appropiate download based on your computers architecture. On newer Macs (containing M1+ chips) this would the arm64 option on the center left of the screen. For the older Intel (pre-2020) Macs, you would select the x86_64 option. If you are unsure, check your About This Mac tab\n\n\n\nAfter the download has completed, launch the installer\n\n\n\nProceed through the Read Me\n\n\n\nYou will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course).\n\n\n\n\n\n\nNext, you will need to navigate through several pages, keeping the defaults.\n\n\n\nAnd with any luck, you should see that the installation was successful." }, { - "objectID": "course/00_WorkstationSetup/MacOSSlides.html#xcode-command-line-tools", - "href": "course/00_WorkstationSetup/MacOSSlides.html#xcode-command-line-tools", + "objectID": "course/00_WorkstationSetup/MacOS.html#xcode-command-line-tools", + "href": "course/00_WorkstationSetup/MacOS.html#xcode-command-line-tools", "title": "Installing Software on MacOS", "section": "Xcode Command Line Tools", - "text": "Xcode Command Line Tools\n\n\n\n\n\n\n\n\n.\n\n\nDepending on your version of macOS, you may or may not already have Git installed on your computer. The reason is that it comes bundled within the Xcode Command Line Tools.\nIf this is not your first foray into coding, you may have previously seen an installation pop-up along the lines of “XYZ requires command line developer tools. Would you like to install the tools now?” when installing an IDE (like Positron, Rstudio or Visual Studio Code)." + "text": "Xcode Command Line Tools\nDepending on your version of macOS, you may or may not already have Git installed on your computer. The reason is that it comes bundled within the Xcode Command Line Tools.\nIf this is not your first foray into coding, you may have previously seen an installation pop-up along the lines of “XYZ requires command line developer tools. Would you like to install the tools now?” when installing an IDE (like Positron, Rstudio or Visual Studio Code).\n\n\n\nSince these command line developer tools contain both Git, and also the equivalent of Rtools for Windows, we will need to install them for this course. To get started, first open your terminal.\n\n\n\nNext run the following code:\n\nxcode-select --install\n\n\n\n\nYou will then have the pop-up asking whether you want to install the command line tools (which contain Git). Select Install.\n\n\n\nYou will then be asked to accept the license\n\n\n\nYour installation will then proceed\n\n\n\nAnd if all goes well, the software will finish installing.\n\n\n\nAfter you complete Positron installation (next section), if you check the version control tab on the action bar on the far left side of the screen, you should see the following if Git was installed correctly.\n\n\n\nAlternatively, if you see this, you will need to reattempt the installation." }, { - "objectID": "course/00_WorkstationSetup/MacOSSlides.html#install-positron", - "href": "course/00_WorkstationSetup/MacOSSlides.html#install-positron", + "objectID": "course/00_WorkstationSetup/MacOS.html#install-positron", + "href": "course/00_WorkstationSetup/MacOS.html#install-positron", "title": "Installing Software on MacOS", "section": "Install Positron", - "text": "Install Positron\n\n\n\n\n\n\n\n\n.\n\n\nFinally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right." - }, - { - "objectID": "course/01_InstallingRPackages/slides_inperson.html#checking-for-loaded-packages", - "href": "course/01_InstallingRPackages/slides_inperson.html#checking-for-loaded-packages", - "title": "01 - Installing R Packages", - "section": "Checking for Loaded Packages", - "text": "Checking for Loaded Packages\n\n\n\n\n\n\n\n\n.\n\n\nFor the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active." - }, - { - "objectID": "course/01_InstallingRPackages/slides_inperson.html#installing-from-cran", - "href": "course/01_InstallingRPackages/slides_inperson.html#installing-from-cran", - "title": "01 - Installing R Packages", - "section": "Installing from CRAN", - "text": "Installing from CRAN\n\n\n\n\n\n\n\n\n.\n\n\nWe will start by installing R packages that are part of the CRAN repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository.\nThese include the tidyverse packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. 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They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems." - }, - { - "objectID": "course/01_InstallingRPackages/slides_inperson.html#install-from-github", - "href": "course/01_InstallingRPackages/slides_inperson.html#install-from-github", - "title": "01 - Installing R Packages", - "section": "Install from GitHub", - "text": "Install from GitHub\n\n\n\n\n\n\n\n\n.\n\n\nIn addition to the CRAN and Bioconductor repositories, individual R packages can also be found on GitHub hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to CRAN or Bioconductor) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all." - }, - { - "objectID": "course/01_InstallingRPackages/slides_inperson.html#troubleshooting-install-errors", - "href": "course/01_InstallingRPackages/slides_inperson.html#troubleshooting-install-errors", - "title": "01 - Installing R Packages", - "section": "Troubleshooting Install Errors", - "text": "Troubleshooting Install Errors\n\n\n\n\n\n\n\n\n.\n\n\nWe have now installed three R packages, dplyr, PeacoQC, and flowSpectrum. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies.\nWhen encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below." - }, - { - "objectID": "course/01_InstallingRPackages/slides_inperson.html#documentation-and-websites", - "href": "course/01_InstallingRPackages/slides_inperson.html#documentation-and-websites", - "title": "01 - Installing R Packages", - "section": "Documentation and Websites", - "text": "Documentation and Websites\n\n\n\n\n\n\n\n\n.\n\n\nWe have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package.\nFor CRAN-based packages, we can start off by searching for the package name. So, in the case of dplyr" + "text": "Install Positron\nFinally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right.\n\n\n\nYou will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).\nWith the license accepted, you will be able to select your operating system and the relevant installer depending on whether you are on an M1+ (ARM) or older Intel (x86) Mac.\n\n\nOnce the Download completes, proceed to install the package as you normally would for any other program." }, { - "objectID": "course/02_FilePaths/slides.html#set-up", - "href": "course/02_FilePaths/slides.html#set-up", - "title": "02 - File Paths", - "section": "Set Up", - "text": "Set Up\n\n\n\n\n\n\n\n\n.\n\n\nBefore we begin, let’s make sure you get the data needed for today transferred to your local computer, and then get the .fcs files copied over from there to your own working project folder. This is the process you will repeat each week throughout the course." + "objectID": "course/00_WorkstationSetup/index.html", + "href": "course/00_WorkstationSetup/index.html", + "title": "Workstation Setup", + "section": "", + "text": "In the previous section, we first set up your GitHub account. Then we modified your GitHub profile and added a README section. Finally, we forked the CytometryInR repository so that you can easily retrieve the new course materials each week.\nIt is now time to install the required software on your computer, which will get your work-station set up with everything needed for this course. Depending on your computers operating system, the installation requirements may differ a bit. In general, you will need to install the following software:\nR website : The programming language we will be using throughout the course.\nPositron : The integrated development environment (IDE) in which we will open, modify and run our code.\nGit : The version control software that will allow us to track changes to our files.\nAdditionally, Windows users will need to install:\nRTools : Used to build R packages from source code.\nYou can find the operating system specific installation walkthroughs below. Once you have completed your specific walkthrough, return to this page and proceed to the next section.\nPlease note: For those using university or company administered computers, please be aware that you may not have the necessary permissions to install these directly, and may need to reach out to your IT department to help get the software installed and running correctly.\nIf you are using your own computer, congratulations, you are your system administrator, and should already have the necessary permissions.", + "crumbs": [ + "About", + "Getting Started", + "00 - Workstation Setup" + ] }, { - "objectID": "course/02_FilePaths/slides.html#working-directory", - "href": "course/02_FilePaths/slides.html#working-directory", - "title": "02 - File Paths", - "section": "Working Directory", - "text": "Working Directory\n\n\n\n\n\n\n\n\n.\n\n\nNow that we are back in our Week2 folder, let’s start by seeing our current location similarly to how our computer perceives it.\nWe will use getwd() function (ie. get working directory) to return the location of the folder we are currently inside of. For example, when getwd() is run within my Week2 project folder, I see the following location" + "objectID": "course/00_WorkstationSetup/index.html#windows", + "href": "course/00_WorkstationSetup/index.html#windows", + "title": "Workstation Setup", + "section": "Windows", + "text": "Windows\n\nInstallation walkthrough for Windows", + "crumbs": [ + "About", + "Getting Started", + "00 - Workstation Setup" + ] }, { - "objectID": "course/02_FilePaths/slides.html#directories", - "href": "course/02_FilePaths/slides.html#directories", - "title": "02 - File Paths", - "section": "Directories", - "text": "Directories\n\n\n\n\n\n\n\n\n.\n\n\nWithin this working directory, we have a variety of project folders and files related to the course. We can see the folders that are present using the list.dirs() function.\n\n\n\n\n\n\n\n\n\n\nlist.dirs(path=\".\", full.names=FALSE, recursive=FALSE)" + "objectID": "course/00_WorkstationSetup/index.html#macos", + "href": "course/00_WorkstationSetup/index.html#macos", + "title": "Workstation Setup", + "section": "MacOS", + "text": "MacOS\n\nInstallation walkthrough for MacOS", + "crumbs": [ + "About", + "Getting Started", + "00 - Workstation Setup" + ] }, { - "objectID": "course/02_FilePaths/slides.html#variables", - "href": "course/02_FilePaths/slides.html#variables", - "title": "02 - File Paths", - "section": "Variables", - "text": "Variables\n\n\n\n\n\n\n\n\n.\n\n\nBefore exploring file paths, we need to have some basic R code knowledge that we can use to work with them. Within R, we have the ability to assign particular values (be they character strings, numbers or logicals) to objects (ie. variables) that can be used when called upon later.\nFor example:\n\n\n\n\n\n\n\nWhatDayDidIWriteThis <- \"Saturday\"\n\n\n\n\n\n\n\n\n\n\n.\n\n\nIn this case, the variable name is what the assignment arrow (“<-”) is pointing at. In this case, WhatDayDidIWriteThis" + "objectID": "course/00_WorkstationSetup/index.html#linux-debian", + "href": "course/00_WorkstationSetup/index.html#linux-debian", + "title": "Workstation Setup", + "section": "Linux (Debian)", + "text": "Linux (Debian)\n\nInstallation walkthrough for Linux", + "crumbs": [ + "About", + "Getting Started", + "00 - Workstation Setup" + ] }, { - "objectID": "course/02_FilePaths/slides.html#indexing", - "href": "course/02_FilePaths/slides.html#indexing", - "title": "02 - File Paths", - "section": "Indexing", - "text": "Indexing\n\n\n\n\n\n\n\n\n.\n\n\nNot all variables contain single objects.\nFor example, we can modify Fluorophores and add additional entries:\n\n\n\n\n\n\n\nFluorophores <- c(\"BV421\", \"FITC\", \"PE\", \"APC\")\nstr(Fluorophores)\n\n chr [1:4] \"BV421\" \"FITC\" \"PE\" \"APC\"\n\n\n\n\n\n\n\n\n\n\n\n.\n\n\nThe c stands for concatenate. It concatenates the objects into a larger object, known as a vector.\nIn this case, you notice in addition to the specification the values are characters, we get a [1:4], denoting four objects are present." + "objectID": "course/00_WorkstationSetup/Windows.html", + "href": "course/00_WorkstationSetup/Windows.html", + "title": "Installing Software on Windows", + "section": "", + "text": "For the YouTube livestream recording, see here\nFor screen-shots slides, click here\nThis is the software installation walkthrough for those whose computers are running Windows. Based on our pre-course interest form, you make up the majority of course participants." }, { - "objectID": "course/02_FilePaths/slides.html#listing-files", - "href": "course/02_FilePaths/slides.html#listing-files", - "title": "02 - File Paths", - "section": "Listing Files", - "text": "Listing Files\n\n\n\n\n\n\n\n\n.\n\n\nAfter this detour into variables and indexing, let’s return our focus to how to use these in context of file paths. Working from within our Week2 project folder, let’s see what directories (folders) are present\n\n\n\n\n\n\n\nlist.dirs(path=\".\", full.names=FALSE, recursive=FALSE)" + "objectID": "course/00_WorkstationSetup/Windows.html#installing-r", + "href": "course/00_WorkstationSetup/Windows.html#installing-r", + "title": "Installing Software on Windows", + "section": "Installing R", + "text": "Installing R\nTo get started, first navigate to the R website. Once there, click on Download R option towards the top of the page.\n\n\n\nOn the next screen, you will need to select a mirror from which to download the software from. You can either select the closest geographic location (which may be faster) or alternatively just select the Cloud option which should redirect you.\n\n\n\nYou will then select your Operating System, in this case, Windows.\n\n\n\nAnd go ahead and select the Install R for the first time link.\n\n\n\nNext, you will select the download the current version option at the top of the page.\n\n\n\nThe popup window will then ask where you want to save the installer (.exe) file. We generally save this to either Downloads or Desktop to make finding it easier.\n\n\n\nAfter the download is complete, double click on the installer’s .exe file. This will open a popup asking you to select your preferred language.\n\n\n\nYou will then be prompted to acccept the software license (which is the free copyleft GPL2 license, which we will learn about later in the course).\n\n\n\nOn Windows, R will normally save it’s software folder under Program Files.\n\n\n\nNext, please accept the defaults.\n\n\n\n\n\n\n\n\n\n\n\n\nWith the defaults accepted, the installation will commence. Feel free to go have a coffee/tea/beverage-of-your choice break while you wait.\n\n\n\nAnd if all goes well, the installation will complete without any issues." }, { - "objectID": "course/02_FilePaths/slides.html#creating-directories", - "href": "course/02_FilePaths/slides.html#creating-directories", - "title": "02 - File Paths", - "section": "Creating directories", - "text": "Creating directories\n\n\n\n\n\n\n\n\n.\n\n\nAlternatively, we can also create a folder via R using the dir.create() function. Since we want it within data, we would modify the path accordingly\n\n\n\n\n\n\n\nNewFolderLocation <- file.path(\"data\", \"target2\")\n\ndir.create(path=NewFolderLocation)" + "objectID": "course/00_WorkstationSetup/Windows.html#installing-rtools", + "href": "course/00_WorkstationSetup/Windows.html#installing-rtools", + "title": "Installing Software on Windows", + "section": "Installing RTools", + "text": "Installing RTools\nWe will now work on installing Rtools. This software is needed when building R packages from source, which we will need throughout the course for R packages hosted on GitHub.\nTo get started, we will return to the R installation page we visited previously and instead click on the Rtools option.\n\n\n\nNext, select the most recent version of Rtools to Download.\n\n\n\nYou will then select for your architecture. For the vast majority of Windows users, your computer will likely be be using a x86 chip architecture, so you would select the Rtools45 installer option.\nIf your computer however uses the ARM chip architecture, you would select the 64-bit ARM Rtools45 installer instead. If you are unsure, see the following.\n\n\n\nNext, you will select the location to save the Rtools installer to. We generally save this to either Downloads or Desktop to make finding it easier.\n\n\n\nOnce downloaded, double click on the .exe to launch the Rtools installer.\n\n\n\nSimilar to what we did when installing R, go ahead and keep the defaults.\n\n\n\nAnd click install to proceed with the installation.\n\n\n\nAnd wait while the installation wraps up.\n\n\n\nIf all goes well, you should see the following installation success page." }, { - "objectID": "course/02_FilePaths/slides.html#file-paths", - "href": "course/02_FilePaths/slides.html#file-paths", - "title": "02 - File Paths", - "section": "File Paths", - "text": "File Paths\n\n\n\n\n\n\n\n\n.\n\n\nOne way we can do this is through a file.path argument. We could potentially provide this by adding either a “/” or a “\" into the path argument, depending on your computers operating system.\n\n\n\n\n\n\n\nlist.files(path=\"data/target\", full.names=FALSE, recursive=FALSE)" + "objectID": "course/00_WorkstationSetup/Windows.html#installing-git", + "href": "course/00_WorkstationSetup/Windows.html#installing-git", + "title": "Installing Software on Windows", + "section": "Installing Git", + "text": "Installing Git\nGit is a version control software widely used among software developers and bioinformaticians. We will use it extensively throughout the course, both locally on our computers (to keep track of changes to our files), as well as in combination with GitHub(to maintain online backups of our files).\nWe will first navigate to the website and select the download from Windows option.\n\n\n\n\n\n\n\n\n\nWe will then proceed and select install 64-bit Git for Windows Setup option\n\n\n\n\n\n\n\nAs was the case with our installation of R and Rtools, a pop-up will appear asking for a location to save the installer to.\nOnce downloaded, double-click and proceed with the installation.\nYou will be asked to accept the Git License (which is the free copyleft GPL2 license, which we will learn about later in the course).\n\n\n\nThen you will be asked to select the folder to save to software to (usually your Programs folder)\n\n\n\nAt this point, the Git installer will ask a series of increasingly niche questions. It is best to just accept all the default options, to avoid wandering too far down a “What is Vim?!?” rabbit-hole.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nHaving made it through all the niche customization screens, we finally reach the install button.\n\n\n\nWe then can wait for the install to complete.\n\n\n\nAnd success, we have now installed Git." }, { - "objectID": "course/02_FilePaths/slides.html#selecting-for-patterns", - "href": "course/02_FilePaths/slides.html#selecting-for-patterns", - "title": "02 - File Paths", - "section": "Selecting for Patterns", - "text": "Selecting for Patterns\n\n\n\n\n\n\n\n\n.\n\n\nIf we currently listed the files within data, we get a return that looks like this:\n\n\n\n\n\n\n\nlist.files(\"data\", full.names=FALSE, recursive=FALSE)" + "objectID": "course/00_WorkstationSetup/Windows.html#installing-positron", + "href": "course/00_WorkstationSetup/Windows.html#installing-positron", + "title": "Installing Software on Windows", + "section": "Installing Positron", + "text": "Installing Positron\nFinally, you will install Positron. It is an integrated development environment (IDE) in which we will open, modify and run our code throughout the course.\nFirst, navigate to their homepage, and select the blue Download option button on the upper-right.\n\n\n\nYou will then need to accept the Elastic License agreement to use the software (we will cover this source-available license type and what it does later in the course).\nWith the license accepted, you will be able to select your operating system. In this case, we will select Windows, specifally the user level install.\n\n\n\nPlease note, if you are using a Windows computer with an ARM based chip (like is the case with Snapdragons), you will need to download the installed from the Positron’s GitHub Release Page, as they are still testing some features.\n\n\nYou will then be prompted to select the location you want to save the installer to. We will generally save this to either Downloads or Desktop to make finding it easier.\n\n\n\nOnce the download is complete, double click on the installer, and again accept the license agreement.\n\n\n\nGenerally, Positron will be store its software folder under Program Files.\n\n\n\nNext up, accept the default options for the following screens\n\n\n\n\n\n\nAnd finally, click Install.\n\n\n\n \n\nIf all goes well, you should then see the installation success page." }, { - "objectID": "course/02_FilePaths/slides.html#conditionals", - "href": "course/02_FilePaths/slides.html#conditionals", - "title": "02 - File Paths", - "section": "Conditionals", - "text": "Conditionals\n\n\n\n\n\n\n\n\n.\n\n\nOne useful thing is that within R, we can set conditions on whether something is carried out. The most typical conditional you will encounter are the “If” statements. They typically take a form that resembles the following.\n\n\n\n\n\n\n\nNeedCoffee <- TRUE\n\nif (NeedCoffee){\n print(\"Take a break\")\n}" + "objectID": "course/01_InstallingRPackages/slides.html#set-up", + "href": "course/01_InstallingRPackages/slides.html#set-up", + "title": "01 - Installing R Packages", + "section": "Set Up", + "text": "Set Up\nAlright, with the background out of the way, let’s get started!\n\n\n\n\n\n\n\nImportant\n\n\nPlease make sure to sync your forked version of the CytometryInR repository, and pull any changes to your local computer’s CytometryInR project folder so that you have the most recent version of the code and data available.\n\n\n\n\n\n\n\n\n\n\n\nWarning\n\n\nPlease remember to always copy over the new material from your local CytometryInR folder to a separate Project Folder that you created and named (ex. “Week_01” or “MyLearningFolder”, etc.). This will ensure any edits you make to the files do not affect your ability to bring in next week’s materials to the CytometryInR folder" }, { - "objectID": "course/02_FilePaths/slides.html#conditionals-in-practice", - "href": "course/02_FilePaths/slides.html#conditionals-in-practice", - "title": "02 - File Paths", - "section": "Conditionals in practice", - "text": "Conditionals in practice\n\n\n\n\n\n\n\n\n.\n\n\nFirst off, let’s write a conditional to check if there is a target3 folder within data.\n\n\n\n\n\n\n\nfiles_present <- list.files(\"data\", full.names=FALSE, recursive=FALSE)\nfiles_present" + "objectID": "course/01_InstallingRPackages/slides.html#checking-for-loaded-packages", + "href": "course/01_InstallingRPackages/slides.html#checking-for-loaded-packages", + "title": "01 - Installing R Packages", + "section": "Checking for Loaded Packages", + "text": "Checking for Loaded Packages\n\n\n\n\n\n\n\n\n.\n\n\nFor the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active." }, { - "objectID": "course/02_FilePaths/slides.html#copying-files", - "href": "course/02_FilePaths/slides.html#copying-files", - "title": "02 - File Paths", - "section": "Copying Files", - "text": "Copying Files\n\n\n\n\n\n\n\n\n.\n\n\nTo copy files to another folder location, we use the file.copy() function. It has two arguments that we will be working with, from being the .fcs files, and to being the folder location we wish to transfer them to. If we tried using them as we currently have them:\n\n\n\n\n\n\n\n# Variable Infants containing 4 .fcs file names\n\nfile.copy(from=Infants, to=FolderTarget3)" + "objectID": "course/01_InstallingRPackages/slides.html#installing-from-cran", + "href": "course/01_InstallingRPackages/slides.html#installing-from-cran", + "title": "01 - Installing R Packages", + "section": "Installing from CRAN", + "text": "Installing from CRAN\n\n\n\n\n\n\n\n\n.\n\n\nWe will start by installing R packages that are part of the CRAN repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository.\nThese include the tidyverse packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today." }, { - "objectID": "course/02_FilePaths/slides.html#removing-files.", - "href": "course/02_FilePaths/slides.html#removing-files.", - "title": "02 - File Paths", - "section": "Removing files.", - "text": "Removing files.\n\n\n\n\n\n\n\n\n.\n\n\nJust like we can add files via R, we can also remove them. However, when we remove them via this route, they are removed permanently, not sent to the recycle bin. We will revisit how later on in the course after you have gained additional experience with file.paths.\n\n\n\n\n\n\n\n?unlink()" + "objectID": "course/01_InstallingRPackages/slides.html#installing-from-bioconductor", + "href": "course/01_InstallingRPackages/slides.html#installing-from-bioconductor", + "title": "01 - Installing R Packages", + "section": "Installing from Bioconductor", + "text": "Installing from Bioconductor\n\n\n\n\n\n\n\n\n.\n\n\nBioconductor is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this link you can find it’s current flow and mass cytometry R packages.\nBioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different standards for acceptance than CRAN. They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems." }, { - "objectID": "course/02_FilePaths/slides.html#basename", - "href": "course/02_FilePaths/slides.html#basename", - "title": "02 - File Paths", - "section": "Basename", - "text": "Basename\n\n\n\n\n\n\n\n\n.\n\n\nIf we look at Infants with the full.names=TRUE, we see the additional pathing folder has been added, allowing us to successfully copy over the files.\n\n\n\n\n\n\n\nInfants" + "objectID": "course/01_InstallingRPackages/slides.html#install-from-github", + "href": "course/01_InstallingRPackages/slides.html#install-from-github", + "title": "01 - Installing R Packages", + "section": "Install from GitHub", + "text": "Install from GitHub\n\n\n\n\n\n\n\n\n.\n\n\nIn addition to the CRAN and Bioconductor repositories, individual R packages can also be found on GitHub hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to CRAN or Bioconductor) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all." }, { - "objectID": "course/02_FilePaths/slides.html#recursive", - "href": "course/02_FilePaths/slides.html#recursive", - "title": "02 - File Paths", - "section": "Recursive", - "text": "Recursive\n\n\n\n\n\n\n\n\n.\n\n\nAnd finally that we have created additional nested folders and populated them with fcs files, let’s see what setting list.files() recursive argument to TRUE\n\n\n\n\n\n\n\nall_files_present <- list.files(full.names=TRUE, recursive=TRUE)\nall_files_present" + "objectID": "course/01_InstallingRPackages/slides.html#troubleshooting-install-errors", + "href": "course/01_InstallingRPackages/slides.html#troubleshooting-install-errors", + "title": "01 - Installing R Packages", + "section": "Troubleshooting Install Errors", + "text": "Troubleshooting Install Errors\n\n\n\n\n\n\n\n\n.\n\n\nWe have now installed three R packages, dplyr, PeacoQC, and flowSpectrum. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies.\nWhen encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below." }, { - "objectID": "course/02_FilePaths/slides.html#saving-changes-to-version-control", - "href": "course/02_FilePaths/slides.html#saving-changes-to-version-control", - "title": "02 - File Paths", - "section": "Saving changes to Version Control", - "text": "Saving changes to Version Control\n\n\n\n\n\n\n\n\n.\n\n\nAnd as is good practice, to maintain version control, let’s stage all the files and folders we created today within the Week2 Project Folder, write a commit message, and send these files back to GitHub until they are needed again next time." + "objectID": "course/01_InstallingRPackages/slides.html#installing-specific-package-versions", + "href": "course/01_InstallingRPackages/slides.html#installing-specific-package-versions", + "title": "01 - Installing R Packages", + "section": "Installing Specific-Package Versions", + "text": "Installing Specific-Package Versions\n\n\n\n\n\n\n\n\n.\n\n\nWhile we may be tempted to think of R packages as static, they change quite often, as their develipers add new features, fix bugs, etc. To help keep track of these changes (essential for reproducibility and replicability), R packages have version numbers.\nWhen we run sessionInfo(), we can see an example of this, with the version number appearing after the package name.\n\n\n\n\n\n\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] PeacoQC_1.20.0 BiocManager_1.30.27\n\nloaded via a namespace (and not attached):\n [1] generics_0.1.4 shape_1.4.6.1 digest_0.6.39 \n [4] magrittr_2.0.4 evaluate_1.0.5 grid_4.5.2 \n [7] RColorBrewer_1.1-3 iterators_1.0.14 circlize_0.4.17 \n[10] fastmap_1.2.0 foreach_1.5.2 doParallel_1.0.17 \n[13] jsonlite_2.0.0 graph_1.88.1 GlobalOptions_0.1.3 \n[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1 scales_1.4.0 \n[19] XML_3.99-0.20 Rgraphviz_2.54.0 codetools_0.2-20 \n[22] cli_3.6.5 RProtoBufLib_2.22.0 rlang_1.1.7 \n[25] crayon_1.5.3 Biobase_2.70.0 yaml_2.3.12 \n[28] otel_0.2.0 cytolib_2.22.0 ncdfFlow_2.56.0 \n[31] tools_4.5.2 parallel_4.5.2 dplyr_1.2.0 \n[34] colorspace_2.1-2 ggplot2_4.0.2 GetoptLong_1.1.0 \n[37] BiocGenerics_0.56.0 vctrs_0.7.1 R6_2.6.1 \n[40] png_0.1-8 matrixStats_1.5.0 stats4_4.5.2 \n[43] lifecycle_1.0.5 flowCore_2.22.1 S4Vectors_0.48.0 \n[46] IRanges_2.44.0 clue_0.3-66 cluster_2.1.8.1 \n[49] pkgconfig_2.0.3 pillar_1.11.1 gtable_0.3.6 \n[52] data.table_1.18.2.1 glue_1.8.0 xfun_0.56 \n[55] tibble_3.3.1 tidyselect_1.2.1 knitr_1.51 \n[58] farver_2.1.2 rjson_0.2.23 htmltools_0.5.9 \n[61] rmarkdown_2.30 compiler_4.5.2 S7_0.2.1" }, { - "objectID": "course/02_FilePaths/index.html", - "href": "course/02_FilePaths/index.html", - "title": "02 - File Paths", + "objectID": "course/01_InstallingRPackages/slides.html#documentation-and-websites", + "href": "course/01_InstallingRPackages/slides.html#documentation-and-websites", + "title": "01 - Installing R Packages", + "section": "Documentation and Websites", + "text": "Documentation and Websites\n\n\n\n\n\n\n\n\n.\n\n\nWe have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package.\nFor CRAN-based packages, we can start off by searching for the package name. So, in the case of dplyr" + }, + { + "objectID": "course/01_InstallingRPackages/index.html", + "href": "course/01_InstallingRPackages/index.html", + "title": "01 - Installing R Packages", "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here\nWelcome to the second week of Cytometry in R! This week we will learn about file.path, namely, how to communicate to our computer (and R) where various files are stored.", + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here\nWelcome to the first week of Cytometry in R! This week we will be diving into how R packages work, and the how to go about installing them.\nBefore getting started, please make sure you have completed the creating a GitHub and Workstation Setup walk-throughs, since we will begin where they left off once the required software was successfully installed.", "crumbs": [ "About", "Intro to R", - "02 - File Paths" + "01 - Installing R Packages" ] }, { - "objectID": "course/02_FilePaths/index.html#set-up", - "href": "course/02_FilePaths/index.html#set-up", - "title": "02 - File Paths", + "objectID": "course/01_InstallingRPackages/index.html#set-up", + "href": "course/01_InstallingRPackages/index.html#set-up", + "title": "01 - Installing R Packages", "section": "Set Up", - "text": "Set Up\nBefore we begin, let’s make sure you get the data needed for today transferred to your local computer, and then get the .fcs files copied over from there to your own working project folder. This is the process you will repeat each week throughout the course.\n\nNew Repository\nFirst off, login to your GitHub account. Once there, you will select the options to create a new repository (similar to what you did during Using GitHub)\n\n\n\nFor this week, let’s set this new repository up as a private repository, and call it Week2. This will keep things consistent with the file.paths we will be showing in the examples.\n\n\n\nOnce the new repository has been created, copy the URL.\n\n\n\nNext, open up Positron, set the interpreter to use R, and then select the option to bring in a “New Folder from Git”.\n\n\n\nPaste in your new repository’s url. Additionally, if you want to match file.paths shown in the examples, set your storage location to your local Documents folder (please note the start of the file.path will look differently depending on whether you are on Windows, MacOS, or Linux).\n\n\n\nYour new repository will then be imported from GitHub. Once this is done, create two subfolders (data and images) and a new .qmd file (naming it filepaths.qmd).\n\n\n\n\n\nSync\nWith this done, return to GitHub and open your forked version of the CytometryInR course folder. If you haven’t yet done so, click on sync to bring in this week’s code and datasets.\n\n\n\nReturning to Positron, you will need to switch Project Folders, switching from Week2 over to CytometryInR.\n\n\n\n\n\nPull\nOnce CytometryInR project folder has opened, you will need to pull in the new data from GitHub to your local computer.\n\n\n\n\n\nCopy Files to Week2\nOnce this is done, you will see within the course folder, containing this weeks folder (02_FilePaths). Within it there is a data folder with .fcs files. To avoid causing conflicts when bringing in next week’s materials, you will want to manually copy over these .fcs files (via your File Explorer) to the data folder within your “Week2” Project Folder.\n\n\n\n\n\nCommit and Push\nWhen you reopen your Week2 project folder in Positron, you should now be able to see the .fcs files within the data folder. Next, from the action bar on the far left, select the Source Control tab. Stage all the changes (as was done in Using Git), and write a short commit message.\n\n\n\nWith these files now being tracked by version control, push (ie. send) your changes to GitHub so that they are remotely backed up.\n\n\n\nAnd with this setup complete, you are now ready to proceed. Remember, run code and write notes in your working project folder (Week2 or otherwise named) to avoid conflicts next week in the CytometryInR folder when you are trying to bring in the Week #3 code and datasets.", + "text": "Set Up\nAlright, with the background out of the way, let’s get started!\n\n\n\n\n\n\nImportant\n\n\n\nPlease make sure to sync your forked version of the CytometryInR repository, and pull any changes to your local computer’s CytometryInR project folder so that you have the most recent version of the code and data available.\n\n\n\n\n\n\n\n\nWarning\n\n\n\nPlease remember to always copy over the new material from your local CytometryInR folder to a separate Project Folder that you created and named (ex. “Week_01” or “MyLearningFolder”, etc.). This will ensure any edits you make to the files do not affect your ability to bring in next week’s materials to the CytometryInR folder\n\n\n\n\nAfter pulling the new data and code locally, open CytometryInR, open the course folder, and open the 01_InstallingRPackages folder. From here, copy the index.qmd file to your own working Project Folder (ex. Week_01) where you can work on it without causing any conflicts. Then return to Positron and open up your working project folder (ex. Week_01).\n\n\n\nNext up, within Positron, let’s make sure to select R as the coding language being used for this session.\n\n\n\nNow that R is running within Positron, the console (lower portion of the screenn) is now able to run (ie. execute) any R code that is sent to it.", "crumbs": [ "About", "Intro to R", - "02 - File Paths" + "01 - Installing R Packages" ] }, { - "objectID": "course/02_FilePaths/index.html#working-directory", - "href": "course/02_FilePaths/index.html#working-directory", - "title": "02 - File Paths", - "section": "Working Directory", - "text": "Working Directory\nNow that we are back in our Week2 folder, let’s start by seeing our current location similarly to how our computer perceives it.\nWe will use getwd() function (ie. get working directory) to return the location of the folder we are currently inside of. For example, when getwd() is run within my Week2 project folder, I see the following location\n\ngetwd()\n\n\nThis returns a file path. The final location (Week2 in this case) is the Working Directory. Your computer when working in R will be descern other locations in relation to this directory.", + "objectID": "course/01_InstallingRPackages/index.html#checking-for-loaded-packages", + "href": "course/01_InstallingRPackages/index.html#checking-for-loaded-packages", + "title": "01 - Installing R Packages", + "section": "Checking for Loaded Packages", + "text": "Checking for Loaded Packages\nFor the contents (ie. the functions) of an R package to be available for your computer to use, they must first be activated (ie. loaded) into your local environment. We will first learn how to check what R packages are currently active.\n\n\n\nAccessing Help Documentation\nWithin your own index.qmd (or a new .qmd file that you created), type out/copy-paste the following sessionInfo() function:\n\nsessionInfo()\n\n\n\nIf you hover over the line of code within Positron, you will glimpse the help file for the particular function you are hovering over.\n\n\n\nIn this case, we can see the help documentation corresponding for sessionInfo(). Beyond hovering over the function, this can also be accessed by adding a ? directly in front of the function, and then running that line of code.\n\n?sessionInfo()\n\n\n\n\nWhen executed, the function’s help file documentation will open up within the Help tab in the secondary side bar on the right-side of the screen. Glancing at the top of the page we can see the name of the package that contains the sessionInfo() function ({utils}). Scrolling down the help page past all the documentation, we can see a link to the index page.\n\n\n\nAfter clicking, the Help tab switches from viewing the documentation for the sessionInfo() function, to showing all the functions within the utils package. Most R packages contain help documentation, so this process can be adapted to find out additional information about what a function does, and what arguments are needed to produce customized outputs.\n\n\n\n\n\nsessionInfo()\nWithin your .qmd file, let’s go ahead and run the following code-block:\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] BiocStyle_2.38.0\n\nloaded via a namespace (and not attached):\n [1] htmlwidgets_1.6.4 BiocManager_1.30.27 compiler_4.5.2 \n [4] fastmap_1.2.0 cli_3.6.5 tools_4.5.2 \n [7] htmltools_0.5.9 otel_0.2.0 yaml_2.3.12 \n[10] rmarkdown_2.30 knitr_1.51 jsonlite_2.0.0 \n[13] xfun_0.56 digest_0.6.39 rlang_1.1.7 \n[16] evaluate_1.0.5 \n\n\n\n\nThe outputs that get returned by sessionInfo() will vary a bit depending on your computer’s operating system, and the version of R you have installed.\nFor today, let’s focus on the last two elements of the output:\n\n\n\nThe R software itself is made up of several base R packages, that are loaded automatically. These contain everything you need to read, write and run R code on your computer. You can see these packages are the stats, graphics, grDevices, utils, datasets, methods and base packages.\nAs we install additional R packages and load them using the library() function throughout this session, sporadically re-run sessionInfo() to see how this list of R packages changes.", "crumbs": [ "About", "Intro to R", - "02 - File Paths" + "01 - Installing R Packages" ] }, { - "objectID": "course/02_FilePaths/index.html#directories", - "href": "course/02_FilePaths/index.html#directories", - "title": "02 - File Paths", - "section": "Directories", - "text": "Directories\nWithin this working directory, we have a variety of project folders and files related to the course. We can see the folders that are present using the list.dirs() function.\n\nlist.dirs(path=\".\", full.names=FALSE, recursive=FALSE)\n\n\nWithin this list.dirs() function, we are specifying two arguments with which we will be working with later today, full.names and recursive. For now, lets set their arguments to FALSE, which means they conditions they implement are inactive (turned off).\n\n\nThe path argument is currently set to “.”, which is a stand-in for the present directory. In R, if an argument is not specified directly, it is inferred based on an order of expected arguments. Thus, if not present, we could still get the same output as seen before.\n\nlist.dirs(full.names=FALSE, recursive=FALSE)\n\n\n\n\nWithin Positron, in addition to visible folders, we also have hidden folders (denoted by the “.” in front of the folder name when using list.dirs()). In the case of one of our course website folders, we can see a “.quarto” folder shown in a lighter gray . The “.git” folder we saw from list.dirs() is typically hidden when viewing from Positron.\n\nIn the case of Week2, the two not-hidden folders we created are listed. We will see how to navigate these in a second.", + "objectID": "course/01_InstallingRPackages/index.html#installing-from-cran", + "href": "course/01_InstallingRPackages/index.html#installing-from-cran", + "title": "01 - Installing R Packages", + "section": "Installing from CRAN", + "text": "Installing from CRAN\nWe will start by installing R packages that are part of the CRAN repository. This is the main R package repository, being part of the broader R software project. In the context of this course, R packages that work primarily with general data structure (rows, columns, matrices, etc.) or visualizations will predominantly be found within this repository.\nThese include the tidyverse packages. These packages have collectively made R easier to use by smoothing out some of the rough edges of base R, which is why R has seen major growth within the last decade. We will be installing several of these R packages today.\n\n\n\ndplyr\nOur first R package we will install during this session is the dplyr package. Since it is hosted on the CRAN repository, to install it, we will need to use the CRAN-specific installation function install.packages().\n\n?install.packages()\n\n\n\n\nFor the install.packages() function, we place within the () the name of the R package from CRAN that we wish to install.\n\ninstall.packages(\"dplyr\")\n\n\n\n\n\n\n\n\n\nTip\n\n\n\nA usual struggle point for beginners is that install.packages() requires ” ” to be placed around the package name. Forgetting them results in the error that we see below.\n\n\n\ninstall.packages(dplyr)\n\nError:\n! object 'dplyr' not found\n\n\n\n\n\ninstall.packages(\"dplyr\")\n\nGo ahead and click on “Run Cell” next to your code-block, to install the dplyr R package.\n\n\nWhen a package starts to install, you will see your console start to display text resembling that seen in the image below (varying a bit depending on your computers operating system).\n\n\n\nWithin this opening scrawl, you will see the location on your computer the R package is being installed to, as well as the file location for the R package being retrieved on CRAN.\nIf the package is successfully located, your computer will proceed to first download, then unpack (ie. unzip) it, before attempting to install to the target folder.\n\n\n\nThe final steps of the installation process involved various steps to verify everything was copied successfully, the help documentation assembled, and that the R package is capable of being loaded. If this is the case, you will see the “Done” line appear, as well as a mention where the original downloaded source package files has been stashed (usually a temp folder).\n\n\n\n\nAttaching packages via library()\nIf an R package has been installed successfully, we are now able to load it (ie. make it’s functions available) to our local environment using the library() function.\n\n?library()\n\n\n\nUnlike install.packages(), where we needed “” around the package name, the library() function does not require “” around the package name. Let’s go ahead and load in dplyr, making its respective functions to our local environment.\n\nlibrary(dplyr)\n\n\nAttaching package: 'dplyr'\n\n\nThe following objects are masked from 'package:stats':\n\n filter, lag\n\n\nThe following objects are masked from 'package:base':\n\n intersect, setdiff, setequal, union\n\n\n\n\nFrom the output, we can see that dplyr has been attached. There are also a couple functions within dplyr that have identical names to functions within the stats and base packages. To avoid confusion, these 6 functions are masked, which is why we get the additional messages.\nWith dplyr now loaded via the library() call, let’s check sessionInfo() to see what has changed.\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] dplyr_1.2.0 BiocStyle_2.38.0\n\nloaded via a namespace (and not attached):\n [1] digest_0.6.39 R6_2.6.1 fastmap_1.2.0 \n [4] tidyselect_1.2.1 xfun_0.56 magrittr_2.0.4 \n [7] glue_1.8.0 tibble_3.3.1 knitr_1.51 \n[10] pkgconfig_2.0.3 htmltools_0.5.9 generics_0.1.4 \n[13] rmarkdown_2.30 lifecycle_1.0.5 cli_3.6.5 \n[16] vctrs_0.7.1 compiler_4.5.2 tools_4.5.2 \n[19] evaluate_1.0.5 pillar_1.11.1 yaml_2.3.12 \n[22] otel_0.2.0 BiocManager_1.30.27 rlang_1.1.7 \n[25] jsonlite_2.0.0 htmlwidgets_1.6.4 \n\n\n\n\nSimilar to what was seen for the base R packages, dplyr is now attached. This means we should theoretically now have access to all its functions. We can verify this by seeing if we can look up the dplyr packages select() function and it’s respective help page.\n\n?select\n\n\n\n\nSince its parent package has been attached to our local environment (via the library() call), we can see dplyr functions appear as suggestions as we begin to type.\nBy contrast, is we check for the ggplot() function from the ggplot2 package (which we haven’t yet installed or attached via library()), no suggestions will pop up.\n\n?ggplot\n\nNo documentation for 'ggplot' in specified packages and libraries:\nyou could try '??ggplot'\n\n\n\n\nBeyond individual functions, some R packages also have help landing pages, that can be similarly accessed by adding a ? in front of the package name:\n\n\n\n\n\nUnattaching\nSo far, we have installed an R package, and then attached it (via library()). How would we reverse these steps?\nWell, to unload it from the local environment, there are a couple options. You could of course simply shut down Positron. The local environment only exist in context of when you open and close the session, which closing the program will do. All previously loaded R packages will be unattached, which is why when you start a new session you will need to load in all packages you plan on using via library().\nAlternatively, although less used, you could detach() it via your console:\n\ndetach(\"package:dplyr\", unload=TRUE)\n\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] BiocStyle_2.38.0\n\nloaded via a namespace (and not attached):\n [1] digest_0.6.39 R6_2.6.1 fastmap_1.2.0 \n [4] tidyselect_1.2.1 xfun_0.56 magrittr_2.0.4 \n [7] glue_1.8.0 tibble_3.3.1 knitr_1.51 \n[10] pkgconfig_2.0.3 htmltools_0.5.9 generics_0.1.4 \n[13] rmarkdown_2.30 lifecycle_1.0.5 cli_3.6.5 \n[16] vctrs_0.7.1 compiler_4.5.2 tools_4.5.2 \n[19] evaluate_1.0.5 pillar_1.11.1 yaml_2.3.12 \n[22] otel_0.2.0 BiocManager_1.30.27 rlang_1.1.7 \n[25] jsonlite_2.0.0 htmlwidgets_1.6.4 \n\n\n\n\nLooking at the sessionInfo() output, dplyr is no longer attached to the local environment. Consequently, if we try to once again look for the documentation, no information will be retrieved.\n\n?dplyr\n\nNo documentation for 'dplyr' in specified packages and libraries:\nyou could try '??dplyr'\n\n\n\n\nThere is a workaround however, if we want to access functions from an unloaded R package. We can specify the R package’s name, followed by two :, and then the function name. The :: conveys the context to your computer that the package is present, but may not be attached.\n\n?dplyr::select()\n\nThis particular use case can be useful if we want to run a particular function, but not load in all a packages functions (which may have identical function names to other R packages we are using and cause some conflicts).\n\n\n\n\nRemoving Packages\nJust as we can install an R package, we can also uninstall an R package (although doing so is rare, most often when encountering package dependency conflict). To do so, we would use the remove.packages() function.\n\n?remove.packages()\n\n\nremove.packages(\"dplyr\")\n\nThis results in the package being removed entirely from our computer. We would then need to reinstall it if needed in the future.\n\n\n\n\nCommon Issues\nAs previously mentioned, CRAN is the main repository for R packages. But what if we tried to install an R package that is only found on Bioconductor or via GitHub using the install.packages() function?\nTo see what occurs, let’s try installing the PeacoQC package (which is found on Bioconductor).\n\ninstall.packages(\"PeacoQC\")\n\nInstalling package into '/home/david/R/x86_64-pc-linux-gnu-library/4.5'\n(as 'lib' is unspecified)\n\n\nWarning: package 'PeacoQC' is not available for this version of R\n\nA version of this package for your version of R might be available elsewhere,\nsee the ideas at\nhttps://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages\n\n\n\n\nAs you can see, the initial warning message suggest that PeacoQC is not available for your version of R. When I first started trying to learn R on my own during COVID, this particular message was the bane of my existence and I couldn’t figure out what was going on.\nThis is just a default warning message, that would apply for both a package having a version mismatch, but also shown when trying to install packages that are not found on CRAN.", "crumbs": [ "About", "Intro to R", - "02 - File Paths" + "01 - Installing R Packages" ] }, { - "objectID": "course/02_FilePaths/index.html#variables", - "href": "course/02_FilePaths/index.html#variables", - "title": "02 - File Paths", - "section": "Variables", - "text": "Variables\nBefore exploring file paths, we need to have some basic R code knowledge that we can use to work with them. Within R, we have the ability to assign particular values (be they character strings, numbers or logicals) to objects (ie. variables) that can be used when called upon later.\nFor example:\n\nWhatDayDidIWriteThis <- \"Saturday\"\n\nIn this case, the variable name is what the assignment arrow (“<-”) is pointing at. In this case, WhatDayDidIWriteThis\n\n\nWhen we run this, we create a variable, that will appear within the right-sidebar.\n\nWhatDayDidIWriteThis <- \"Saturday\"\n\n\n\n\nThese variables can subsequently be retrieved by printing (ie. running) the name of the variable\n\nWhatDayDidIWriteThis \n\n[1] \"Saturday\"\n\n\n\n\nYou can create variables with almost any name you can think of\n\nTopSecretMeetingDay <- \"Saturday\"\n\n\n\nWith a few exceptions. R doesn’t play well with spaces:\n\nTop Secret Meeting Day <- \"Saturday\"\n\nError in parse(text = input): <text>:1:5: unexpected symbol\n1: Top Secret\n ^\n\n\n\n\nBut does play well with underscores:\n\nTop_Secret_Meeting_Day <- \"Saturday\"\n\n\n\nThe above (with individual words separated by _) is collectively known as snake case. The alternate way to help delineate variable names is “camelCase”, with first letter of each word being capitalized (seen in the previous example).\n\n\n\n\nTopSecretMeetingDay\n\n[1] \"Saturday\"\n\n\n\n\nYou can overwrite a Variable name by assigning a different value to it:\n\nTopSecretMeetingDay <- \"Monday\"\n\n\nTopSecretMeetingDay\n\n[1] \"Monday\"\n\n\n\n\nYou can also remove individual variables via the rm function\n\nrm(Top_Secret_Meeting_Day)\n\n\n\nOr if trying to remove all, via the right sidebar\n\n\n\nIn the prior case, we are creating a variable that is a “string” of character values, due to our use of “” around the word. We can see this when we use the str() function.\n\nFluorophores <- \"FITC\"\nstr(Fluorophores)\n\n chr \"FITC\"\n\n\nThe “chr” in front denotating that Fluorophores contains a character string.\n\n\nThis could also be retrieved using the class() function.\n\nclass(Fluorophores)\n\n[1] \"character\"\n\n\n\n\nAlternatively, we could assign a numeric value to a variable\n\nFluorophores <- 29\nstr(Fluorophores)\n\n num 29\n\n\nWhich returns “num”, ie. numeric.\n\n\nWe can also specify a logical (ie. True or FALSE) to a particular object\n\nIsPerCPCy5AGoodFluorophore <- FALSE\nstr(IsPerCPCy5AGoodFluorophore)\n\n logi FALSE\n\n\nWhich returns logi in front, denoting this variable contains a logical value.\n\n\nLast week, when we were installing dplyr, the reason that installation failed was install.packages() expects a character string. However, when we left off the ““, it looked within our local environments created variables for the dplyr variable, couldn’t find it, and thus failed.\nWe could of course, have assigned a character value to a variable name, and then used that variable name, which would have worked.\n\nPackageToInstall <- \"dplyr\"\n\ninstall.packages(PackageToInstall)", + "objectID": "course/01_InstallingRPackages/index.html#installing-from-bioconductor", + "href": "course/01_InstallingRPackages/index.html#installing-from-bioconductor", + "title": "01 - Installing R Packages", + "section": "Installing from Bioconductor", + "text": "Installing from Bioconductor\nBioconductor is the second R package repository we will be working with throughout the course. While it contains far fewer packages than CRAN, it contains packages that are primarily used by the biomedical sciences. Following this link you can find it’s current flow and mass cytometry R packages.\nBioconductor R packages differ from CRAN R packages in a couple of ways. Bioconductor has different standards for acceptance than CRAN. They usually contain interoperable object-types, put more effort into documentation and continous testing to ensure that the R package remains functional across operating systems.\n\n\nTo install an R package that is located on Bioconductor, we first need to install the BiocManager package from CRAN. This package will allow us to install Bioconductor packages from their respective repository.\n\ninstall.packages(\"BiocManager\")\n\n\n\nOnce BiocManager is installed, we can attach it to our local environment using the library() function\n\nlibrary(BiocManager)\n\n\n\nWhen loaded, you will see an output showing the current Bioconductor and R versions.\nWe can then use BiocManager’s install() function to go back and install PeacoQC().\n\n\n\n\n\n\nTip\n\n\n\nAs always, don’t forget the “” when running an install() command.\n\n\n\n?install()\n\n\ninstall(\"PeacoQC\")\n\n\n\nWe see a similar opening sequence of installation steps as what we saw when installing the dplyr package from CRAN. However, in this case, several package dependencies (rjson, GlobalOptions, etc.) are present. Consequently, you can see these packages are also being downloaded from their respective repositories (either CRAN or Bioconductor), then unzipped and assembled before PeacoQC undergoes installation.\n\n\n\n\n\n\nNote\n\n\n\nBehind the scenes, within an R package, what package dependencies need to be installed are specified through the Description and Namespace files. If a package name is removed from these files, it will not be installed during the installation process\n\n\n\n\n\nWithin the scrawl of installation outputs, we can see individual dependencies undergoing installation similar to what we saw with dplyr, with a “Done (packagename)” being printed upon successful installation.\n\n\n\nThis process continues for each dependency being installed.\n\n\n\nAnd finally, once all the dependencies are installed, PeacoQC starts to install.\n\n\n\nOccasionally, during installation, you will see a pop-up windown like this one in the console. This let’s you know that some of the package dependencies have newer updated versions that are available to download. We are prompted to select between updating all, some or none. You will need to specify via the console how you want to proceed, by typing and entering one of the suggested options [a/s/n].\n\n\n\nAlternatively you may encounter a pop-up that resembles this one. Unlike the a/s/n output, we would need to provide a number for our intended choice. In this case, I went ahead and skipped all updates by typing 3 into the console, then hitting enter.\n\n\n\nGenerally, it’s okay to update if you have the time. Updates generally consist of minor improvements or bug fixes, that shouldn’t cause major issues. If you are short on time, you can go ahead and select skip the update by entering the value (n) for the none option.\n\n\n\nWith PeacoQC has been installed, we can load it via the library() call\n\n\n\n\n\n\nTip\n\n\n\nRemeber, library() doesn’t require ” ”\n\n\n\nlibrary(PeacoQC)\n\n\n\nAnd we can check to see if it has been attached to the local environment\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] PeacoQC_1.20.0 BiocManager_1.30.27 BiocStyle_2.38.0 \n\nloaded via a namespace (and not attached):\n [1] generics_0.1.4 shape_1.4.6.1 digest_0.6.39 \n [4] magrittr_2.0.4 evaluate_1.0.5 grid_4.5.2 \n [7] RColorBrewer_1.1-3 iterators_1.0.14 circlize_0.4.17 \n[10] fastmap_1.2.0 foreach_1.5.2 doParallel_1.0.17 \n[13] jsonlite_2.0.0 graph_1.88.1 GlobalOptions_0.1.3 \n[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1 scales_1.4.0 \n[19] XML_3.99-0.20 Rgraphviz_2.54.0 codetools_0.2-20 \n[22] cli_3.6.5 RProtoBufLib_2.22.0 rlang_1.1.7 \n[25] crayon_1.5.3 Biobase_2.70.0 yaml_2.3.12 \n[28] otel_0.2.0 cytolib_2.22.0 ncdfFlow_2.56.0 \n[31] tools_4.5.2 parallel_4.5.2 dplyr_1.2.0 \n[34] colorspace_2.1-2 ggplot2_4.0.2 GetoptLong_1.1.0 \n[37] BiocGenerics_0.56.0 vctrs_0.7.1 R6_2.6.1 \n[40] png_0.1-8 matrixStats_1.5.0 stats4_4.5.2 \n[43] lifecycle_1.0.5 flowCore_2.22.1 S4Vectors_0.48.0 \n[46] htmlwidgets_1.6.4 IRanges_2.44.0 clue_0.3-66 \n[49] cluster_2.1.8.1 pkgconfig_2.0.3 pillar_1.11.1 \n[52] gtable_0.3.6 data.table_1.18.2.1 glue_1.8.0 \n[55] xfun_0.56 tibble_3.3.1 tidyselect_1.2.1 \n[58] knitr_1.51 farver_2.1.2 rjson_0.2.23 \n[61] htmltools_0.5.9 rmarkdown_2.30 compiler_4.5.2 \n[64] S7_0.2.1 \n\n\n\n\nAs you may have noticed, the section of loaded via namespace (but not attached) packages has grown larger. These packages are dependencies for the attached packages (dplyr, BiocManager and PeacoQC). Since the functions within these dependencies are only used selectively by the attached packages, they do not need to be active within the local environment.\n\n\n\nTo see what packages are installed (but not yet loaded), we can use the installed.packages() function to return a list of R packages for your computer.\n\ninstalled.packages()", "crumbs": [ "About", "Intro to R", - "02 - File Paths" + "01 - Installing R Packages" ] }, { - "objectID": "course/02_FilePaths/index.html#indexing", - "href": "course/02_FilePaths/index.html#indexing", - "title": "02 - File Paths", - "section": "Indexing", - "text": "Indexing\nNot all variables contain single objects.\nFor example, we can modify Fluorophores and add additional entries:\n\nFluorophores <- c(\"BV421\", \"FITC\", \"PE\", \"APC\")\nstr(Fluorophores)\n\n chr [1:4] \"BV421\" \"FITC\" \"PE\" \"APC\"\n\n\nThe c stands for concatenate. It concatenates the objects into a larger object, known as a vector.\nIn this case, you notice in addition to the specification the values are characters, we get a [1:4], denoting four objects are present.\n\n\nWe can similarly retrieve this information using the length() function\n\nlength(Fluorophores)\n\n[1] 4\n\n\n\n\nWhen multiple objects are present, we can specify them individidually by providing their index number within square brackets [].\n\nFluorophores[1]\n\n[1] \"BV421\"\n\n\n\n\n\nFluorophores[3]\n\n[1] \"PE\"\n\n\n\n\nOr specify in sequence using a colon (:)\n\nFluorophores[3:4]\n\n[1] \"PE\" \"APC\"\n\n\n\n\nOr if not adjacent, reusing c within the square brackets\n\nFluorophores[c(1,4)]\n\n[1] \"BV421\" \"APC\" \n\n\n\n\nWe will revisit these concepts throughout the course, with what we have covered today, this will help us create file.paths and select fcs files that we want to work with via index number.", + "objectID": "course/01_InstallingRPackages/index.html#install-from-github", + "href": "course/01_InstallingRPackages/index.html#install-from-github", + "title": "01 - Installing R Packages", + "section": "Install from GitHub", + "text": "Install from GitHub\nIn addition to the CRAN and Bioconductor repositories, individual R packages can also be found on GitHub hosted on their respective developers GitHub accounts. Newer packages that are still being worked on (often in the process of submission to CRAN or Bioconductor) can be found here, as well as those where the author decided not to bother with a review process, and just made the packages immediately available, warts and all.\n\n\nWhile many gems of R packages can be found on GitHub, there are also a bunch of R packages that due to deprecation since when they were published and released have stopped working. This is often the case for R packages that are not maintained, which is why it’s useful to check the commits and issues pages to see when the last contribution occurred. We will take a closer look at how to do so later on.\n\n\nTo install packages from GitHub, you will need the remotes package, which can be found on CRAN.\n\n\n\n\n\n\nSpot Check #1\n\n\n\nTo install a package from CRAN, what function would you use? Click on the code-fold arrow below to reveal the answer.\n\n\n\n\nCode\ninstall.packages(\"remotes\")\n\n\n\n\nWith the remotes package now installed, we can attach it to our local environment.\n\n\n\n\n\n\nSpot Check #2\n\n\n\nWhat function would be used to do so?\n\n\n\n\nCode\nlibrary(remotes)\n\n\n\n\nAnd finally, we can use the install_github() function to download R packages from the invidual developers GitHub account.\n\n\n\n\n\n\nSpot Check #3\n\n\n\nHow would you look up the help documentation for this function?\n\n\n\n\nCode\n# Either by hovering over it within Positron or via\n\n?install_github()\n\n\n\n\nWe will be installing a small R package flowSpectrum for this example. It’s one of the packages created by Christopher Hall, whose small series of Flow Cytometry Data Analysis in R tutorials were immensely useful when I was first getting started learning R. flowSpectrum can be used to generate spectrum-style plots for spectral flow cytometry data.\n\n\n\nTo install an R package from GitHub, we first need the GitHub username (so hally166 in this case), which is followed by a “/”, and then the name of the package repository (so flowSpectrum in this case). Our code should consequently be:\n\ninstall_github(\"hally166/flowSpectrum\")\n\n\n\nWhen installing from GitHub, the opening installation scrawl will look different. Unlike R packages from CRAN or Bioconductor, which are usually shipped in an assembled binary format, R packages from GitHub start off as source code. So the first steps shown in the scrawl are the process of converting them to binary before proceeding.\nThis process of building R packages from source code is one of the reasons we needed to install Rtools (for Windows users) or Xcode Developer Tools (for MacOS) for this course. We will look at this topic in greater depth later in the course when we talk about creating R packages.", "crumbs": [ "About", "Intro to R", - "02 - File Paths" + "01 - Installing R Packages" ] }, { - "objectID": "course/02_FilePaths/index.html#listing-files", - "href": "course/02_FilePaths/index.html#listing-files", - "title": "02 - File Paths", - "section": "Listing Files", - "text": "Listing Files\nAfter this detour into variables and indexing, let’s return our focus to how to use these in context of file paths. Working from within our Week2 project folder, let’s see what directories (folders) are present\n\nlist.dirs(path=\".\", full.names=FALSE, recursive=FALSE)\n\n\n\n\nWe can also list any files that are present within our working directory using the list.files() function.\n\nlist.files()\n\n\nIn this case, in addition to our filepaths.qmd file, we can see the LICENSE and README files created when we set up the repository.\n\n\nWe can also specify a particular folder we want to show items present within by changing the path argument. For example, if we wanted to see the contents of the “data” folder\n\nlist.files(path=\"data\", full.names=FALSE, recursive=FALSE)\n\n\nWhich in this case returns the fcs files we copied over at the start of this lesson.\n\n\nIn this case, there are no folders under “data”. Let’s go ahead and create a new one, calling it target.", + "objectID": "course/01_InstallingRPackages/index.html#troubleshooting-install-errors", + "href": "course/01_InstallingRPackages/index.html#troubleshooting-install-errors", + "title": "01 - Installing R Packages", + "section": "Troubleshooting Install Errors", + "text": "Troubleshooting Install Errors\nWe have now installed three R packages, dplyr, PeacoQC, and flowSpectrum. In my case, I did not encounter any errors during the installation. However, sometimes a package installation will fail due to an error encountered during the installation process. This can be due to a number of reasons, ranging from a missing dependency, or an update that caused a conflict. While these can occur for CRAN or Bioconductor packages, they are more frequently seen for GitHub packages where the Description/Namespace files may not have been fully updated yet to install all the required dependencies.\nWhen encountering an error, start of by first reading through the message to see if you can parse any useful information about what package failed to install, and if it list the missing dependency packages name. The later was the case in the error message example shown below.\n\n\n\nIf you encounter an installation error this week, please take screenshots of the error message and post them to this Discussion. This will help us troubleshoot your installation, as well as provide additional examples of installation errors that will be used to update this section in the future.", "crumbs": [ "About", "Intro to R", - "02 - File Paths" + "01 - Installing R Packages" ] }, { - "objectID": "course/02_FilePaths/index.html#creating-directories", - "href": "course/02_FilePaths/index.html#creating-directories", - "title": "02 - File Paths", - "section": "Creating directories", - "text": "Creating directories\nAlternatively, we can also create a folder via R using the dir.create() function. Since we want it within data, we would modify the path accordingly\n\nNewFolderLocation <- file.path(\"data\", \"target2\")\n\ndir.create(path=NewFolderLocation)\n\n\n\n\nBefore continuing, let’s copy the first two .fcs files into both target and target2.\n\n\n\nGiven our working directory is set the top-level of the Week2 project folder, we can’t just check inside nested target folders directly. If we attempt to:\n\nlist.files(path=\"target\", full.names=FALSE, recursive=FALSE)\n\ncharacter(0)\n\n\n\n\nNo files are returned (ie, character(0)), since from our computers perspective, “target” doesn’t exist within the active working directory.\n\nfile.exists(\"target\")\n\n[1] FALSE\n\n\n\n\nOn the other hand, within it’s view, it knows that the data folder exist\n\nfile.exists(\"data\")\n\n\nSo here we encounter the first challenge when communicating to our computer where to search for and find files. We need to provide a file.path that incorporates the path of folders between where the computer is currently at (ie. the working directory) and the target file itself.", + "objectID": "course/01_InstallingRPackages/index.html#installing-specific-package-versions", + "href": "course/01_InstallingRPackages/index.html#installing-specific-package-versions", + "title": "01 - Installing R Packages", + "section": "Installing Specific-Package Versions", + "text": "Installing Specific-Package Versions\nWhile we may be tempted to think of R packages as static, they change quite often, as their develipers add new features, fix bugs, etc. To help keep track of these changes (essential for reproducibility and replicability), R packages have version numbers.\nWhen we run sessionInfo(), we can see an example of this, with the version number appearing after the package name.\n\nsessionInfo()\n\nR version 4.5.2 (2025-10-31)\nPlatform: x86_64-pc-linux-gnu\nRunning under: Debian GNU/Linux 13 (trixie)\n\nMatrix products: default\nBLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1 \nLAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0\n\nlocale:\n [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C \n [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 \n [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 \n [7] LC_PAPER=en_US.UTF-8 LC_NAME=C \n [9] LC_ADDRESS=C LC_TELEPHONE=C \n[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C \n\ntime zone: America/New_York\ntzcode source: system (glibc)\n\nattached base packages:\n[1] stats graphics grDevices utils datasets methods base \n\nother attached packages:\n[1] PeacoQC_1.20.0 BiocManager_1.30.27 BiocStyle_2.38.0 \n\nloaded via a namespace (and not attached):\n [1] generics_0.1.4 shape_1.4.6.1 digest_0.6.39 \n [4] magrittr_2.0.4 evaluate_1.0.5 grid_4.5.2 \n [7] RColorBrewer_1.1-3 iterators_1.0.14 circlize_0.4.17 \n[10] fastmap_1.2.0 foreach_1.5.2 doParallel_1.0.17 \n[13] jsonlite_2.0.0 graph_1.88.1 GlobalOptions_0.1.3 \n[16] ComplexHeatmap_2.26.0 flowWorkspace_4.22.1 scales_1.4.0 \n[19] XML_3.99-0.20 Rgraphviz_2.54.0 codetools_0.2-20 \n[22] cli_3.6.5 RProtoBufLib_2.22.0 rlang_1.1.7 \n[25] crayon_1.5.3 Biobase_2.70.0 yaml_2.3.12 \n[28] otel_0.2.0 cytolib_2.22.0 ncdfFlow_2.56.0 \n[31] tools_4.5.2 parallel_4.5.2 dplyr_1.2.0 \n[34] colorspace_2.1-2 ggplot2_4.0.2 GetoptLong_1.1.0 \n[37] BiocGenerics_0.56.0 vctrs_0.7.1 R6_2.6.1 \n[40] png_0.1-8 matrixStats_1.5.0 stats4_4.5.2 \n[43] lifecycle_1.0.5 flowCore_2.22.1 S4Vectors_0.48.0 \n[46] htmlwidgets_1.6.4 IRanges_2.44.0 clue_0.3-66 \n[49] cluster_2.1.8.1 pkgconfig_2.0.3 pillar_1.11.1 \n[52] gtable_0.3.6 data.table_1.18.2.1 glue_1.8.0 \n[55] xfun_0.56 tibble_3.3.1 tidyselect_1.2.1 \n[58] knitr_1.51 farver_2.1.2 rjson_0.2.23 \n[61] htmltools_0.5.9 rmarkdown_2.30 compiler_4.5.2 \n[64] S7_0.2.1 \n\n\n\n\nAlternatively, we can retrieve the same information for the individual packages via the packageVersion() function\n\npackageVersion(\"PeacoQC\")\n\n[1] '1.20.0'\n\n\n\n\nAs well as from the citation() function.\n\ncitation(\"PeacoQC\")\n\nTo cite package 'PeacoQC' in publications use:\n\n Emmaneel A (2025). _PeacoQC: Peak-based selection of high quality\n cytometry data_. doi:10.18129/B9.bioc.PeacoQC\n <https://doi.org/10.18129/B9.bioc.PeacoQC>, R package version 1.20.0,\n <https://bioconductor.org/packages/PeacoQC>.\n\nA BibTeX entry for LaTeX users is\n\n @Manual{,\n title = {PeacoQC: Peak-based selection of high quality cytometry data},\n author = {Annelies Emmaneel},\n year = {2025},\n note = {R package version 1.20.0},\n url = {https://bioconductor.org/packages/PeacoQC},\n doi = {10.18129/B9.bioc.PeacoQC},\n }\n\n\n\n\nHow does a version number work? Lets say we have the following version number: 1.20.0\nThe first number of the version (1. in this case) denotes major changes, primarily those where after the version change the package may not be compatible with the code used in the prior version. As a consequence, this number changes rarely.\nThe second number (.20. in this case) is the minor version. Minor changes typically consist of new features that are added, that don’t affect the overall package function. These will change more frequently, especially for Bioconductor packages with fixed release cycles.\nThe final number (.0 in this case) is often used to denote small changes occuring within a minor release period, often bug-fixes or fixing typos within the documentation.\n\n\nWe may in the future need to install specific package versions (but wont be doing so today). As expected, which repository contains the R package influences how we would go about doing this.\nFor CRAN packages, we can use the remotes packages install_version() function. This allows us to provide the version number, and designate the repository location (the CRAN url in this case).\n\nremotes::install_version(\"ggplot2\", version = \"3.5.2\", repos = \"https://cloud.r-project.org\")\n\nFor GitHub-based R packages, the package versioning schema is not as strict as that of CRAN or Bioconductor. Typically, changes in R packagaes are put out by their developers as releases. When trying to install a particular release, we can add an additional argument to the install_github() function, specifying the release version’s tag number. For example:\n\nremotes::install_github(\"DavidRach/Luciernaga\", ref = \"v0.99.7\")\n\nAlternatively, if the developer doesn’t implement releases, you can provide the hash number of a particular commit.\n\nremotes::install_github(\"DavidRach/Luciernaga\", ref = \"8d1d694\")", "crumbs": [ "About", "Intro to R", - "02 - File Paths" + "01 - Installing R Packages" ] }, { - "objectID": "course/02_FilePaths/index.html#file-paths", - "href": "course/02_FilePaths/index.html#file-paths", - "title": "02 - File Paths", - "section": "File Paths", - "text": "File Paths\nOne way we can do this is through a file.path argument. We could potentially provide this by adding either a / or a  into the path argument, depending on your computers operating system.\n\nlist.files(path=\"data/target\", full.names=FALSE, recursive=FALSE)\n\n\n\nWhile this works in your particular context, if you are sharing the code with others who have a different operating system, these hard-coded “/” or “\" will cause the code for them to error out at these particular steps.\n\nFor that reason, it is better to assemble a file.path using the file.path() function. This function takes into account the operating system, removing your need to have to worry about this particular computing nuance, and write code that is reproducible and replicable for everyone.\n\nFolderLocation <- file.path(\"data\", \"target\")\nFolderLocation\n\n[1] \"data/target\"\n\n\n\nlist.files(path=FolderLocation, full.names=FALSE, recursive=FALSE)\n\n\n\n\nWe can also append additional locations to existing file paths, by including the variable name within the file.path() we are creating.\n\nFolderLocation <- \"data\"\nScreenshotFolder <- file.path(FolderLocation, \"target\")\nScreenshotFolder\n\n[1] \"data/target\"\n\n\n\nlist.files(path=ScreenshotFolder, full.names=FALSE, recursive=FALSE)\n\n\n\n\nAdditionally, list.files() has the ability to filter for files that contain a particular character string. This can be useful is we are searching for “.fcs” or “.csv” files, but also for files that contain a particular word. In the case of the ScreenshotFolders\n\nlist.files(path=ScreenshotFolder, pattern=\"ND050\", full.names=FALSE, recursive=FALSE)\n\n\nYou will notice, the index numbers are in the context of what is filtered, not all the folder contents.", + "objectID": "course/01_InstallingRPackages/index.html#documentation-and-websites", + "href": "course/01_InstallingRPackages/index.html#documentation-and-websites", + "title": "01 - Installing R Packages", + "section": "Documentation and Websites", + "text": "Documentation and Websites\nWe have already seen a couple ways to access the help documentation contained within an R package via Positron. Beyond internal documentation, R packages often have external websites that contain additional walk-through articles (ie. vignettes) to better document how to use the package.\nFor CRAN-based packages, we can start off by searching for the package name. So, in the case of dplyr:\n\n\n\nTwo main suggestions pop up. One is the package’s CRAN page. Unfortunately, this one is not particularly user-friendly, although some text-based vignettes are accessible.\n\n\n\nBecause of this, many CRAN-based R packages (especially those part of the tidyverse) use pkgdown-generated websites hosted via a GitHub page (similar to the one used by this course. The second option on the search is dplyr’s pkgdown-style website\n\n\n\nWe can usually find the list of functions under the Reference tab, with the more extensive documentation vignettes being found under the Articles tab.\n\n\n\nGitHub-based packages will vary depending on their individual developers, but often will also use pkgdown-style websites. These often appear as links on the right-hand side, or within the repository’s ReadMe.\n\n\n\nFor Bioconductor-based packages, on the package’s page we can typically find the already rendered vignette articles, usually as either html or pdf files. For example, with PeacoQC:\n\n\n\nAdditionally, package vignettes can also be reached via the packages help index page. These will usually appear under User guides, package vignettes, and other documentation.", "crumbs": [ "About", "Intro to R", - "02 - File Paths" + "01 - Installing R Packages" ] }, { - "objectID": "course/02_FilePaths/index.html#selecting-for-patterns", - "href": "course/02_FilePaths/index.html#selecting-for-patterns", - "title": "02 - File Paths", - "section": "Selecting for Patterns", - "text": "Selecting for Patterns\nIf we currently listed the files within data, we get a return that looks like this:\n\nlist.files(\"data\", full.names=FALSE, recursive=FALSE)\n\n\n\n\nAs you can see, we are getting back both folders and individual .fcs files. We could consequently change the pattern to provide a character string that will only return the .fcs files. We will go ahead and assign this list to a variable named files, for later retrieval.\n\nfiles <- list.files(\"data\", pattern=\".fcs\", full.names=FALSE, recursive=FALSE)\nfiles\n\n\n\n\nOne of the R packages we will be using througout the course is the stringr package. It contains two functions that can be useful when identifying more complicated character strings. In this case, if we run the str_detect() function to identify which of the .fcs files within the files variable contains the “INF” character string, we get a vector of logical (ie. True or FALSE) outputs corresponding to each file.\n\n# install.packages(\"stringr\") # CRAN\nlibrary(stringr)\n\n\nstr_detect(files, \"INF\")\n\n\n\n\nSimilar to how we indexed the Fluorophore list (ex. Fluorophore[1:2]) which returned a subset, we can similarly use this logical vector to subset files that returned as TRUE for containing the pattern “INF”\n\nfiles[str_detect(files, \"INF\")]\n\n\n\n\nLet’s go ahead and save these subsetted file names to a new variable, called Infants.\n\nInfants <- files[str_detect(files, \"INF\")]", - "crumbs": [ - "About", - "Intro to R", - "02 - File Paths" - ] + "objectID": "course/02_FilePaths/Downsampler.html", + "href": "course/02_FilePaths/Downsampler.html", + "title": "Downsampling", + "section": "", + "text": "Due to trying to keep the overall file size down, I am downsampling to 100 events. For anyone interested in how I did this, this Quarto Markdown Document contains the code needed to repeat the process." + }, + { + "objectID": "course/02_FilePaths/Downsampler.html#specify-file.path-and-identify-files", + "href": "course/02_FilePaths/Downsampler.html#specify-file.path-and-identify-files", + "title": "Downsampling", + "section": "Specify file.path and identify files", + "text": "Specify file.path and identify files\nDue to the counts being conducter on two separate instruments, the number of columns differs, so they will need to be loaded into separate GatingSet objects.\n\nStorageLocation <- file.path(\"course\", \"02_FilePaths\", \"data\")\nExisting <- list.files(StorageLocation, pattern=\".fcs\", full.names=TRUE)\nList1 <- Existing[1:2] # 3L Aurora\nList2 <- Existing[3:8] # 4L Aurora" + }, + { + "objectID": "course/02_FilePaths/Downsampler.html#load-.fcs-files-into-a-gatingset", + "href": "course/02_FilePaths/Downsampler.html#load-.fcs-files-into-a-gatingset", + "title": "Downsampling", + "section": "Load .fcs files into a GatingSet", + "text": "Load .fcs files into a GatingSet\nLoad in files to their respective GatingSet objects\n\ncs1 <- load_cytoset_from_fcs(List1, truncate_max_range = FALSE, transformation = FALSE)\ngs1 <- GatingSet(cs1)\n\ncs2 <- load_cytoset_from_fcs(List2, truncate_max_range = FALSE, transformation = FALSE)\ngs2 <- GatingSet(cs2)" + }, + { + "objectID": "course/03_InsideFCSFile/slides.html#getting-set-up", + "href": "course/03_InsideFCSFile/slides.html#getting-set-up", + "title": "03 - Inside an FCS File", + "section": "Getting Set Up", + "text": "Getting Set Up" + }, + { + "objectID": "course/03_InsideFCSFile/slides.html#flowcore", + "href": "course/03_InsideFCSFile/slides.html#flowcore", + "title": "03 - Inside an FCS File", + "section": "flowCore", + "text": "flowCore\n\n\n\n\n\n\n\n\n.\n\n\nWe will be using the flowCore package, which is the oldest and most-frequently downloaded flow cytometry package on Bioconductor." + }, + { + "objectID": "course/03_InsideFCSFile/slides.html#flowframe", + "href": "course/03_InsideFCSFile/slides.html#flowframe", + "title": "03 - Inside an FCS File", + "section": "flowFrame", + "text": "flowFrame\n\n\n\n\n\n\n\n\n.\n\n\nFor read.FCS(), it accepts several arguments. The argument “filename” is where we provide our file.path to .fcs file that we wish to load into R. Let’s go ahead and do so\n\n\n\n\n\n\n\nread.FCS(filename=firstfile)" + }, + { + "objectID": "course/03_InsideFCSFile/slides.html#early-metadata", + "href": "course/03_InsideFCSFile/slides.html#early-metadata", + "title": "03 - Inside an FCS File", + "section": "Early Metadata", + "text": "Early Metadata\n\n\n\n\n\n\n\n\n.\n\n\nWithin the initial portion, we are getting back metadata keywords related to where and how the particular file was acquired. Keywords of potential interest include:\n\n\n\n\n\n\n\n\n\n\n\n\n\nStart Time\n\n\nWhat time was the .fcs file acquired\n\n\n\n\n\n\n\nDescriptionList$`$BTIM`\n\n[1] \"13:55:29.85\"" + }, + { + "objectID": "course/03_InsideFCSFile/slides.html#detector-values", + "href": "course/03_InsideFCSFile/slides.html#detector-values", + "title": "03 - Inside an FCS File", + "section": "Detector Values", + "text": "Detector Values\n\n\n\n\n\n\n\n\n.\n\n\nThe next major stretch of keywords encode parameter values associated with the individual detectors for at the time of acquisition.\n\n\n\n\n\n\n\nDetectors <- DescriptionList[20:384]\nDetectors\n\n$`$P10B`\n[1] \"32\"\n\n$`$P10E`\n[1] \"0,0\"\n\n$`$P10N`\n[1] \"UV9-A\"\n\n$`$P10R`\n[1] \"4194304\"\n\n$`$P10TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P10V`\n[1] \"710\"\n\n$`$P11B`\n[1] \"32\"\n\n$`$P11E`\n[1] \"0,0\"\n\n$`$P11N`\n[1] \"UV10-A\"\n\n$`$P11R`\n[1] \"4194304\"\n\n$`$P11TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P11V`\n[1] \"377\"\n\n$`$P12B`\n[1] \"32\"\n\n$`$P12E`\n[1] \"0,0\"\n\n$`$P12N`\n[1] \"UV11-A\"\n\n$`$P12R`\n[1] \"4194304\"\n\n$`$P12TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P12V`\n[1] \"469\"\n\n$`$P13B`\n[1] \"32\"\n\n$`$P13E`\n[1] \"0,0\"\n\n$`$P13N`\n[1] \"UV12-A\"\n\n$`$P13R`\n[1] \"4194304\"\n\n$`$P13TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P13V`\n[1] \"434\"\n\n$`$P14B`\n[1] \"32\"\n\n$`$P14E`\n[1] \"0,0\"\n\n$`$P14N`\n[1] \"UV13-A\"\n\n$`$P14R`\n[1] \"4194304\"\n\n$`$P14TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P14V`\n[1] \"564\"\n\n$`$P15B`\n[1] \"32\"\n\n$`$P15E`\n[1] \"0,0\"\n\n$`$P15N`\n[1] \"UV14-A\"\n\n$`$P15R`\n[1] \"4194304\"\n\n$`$P15TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P15V`\n[1] \"975\"\n\n$`$P16B`\n[1] \"32\"\n\n$`$P16E`\n[1] \"0,0\"\n\n$`$P16N`\n[1] \"UV15-A\"\n\n$`$P16R`\n[1] \"4194304\"\n\n$`$P16TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P16V`\n[1] \"737\"\n\n$`$P17B`\n[1] \"32\"\n\n$`$P17E`\n[1] \"0,0\"\n\n$`$P17N`\n[1] \"UV16-A\"\n\n$`$P17R`\n[1] \"4194304\"\n\n$`$P17TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P17V`\n[1] \"1069\"\n\n$`$P18B`\n[1] \"32\"\n\n$`$P18E`\n[1] \"0,0\"\n\n$`$P18N`\n[1] \"SSC-H\"\n\n$`$P18R`\n[1] \"4194304\"\n\n$`$P18TYPE`\n[1] \"Side_Scatter\"\n\n$`$P18V`\n[1] \"334\"\n\n$`$P19B`\n[1] \"32\"\n\n$`$P19E`\n[1] \"0,0\"\n\n$`$P19N`\n[1] \"SSC-A\"\n\n$`$P19R`\n[1] \"4194304\"\n\n$`$P19TYPE`\n[1] \"Side_Scatter\"\n\n$`$P19V`\n[1] \"334\"\n\n$`$P1B`\n[1] \"32\"\n\n$`$P1E`\n[1] \"0,0\"\n\n$`$P1N`\n[1] \"Time\"\n\n$`$P1R`\n[1] \"272140\"\n\n$`$P1TYPE`\n[1] \"Time\"\n\n$`$P20B`\n[1] \"32\"\n\n$`$P20E`\n[1] \"0,0\"\n\n$`$P20N`\n[1] \"V1-A\"\n\n$`$P20R`\n[1] \"4194304\"\n\n$`$P20TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P20V`\n[1] \"352\"\n\n$`$P21B`\n[1] \"32\"\n\n$`$P21E`\n[1] \"0,0\"\n\n$`$P21N`\n[1] \"V2-A\"\n\n$`$P21R`\n[1] \"4194304\"\n\n$`$P21TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P21V`\n[1] \"412\"\n\n$`$P22B`\n[1] \"32\"\n\n$`$P22E`\n[1] \"0,0\"\n\n$`$P22N`\n[1] \"V3-A\"\n\n$`$P22R`\n[1] \"4194304\"\n\n$`$P22TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P22V`\n[1] \"304\"\n\n$`$P23B`\n[1] \"32\"\n\n$`$P23E`\n[1] \"0,0\"\n\n$`$P23N`\n[1] \"V4-A\"\n\n$`$P23R`\n[1] \"4194304\"\n\n$`$P23TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P23V`\n[1] \"217\"\n\n$`$P24B`\n[1] \"32\"\n\n$`$P24E`\n[1] \"0,0\"\n\n$`$P24N`\n[1] \"V5-A\"\n\n$`$P24R`\n[1] \"4194304\"\n\n$`$P24TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P24V`\n[1] \"257\"\n\n$`$P25B`\n[1] \"32\"\n\n$`$P25E`\n[1] \"0,0\"\n\n$`$P25N`\n[1] \"V6-A\"\n\n$`$P25R`\n[1] \"4194304\"\n\n$`$P25TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P25V`\n[1] \"218\"\n\n$`$P26B`\n[1] \"32\"\n\n$`$P26E`\n[1] \"0,0\"\n\n$`$P26N`\n[1] \"V7-A\"\n\n$`$P26R`\n[1] \"4194304\"\n\n$`$P26TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P26V`\n[1] \"303\"\n\n$`$P27B`\n[1] \"32\"\n\n$`$P27E`\n[1] \"0,0\"\n\n$`$P27N`\n[1] \"V8-A\"\n\n$`$P27R`\n[1] \"4194304\"\n\n$`$P27TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P27V`\n[1] \"461\"\n\n$`$P28B`\n[1] \"32\"\n\n$`$P28E`\n[1] \"0,0\"\n\n$`$P28N`\n[1] \"V9-A\"\n\n$`$P28R`\n[1] 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\"490\"\n\n$`$P4B`\n[1] \"32\"\n\n$`$P4E`\n[1] \"0,0\"\n\n$`$P4N`\n[1] \"UV3-A\"\n\n$`$P4R`\n[1] \"4194304\"\n\n$`$P4TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P4V`\n[1] \"677\"\n\n$`$P50B`\n[1] \"32\"\n\n$`$P50E`\n[1] \"0,0\"\n\n$`$P50N`\n[1] \"B11-A\"\n\n$`$P50R`\n[1] \"4194304\"\n\n$`$P50TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P50V`\n[1] \"286\"\n\n$`$P51B`\n[1] \"32\"\n\n$`$P51E`\n[1] \"0,0\"\n\n$`$P51N`\n[1] \"B12-A\"\n\n$`$P51R`\n[1] \"4194304\"\n\n$`$P51TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P51V`\n[1] \"407\"\n\n$`$P52B`\n[1] \"32\"\n\n$`$P52E`\n[1] \"0,0\"\n\n$`$P52N`\n[1] \"B13-A\"\n\n$`$P52R`\n[1] \"4194304\"\n\n$`$P52TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P52V`\n[1] \"700\"\n\n$`$P53B`\n[1] \"32\"\n\n$`$P53E`\n[1] \"0,0\"\n\n$`$P53N`\n[1] \"B14-A\"\n\n$`$P53R`\n[1] \"4194304\"\n\n$`$P53TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P53V`\n[1] \"693\"\n\n$`$P54B`\n[1] \"32\"\n\n$`$P54E`\n[1] \"0,0\"\n\n$`$P54N`\n[1] \"R1-A\"\n\n$`$P54R`\n[1] \"4194304\"\n\n$`$P54TYPE`\n[1] 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\"4194304\"\n\n$`$P5TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P5V`\n[1] \"1022\"\n\n$`$P60B`\n[1] \"32\"\n\n$`$P60E`\n[1] \"0,0\"\n\n$`$P60N`\n[1] \"R7-A\"\n\n$`$P60R`\n[1] \"4194304\"\n\n$`$P60TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P60V`\n[1] \"524\"\n\n$`$P61B`\n[1] \"32\"\n\n$`$P61E`\n[1] \"0,0\"\n\n$`$P61N`\n[1] \"R8-A\"\n\n$`$P61R`\n[1] \"4194304\"\n\n$`$P61TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P61V`\n[1] \"243\"\n\n$`$P6B`\n[1] \"32\"\n\n$`$P6E`\n[1] \"0,0\"\n\n$`$P6N`\n[1] \"UV5-A\"\n\n$`$P6R`\n[1] \"4194304\"\n\n$`$P6TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P6V`\n[1] \"616\"\n\n$`$P7B`\n[1] \"32\"\n\n$`$P7E`\n[1] \"0,0\"\n\n$`$P7N`\n[1] \"UV6-A\"\n\n$`$P7R`\n[1] \"4194304\"\n\n$`$P7TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P7V`\n[1] \"506\"\n\n$`$P8B`\n[1] \"32\"\n\n$`$P8E`\n[1] \"0,0\"\n\n$`$P8N`\n[1] \"UV7-A\"\n\n$`$P8R`\n[1] \"4194304\"\n\n$`$P8TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P8V`\n[1] \"661\"\n\n$`$P9B`\n[1] \"32\"\n\n$`$P9E`\n[1] \"0,0\"\n\n$`$P9N`\n[1] \"UV8-A\"\n\n$`$P9R`\n[1] \"4194304\"\n\n$`$P9TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P9V`\n[1] \"514\"" + }, + { + "objectID": "course/03_InsideFCSFile/slides.html#middle-metadata", + "href": "course/03_InsideFCSFile/slides.html#middle-metadata", + "title": "03 - Inside an FCS File", + "section": "Middle Metadata", + "text": "Middle Metadata\n\n\n\n\n\n\n\n\n.\n\n\nOnce we are out of the detector keywords, we find the last of the $Metadata associated keywords.\n\n\n\n\n\n\n\nDetectors <- DescriptionList[385:398]\nDetectors\n\n$`$PAR`\n[1] \"61\"\n\n$`$PROJ`\n[1] \"CellCounts4L_AB_05\"\n\n$`$SPILLOVER`\n UV1-A UV2-A UV3-A UV4-A UV5-A UV6-A UV7-A UV8-A UV9-A UV10-A UV11-A\n [1,] 1e+00 0 0 0 0 0 0 0 0 0 0\n [2,] 1e-06 1 0 0 0 0 0 0 0 0 0\n [3,] 0e+00 0 1 0 0 0 0 0 0 0 0\n [4,] 0e+00 0 0 1 0 0 0 0 0 0 0\n [5,] 0e+00 0 0 0 1 0 0 0 0 0 0\n [6,] 0e+00 0 0 0 0 1 0 0 0 0 0\n [7,] 0e+00 0 0 0 0 0 1 0 0 0 0\n [8,] 0e+00 0 0 0 0 0 0 1 0 0 0\n [9,] 0e+00 0 0 0 0 0 0 0 1 0 0\n[10,] 0e+00 0 0 0 0 0 0 0 0 1 0\n[11,] 0e+00 0 0 0 0 0 0 0 0 0 1\n[12,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[13,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[14,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[15,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[16,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[17,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[18,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[19,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[20,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[21,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[22,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[23,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[24,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[25,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[26,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[27,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[28,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[29,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[30,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[31,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[32,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[33,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[34,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[35,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[36,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[37,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[38,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[39,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[40,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[41,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[42,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[43,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[44,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[45,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[46,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[47,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[48,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[49,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[50,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[51,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[52,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[53,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[54,] 0e+00 0 0 0 0 0 0 0 0 0 0\n UV12-A UV13-A UV14-A UV15-A UV16-A V1-A V2-A V3-A V4-A V5-A V6-A V7-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 1 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 1 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 1 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 1 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 1 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 1 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 1 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 1 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 1 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 1 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 1 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 1\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0\n V8-A V9-A V10-A V11-A V12-A V13-A V14-A V15-A V16-A B1-A B2-A B3-A B4-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n B5-A B6-A B7-A B8-A B9-A B10-A B11-A B12-A B13-A B14-A R1-A R2-A R3-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n R4-A R5-A R6-A R7-A R8-A\n [1,] 0 0 0 0 0\n [2,] 0 0 0 0 0\n [3,] 0 0 0 0 0\n [4,] 0 0 0 0 0\n [5,] 0 0 0 0 0\n [6,] 0 0 0 0 0\n [7,] 0 0 0 0 0\n [8,] 0 0 0 0 0\n [9,] 0 0 0 0 0\n[10,] 0 0 0 0 0\n[11,] 0 0 0 0 0\n[12,] 0 0 0 0 0\n[13,] 0 0 0 0 0\n[14,] 0 0 0 0 0\n[15,] 0 0 0 0 0\n[16,] 0 0 0 0 0\n[17,] 0 0 0 0 0\n[18,] 0 0 0 0 0\n[19,] 0 0 0 0 0\n[20,] 0 0 0 0 0\n[21,] 0 0 0 0 0\n[22,] 0 0 0 0 0\n[23,] 0 0 0 0 0\n[24,] 0 0 0 0 0\n[25,] 0 0 0 0 0\n[26,] 0 0 0 0 0\n[27,] 0 0 0 0 0\n[28,] 0 0 0 0 0\n[29,] 0 0 0 0 0\n[30,] 0 0 0 0 0\n[31,] 0 0 0 0 0\n[32,] 0 0 0 0 0\n[33,] 0 0 0 0 0\n[34,] 0 0 0 0 0\n[35,] 0 0 0 0 0\n[36,] 0 0 0 0 0\n[37,] 0 0 0 0 0\n[38,] 0 0 0 0 0\n[39,] 0 0 0 0 0\n[40,] 0 0 0 0 0\n[41,] 0 0 0 0 0\n[42,] 0 0 0 0 0\n[43,] 0 0 0 0 0\n[44,] 0 0 0 0 0\n[45,] 0 0 0 0 0\n[46,] 0 0 0 0 0\n[47,] 0 0 0 0 0\n[48,] 0 0 0 0 0\n[49,] 0 0 0 0 0\n[50,] 1 0 0 0 0\n[51,] 0 1 0 0 0\n[52,] 0 0 1 0 0\n[53,] 0 0 0 1 0\n[54,] 0 0 0 0 1\n\n$`$TIMESTEP`\n[1] \"0.0001\"\n\n$`$TOT`\n[1] \"100\"\n\n$`$VOL`\n[1] \"30.31\"\n\n$`APPLY COMPENSATION`\n[1] \"FALSE\"\n\n$CHARSET\n[1] \"utf-8\"\n\n$CREATOR\n[1] \"SpectroFlo 3.3.0\"\n\n$FCSversion\n[1] \"3\"\n\n$FILENAME\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n$`FSC ASF`\n[1] \"1.21\"\n\n$GROUPNAME\n[1] \"ND050\"\n\n$GUID\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"" + }, + { + "objectID": "course/03_InsideFCSFile/slides.html#laser-metadata", + "href": "course/03_InsideFCSFile/slides.html#laser-metadata", + "title": "03 - Inside an FCS File", + "section": "Laser Metadata", + "text": "Laser Metadata\n\n\n\n\n\n\n\n\n.\n\n\nNext up, there is a small stretch of keywords containing the values associated with the individual lasers as far as delays and area scaling factors for a particular day (also useful when plotted).\n\n\n\n\n\n\n\nDetectors <- DescriptionList[399:410]\nDetectors\n\n$LASER1ASF\n[1] \"1.09\"\n\n$LASER1DELAY\n[1] \"-19.525\"\n\n$LASER1NAME\n[1] \"Violet\"\n\n$LASER2ASF\n[1] \"1.14\"\n\n$LASER2DELAY\n[1] \"0\"\n\n$LASER2NAME\n[1] \"Blue\"\n\n$LASER3ASF\n[1] \"1.02\"\n\n$LASER3DELAY\n[1] \"20.15\"\n\n$LASER3NAME\n[1] \"Red\"\n\n$LASER4ASF\n[1] \"0.92\"\n\n$LASER4DELAY\n[1] \"40.725\"\n\n$LASER4NAME\n[1] \"UV\"" + }, + { + "objectID": "course/03_InsideFCSFile/slides.html#display", + "href": "course/03_InsideFCSFile/slides.html#display", + "title": "03 - Inside an FCS File", + "section": "Display", + "text": "Display\n\n\n\n\n\n\n\n\n.\n\n\nThen there is a stretch matching whether a particular detector needs to be displayed as linear (in the case of time and scatter) or as log (for individual detectors).\n\n\n\n\n\n\n\nDetectors <- DescriptionList[412:472]\nDetectors\n\n$P10DISPLAY\n[1] \"LOG\"\n\n$P11DISPLAY\n[1] \"LOG\"\n\n$P12DISPLAY\n[1] \"LOG\"\n\n$P13DISPLAY\n[1] \"LOG\"\n\n$P14DISPLAY\n[1] \"LOG\"\n\n$P15DISPLAY\n[1] \"LOG\"\n\n$P16DISPLAY\n[1] \"LOG\"\n\n$P17DISPLAY\n[1] \"LOG\"\n\n$P18DISPLAY\n[1] \"LIN\"\n\n$P19DISPLAY\n[1] \"LIN\"\n\n$P1DISPLAY\n[1] \"LOG\"\n\n$P20DISPLAY\n[1] \"LOG\"\n\n$P21DISPLAY\n[1] \"LOG\"\n\n$P22DISPLAY\n[1] \"LOG\"\n\n$P23DISPLAY\n[1] \"LOG\"\n\n$P24DISPLAY\n[1] \"LOG\"\n\n$P25DISPLAY\n[1] \"LOG\"\n\n$P26DISPLAY\n[1] \"LOG\"\n\n$P27DISPLAY\n[1] \"LOG\"\n\n$P28DISPLAY\n[1] \"LOG\"\n\n$P29DISPLAY\n[1] \"LOG\"\n\n$P2DISPLAY\n[1] \"LOG\"\n\n$P30DISPLAY\n[1] \"LOG\"\n\n$P31DISPLAY\n[1] \"LOG\"\n\n$P32DISPLAY\n[1] \"LOG\"\n\n$P33DISPLAY\n[1] \"LOG\"\n\n$P34DISPLAY\n[1] \"LOG\"\n\n$P35DISPLAY\n[1] \"LOG\"\n\n$P36DISPLAY\n[1] \"LIN\"\n\n$P37DISPLAY\n[1] \"LIN\"\n\n$P38DISPLAY\n[1] \"LIN\"\n\n$P39DISPLAY\n[1] \"LIN\"\n\n$P3DISPLAY\n[1] \"LOG\"\n\n$P40DISPLAY\n[1] \"LOG\"\n\n$P41DISPLAY\n[1] \"LOG\"\n\n$P42DISPLAY\n[1] \"LOG\"\n\n$P43DISPLAY\n[1] \"LOG\"\n\n$P44DISPLAY\n[1] \"LOG\"\n\n$P45DISPLAY\n[1] \"LOG\"\n\n$P46DISPLAY\n[1] \"LOG\"\n\n$P47DISPLAY\n[1] \"LOG\"\n\n$P48DISPLAY\n[1] \"LOG\"\n\n$P49DISPLAY\n[1] \"LOG\"\n\n$P4DISPLAY\n[1] \"LOG\"\n\n$P50DISPLAY\n[1] \"LOG\"\n\n$P51DISPLAY\n[1] \"LOG\"\n\n$P52DISPLAY\n[1] \"LOG\"\n\n$P53DISPLAY\n[1] \"LOG\"\n\n$P54DISPLAY\n[1] \"LOG\"\n\n$P55DISPLAY\n[1] \"LOG\"\n\n$P56DISPLAY\n[1] \"LOG\"\n\n$P57DISPLAY\n[1] \"LOG\"\n\n$P58DISPLAY\n[1] \"LOG\"\n\n$P59DISPLAY\n[1] \"LOG\"\n\n$P5DISPLAY\n[1] \"LOG\"\n\n$P60DISPLAY\n[1] \"LOG\"\n\n$P61DISPLAY\n[1] \"LOG\"\n\n$P6DISPLAY\n[1] \"LOG\"\n\n$P7DISPLAY\n[1] \"LOG\"\n\n$P8DISPLAY\n[1] \"LOG\"\n\n$P9DISPLAY\n[1] \"LOG\"" + }, + { + "objectID": "course/03_InsideFCSFile/slides.html#flowcore-parameters", + "href": "course/03_InsideFCSFile/slides.html#flowcore-parameters", + "title": "03 - Inside an FCS File", + "section": "flowCore Parameters", + "text": "flowCore Parameters\n\n\n\n\n\n\n\n\n.\n\n\nDepending on the arguments selected during read.FCS(), we might also encounter additional keywords that are added in by flowCore. For example, we do not see these keywords when “transformation” is set to FALSE.\n\n\n\n\n\n\n\nflowCoreCheck <- read.FCS(filename=firstfile,\n transformation = FALSE, truncate_max_range = FALSE)\n\nflowCoreCheck\n\nflowFrame object 'CellCounts4L_AB_05-ND050-05.fcs'\nwith 100 cells and 61 observables:\n name desc range minRange maxRange\n$P1 Time NA 272140 0 272139\n$P2 UV1-A NA 4194304 -111 4194303\n$P3 UV2-A NA 4194304 -111 4194303\n$P4 UV3-A NA 4194304 -111 4194303\n$P5 UV4-A NA 4194304 -111 4194303\n... ... ... ... ... ...\n$P57 R4-A NA 4194304 -111 4194303\n$P58 R5-A NA 4194304 -111 4194303\n$P59 R6-A NA 4194304 -111 4194303\n$P60 R7-A NA 4194304 -111 4194303\n$P61 R8-A NA 4194304 -111 4194303\n476 keywords are stored in the 'description' slot" + }, + { + "objectID": "course/04_IntroToTidyverse/slides.html#read.csv", + "href": "course/04_IntroToTidyverse/slides.html#read.csv", + "title": "04 - Introduction to Tidyverse", + "section": "read.csv", + "text": "read.csv\n\n\n\n\n\n\n\n\n.\n\n\nWe will start by first loading in our copied over dataset (Dataset.csv) from it’s location in the project folder. If you are following the organization scheme we have been using throughout the course, your file path will look something like this:\n\n\n\n\n\n\n\n\n\n\nthefilepath <- file.path(\"data\", \"Dataset.csv\")\n\nthefilepath\n\n[1] \"data/Dataset.csv\"" + }, + { + "objectID": "course/04_IntroToTidyverse/slides.html#data.frame", + "href": "course/04_IntroToTidyverse/slides.html#data.frame", + "title": "04 - Introduction to Tidyverse", + "section": "data.frame", + "text": "data.frame\n\n\n\n\n\n\n\n\n.\n\n\nOr alternatively using the new-to-us glimpse() function\n\n\n\n\n\n\n\nglimpse(Data)\n\nError in `glimpse()`:\n! could not find function \"glimpse\"" + }, + { + "objectID": "course/04_IntroToTidyverse/slides.html#column-value-type", + "href": "course/04_IntroToTidyverse/slides.html#column-value-type", + "title": "04 - Introduction to Tidyverse", + "section": "Column value type", + "text": "Column value type\n\n\n\n\n\n\n\n\n.\n\n\nAs we saw last week, functions often need values that match a certain type (the paintbrush needing paint analogy). As we inspect the columns of Data, we can notice some of the columns contain values within that are character (ie. “char”) values. Others appear to contain numeric values (which are subtyped as either double (“ie. dbl”) or integer (ie. “int”)). At first glance, we do not appear to have any logical (ie. TRUE or FALSE) columns in this dataset." + }, + { + "objectID": "course/04_IntroToTidyverse/slides.html#select-columns", + "href": "course/04_IntroToTidyverse/slides.html#select-columns", + "title": "04 - Introduction to Tidyverse", + "section": "select (Columns)", + "text": "select (Columns)\n\n\n\n\n\n\n\n\n.\n\n\nNow that we have read in our data, and have a general picture of the structure and contents, lets start learning the main dplyr functions we will be using throughout the course. To do this, lets go ahead and attach dplyr to our local environment via the library() call.\n\n\n\n\n\n\n\nlibrary(dplyr)" }, { - "objectID": "course/02_FilePaths/index.html#conditionals", - "href": "course/02_FilePaths/index.html#conditionals", - "title": "02 - File Paths", - "section": "Conditionals", - "text": "Conditionals\nOne useful thing is that within R, we can set conditions on whether something is carried out. The most typical conditional you will encounter are the “If” statements. They typically take a form that resembles the following.\n\nNeedCoffee <- TRUE\n\nif (NeedCoffee){\n print(\"Take a break\")\n}\n\n\n\nIn this case of the above, if the variable within the () is equal to true, the code within the {} will be executed.\n\nNeedCoffee <- TRUE\n\nif (NeedCoffee){\n print(\"Take a break\")\n}\n\n[1] \"Take a break\"\n\n\n\n\nBy contrast, when the variable within the () is equal to false, the code within the {} will not be executed.\n\nNeedCoffee <- FALSE\n\nif (NeedCoffee){\n print(\"Take a break\")\n}\n\n\n\nThese “If” statements will trigger as long as the specified condition within the () is TRUE. For a different example:\n\nRowNumber <- 299\n2 + RowNumber > 300\n\n[1] TRUE\n\n\n\nif (2 + RowNumber > 3){\n print(\"Stop Iterating\")\n}\n\n[1] \"Stop Iterating\"\n\n\n\n\nWhen you add an ! in front a conditional, it flips the expected outcome.\n\nItsRaining <- TRUE\n\nif (ItsRaining){print(\"Bring an Umbrella\")}\n\n[1] \"Bring an Umbrella\"\n\n\n\n!ItsRaining\n\n[1] FALSE\n\n\n\nif (!ItsRaining){print(\"Bring an Umbrella\")}\n\n\nItsRaining <- TRUE\n\nif (!ItsRaining){print(\"Bring Sunglasses\")}\n\n\n\nWe will explore more complicated conditionals throughout the course, but for now, let’s implement a couple simple ones in the context of copying over the .fcs files in Infants over to a new target3 folder.", - "crumbs": [ - "About", - "Intro to R", - "02 - File Paths" - ] + "objectID": "course/04_IntroToTidyverse/slides.html#relocate", + "href": "course/04_IntroToTidyverse/slides.html#relocate", + "title": "04 - Introduction to Tidyverse", + "section": "relocate", + "text": "relocate\n\n\n\n\n\n\n\n\n.\n\n\nAlternatively, we occasionally want to move one column. While we could respecify the location using select(), specifying the names of all the other columns out in a line of code to just to rearrange one does not sound like a good use of time. For this reason, the second dplyr function we will be learning is the relocate() function." }, { - "objectID": "course/02_FilePaths/index.html#conditionals-in-practice", - "href": "course/02_FilePaths/index.html#conditionals-in-practice", - "title": "02 - File Paths", - "section": "Conditionals in practice", - "text": "Conditionals in practice\nFirst off, let’s write a conditional to check if there is a target3 folder within data.\n\nfiles_present <- list.files(\"data\", full.names=FALSE, recursive=FALSE)\nfiles_present\n\n\n\n\n\nFolderTarget3 <- file.path(\"data\", \"target3\")\ndir.exists(FolderTarget3)\n\n\n\n\nWe can write a conditional to create a folder if one does not yet exist.\n\nif (!dir.exists(FolderTarget3)){\n dir.create(FolderTarget3)\n}", - "crumbs": [ - "About", - "Intro to R", - "02 - File Paths" - ] + "objectID": "course/04_IntroToTidyverse/slides.html#rename", + "href": "course/04_IntroToTidyverse/slides.html#rename", + "title": "04 - Introduction to Tidyverse", + "section": "rename", + "text": "rename\n\n\n\n\n\n\n\n\n.\n\n\nAt this point, we are able to both move and select particular columns, allowing us to rearrange and subset a larger data.frame object however we want it to appear. However, as we encountered, some of the names contain special characters and spaces, requiring use of tick marks (``) to avoid issues. How can we change a column name?" }, { - "objectID": "course/02_FilePaths/index.html#copying-files", - "href": "course/02_FilePaths/index.html#copying-files", - "title": "02 - File Paths", - "section": "Copying Files", - "text": "Copying Files\nTo copy files to another folder location, we use the file.copy() function. It has two arguments that we will be working with, from being the .fcs files, and to being the folder location we wish to transfer them to. If we tried using them as we currently have them:\n\n# Variable Infants containing 4 .fcs file names\n\nfile.copy(from=Infants, to=FolderTarget3)\n\n\n\n\nThe reason for this error is we are only working with a partial file path, as viewed from our Working directory. In this case, what is needed is the full file.path, so the file.path should also include the upstream folders from your current working directory.\n\ngetwd()\n\n\n\n\nIn this case, we can update the .fcs files location by switching the full.names argument within list.files() from FALSE, to TRUE.\n\nfiles_present <- list.files(\"data\", full.names=TRUE, recursive=FALSE)\nfiles_present\n\n\nAnd filter for those containing “INF” again\n\nInfants <- files_present[str_detect(files_present, \"INF\")]\n\nAnd then try again:\n\n# Variable Infants containing 4 .fcs file names\n\nfile.copy(from=Infants, to=FolderTarget3)", - "crumbs": [ - "About", - "Intro to R", - "02 - File Paths" - ] + "objectID": "course/04_IntroToTidyverse/slides.html#pull", + "href": "course/04_IntroToTidyverse/slides.html#pull", + "title": "04 - Introduction to Tidyverse", + "section": "pull", + "text": "pull\n\n\n\n\n\n\n\n\n.\n\n\nSometimes, we may want to retrieve individual values present in a column, to use within either a vector or a list. We can do this using the pull() function, which will retrieve the column contents and strip the column formatting\n\n\n\n\n\n\n\nData |> pull(Date) |> head(10)\n\n [1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [6] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"" }, { - "objectID": "course/02_FilePaths/index.html#removing-files.", - "href": "course/02_FilePaths/index.html#removing-files.", - "title": "02 - File Paths", - "section": "Removing files.", - "text": "Removing files.\nJust like we can add files via R, we can also remove them. However, when we remove them via this route, they are removed permanently, not sent to the recycle bin. We will revisit how later on in the course after you have gained additional experience with file.paths.\n\n?unlink()", - "crumbs": [ - "About", - "Intro to R", - "02 - File Paths" - ] + "objectID": "course/04_IntroToTidyverse/slides.html#filter-rows", + "href": "course/04_IntroToTidyverse/slides.html#filter-rows", + "title": "04 - Introduction to Tidyverse", + "section": "filter (Rows)", + "text": "filter (Rows)\n\n\n\n\n\n\n\n\n.\n\n\nSo far, we have been working with dplyr functions primarily used when working with and subsetting columns (including select(), pull(), rename() and relocate()). What if we wanted to work with rows of a data.frame? This is where the filter() function is used." }, { - "objectID": "course/02_FilePaths/index.html#basename", - "href": "course/02_FilePaths/index.html#basename", - "title": "02 - File Paths", - "section": "Basename", - "text": "Basename\nIf we look at Infants with the full.names=TRUE, we see the additional pathing folder has been added, allowing us to successfully copy over the files.\n\nInfants\n\n\n\n\nIf we were trying to retrieve just the local file names from the full.names, we could do so with basename() function. We will use this in combination with additional arguments later in the course\n\nbasename(Infants)", - "crumbs": [ - "About", - "Intro to R", - "02 - File Paths" - ] + "objectID": "course/04_IntroToTidyverse/slides.html#mutate", + "href": "course/04_IntroToTidyverse/slides.html#mutate", + "title": "04 - Introduction to Tidyverse", + "section": "mutate", + "text": "mutate\n\n\n\n\n\n\n\n\n.\n\n\nAs we can see, with just these handful of functions, we have the building blocks to rearrange and subset a larger data.frame into a format that we prefer. But what if we wanted to alter the content of a column, or add new columns to an existing data.frame? This is where the mutate() function can be used." }, { - "objectID": "course/02_FilePaths/index.html#recursive", - "href": "course/02_FilePaths/index.html#recursive", - "title": "02 - File Paths", - "section": "Recursive", - "text": "Recursive\nAnd finally that we have created additional nested folders and populated them with fcs files, let’s see what setting list.files() recursive argument to TRUE\n\nall_files_present <- list.files(full.names=TRUE, recursive=TRUE)\nall_files_present \n\n\n\n\nIn this case, all files in all folders within the working directory are shown. This can be useful when exploring folder contents, but if there are a lot of files present within the folder, it will take a while to return the list.", - "crumbs": [ - "About", - "Intro to R", - "02 - File Paths" - ] + "objectID": "course/04_IntroToTidyverse/slides.html#arrange", + "href": "course/04_IntroToTidyverse/slides.html#arrange", + "title": "04 - Introduction to Tidyverse", + "section": "arrange", + "text": "arrange\n\n\n\n\n\n\n\n\n.\n\n\nAnd while we are here, let’s rearrange the rows so that they are descending based on the Tcell proportion. We can use this by using the desc() and arrange() functions from dplyr:\n\n\n\n\n\n\n\nTidyData <- TidyData |> arrange(desc(TcellsRounded))" }, { - "objectID": "course/02_FilePaths/index.html#saving-changes-to-version-control", - "href": "course/02_FilePaths/index.html#saving-changes-to-version-control", - "title": "02 - File Paths", - "section": "Saving changes to Version Control", - "text": "Saving changes to Version Control\nAnd as is good practice, to maintain version control, let’s stage all the files and folders we created today within the Week2 Project Folder, write a commit message, and send these files back to GitHub until they are needed again next time.", + "objectID": "course/04_IntroToTidyverse/index.html", + "href": "course/04_IntroToTidyverse/index.html", + "title": "04 - Introduction to Tidyverse", + "section": "", + "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", "crumbs": [ "About", "Intro to R", - "02 - File Paths" + "04 - Intro to Tidyverse" ] }, { - "objectID": "course/03_InsideFCSFile/index.html", - "href": "course/03_InsideFCSFile/index.html", - "title": "03 - Inside an FCS File", - "section": "", - "text": "For the YouTube livestream recording, see here\nFor screen-shot slides, click here", + "objectID": "course/04_IntroToTidyverse/index.html#read.csv", + "href": "course/04_IntroToTidyverse/index.html#read.csv", + "title": "04 - Introduction to Tidyverse", + "section": "read.csv", + "text": "read.csv\nWe will start by first loading in our copied over dataset (Dataset.csv) from it’s location in the project folder. If you are following the organization scheme we have been using throughout the course, your file path will look something like this:\n\nthefilepath <- file.path(\"data\", \"Dataset.csv\")\n\nthefilepath\n\n[1] \"data/Dataset.csv\"\n\n\n\n\n\n\n\n\nReminder\n\n\n\nWe encourage using the file.path function to build our file paths, as this keeps our code reproducible and replicable when a project folder is copied to other people’s computers that differ on whether the operating system uses forward or backward slash separation between folders.\n\n\nAbove, we directly specified the name (Dataset) and filetype (.csv) of the file we wanted in the last argument of the file.path (“Dataset.csv”). This allows us to skip the list.files() step we used last week as we have provided the full file path. While this approach can be faster, if we accidentally mistype the file name, we could end up with an error at the next step due to no files being found with the mistyped name.\nSince our dataset is stored as a .csv file, we will be using the read.csv() function from the utils package (included in our base R software installation) to read it into R. We will also use the colnames() function from last week to get a read-out of the column names.\n\nData <- read.csv(file=thefilepath, check.names=FALSE)\ncolnames(Data)\n\n [1] \"bid\" \"timepoint\" \"Condition\" \n [4] \"Date\" \"infant_sex\" \"ptype\" \n [7] \"root\" \"singletsFSC\" \"singletsSSC\" \n[10] \"singletsSSCB\" \"CD45\" \"NotMonocytes\" \n[13] \"nonDebris\" \"lymphocytes\" \"live\" \n[16] \"Dump+\" \"Dump-\" \"Tcells\" \n[19] \"Vd2+\" \"Vd2-\" \"Va7.2+\" \n[22] \"Va7.2-\" \"CD4+\" \"CD4-\" \n[25] \"CD8+\" \"CD8-\" \"Tcells_count\" \n[28] \"lymphocytes_count\" \"Monocytes\" \"Debris\" \n[31] \"CD45_count\" \n\n\nAs we look at the line of code, we now have enough context to decipher that the “file” argument is where we provide a file path to an individual file, but what does the “check.names” argument do?\nLet’s see what happens to the column names when we set “check.names” argument to TRUE:\n\nData_Alternative <- read.csv(thefilepath, check.names=TRUE)\ncolnames(Data_Alternative)\n\n [1] \"bid\" \"timepoint\" \"Condition\" \n [4] \"Date\" \"infant_sex\" \"ptype\" \n [7] \"root\" \"singletsFSC\" \"singletsSSC\" \n[10] \"singletsSSCB\" \"CD45\" \"NotMonocytes\" \n[13] \"nonDebris\" \"lymphocytes\" \"live\" \n[16] \"Dump.\" \"Dump..1\" \"Tcells\" \n[19] \"Vd2.\" \"Vd2..1\" \"Va7.2.\" \n[22] \"Va7.2..1\" \"CD4.\" \"CD4..1\" \n[25] \"CD8.\" \"CD8..1\" \"Tcells_count\" \n[28] \"lymphocytes_count\" \"Monocytes\" \"Debris\" \n[31] \"CD45_count\" \n\n\nAs we can see, any column name that contained a special character or a space was automatically converted over to R-approved syntax. However, this resulted in the loss of both +” and “-”, leaving us unable to determine whether we are looking at cells within or outside a particular gate.\n\nBecause of this, it is often better to rename columns individually after import, which we will learn how to do later today.\nFollowing up with what we practiced last week, lets use the head() function to visualize the first few rows of data.\n\nhead(Data, 3)\n\n bid timepoint Condition Date infant_sex ptype root singletsFSC\n1 INF0052 0 Ctrl 2025-07-26 Male HEU-hi 2098368 1894070\n2 INF0100 0 Ctrl 2025-07-26 Male HEU-lo 2020184 1791890\n3 INF0100 4 Ctrl 2025-07-26 Male HEU-lo 1155040 1033320\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1666179 1537396 0.5952943 0.8820349 0.8627649 0.6420138\n2 1697083 1579098 0.9106762 0.9052256 0.8602660 0.2145848\n3 875465 845446 0.9705765 0.9845400 0.9578793 0.7403110\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9020581 0.21090996 0.6911482 0.2804264 0.008120361 0.9918796 0.01448070\n2 0.8908981 0.06252775 0.8283703 0.6748298 0.007265620 0.9927344 0.01577499\n3 0.8757665 0.20023803 0.6755285 0.6119129 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Monocytes Debris CD45_count\n1 587573 0.11796509 0.13723513 915203\n2 308583 0.09477437 0.13973396 1438047\n3 607477 0.01545999 0.04212072 820570\n\n\nWhen working in Positron, we could have alternatively clicked on the little grid icon next to our created variable “Data” in the right secondary sidebar, which would have opened the data in our Editor window. From this same window, we can see it is stored as a “data.frame” object type.\n\nWe could also achieve the same window to open using the View() function:\n\nView(Data)\n\nWrapping up our brief recap of last week functions, we can check an objects type using both the class() and str() functions.\n\nclass(Data)\n\n[1] \"data.frame\"\n\n\n\nstr(Data)\n\n'data.frame': 196 obs. of 31 variables:\n $ bid : chr \"INF0052\" \"INF0100\" \"INF0100\" \"INF0100\" ...\n $ timepoint : int 0 0 4 9 0 4 9 4 9 0 ...\n $ Condition : chr \"Ctrl\" \"Ctrl\" \"Ctrl\" \"Ctrl\" ...\n $ Date : chr \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" ...\n $ infant_sex : chr \"Male\" \"Male\" \"Male\" \"Male\" ...\n $ ptype : chr \"HEU-hi\" \"HEU-lo\" \"HEU-lo\" \"HEU-lo\" ...\n $ root : int 2098368 2020184 1155040 358624 1362216 1044808 1434840 972056 1521928 2363512 ...\n $ singletsFSC : int 1894070 1791890 1033320 328624 1206309 917398 1265022 875707 1359574 2136616 ...\n $ singletsSSC : int 1666179 1697083 875465 289327 1032946 735579 988445 767323 1175755 1875394 ...\n $ singletsSSCB : int 1537396 1579098 845446 276289 982736 685592 940454 718000 1097478 1732620 ...\n $ CD45 : num 0.595 0.911 0.971 0.982 0.957 ...\n $ NotMonocytes : num 0.882 0.905 0.985 0.986 0.956 ...\n $ nonDebris : num 0.863 0.86 0.958 0.941 0.841 ...\n $ lymphocytes : num 0.642 0.215 0.74 0.651 0.705 ...\n $ live : num 0.902 0.891 0.876 0.915 0.895 ...\n $ Dump+ : num 0.2109 0.0625 0.2002 0.2147 0.3383 ...\n $ Dump- : num 0.691 0.828 0.676 0.701 0.557 ...\n $ Tcells : num 0.28 0.675 0.612 0.631 0.44 ...\n $ Vd2+ : num 0.00812 0.00727 0.00465 0.01135 0.00475 ...\n $ Vd2- : num 0.992 0.993 0.995 0.989 0.995 ...\n $ Va7.2+ : num 0.0145 0.0158 0.0158 0.017 0.0133 ...\n $ Va7.2- : num 0.977 0.977 0.98 0.972 0.982 ...\n $ CD4+ : num 0.634 0.612 0.664 0.438 0.739 ...\n $ CD4- : num 0.343 0.365 0.316 0.534 0.243 ...\n $ CD8+ : num 0.273 0.336 0.286 0.486 0.195 ...\n $ CD8- : num 0.0698 0.0293 0.0294 0.0476 0.0476 ...\n $ Tcells_count : int 164771 208241 371723 111552 291777 271870 487937 220634 415867 184930 ...\n $ lymphocytes_count: int 587573 308583 607477 176662 663667 510730 726238 451047 710964 652155 ...\n $ Monocytes : num 0.118 0.0948 0.0155 0.0145 0.0444 ...\n $ Debris : num 0.1372 0.1397 0.0421 0.0587 0.1592 ...\n $ CD45_count : int 915203 1438047 820570 271304 940733 675857 921660 701657 1066884 1017713 ...", "crumbs": [ "About", "Intro to R", - "03 - Inside a .FCS file" + "04 - Intro to Tidyverse" ] }, { - "objectID": "course/03_InsideFCSFile/index.html#getting-set-up", - "href": "course/03_InsideFCSFile/index.html#getting-set-up", - "title": "03 - Inside an FCS File", - "section": "Getting Set Up", - "text": "Getting Set Up\n\n\nSet up File Paths\nHaving copied over the new data to your working project folder (Week 3 or whatever your chosen name), let’s identify the file paths between our working directory and the fcs files. If you retained the same project organization structure we had during Week #2, it may look similar to the following:\n\nPathToDataFolder <- file.path(\"data\")\n\n\nPathToDataFolder\n\n[1] \"data\"\n\n\n\n\n\n\nLocate .fcs files\nWe will now locate our .fcs files. As we saw last week, our computer will need the full file.paths to these individual files, so we will set the list.files() “full.names” argument to TRUE.\n\nfcs_files <- list.files(PathToDataFolder, pattern=\".fcs\", full.names=TRUE)\nfcs_files\n\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n\nBy contrast, if the “full.names” argument was set to FALSE, we would have retrieved just the file names\n\nlist.files(PathToDataFolder, pattern=\".fcs\", full.names=FALSE)\n\n[1] \"CellCounts4L_AB_05_ND050_05.fcs\"\n\n\nThis would have been the equivalent of running the basename function on the “full.names=TRUE” output.\n\nbasename(fcs_files)\n\n[1] \"CellCounts4L_AB_05_ND050_05.fcs\"", + "objectID": "course/04_IntroToTidyverse/index.html#data.frame", + "href": "course/04_IntroToTidyverse/index.html#data.frame", + "title": "04 - Introduction to Tidyverse", + "section": "data.frame", + "text": "data.frame\nOr alternatively using the new-to-us glimpse() function\n\nglimpse(Data)\n\nError in `glimpse()`:\n! could not find function \"glimpse\"\n\n\n\n\n\n\n\n\nCheckpoint 1\n\n\n\nThis however returns an error. Any idea why this might be occuring?\n\n\n\n\nCode\n# We haven't attached/loaded the package in which the function glimpse is within\n\n\n\n\n\n\n\n\nCheckpoint 2\n\n\n\nHow would we locate a package a not-yet-loaded function is within?\n\n\n\n\nCode\n# We can use double ? to search all installed packages for a function, regardless\n# if the package is attached to the environment or not\n\n??glimpse\n\n\n\nFrom the list of search matches (in the right secondary sidebar), it looks likely that the glimpse() function in the dplyr package was the one we were looking for. This is one the main tidyverse packages we will be using throughout the course. Let’s attach it to our environment via the library() call first and try running glimpse() again.\n\nlibrary(dplyr)\nglimpse(Data)\n\nRows: 196\nColumns: 31\n$ bid <chr> \"INF0052\", \"INF0100\", \"INF0100\", \"INF0100\", \"INF0179…\n$ timepoint <int> 0, 0, 4, 9, 0, 4, 9, 4, 9, 0, 0, 4, 9, 0, 4, 9, 4, 9…\n$ Condition <chr> \"Ctrl\", \"Ctrl\", \"Ctrl\", \"Ctrl\", \"Ctrl\", \"Ctrl\", \"Ctr…\n$ Date <chr> \"2025-07-26\", \"2025-07-26\", \"2025-07-26\", \"2025-07-2…\n$ infant_sex <chr> \"Male\", \"Male\", \"Male\", \"Male\", \"Male\", \"Male\", \"Mal…\n$ ptype <chr> \"HEU-hi\", \"HEU-lo\", \"HEU-lo\", \"HEU-lo\", \"HU\", \"HU\", …\n$ root <int> 2098368, 2020184, 1155040, 358624, 1362216, 1044808,…\n$ singletsFSC <int> 1894070, 1791890, 1033320, 328624, 1206309, 917398, …\n$ singletsSSC <int> 1666179, 1697083, 875465, 289327, 1032946, 735579, 9…\n$ singletsSSCB <int> 1537396, 1579098, 845446, 276289, 982736, 685592, 94…\n$ CD45 <dbl> 0.5952943, 0.9106762, 0.9705765, 0.9819573, 0.957259…\n$ NotMonocytes <dbl> 0.8820349, 0.9052256, 0.9845400, 0.9855070, 0.955627…\n$ nonDebris <dbl> 0.8627649, 0.8602660, 0.9578793, 0.9412615, 0.840783…\n$ lymphocytes <dbl> 0.6420138, 0.2145848, 0.7403110, 0.6511588, 0.705478…\n$ live <dbl> 0.9020581, 0.8908981, 0.8757665, 0.9153242, 0.895214…\n$ `Dump+` <dbl> 0.21090996, 0.06252775, 0.20023803, 0.21469246, 0.33…\n$ `Dump-` <dbl> 0.6911482, 0.8283703, 0.6755285, 0.7006317, 0.556895…\n$ Tcells <dbl> 0.2804264, 0.6748298, 0.6119129, 0.6314431, 0.439643…\n$ `Vd2+` <dbl> 0.008120361, 0.007265620, 0.004651313, 0.011348967, …\n$ `Vd2-` <dbl> 0.9918796, 0.9927344, 0.9953487, 0.9886510, 0.995246…\n$ `Va7.2+` <dbl> 0.014480704, 0.015774991, 0.015794019, 0.017023451, …\n$ `Va7.2-` <dbl> 0.9773989, 0.9769594, 0.9795547, 0.9716276, 0.981924…\n$ `CD4+` <dbl> 0.6341164, 0.6119112, 0.6639621, 0.4378944, 0.739256…\n$ `CD4-` <dbl> 0.3432825, 0.3650482, 0.3155925, 0.5337331, 0.242668…\n$ `CD8+` <dbl> 0.2734826, 0.3357696, 0.2862104, 0.4861231, 0.195063…\n$ `CD8-` <dbl> 0.06979990, 0.02927858, 0.02938209, 0.04761008, 0.04…\n$ Tcells_count <int> 164771, 208241, 371723, 111552, 291777, 271870, 4879…\n$ lymphocytes_count <int> 587573, 308583, 607477, 176662, 663667, 510730, 7262…\n$ Monocytes <dbl> 0.11796509, 0.09477437, 0.01545999, 0.01449297, 0.04…\n$ Debris <dbl> 0.13723513, 0.13973396, 0.04212072, 0.05873854, 0.15…\n$ CD45_count <int> 915203, 1438047, 820570, 271304, 940733, 675857, 921…\n\n\nWe notice that while similar to the str() output, glimpse() handles spacing a little differently, and includes the dimensions at the top. However, we can also retrieve the dimensions directly using the dim() function (which maintains the row followed by column position convention of base R (ex. [196,31]))\n\ndim(Data)\n\n[1] 196 31", "crumbs": [ "About", "Intro to R", - "03 - Inside a .FCS file" + "04 - Intro to Tidyverse" ] }, { - "objectID": "course/03_InsideFCSFile/index.html#flowcore", - "href": "course/03_InsideFCSFile/index.html#flowcore", - "title": "03 - Inside an FCS File", - "section": "flowCore", - "text": "flowCore\nWe will be using the flowCore package, which is the oldest and most-frequently downloaded flow cytometry package on Bioconductor.\n\n\nCode\n# I have attached this code for anyone that is interested in seeing how these plots were made. The content is not part of today's lesson, so if you are just starting off, we will cover the details of data-tidying and creating ggplot objects over the next several weeks. Best, David\n\n# Load required packages via a library call\n\nlibrary(dplyr) # CRAN\nlibrary(stringr) # CRAN\nlibrary(ggplot2) # CRAN\n#library(plotly) # Using the :: to access \n\n# Loading in the dataset contained within the .csv file\nBioconductorFlow_path <- file.path(PathToDataFolder, \"BioconductorFlow.csv\")\nBioconductorFlowPackages <- read.csv(BioconductorFlow_path, check.names=FALSE)\nBioconductorFlowPackages <- BioconductorFlowPackages |>\n arrange(desc(since)) |> mutate(package = factor(package, levels = package))\n\n# Newer Base R Pipe : |> \n# Older mostly equivalent Magrittr Pipe %>% \n\n\n\n\nCode\n# Notice the code-chunk eval arguments above dictate the shape of the final rendered plot. \n\n# Taking the imported dataset and passing it to ggplot2 to create the first plot. \n\nplot <- ggplot(BioconductorFlowPackages,\n aes(x = 0, xend = since, y = package, yend = package)) +\n geom_segment(linewidth = 2, color = \"steelblue\") +\n scale_x_continuous(trans = \"reverse\", \n breaks = seq(0, max(BioconductorFlowPackages$since), by = 5)) +\n labs(\n x = \"Years in Bioconductor\",\n y = NULL,\n title = \"Bioconductor Flow Cytometry R packages\"\n ) +\n theme_bw()\n\n# Taking the static plot and making it interactive using the plotly package\n\nplotly::ggplotly(plot)\n\n\n\n\n\n\n\n\nCode\n# Retrieving the names of Bioconductor flow cytometry R packages in correct release order. \n\nHistoricalOrder <- BioconductorFlowPackages |> pull(package)\n\n# Bringing in 2025 package usage dataset from a .csv file\nBioconductorUsage_path <- file.path(PathToDataFolder, \"BioconductorDownloads.csv\")\nBioconductorUsage <- read.csv(BioconductorUsage_path, check.names=FALSE)\nBioconductorUsage <- BioconductorUsage |> dplyr::filter(Month %in% \"all\")\n\n# Note, dplyr::filter is used due to flowCore also having a filter function, which causes conflicts once it is attached to the local environment. \n\n# Combining both data.frames for use in the plot\n\nDataset <- left_join(BioconductorFlowPackages, BioconductorUsage, by=\"package\")\n\n# Rearranging the order in which packages are displayed\n\nDataset$package <- factor(Dataset$package, levels=HistoricalOrder)\n\n\n\n\nCode\n# Generating the 2nd plot with ggplot2\n\nplot <- ggplot(Dataset, aes(x = since, y = Nb_of_distinct_IPs)) +\n geom_point(aes(color = package), size = 3, alpha = 0.7) + \n labs(\n x = \"Years in Bioconductor\",\n y = \"Number of Yearly Downloads\",\n title = \"\",\n color = \"Package\"\n ) +\n theme_bw()\n\n# Making it interactive with plotly\n\nplotly::ggplotly(plot)\n\n\n\n\n\n\nflowCore is also one of the many Bioconductor packages maintained by Mike Jiang. In many ways (as those who completed the optional take-home problems for Week #1 know) reminiscent of this xkcd comic:\n\nAs with all our R packages, we first need to make sure flowCore is attached to our local environment via the library call.\n\nlibrary(flowCore)\n\nThe function we will be using today is the read.FCS() function. Do you remember how to access the help documentation?\n\n\nCode\n# Or when in Positron, hovering over the highlighted function name within the code-chunk\n\n?flowCore::read.FCS\n\n\nTo start, lets select just the first .fcs file. We will do this by indexing the first item within fcs_files via the square brackets [].\n\nfirstfile <- fcs_files[1]\nfirstfile\n\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"", + "objectID": "course/04_IntroToTidyverse/index.html#column-value-type", + "href": "course/04_IntroToTidyverse/index.html#column-value-type", + "title": "04 - Introduction to Tidyverse", + "section": "Column value type", + "text": "Column value type\nAs we saw last week, functions often need values that match a certain type (the paintbrush needing paint analogy). As we inspect the columns of Data, we can notice some of the columns contain values within that are character (ie. “char”) values. Others appear to contain numeric values (which are subtyped as either double (“ie. dbl”) or integer (ie. “int”)). At first glance, we do not appear to have any logical (ie. TRUE or FALSE) columns in this dataset.\n\nIf we were trying to verify type of values contained within a data.frame column, we could employ several similarly-named functions (is.character(), is.numeric() or is.logical()) to check\n\n# colnames(Data) # To recheck the column names\n\nis.character(Data$bid)\n\n[1] TRUE\n\n\n\nis.numeric(Data$bid)\n\n[1] FALSE\n\n\n\n# colnames(Data) # To recheck the column names\n\nis.character(Data$Tcells_count)\n\n[1] FALSE\n\n\nFor numeric columns using the is.numeric() function, we can also be subtype specific using either is.integer() or is.double().\n\n# colnames(Data) # To recheck the column names\n\nis.numeric(Data$Tcells_count)\n\n[1] TRUE\n\nis.integer(Data$Tcells_count)\n\n[1] TRUE\n\nis.double(Data$Tcells_count)\n\n[1] FALSE\n\n\n\n\n\n\n\n\nReminder\n\n\n\nAs we observed last week with keywords, column names that contain special characters like $ or spaces will need to be surrounded with tick marks in order for the function to be able to run.\n\n\n\n# colnames(Data) # To recheck the column names\nis.numeric(Data$CD8-)\n\nError in parse(text = input): <text>:2:21: unexpected ')'\n1: # colnames(Data) # To recheck the column names\n2: is.numeric(Data$CD8-)\n ^\n\n\n\n# colnames(Data) # To recheck the column names\nis.numeric(Data$`CD8-`)\n\n[1] TRUE", "crumbs": [ "About", "Intro to R", - "03 - Inside a .FCS file" + "04 - Intro to Tidyverse" ] }, { - "objectID": "course/03_InsideFCSFile/index.html#flowframe", - "href": "course/03_InsideFCSFile/index.html#flowframe", - "title": "03 - Inside an FCS File", - "section": "flowFrame", - "text": "flowFrame\nFor read.FCS(), it accepts several arguments. The argument “filename” is where we provide our file.path to .fcs file that we wish to load into R. Let’s go ahead and do so\n\nread.FCS(filename=firstfile)\n\nPlease note, if you are doing this with your own .fcs files, you will need to provide two additional arguments, “transformation” = FALSE, and “truncate_max_range” = FALSE for the files to be read in correctly. We will revisit the reasons why in Week #5.\n\nread.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE)\n\nflowFrame object 'CellCounts4L_AB_05-ND050-05.fcs'\nwith 100 cells and 61 observables:\n name desc range minRange maxRange\n$P1 Time NA 272140 0 272139\n$P2 UV1-A NA 4194304 -111 4194303\n$P3 UV2-A NA 4194304 -111 4194303\n$P4 UV3-A NA 4194304 -111 4194303\n$P5 UV4-A NA 4194304 -111 4194303\n... ... ... ... ... ...\n$P57 R4-A NA 4194304 -111 4194303\n$P58 R5-A NA 4194304 -111 4194303\n$P59 R6-A NA 4194304 -111 4194303\n$P60 R7-A NA 4194304 -111 4194303\n$P61 R8-A NA 4194304 -111 4194303\n476 keywords are stored in the 'description' slot\n\n\nIn this case, we can see the .fcs file has been read into R as a “flowFrame” object. We can also see the file name, as well as details about the number of cells, and number of columns (whether detectors (for raw spectral flow data) or fluorophores (for unmixed spectral flow data)).\n\nDirectly below we see what resembles a table. At first glance, the only column with an immediately discernable purpose is the one with the name column, which is listing the detectors present on a Cytek Aurora.\n\nAnd finally, at the bottom we reach a line that tells us that for this .fcs files, 599 keyword can be found in a description slot.\n\n\n\nSo let’s get our bearings, we have loaded in an .fcs file to R, but let’s use some of the concepts we covered last week to try to understand a bit about what type or class of object we are working with. From the output, we saw the words flowFrame object, so let’s read it back in again, but assign it to an variable/object called flowFrame so that we can use the type-discerning functions we worked with last week on.\n\nflowFrame <- read.FCS(filename=firstfile, transformation = FALSE, truncate_max_range = FALSE)\n\nAs we create this variable, if we have the session tab selected on our right secondary side bar, we see it appear:\n\nIf we were to use the type-determining functions we learned last week\n\nclass(flowFrame)\n\n[1] \"flowFrame\"\nattr(,\"package\")\n[1] \"flowCore\"\n\n\nflowFrames are a class of object with a structure defined within the flowCore package. They are used to work with the data contained within individual .fcs files. Looking again at the right secondary side bar, we can see that it shows up as a ““S4 class flowFrame package flowCore”“” with 3 slots, with the words flowFrame adjacent to it.\nA perfectly valid first reaction to first reading this is “well how should I know what any of this means?”. Powering through this initial discomfort, let’s go ahead and click on the dropdown arrow next to the variables name and see if we get any additional clarity on the issue.\n\nWhen we do so, three additional drop-downs appear. Based on the previous line that mentioned 3 slots, we could infer that each line corresponds to one of those slots.\nWhat we are encountering with flowFrame is our first example of an S4 object type. These more-complicated object types are quite common for the various Bioconductor affilitated R packages.\nThese objects will usually appear with either S4 or S3 in their metadata, and are made up of various simpler object types that are cobbled together within the larger object, usually occupying individual slots.\nWhat advantage this bundling provides will be something we revisit throughout the course as you encounter more of these S4/S3 objects.\n\n\n\nexprs\nThe first slot within the flowFrame object shows up with the name “exprs”. For the exprs object, glancing at it’s middle column, we can based on the 100 rows and 61 columns, that it is likely a matrix-style object. We might also recall we saw similar numbers in the printed output when we ran read.FCS()earlier.\n\nWhich likely means that “exprs” slot is where the MFI data for the individual acquired cells within our .fcs file is being stored. Within Positron, for a matrix object, we can click on the little grid symbol on the far right to open up the table within editor.\n\nIf we utilize the scroll bars, we can see that the individual detectors (in the case of uploading a raw spectral fcs file, they would appear as fluorophores for unmixed spectral or conventional fcs files) occupy the individual columns, which are named. The rows are not named, but number 100, matching the number of cells present in the .fcs file. Additionally, on the far left there is a little summary table about the overall data.\n\nLet’s go ahead and assign this matrix to a new variable/object so that we can explore it later. Since flowFrame is an S4 object, it’s slots can be individually accessed by adding the @ symbol and the respective slot name.\n\nMFI_Matrix <- flowFrame@exprs\n\nAlternatively, we can use the Bioconductor helper function exprs() to get data held in that slot\n\nMFI_Matrix_Alternate <- exprs(flowFrame)\n\nIn the case of the above, this displayed text output to the console would be unwiedly to display all at once. If we wanted to only see the first five rows, we could use the head() function, and provide a value of 5.\n\nhead(MFI_Matrix, 5)\n\n Time UV1-A UV2-A UV3-A UV4-A UV5-A UV6-A\n[1,] 38823 37.79983 -184.479996 353.87714 1106.22998 1145.18140 2130.21899\n[2,] 39780 234.23021 -98.456429 26.43876 70.65833 -89.93541 -29.14263\n[3,] 267292 -117.96355 40.732426 473.94574 1177.86975 1516.70935 1985.46130\n[4,] 128101 289.87671 -2.723389 -54.11960 -163.71489 32.62989 -134.90411\n[5,] 255221 -104.50541 -71.163338 567.57562 610.23627 1416.61328 2868.16040\n UV7-A UV8-A UV9-A UV10-A UV11-A UV12-A UV13-A\n[1,] 4376.34277 3246.7952 32050.65039 8123.2637 1992.5785 1070.3323 956.43573\n[2,] -26.34649 -162.6675 17.98848 271.9152 154.8575 163.5411 -32.81524\n[3,] 3658.87671 4140.1724 59792.16406 14013.7969 3427.4324 1668.7588 1071.14636\n[4,] 739.71960 402.9025 427.37534 315.6364 -223.0423 145.7121 127.03777\n[5,] 4034.58789 3234.6626 40126.46484 10325.0371 1974.0907 1033.8450 -21.57245\n UV14-A UV15-A UV16-A SSC-H SSC-A V1-A V2-A\n[1,] 290.8685 385.49921 670.97687 657613 750760.12 1171.1390 154.5628\n[2,] -104.9198 103.41382 71.41528 83481 81552.85 266.2424 705.2527\n[3,] 730.1430 214.93053 252.75406 890845 1183519.00 1196.0931 1183.1105\n[4,] -207.8978 -55.37944 -45.10131 75103 72457.33 227.9926 556.9189\n[5,] 273.6271 960.16290 341.20633 415791 501690.97 717.2498 929.9780\n V3-A V4-A V5-A V6-A V7-A V8-A\n[1,] 1346.4488525 1706.9260 1923.50940 898.2527 3162.55371 83596.5078\n[2,] 244.3218689 341.0508 381.15939 87.1600 151.68785 119.5544\n[3,] 2087.0092773 824.6352 1635.27258 1613.9069 4653.16260 176981.6094\n[4,] -0.8137281 205.4732 18.12125 179.6371 -69.50061 -132.4348\n[5,] 1358.4512939 788.6506 1208.81006 1156.7040 3118.42627 104951.2578\n V9-A V10-A V11-A V12-A V13-A V14-A\n[1,] 32506.7617 27161.5137 6236.072754 2220.303223 2023.39966 753.589355\n[2,] -79.7691 -109.1783 -73.991196 114.375542 -11.53453 124.986206\n[3,] 69236.4297 57626.8984 13175.838867 4534.874023 3434.38989 1995.172363\n[4,] 129.2739 231.8918 -5.473321 8.792875 -24.62049 -8.212234\n[5,] 42090.0781 34104.3164 7620.552734 3103.544189 2426.43359 650.836304\n V15-A V16-A FSC-H FSC-A SSC-B-H SSC-B-A B1-A\n[1,] 510.9540 228.34962 1055905 1217097.50 716733 815959.06 606.6683\n[2,] -207.3494 -28.96272 79696 83439.11 104575 103132.83 195.2795\n[3,] 1321.8030 615.05560 1092481 1453969.38 757351 982038.31 2010.5110\n[4,] -133.7503 -34.32619 64760 60415.23 67955 66806.13 -146.8936\n[5,] 290.2892 473.32599 1038362 1184479.00 425296 522873.12 1015.5981\n B2-A B3-A B4-A B5-A B6-A B7-A\n[1,] 416.98294 4172.4712 192400.0938 93929.9375 54236.3320 19342.6445\n[2,] 333.25662 332.1675 -230.9639 196.7810 292.8945 -187.2845\n[3,] 2150.21826 10106.9551 437801.5625 212176.1562 124294.3594 45068.3008\n[4,] -34.90987 165.7988 675.0156 136.3076 482.8665 133.0948\n[5,] 639.77527 6034.0200 244022.6094 118871.4609 68616.9688 24067.7949\n B8-A B9-A B10-A B11-A B12-A B13-A\n[1,] 10507.24219 9498.1270 4465.50928 1668.048096 2199.9475 1581.7345\n[2,] 70.90886 -334.3563 188.05545 -663.359619 -163.2331 27.9856\n[3,] 24289.59180 22500.1914 10624.99219 4684.497559 3471.7749 2727.3904\n[4,] 432.28091 246.8794 -94.44906 2.905877 106.8489 283.3633\n[5,] 14182.12793 13019.7100 5577.33984 2753.355957 1279.3009 1423.0276\n B14-A R1-A R2-A R3-A R4-A R5-A\n[1,] 1487.56860 147.1335 129.867630 35.90353 267.23999 49.79849\n[2,] 205.82298 -142.9224 66.516052 113.63218 -94.41375 98.13978\n[3,] 2371.95850 -128.3749 -105.482544 726.48547 18.87000 95.47879\n[4,] 33.24665 127.5455 122.607941 37.83584 -82.87500 -343.83768\n[5,] 1565.72742 -266.4482 -3.350622 -178.39566 -117.10875 -100.10384\n R6-A R7-A R8-A\n[1,] -732.7097 42.83144 248.56728\n[2,] 143.4497 -263.28741 -85.83299\n[3,] -194.4526 -84.08820 -301.46066\n[4,] 82.3745 60.27896 -94.38461\n[5,] -182.0066 184.36417 186.17207\n\n\nThis is much more workable, especially on a small laptop screen. We can see that there are names for each column corresponding to detector/fluorophore/metal depending on the .fcs file we are accessing. Lets retrieve these column names using the colnames() function.\n\nColumnNames <- colnames(MFI_Matrix)\nColumnNames\n\n $P1N $P2N $P3N $P4N $P5N $P6N $P7N $P8N \n \"Time\" \"UV1-A\" \"UV2-A\" \"UV3-A\" \"UV4-A\" \"UV5-A\" \"UV6-A\" \"UV7-A\" \n $P9N $P10N $P11N $P12N $P13N $P14N $P15N $P16N \n \"UV8-A\" \"UV9-A\" \"UV10-A\" \"UV11-A\" \"UV12-A\" \"UV13-A\" \"UV14-A\" \"UV15-A\" \n $P17N $P18N $P19N $P20N $P21N $P22N $P23N $P24N \n \"UV16-A\" \"SSC-H\" \"SSC-A\" \"V1-A\" \"V2-A\" \"V3-A\" \"V4-A\" \"V5-A\" \n $P25N $P26N $P27N $P28N $P29N $P30N $P31N $P32N \n \"V6-A\" \"V7-A\" \"V8-A\" \"V9-A\" \"V10-A\" \"V11-A\" \"V12-A\" \"V13-A\" \n $P33N $P34N $P35N $P36N $P37N $P38N $P39N $P40N \n \"V14-A\" \"V15-A\" \"V16-A\" \"FSC-H\" \"FSC-A\" \"SSC-B-H\" \"SSC-B-A\" \"B1-A\" \n $P41N $P42N $P43N $P44N $P45N $P46N $P47N $P48N \n \"B2-A\" \"B3-A\" \"B4-A\" \"B5-A\" \"B6-A\" \"B7-A\" \"B8-A\" \"B9-A\" \n $P49N $P50N $P51N $P52N $P53N $P54N $P55N $P56N \n \"B10-A\" \"B11-A\" \"B12-A\" \"B13-A\" \"B14-A\" \"R1-A\" \"R2-A\" \"R3-A\" \n $P57N $P58N $P59N $P60N $P61N \n \"R4-A\" \"R5-A\" \"R6-A\" \"R7-A\" \"R8-A\" \n\n\nSomething interesting occurred when this occurred, we can see in addition to the detector names directly above each a “$P#N” pattern appear, with # standing for increasing numbers. If we recall, we saw something similar in the first output column when we first ran read.FCS().\n\nLets break out the str() and class() functions from last week and see what we can find out about why this is occuring.\n\nstr(ColumnNames)\n\n Named chr [1:61] \"Time\" \"UV1-A\" \"UV2-A\" \"UV3-A\" \"UV4-A\" \"UV5-A\" \"UV6-A\" ...\n - attr(*, \"names\")= chr [1:61] \"$P1N\" \"$P2N\" \"$P3N\" \"$P4N\" ...\n\n\nIn this case we can see that we don’t just have a vector (list) similar to what we saw with Fluorophores object last week, because instead of a chr [1:61] we get back a Named chr [1:61] designation. What we see is that in this case, each value has a corresponding index name as well. (ex. $P1N, $P2N, etc.) Let’s double check with class() function.\n\nclass(ColumnNames)\n\n[1] \"character\"\n\n\nWe can see that everything is character, but it doesn’t inform us that each index was named. This is one of the reasons it is best when trying to see what type of an object something is, to use multiple functions, to avoid missing some important details.\nIf we were trying to remove the names, being left with just the values (similar to what we saw with the vector-style list last week), we could use the unname() function:\n\nunname(ColumnNames)\n\n [1] \"Time\" \"UV1-A\" \"UV2-A\" \"UV3-A\" \"UV4-A\" \"UV5-A\" \"UV6-A\" \n [8] \"UV7-A\" \"UV8-A\" \"UV9-A\" \"UV10-A\" \"UV11-A\" \"UV12-A\" \"UV13-A\" \n[15] \"UV14-A\" \"UV15-A\" \"UV16-A\" \"SSC-H\" \"SSC-A\" \"V1-A\" \"V2-A\" \n[22] \"V3-A\" \"V4-A\" \"V5-A\" \"V6-A\" \"V7-A\" \"V8-A\" \"V9-A\" \n[29] \"V10-A\" \"V11-A\" \"V12-A\" \"V13-A\" \"V14-A\" \"V15-A\" \"V16-A\" \n[36] \"FSC-H\" \"FSC-A\" \"SSC-B-H\" \"SSC-B-A\" \"B1-A\" \"B2-A\" \"B3-A\" \n[43] \"B4-A\" \"B5-A\" \"B6-A\" \"B7-A\" \"B8-A\" \"B9-A\" \"B10-A\" \n[50] \"B11-A\" \"B12-A\" \"B13-A\" \"B14-A\" \"R1-A\" \"R2-A\" \"R3-A\" \n[57] \"R4-A\" \"R5-A\" \"R6-A\" \"R7-A\" \"R8-A\" \n\n\n\n\nLet’s return to the right sidebar to continue our exploration, by clicking on the dropdown arrow for exprs in the side-bar\n\nThe output is less user-friendly than what we saw when clicking on the little grid. If we scroll down far enough, we get down as far as [,61], which corresponds to the total number of columns.\n\nIn base R, column order can be defined by placing the corresponding column index number after a comma “,”. So for this case, the first column would be designated would be [,1] while the last column would be designated [,61].\n\nMFI_Matrix[,1]\n\n [1] 38823 39780 267292 128101 255221 79210 196643 83855 109315 26128\n [11] 114423 120001 71831 70551 197021 239994 252611 223012 152780 171822\n [21] 172611 168464 191503 253015 73885 82221 176641 128533 4117 191632\n [31] 191229 58093 141776 265894 55593 227555 233212 248578 95165 171934\n [41] 1360 251847 195764 147503 118723 1060 90033 253553 268268 74610\n [51] 23531 150119 226391 201568 179264 79944 196686 252667 117309 3903\n [61] 77690 195142 229873 254472 179943 236618 68193 87154 28541 78622\n [71] 155664 50115 40866 70753 260118 12033 96149 20740 37461 73998\n [81] 231939 192329 88649 197664 86006 142486 159539 251298 104864 164090\n [91] 102380 218968 145182 239323 261272 118979 17202 194277 229284 258723\n\n\n\nMFI_Matrix[,61]\n\n [1] 248.567276 -85.832993 -301.460663 -94.384613 186.172073 -461.407745\n [7] 843.507080 277.516113 -106.166855 281.633545 195.927261 818.865723\n [13] 734.996460 209.356476 206.442596 279.859894 518.165222 56.947498\n [19] 285.751007 857.126343 -94.384613 -213.030518 62.585236 138.409653\n [25] 118.012444 328.255768 -61.635056 185.285233 464.384979 5.637739\n [31] -66.385956 31.229273 1198.241211 185.475266 873.279419 457.607025\n [37] -73.353951 37.880539 729.168640 221.772171 -169.512238 348.272888\n [43] -338.391022 845.534119 -4.434176 620.024597 610.269409 -193.900208\n [49] 230.830566 -23.754517 607.102112 14.949510 -34.333195 -169.132172\n [55] -96.158287 220.631958 125.297165 -15.202891 -126.057304 193.393448\n [61] 90.203819 -277.706146 590.505615 911.096619 -92.230873 347.259369\n [67] 135.559113 369.430267 -62.015125 -180.597672 -146.517868 810.440796\n [73] 134.038818 -165.268097 727.711731 -88.746880 62.901962 203.275330\n [79] 436.196289 -242.676147 -40.857769 222.278946 -170.272385 525.513245\n [85] -41.491222 176.670258 201.501648 175.530045 329.839386 474.140167\n [91] -48.142490 -174.833252 46.052090 357.584656 -26.541714 191.493088\n [97] 211.320190 124.790398 -113.324883 343.268616\n\n\nWhat would happen if used a column index number that didn’t exist? Let’s check.\n\nMFI_Matrix[,350]\n\nError in `MFI_Matrix[, 350]`:\n! subscript out of bounds\n\n\nWe get back an error message telling us the subscript is out of bounds.\nSo if columns are specified by a number after the comma (ex. [,1]), how are rows specified? In R, rows would be specified by a number before the comma [1,]\n\nMFI_Matrix[1,]\n\n Time UV1-A UV2-A UV3-A UV4-A \n 38823.00000 37.79983 -184.48000 353.87714 1106.22998 \n UV5-A UV6-A UV7-A UV8-A UV9-A \n 1145.18140 2130.21899 4376.34277 3246.79517 32050.65039 \n UV10-A UV11-A UV12-A UV13-A UV14-A \n 8123.26367 1992.57849 1070.33228 956.43573 290.86853 \n UV15-A UV16-A SSC-H SSC-A V1-A \n 385.49921 670.97687 657613.00000 750760.12500 1171.13904 \n V2-A V3-A V4-A V5-A V6-A \n 154.56281 1346.44885 1706.92603 1923.50940 898.25269 \n V7-A V8-A V9-A V10-A V11-A \n 3162.55371 83596.50781 32506.76172 27161.51367 6236.07275 \n V12-A V13-A V14-A V15-A V16-A \n 2220.30322 2023.39966 753.58936 510.95404 228.34962 \n FSC-H FSC-A SSC-B-H SSC-B-A B1-A \n1055905.00000 1217097.50000 716733.00000 815959.06250 606.66833 \n B2-A B3-A B4-A B5-A B6-A \n 416.98294 4172.47119 192400.09375 93929.93750 54236.33203 \n B7-A B8-A B9-A B10-A B11-A \n 19342.64453 10507.24219 9498.12695 4465.50928 1668.04810 \n B12-A B13-A B14-A R1-A R2-A \n 2199.94751 1581.73450 1487.56860 147.13348 129.86763 \n R3-A R4-A R5-A R6-A R7-A \n 35.90353 267.23999 49.79849 -732.70966 42.83144 \n R8-A \n 248.56728 \n\n\nAnd while not the focus of today, we could retrieve individual values from a matrix by specifying both a row and a column index number. So for example, if we wanted the MFI value for the UV1-A detector for the first acquired cell (knowing that UV1-A is the 2nd column):\n\nMFI_Matrix[1,2]\n\n UV1-A \n37.79983 \n\n\nFrom our exploration, this looks to be all the information contained within the “exprs” slot, so let’s back up and check on the next slot.\n\n\n\n\nparameters\nAs we look at the next slot in the flowFrame object, we can see that parameters looks like it is going to be another more complex object, as it is showing up as an AnnotatedDataFrame object (defined by the Biobase R package, and itself contains 4 slots).\n\n\nHaving carved our way this far into the heart of an .fcs file, we are not about to call it quits now, so CHARGE my fellow cytometrist!!! Click that drop-down arrow!\n\nHaving survived our charge into the unknown, the four parameter slots appear to be “varMetadata”, “data”, “dimLabels” and “._classVersion_”.\n\n\nvarMetadata\nFortunately for us, both “varMetadata” and “data” at least appear to be table-like objects of a type known as a “data.frame”, so lets click on the grid to open in our editor window.\nIn the case of varMetadata, we seem to have retrieved a column of metadata names.\n\nThese look reminiscent of what we saw at the top of the read.FCS() column outputs previously\n\n\n\ndata\nClicking on the grid for parameters’s data slot will end opening the actual content that was displayed.\n\nLet’s try to retrieve the data contained within this slot and save it as it’s own variable/object within our R session. First, we need to open flowFrame object, then use @ to get inside its parameters slot. Since parameters is also a complex object (AnnotatedDataFrame specifically), we will need to use another @ to get inside its data slot:\n\nParameterData <- flowFrame@parameters@data\n\nhead(ParameterData, 10)\n\n name desc range minRange maxRange\n$P1 Time <NA> 272140 0.00000 272139\n$P2 UV1-A <NA> 4194304 -111.00000 4194303\n$P3 UV2-A <NA> 4194304 -111.00000 4194303\n$P4 UV3-A <NA> 4194304 -111.00000 4194303\n$P5 UV4-A <NA> 4194304 -111.00000 4194303\n$P6 UV5-A <NA> 4194304 -111.00000 4194303\n$P7 UV6-A <NA> 4194304 -111.00000 4194303\n$P8 UV7-A <NA> 4194304 -26.34649 4194303\n$P9 UV8-A <NA> 4194304 -111.00000 4194303\n$P10 UV9-A <NA> 4194304 0.00000 4194303\n\n\nAnd similarly, we could access with the Bioconductor helper function parameters(), but we would need to specify the accessor for data outside the parenthesis.\n\nParameterData_Alternate <- parameters(flowFrame)@data\n\nIf we ran the str() function, we get the following insight into ParameterData’s object type\n\nstr(ParameterData)\n\n'data.frame': 61 obs. of 5 variables:\n $ name : 'AsIs' Named chr \"Time\" \"UV1-A\" \"UV2-A\" \"UV3-A\" ...\n ..- attr(*, \"names\")= chr [1:61] \"$P1N\" \"$P2N\" \"$P3N\" \"$P4N\" ...\n $ desc : 'AsIs' Named chr NA NA NA NA ...\n ..- attr(*, \"names\")= chr [1:61] NA NA NA NA ...\n $ range : num 272140 4194304 4194304 4194304 4194304 ...\n $ minRange: num 0 -111 -111 -111 -111 ...\n $ maxRange: num 272139 4194303 4194303 4194303 4194303 ...\n\n\nWe can see this class of object is a “data.frame”. This is one of the more common object types in R, and we will be seeing these extensively throughout the course. We see that each of the columns appears to be designated by a $ followed by the column name, and then type of column (numeric, character, etc).\n\nIf we are trying to see these columns in R, we notice that data.frame is not like the previous S4 class objets we interacted with, as the @ symbol after doesn’t bring up any suggestions\n\nParameterData@\n\nBy contrast, adding the $ we saw when using the str() function does retrieve the underlying information\n\nParameterData$\n\n\nAs you become more familiar with R, remembering to check what kind of object you are working with, and how to access the contents will with practice become more familiar to you.\nSimilar to what we saw with a matrix, we can subset a data.frame based on the column or row index using square brackets [].\n\nParameterData[,1]\n\n $P1N $P2N $P3N $P4N $P5N $P6N $P7N $P8N \n \"Time\" \"UV1-A\" \"UV2-A\" \"UV3-A\" \"UV4-A\" \"UV5-A\" \"UV6-A\" \"UV7-A\" \n $P9N $P10N $P11N $P12N $P13N $P14N $P15N $P16N \n \"UV8-A\" \"UV9-A\" \"UV10-A\" \"UV11-A\" \"UV12-A\" \"UV13-A\" \"UV14-A\" \"UV15-A\" \n $P17N $P18N $P19N $P20N $P21N $P22N $P23N $P24N \n \"UV16-A\" \"SSC-H\" \"SSC-A\" \"V1-A\" \"V2-A\" \"V3-A\" \"V4-A\" \"V5-A\" \n $P25N $P26N $P27N $P28N $P29N $P30N $P31N $P32N \n \"V6-A\" \"V7-A\" \"V8-A\" \"V9-A\" \"V10-A\" \"V11-A\" \"V12-A\" \"V13-A\" \n $P33N $P34N $P35N $P36N $P37N $P38N $P39N $P40N \n \"V14-A\" \"V15-A\" \"V16-A\" \"FSC-H\" \"FSC-A\" \"SSC-B-H\" \"SSC-B-A\" \"B1-A\" \n $P41N $P42N $P43N $P44N $P45N $P46N $P47N $P48N \n \"B2-A\" \"B3-A\" \"B4-A\" \"B5-A\" \"B6-A\" \"B7-A\" \"B8-A\" \"B9-A\" \n $P49N $P50N $P51N $P52N $P53N $P54N $P55N $P56N \n \"B10-A\" \"B11-A\" \"B12-A\" \"B13-A\" \"B14-A\" \"R1-A\" \"R2-A\" \"R3-A\" \n $P57N $P58N $P59N $P60N $P61N \n \"R4-A\" \"R5-A\" \"R6-A\" \"R7-A\" \"R8-A\" \n\n\nThe individual detectors or fluorophore appear under “name”. For now, based on what we know, the $P# appears to be some sort of name being used as an internal consistent reference to the respective.\n“desc” is appearing empty for this raw spectral fcs file, but if you were to checked an unmixed file, this would be occupied the marker/ligand name assigned to it during the experiment setup.\n“range”, “minRange” and “maxRange” are beyond the scope of today, but are used by both instrument manufacturers and software vendors when setting appropiate scaling for a plot. For the actual details, see the Flow Cytometry Standard documentation.\nHaving exhausted our options under parameters “varMetadata” and “data” slots, let’s continue to the next slot.\n\n\ndimLabels\n\nIn this case, not much is returned. Yey!\n\nflowFrame@parameters@dimLabels\n\n[1] \"rowNames\" \"columnNames\"\n\n\n\n\nclassVersion\nContinuing on to the last slot “.__classVersion__”\n\nflowFrame@parameters@.__classVersion__\n\nAnnotatedDataFrame \n \"1.1.0\" \n\n\nAlso mercifully short, both of these seem to be more involved in defining the S4 class object, and don’t contain anything we need to retrieve today.\n\n\n\n\nDescription\nAt this point, we have explored both “exprs” and “parameter” slots for the flowFrame object we created. Let’s tackle the final slot, named description.\n\nWhen doing so, a very large list is opened within the Positron variables window. While we could scroll through it, it might be easier to retrieve certain number of rows via the console to make interpreting this more structured.\n\nTo retrieve the list itself, we would need to access the description slot of the flowFrame object. Since it is a slot, we will need to use the @ accessor.\n\n\nDescriptionList <- flowFrame@description\n\n\nDescriptionList \n\n$`$BEGINANALYSIS`\n[1] \"0\"\n\n$`$BEGINDATA`\n[1] \"33312\"\n\n$`$BEGINSTEXT`\n[1] \"0\"\n\n$`$BTIM`\n[1] \"13:55:29.85\"\n\n$`$BYTEORD`\n[1] \"4,3,2,1\"\n\n$`$CYT`\n[1] \"Aurora\"\n\n$`$CYTOLIB_VERSION`\n[1] \"2.22.0\"\n\n$`$CYTSN`\n[1] \"V0333\"\n\n$`$DATATYPE`\n[1] \"F\"\n\n$`$DATE`\n[1] \"04-Aug-2025\"\n\n$`$ENDANALYSIS`\n[1] \"0\"\n\n$`$ENDDATA`\n[1] \"57711\"\n\n$`$ENDSTEXT`\n[1] \"0\"\n\n$`$ETIM`\n[1] \"13:55:57.02\"\n\n$`$FIL`\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n$`$INST`\n[1] \"UMBC\"\n\n$`$MODE`\n[1] \"L\"\n\n$`$NEXTDATA`\n[1] \"0\"\n\n$`$OP`\n[1] \"David Rach\"\n\n$`$P10B`\n[1] \"32\"\n\n$`$P10E`\n[1] \"0,0\"\n\n$`$P10N`\n[1] \"UV9-A\"\n\n$`$P10R`\n[1] \"4194304\"\n\n$`$P10TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P10V`\n[1] \"710\"\n\n$`$P11B`\n[1] \"32\"\n\n$`$P11E`\n[1] \"0,0\"\n\n$`$P11N`\n[1] \"UV10-A\"\n\n$`$P11R`\n[1] \"4194304\"\n\n$`$P11TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P11V`\n[1] \"377\"\n\n$`$P12B`\n[1] \"32\"\n\n$`$P12E`\n[1] \"0,0\"\n\n$`$P12N`\n[1] \"UV11-A\"\n\n$`$P12R`\n[1] \"4194304\"\n\n$`$P12TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P12V`\n[1] \"469\"\n\n$`$P13B`\n[1] \"32\"\n\n$`$P13E`\n[1] \"0,0\"\n\n$`$P13N`\n[1] \"UV12-A\"\n\n$`$P13R`\n[1] \"4194304\"\n\n$`$P13TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P13V`\n[1] \"434\"\n\n$`$P14B`\n[1] \"32\"\n\n$`$P14E`\n[1] \"0,0\"\n\n$`$P14N`\n[1] \"UV13-A\"\n\n$`$P14R`\n[1] \"4194304\"\n\n$`$P14TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P14V`\n[1] \"564\"\n\n$`$P15B`\n[1] \"32\"\n\n$`$P15E`\n[1] \"0,0\"\n\n$`$P15N`\n[1] \"UV14-A\"\n\n$`$P15R`\n[1] \"4194304\"\n\n$`$P15TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P15V`\n[1] \"975\"\n\n$`$P16B`\n[1] \"32\"\n\n$`$P16E`\n[1] \"0,0\"\n\n$`$P16N`\n[1] \"UV15-A\"\n\n$`$P16R`\n[1] \"4194304\"\n\n$`$P16TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P16V`\n[1] \"737\"\n\n$`$P17B`\n[1] \"32\"\n\n$`$P17E`\n[1] \"0,0\"\n\n$`$P17N`\n[1] \"UV16-A\"\n\n$`$P17R`\n[1] \"4194304\"\n\n$`$P17TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P17V`\n[1] \"1069\"\n\n$`$P18B`\n[1] \"32\"\n\n$`$P18E`\n[1] \"0,0\"\n\n$`$P18N`\n[1] \"SSC-H\"\n\n$`$P18R`\n[1] \"4194304\"\n\n$`$P18TYPE`\n[1] \"Side_Scatter\"\n\n$`$P18V`\n[1] \"334\"\n\n$`$P19B`\n[1] \"32\"\n\n$`$P19E`\n[1] \"0,0\"\n\n$`$P19N`\n[1] \"SSC-A\"\n\n$`$P19R`\n[1] \"4194304\"\n\n$`$P19TYPE`\n[1] \"Side_Scatter\"\n\n$`$P19V`\n[1] \"334\"\n\n$`$P1B`\n[1] \"32\"\n\n$`$P1E`\n[1] \"0,0\"\n\n$`$P1N`\n[1] \"Time\"\n\n$`$P1R`\n[1] \"272140\"\n\n$`$P1TYPE`\n[1] \"Time\"\n\n$`$P20B`\n[1] \"32\"\n\n$`$P20E`\n[1] \"0,0\"\n\n$`$P20N`\n[1] \"V1-A\"\n\n$`$P20R`\n[1] \"4194304\"\n\n$`$P20TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P20V`\n[1] \"352\"\n\n$`$P21B`\n[1] \"32\"\n\n$`$P21E`\n[1] \"0,0\"\n\n$`$P21N`\n[1] \"V2-A\"\n\n$`$P21R`\n[1] \"4194304\"\n\n$`$P21TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P21V`\n[1] \"412\"\n\n$`$P22B`\n[1] \"32\"\n\n$`$P22E`\n[1] \"0,0\"\n\n$`$P22N`\n[1] \"V3-A\"\n\n$`$P22R`\n[1] \"4194304\"\n\n$`$P22TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P22V`\n[1] \"304\"\n\n$`$P23B`\n[1] \"32\"\n\n$`$P23E`\n[1] \"0,0\"\n\n$`$P23N`\n[1] \"V4-A\"\n\n$`$P23R`\n[1] \"4194304\"\n\n$`$P23TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P23V`\n[1] \"217\"\n\n$`$P24B`\n[1] \"32\"\n\n$`$P24E`\n[1] \"0,0\"\n\n$`$P24N`\n[1] \"V5-A\"\n\n$`$P24R`\n[1] \"4194304\"\n\n$`$P24TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P24V`\n[1] \"257\"\n\n$`$P25B`\n[1] \"32\"\n\n$`$P25E`\n[1] \"0,0\"\n\n$`$P25N`\n[1] \"V6-A\"\n\n$`$P25R`\n[1] \"4194304\"\n\n$`$P25TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P25V`\n[1] \"218\"\n\n$`$P26B`\n[1] \"32\"\n\n$`$P26E`\n[1] \"0,0\"\n\n$`$P26N`\n[1] \"V7-A\"\n\n$`$P26R`\n[1] \"4194304\"\n\n$`$P26TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P26V`\n[1] \"303\"\n\n$`$P27B`\n[1] \"32\"\n\n$`$P27E`\n[1] \"0,0\"\n\n$`$P27N`\n[1] \"V8-A\"\n\n$`$P27R`\n[1] \"4194304\"\n\n$`$P27TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P27V`\n[1] \"461\"\n\n$`$P28B`\n[1] \"32\"\n\n$`$P28E`\n[1] \"0,0\"\n\n$`$P28N`\n[1] \"V9-A\"\n\n$`$P28R`\n[1] \"4194304\"\n\n$`$P28TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P28V`\n[1] \"320\"\n\n$`$P29B`\n[1] \"32\"\n\n$`$P29E`\n[1] \"0,0\"\n\n$`$P29N`\n[1] \"V10-A\"\n\n$`$P29R`\n[1] \"4194304\"\n\n$`$P29TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P29V`\n[1] \"359\"\n\n$`$P2B`\n[1] \"32\"\n\n$`$P2E`\n[1] \"0,0\"\n\n$`$P2N`\n[1] \"UV1-A\"\n\n$`$P2R`\n[1] \"4194304\"\n\n$`$P2TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P2V`\n[1] \"1008\"\n\n$`$P30B`\n[1] \"32\"\n\n$`$P30E`\n[1] \"0,0\"\n\n$`$P30N`\n[1] \"V11-A\"\n\n$`$P30R`\n[1] \"4194304\"\n\n$`$P30TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P30V`\n[1] \"271\"\n\n$`$P31B`\n[1] \"32\"\n\n$`$P31E`\n[1] \"0,0\"\n\n$`$P31N`\n[1] \"V12-A\"\n\n$`$P31R`\n[1] \"4194304\"\n\n$`$P31TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P31V`\n[1] \"234\"\n\n$`$P32B`\n[1] \"32\"\n\n$`$P32E`\n[1] \"0,0\"\n\n$`$P32N`\n[1] \"V13-A\"\n\n$`$P32R`\n[1] \"4194304\"\n\n$`$P32TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P32V`\n[1] \"236\"\n\n$`$P33B`\n[1] \"32\"\n\n$`$P33E`\n[1] \"0,0\"\n\n$`$P33N`\n[1] \"V14-A\"\n\n$`$P33R`\n[1] \"4194304\"\n\n$`$P33TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P33V`\n[1] \"318\"\n\n$`$P34B`\n[1] \"32\"\n\n$`$P34E`\n[1] \"0,0\"\n\n$`$P34N`\n[1] \"V15-A\"\n\n$`$P34R`\n[1] \"4194304\"\n\n$`$P34TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P34V`\n[1] \"602\"\n\n$`$P35B`\n[1] \"32\"\n\n$`$P35E`\n[1] \"0,0\"\n\n$`$P35N`\n[1] \"V16-A\"\n\n$`$P35R`\n[1] \"4194304\"\n\n$`$P35TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P35V`\n[1] \"372\"\n\n$`$P36B`\n[1] \"32\"\n\n$`$P36E`\n[1] \"0,0\"\n\n$`$P36N`\n[1] \"FSC-H\"\n\n$`$P36R`\n[1] \"4194304\"\n\n$`$P36TYPE`\n[1] \"Forward_Scatter\"\n\n$`$P36V`\n[1] \"55\"\n\n$`$P37B`\n[1] \"32\"\n\n$`$P37E`\n[1] \"0,0\"\n\n$`$P37N`\n[1] \"FSC-A\"\n\n$`$P37R`\n[1] \"4194304\"\n\n$`$P37TYPE`\n[1] \"Forward_Scatter\"\n\n$`$P37V`\n[1] \"55\"\n\n$`$P38B`\n[1] \"32\"\n\n$`$P38E`\n[1] \"0,0\"\n\n$`$P38N`\n[1] \"SSC-B-H\"\n\n$`$P38R`\n[1] \"4194304\"\n\n$`$P38TYPE`\n[1] \"Side_Scatter\"\n\n$`$P38V`\n[1] \"241\"\n\n$`$P39B`\n[1] \"32\"\n\n$`$P39E`\n[1] \"0,0\"\n\n$`$P39N`\n[1] \"SSC-B-A\"\n\n$`$P39R`\n[1] \"4194304\"\n\n$`$P39TYPE`\n[1] \"Side_Scatter\"\n\n$`$P39V`\n[1] \"241\"\n\n$`$P3B`\n[1] \"32\"\n\n$`$P3E`\n[1] \"0,0\"\n\n$`$P3N`\n[1] \"UV2-A\"\n\n$`$P3R`\n[1] \"4194304\"\n\n$`$P3TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P3V`\n[1] \"286\"\n\n$`$P40B`\n[1] \"32\"\n\n$`$P40E`\n[1] \"0,0\"\n\n$`$P40N`\n[1] \"B1-A\"\n\n$`$P40R`\n[1] \"4194304\"\n\n$`$P40TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P40V`\n[1] \"1013\"\n\n$`$P41B`\n[1] \"32\"\n\n$`$P41E`\n[1] \"0,0\"\n\n$`$P41N`\n[1] \"B2-A\"\n\n$`$P41R`\n[1] \"4194304\"\n\n$`$P41TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P41V`\n[1] \"483\"\n\n$`$P42B`\n[1] \"32\"\n\n$`$P42E`\n[1] \"0,0\"\n\n$`$P42N`\n[1] \"B3-A\"\n\n$`$P42R`\n[1] \"4194304\"\n\n$`$P42TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P42V`\n[1] \"471\"\n\n$`$P43B`\n[1] \"32\"\n\n$`$P43E`\n[1] \"0,0\"\n\n$`$P43N`\n[1] \"B4-A\"\n\n$`$P43R`\n[1] \"4194304\"\n\n$`$P43TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P43V`\n[1] \"473\"\n\n$`$P44B`\n[1] \"32\"\n\n$`$P44E`\n[1] \"0,0\"\n\n$`$P44N`\n[1] \"B5-A\"\n\n$`$P44R`\n[1] \"4194304\"\n\n$`$P44TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P44V`\n[1] \"467\"\n\n$`$P45B`\n[1] \"32\"\n\n$`$P45E`\n[1] \"0,0\"\n\n$`$P45N`\n[1] \"B6-A\"\n\n$`$P45R`\n[1] \"4194304\"\n\n$`$P45TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P45V`\n[1] \"284\"\n\n$`$P46B`\n[1] \"32\"\n\n$`$P46E`\n[1] \"0,0\"\n\n$`$P46N`\n[1] \"B7-A\"\n\n$`$P46R`\n[1] \"4194304\"\n\n$`$P46TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P46V`\n[1] \"531\"\n\n$`$P47B`\n[1] \"32\"\n\n$`$P47E`\n[1] \"0,0\"\n\n$`$P47N`\n[1] \"B8-A\"\n\n$`$P47R`\n[1] \"4194304\"\n\n$`$P47TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P47V`\n[1] \"432\"\n\n$`$P48B`\n[1] \"32\"\n\n$`$P48E`\n[1] \"0,0\"\n\n$`$P48N`\n[1] \"B9-A\"\n\n$`$P48R`\n[1] \"4194304\"\n\n$`$P48TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P48V`\n[1] \"675\"\n\n$`$P49B`\n[1] \"32\"\n\n$`$P49E`\n[1] \"0,0\"\n\n$`$P49N`\n[1] \"B10-A\"\n\n$`$P49R`\n[1] \"4194304\"\n\n$`$P49TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P49V`\n[1] \"490\"\n\n$`$P4B`\n[1] \"32\"\n\n$`$P4E`\n[1] \"0,0\"\n\n$`$P4N`\n[1] \"UV3-A\"\n\n$`$P4R`\n[1] \"4194304\"\n\n$`$P4TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P4V`\n[1] \"677\"\n\n$`$P50B`\n[1] \"32\"\n\n$`$P50E`\n[1] \"0,0\"\n\n$`$P50N`\n[1] \"B11-A\"\n\n$`$P50R`\n[1] \"4194304\"\n\n$`$P50TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P50V`\n[1] \"286\"\n\n$`$P51B`\n[1] \"32\"\n\n$`$P51E`\n[1] \"0,0\"\n\n$`$P51N`\n[1] \"B12-A\"\n\n$`$P51R`\n[1] \"4194304\"\n\n$`$P51TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P51V`\n[1] \"407\"\n\n$`$P52B`\n[1] \"32\"\n\n$`$P52E`\n[1] \"0,0\"\n\n$`$P52N`\n[1] \"B13-A\"\n\n$`$P52R`\n[1] \"4194304\"\n\n$`$P52TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P52V`\n[1] \"700\"\n\n$`$P53B`\n[1] \"32\"\n\n$`$P53E`\n[1] \"0,0\"\n\n$`$P53N`\n[1] \"B14-A\"\n\n$`$P53R`\n[1] \"4194304\"\n\n$`$P53TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P53V`\n[1] \"693\"\n\n$`$P54B`\n[1] \"32\"\n\n$`$P54E`\n[1] \"0,0\"\n\n$`$P54N`\n[1] \"R1-A\"\n\n$`$P54R`\n[1] \"4194304\"\n\n$`$P54TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P54V`\n[1] \"158\"\n\n$`$P55B`\n[1] \"32\"\n\n$`$P55E`\n[1] \"0,0\"\n\n$`$P55N`\n[1] \"R2-A\"\n\n$`$P55R`\n[1] \"4194304\"\n\n$`$P55TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P55V`\n[1] \"245\"\n\n$`$P56B`\n[1] \"32\"\n\n$`$P56E`\n[1] \"0,0\"\n\n$`$P56N`\n[1] \"R3-A\"\n\n$`$P56R`\n[1] \"4194304\"\n\n$`$P56TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P56V`\n[1] \"338\"\n\n$`$P57B`\n[1] \"32\"\n\n$`$P57E`\n[1] \"0,0\"\n\n$`$P57N`\n[1] \"R4-A\"\n\n$`$P57R`\n[1] \"4194304\"\n\n$`$P57TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P57V`\n[1] \"238\"\n\n$`$P58B`\n[1] \"32\"\n\n$`$P58E`\n[1] \"0,0\"\n\n$`$P58N`\n[1] \"R5-A\"\n\n$`$P58R`\n[1] \"4194304\"\n\n$`$P58TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P58V`\n[1] \"191\"\n\n$`$P59B`\n[1] \"32\"\n\n$`$P59E`\n[1] \"0,0\"\n\n$`$P59N`\n[1] \"R6-A\"\n\n$`$P59R`\n[1] \"4194304\"\n\n$`$P59TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P59V`\n[1] \"274\"\n\n$`$P5B`\n[1] \"32\"\n\n$`$P5E`\n[1] \"0,0\"\n\n$`$P5N`\n[1] \"UV4-A\"\n\n$`$P5R`\n[1] \"4194304\"\n\n$`$P5TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P5V`\n[1] \"1022\"\n\n$`$P60B`\n[1] \"32\"\n\n$`$P60E`\n[1] \"0,0\"\n\n$`$P60N`\n[1] \"R7-A\"\n\n$`$P60R`\n[1] \"4194304\"\n\n$`$P60TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P60V`\n[1] \"524\"\n\n$`$P61B`\n[1] \"32\"\n\n$`$P61E`\n[1] \"0,0\"\n\n$`$P61N`\n[1] \"R8-A\"\n\n$`$P61R`\n[1] \"4194304\"\n\n$`$P61TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P61V`\n[1] \"243\"\n\n$`$P6B`\n[1] \"32\"\n\n$`$P6E`\n[1] \"0,0\"\n\n$`$P6N`\n[1] \"UV5-A\"\n\n$`$P6R`\n[1] \"4194304\"\n\n$`$P6TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P6V`\n[1] \"616\"\n\n$`$P7B`\n[1] \"32\"\n\n$`$P7E`\n[1] \"0,0\"\n\n$`$P7N`\n[1] \"UV6-A\"\n\n$`$P7R`\n[1] \"4194304\"\n\n$`$P7TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P7V`\n[1] \"506\"\n\n$`$P8B`\n[1] \"32\"\n\n$`$P8E`\n[1] \"0,0\"\n\n$`$P8N`\n[1] \"UV7-A\"\n\n$`$P8R`\n[1] \"4194304\"\n\n$`$P8TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P8V`\n[1] \"661\"\n\n$`$P9B`\n[1] \"32\"\n\n$`$P9E`\n[1] \"0,0\"\n\n$`$P9N`\n[1] \"UV8-A\"\n\n$`$P9R`\n[1] \"4194304\"\n\n$`$P9TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P9V`\n[1] \"514\"\n\n$`$PAR`\n[1] \"61\"\n\n$`$PROJ`\n[1] \"CellCounts4L_AB_05\"\n\n$`$SPILLOVER`\n UV1-A UV2-A UV3-A UV4-A UV5-A UV6-A UV7-A UV8-A UV9-A UV10-A UV11-A\n [1,] 1e+00 0 0 0 0 0 0 0 0 0 0\n [2,] 1e-06 1 0 0 0 0 0 0 0 0 0\n [3,] 0e+00 0 1 0 0 0 0 0 0 0 0\n [4,] 0e+00 0 0 1 0 0 0 0 0 0 0\n [5,] 0e+00 0 0 0 1 0 0 0 0 0 0\n [6,] 0e+00 0 0 0 0 1 0 0 0 0 0\n [7,] 0e+00 0 0 0 0 0 1 0 0 0 0\n [8,] 0e+00 0 0 0 0 0 0 1 0 0 0\n [9,] 0e+00 0 0 0 0 0 0 0 1 0 0\n[10,] 0e+00 0 0 0 0 0 0 0 0 1 0\n[11,] 0e+00 0 0 0 0 0 0 0 0 0 1\n[12,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[13,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[14,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[15,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[16,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[17,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[18,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[19,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[20,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[21,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[22,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[23,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[24,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[25,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[26,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[27,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[28,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[29,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[30,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[31,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[32,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[33,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[34,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[35,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[36,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[37,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[38,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[39,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[40,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[41,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[42,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[43,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[44,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[45,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[46,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[47,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[48,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[49,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[50,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[51,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[52,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[53,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[54,] 0e+00 0 0 0 0 0 0 0 0 0 0\n UV12-A UV13-A UV14-A UV15-A UV16-A V1-A V2-A V3-A V4-A V5-A V6-A V7-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 1 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 1 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 1 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 1 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 1 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 1 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 1 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 1 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 1 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 1 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 1 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 1\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0\n V8-A V9-A V10-A V11-A V12-A V13-A V14-A V15-A V16-A B1-A B2-A B3-A B4-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n B5-A B6-A B7-A B8-A B9-A B10-A B11-A B12-A B13-A B14-A R1-A R2-A R3-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n R4-A R5-A R6-A R7-A R8-A\n [1,] 0 0 0 0 0\n [2,] 0 0 0 0 0\n [3,] 0 0 0 0 0\n [4,] 0 0 0 0 0\n [5,] 0 0 0 0 0\n [6,] 0 0 0 0 0\n [7,] 0 0 0 0 0\n [8,] 0 0 0 0 0\n [9,] 0 0 0 0 0\n[10,] 0 0 0 0 0\n[11,] 0 0 0 0 0\n[12,] 0 0 0 0 0\n[13,] 0 0 0 0 0\n[14,] 0 0 0 0 0\n[15,] 0 0 0 0 0\n[16,] 0 0 0 0 0\n[17,] 0 0 0 0 0\n[18,] 0 0 0 0 0\n[19,] 0 0 0 0 0\n[20,] 0 0 0 0 0\n[21,] 0 0 0 0 0\n[22,] 0 0 0 0 0\n[23,] 0 0 0 0 0\n[24,] 0 0 0 0 0\n[25,] 0 0 0 0 0\n[26,] 0 0 0 0 0\n[27,] 0 0 0 0 0\n[28,] 0 0 0 0 0\n[29,] 0 0 0 0 0\n[30,] 0 0 0 0 0\n[31,] 0 0 0 0 0\n[32,] 0 0 0 0 0\n[33,] 0 0 0 0 0\n[34,] 0 0 0 0 0\n[35,] 0 0 0 0 0\n[36,] 0 0 0 0 0\n[37,] 0 0 0 0 0\n[38,] 0 0 0 0 0\n[39,] 0 0 0 0 0\n[40,] 0 0 0 0 0\n[41,] 0 0 0 0 0\n[42,] 0 0 0 0 0\n[43,] 0 0 0 0 0\n[44,] 0 0 0 0 0\n[45,] 0 0 0 0 0\n[46,] 0 0 0 0 0\n[47,] 0 0 0 0 0\n[48,] 0 0 0 0 0\n[49,] 0 0 0 0 0\n[50,] 1 0 0 0 0\n[51,] 0 1 0 0 0\n[52,] 0 0 1 0 0\n[53,] 0 0 0 1 0\n[54,] 0 0 0 0 1\n\n$`$TIMESTEP`\n[1] \"0.0001\"\n\n$`$TOT`\n[1] \"100\"\n\n$`$VOL`\n[1] \"30.31\"\n\n$`APPLY COMPENSATION`\n[1] \"FALSE\"\n\n$CHARSET\n[1] \"utf-8\"\n\n$CREATOR\n[1] \"SpectroFlo 3.3.0\"\n\n$FCSversion\n[1] \"3\"\n\n$FILENAME\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n$`FSC ASF`\n[1] \"1.21\"\n\n$GROUPNAME\n[1] \"ND050\"\n\n$GUID\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n$LASER1ASF\n[1] \"1.09\"\n\n$LASER1DELAY\n[1] \"-19.525\"\n\n$LASER1NAME\n[1] \"Violet\"\n\n$LASER2ASF\n[1] \"1.14\"\n\n$LASER2DELAY\n[1] \"0\"\n\n$LASER2NAME\n[1] \"Blue\"\n\n$LASER3ASF\n[1] \"1.02\"\n\n$LASER3DELAY\n[1] \"20.15\"\n\n$LASER3NAME\n[1] \"Red\"\n\n$LASER4ASF\n[1] \"0.92\"\n\n$LASER4DELAY\n[1] \"40.725\"\n\n$LASER4NAME\n[1] \"UV\"\n\n$ORIGINALGUID\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n$P10DISPLAY\n[1] \"LOG\"\n\n$P11DISPLAY\n[1] \"LOG\"\n\n$P12DISPLAY\n[1] \"LOG\"\n\n$P13DISPLAY\n[1] \"LOG\"\n\n$P14DISPLAY\n[1] \"LOG\"\n\n$P15DISPLAY\n[1] \"LOG\"\n\n$P16DISPLAY\n[1] \"LOG\"\n\n$P17DISPLAY\n[1] \"LOG\"\n\n$P18DISPLAY\n[1] \"LIN\"\n\n$P19DISPLAY\n[1] \"LIN\"\n\n$P1DISPLAY\n[1] \"LOG\"\n\n$P20DISPLAY\n[1] \"LOG\"\n\n$P21DISPLAY\n[1] \"LOG\"\n\n$P22DISPLAY\n[1] \"LOG\"\n\n$P23DISPLAY\n[1] \"LOG\"\n\n$P24DISPLAY\n[1] \"LOG\"\n\n$P25DISPLAY\n[1] \"LOG\"\n\n$P26DISPLAY\n[1] \"LOG\"\n\n$P27DISPLAY\n[1] \"LOG\"\n\n$P28DISPLAY\n[1] \"LOG\"\n\n$P29DISPLAY\n[1] \"LOG\"\n\n$P2DISPLAY\n[1] \"LOG\"\n\n$P30DISPLAY\n[1] \"LOG\"\n\n$P31DISPLAY\n[1] \"LOG\"\n\n$P32DISPLAY\n[1] \"LOG\"\n\n$P33DISPLAY\n[1] \"LOG\"\n\n$P34DISPLAY\n[1] \"LOG\"\n\n$P35DISPLAY\n[1] \"LOG\"\n\n$P36DISPLAY\n[1] \"LIN\"\n\n$P37DISPLAY\n[1] \"LIN\"\n\n$P38DISPLAY\n[1] \"LIN\"\n\n$P39DISPLAY\n[1] \"LIN\"\n\n$P3DISPLAY\n[1] \"LOG\"\n\n$P40DISPLAY\n[1] \"LOG\"\n\n$P41DISPLAY\n[1] \"LOG\"\n\n$P42DISPLAY\n[1] \"LOG\"\n\n$P43DISPLAY\n[1] \"LOG\"\n\n$P44DISPLAY\n[1] \"LOG\"\n\n$P45DISPLAY\n[1] \"LOG\"\n\n$P46DISPLAY\n[1] \"LOG\"\n\n$P47DISPLAY\n[1] \"LOG\"\n\n$P48DISPLAY\n[1] \"LOG\"\n\n$P49DISPLAY\n[1] \"LOG\"\n\n$P4DISPLAY\n[1] \"LOG\"\n\n$P50DISPLAY\n[1] \"LOG\"\n\n$P51DISPLAY\n[1] \"LOG\"\n\n$P52DISPLAY\n[1] \"LOG\"\n\n$P53DISPLAY\n[1] \"LOG\"\n\n$P54DISPLAY\n[1] \"LOG\"\n\n$P55DISPLAY\n[1] \"LOG\"\n\n$P56DISPLAY\n[1] \"LOG\"\n\n$P57DISPLAY\n[1] \"LOG\"\n\n$P58DISPLAY\n[1] \"LOG\"\n\n$P59DISPLAY\n[1] \"LOG\"\n\n$P5DISPLAY\n[1] \"LOG\"\n\n$P60DISPLAY\n[1] \"LOG\"\n\n$P61DISPLAY\n[1] \"LOG\"\n\n$P6DISPLAY\n[1] \"LOG\"\n\n$P7DISPLAY\n[1] \"LOG\"\n\n$P8DISPLAY\n[1] \"LOG\"\n\n$P9DISPLAY\n[1] \"LOG\"\n\n$THRESHOLD\n[1] \"(FSC,50000)\"\n\n$TUBENAME\n[1] \"05\"\n\n$USERSETTINGNAME\n[1] \"DTR_CellCounts\"\n\n$`WINDOW EXTENSION`\n[1] \"3\"\n\n\nThe returned list is a little too large to reasonably explore. We can attempt to subset using the head() function as shown below\n\nhead(DescriptionList, 5)\n\n$`$BEGINANALYSIS`\n[1] \"0\"\n\n$`$BEGINDATA`\n[1] \"33312\"\n\n$`$BEGINSTEXT`\n[1] \"0\"\n\n$`$BTIM`\n[1] \"13:55:29.85\"\n\n$`$BYTEORD`\n[1] \"4,3,2,1\"\n\n\nAlternatively, it might be better to subset based on position index\n\nDescriptionList[1:10]\n\n$`$BEGINANALYSIS`\n[1] \"0\"\n\n$`$BEGINDATA`\n[1] \"33312\"\n\n$`$BEGINSTEXT`\n[1] \"0\"\n\n$`$BTIM`\n[1] \"13:55:29.85\"\n\n$`$BYTEORD`\n[1] \"4,3,2,1\"\n\n$`$CYT`\n[1] \"Aurora\"\n\n$`$CYTOLIB_VERSION`\n[1] \"2.22.0\"\n\n$`$CYTSN`\n[1] \"V0333\"\n\n$`$DATATYPE`\n[1] \"F\"\n\n$`$DATE`\n[1] \"04-Aug-2025\"\n\n\nAnd just as we saw for exprs and parameters, there is also a Bioconductor helper keyword() function to access this same information directly from the flowFrame.\n\nDescriptionList_Alternate <- keyword(flowFrame)\n\nIf we run the class() function, we can see that DescriptionList is an actual “list”.\n\nclass(DescriptionList)\n\n[1] \"list\"\n\n\nThis is in contrast to the vectors we have previously generated. While these are also list like, they are what are known as as atomic list, which contain values that are all either characters, numerics or logicals.\n\nFluorophores <- c(\"BV421\", \"FITC\", \"PE\", \"APC\")\nclass(Fluorophores)\n\n[1] \"character\"\n\n\n\nPanelAntibodyCounts <- c(5, 12, 19, 26, 34, 46, 51)\nclass(PanelAntibodyCounts)\n\n[1] \"numeric\"\n\n\n\nSpecimenIndexToKeep <- c(TRUE, TRUE, FALSE, TRUE)\nclass(SpecimenIndexToKeep)\n\n[1] \"logical\"\n\n\nA list on the other hand is not restricted to contain objects composed entirely of a certain atomic type. For example, I could include the three previous vectors into a list using the list() function.\n\nMyListofVectors <- list(Fluorophores, PanelAntibodyCounts, SpecimenIndexToKeep)\nstr(MyListofVectors)\n\nList of 3\n $ : chr [1:4] \"BV421\" \"FITC\" \"PE\" \"APC\"\n $ : num [1:7] 5 12 19 26 34 46 51\n $ : logi [1:4] TRUE TRUE FALSE TRUE\n\n\nWe can see that with the Description/Keyword list we retrieved from our flowFrame shares a somewhat similar format.\n\nstr(DescriptionList[1:10])\n\nList of 10\n $ $BEGINANALYSIS : chr \"0\"\n $ $BEGINDATA : chr \"33312\"\n $ $BEGINSTEXT : chr \"0\"\n $ $BTIM : chr \"13:55:29.85\"\n $ $BYTEORD : chr \"4,3,2,1\"\n $ $CYT : chr \"Aurora\"\n $ $CYTOLIB_VERSION: chr \"2.22.0\"\n $ $CYTSN : chr \"V0333\"\n $ $DATATYPE : chr \"F\"\n $ $DATE : chr \"04-Aug-2025\"\n\n\nBut in this case, there are also names present ($BEGINANALYSIS, $BEGINDATA, etc). What if we had tried to provide names to our List of Vectors? Would the format match?\nWhen we assigned a name to each of the vectors (by providing an equal to = ), we get the same kind of structure format to what we see in Description.\n\nMyNamedListofVectors <- list(FluorophoresNamed=Fluorophores,\n PanelAntibodyCountsNamed=PanelAntibodyCounts,\n SpecimenIndexToKeepNamed=SpecimenIndexToKeep)\n\nstr(MyNamedListofVectors)\n\nList of 3\n $ FluorophoresNamed : chr [1:4] \"BV421\" \"FITC\" \"PE\" \"APC\"\n $ PanelAntibodyCountsNamed: num [1:7] 5 12 19 26 34 46 51\n $ SpecimenIndexToKeepNamed: logi [1:4] TRUE TRUE FALSE TRUE\n\n\nWe could then subsequently be able to isolate items from that list using the $ operator.\n\nMyNamedListofVectors$\n\n\nAlternatively, we could also access by list index position\n\nMyNamedListofVectors[1]\n\n$FluorophoresNamed\n[1] \"BV421\" \"FITC\" \"PE\" \"APC\" \n\n\nRemembering back to the original output from read.FCS() we remember that it mentioned 599 keywords being in the description slot, so now we know that this is what was being referenced.", + "objectID": "course/04_IntroToTidyverse/index.html#select-columns", + "href": "course/04_IntroToTidyverse/index.html#select-columns", + "title": "04 - Introduction to Tidyverse", + "section": "select (Columns)", + "text": "select (Columns)\nNow that we have read in our data, and have a general picture of the structure and contents, lets start learning the main dplyr functions we will be using throughout the course. To do this, lets go ahead and attach dplyr to our local environment via the library() call.\n\nlibrary(dplyr)\n\nWe will start with the select() function. It is used to “select” a column from a data.frame type object. In the simplest usage, we provide the name of our data.frame variable/object as the first argument after the opening parenthesis. This is then followed by the name of the column we want to select as the second argument (let’s place around the “” around the column name for now)\n\nDateColumn <- select(Data, \"Date\")\nDateColumn[1:10,]\n\n [1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [6] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n\n\nThis results in the column being selected, resulting in the new object containing only that subsetted out column from the original Data object.\n\nPipe Operators\nWhile the above line of code works to select a column, when you encounter select() out in the wild, it will more often be in a line of code that looks like this:\n\nDateColumn <- Data |> select(\"Date\")\nDateColumn[1:10,]\n\n [1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [6] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n\n\n… “What in the world is that thing |> ?” …\nGlad you asked! An useful feature of the tidyverse packages is their use of pipes (either the original magrittr package’s “%>%” or base R version >4.1.0's “|>”“), usually appearing like this:\n\n# magrittr %>% pipe\n\nDateColumn <- Data %>% select(\"Date\")\n\n# base R |> pipe\nDateColumn <- Data |> select(\"Date\")\n\n… “How do we interpret/read that line of code?” …\nLet’s break it down, starting off just to the right of the assignment arrow (<-) with our data.frame “Data”.\n\nData\n\nWe then proceed to read to the right, adding in our pipe operator. The pipe essentially serves as an intermediate passing the contents of data onward to the subsequent function.\n\nData |> \n\nIn our case, this subsequent function is the select() function, which will select a particular column from the available data. When using the pipe, the first argument slot we saw for “select(Data,”Date”)” is occupied by the contents Data that are being passed by the pipe.\n\nData |> select()\n\nTo complete the transfer, we provide the desired column name to select() to act on (“Date” in this case)\n\nData |> select(\"Date\")\n\nIn summary, contents of Data are passed to the pipe, and select runs on those contents to select the Date column\n\nData |> select(\"Date\")\n\nOne of the main advantages for using pipes, is they can be linked together, passing resulting objects of one operation on to the next pipe and subsequent function. We can see this in operation in the example below where we hand off the isolated “Date” column to the nrow() function to determine number of rows. We will use pipes throughout the course, so you will gradually gain familiarity as you encounter them.\n\nData |> select(\"Date\") |> nrow()\n\n[1] 196\n\n\nFor those with prior R experience, you will be more familiar with the older magrittr %>% pipe. The base R |> pipe operator was introduced starting with R version 4.1.0. While mostly interchangeable, they have a few nuances that come into play for more advance use cases. You are welcome to use whichever you prefer (my current preference is |> as it’s one less key to press).\n\n\nR Quirks\n\n\n\n\n\n\nOdd R Behavior # 1\n\n\n\nWhile we used “” around the column name in our previous example, unlike what we encountered with install.packages() when we forget to include quotation marks, select() still retrieves the correct column despite Date not being an environment variable:\n\n\n\nData |> select(Date) |> head(3)\n\n Date\n1 2025-07-26\n2 2025-07-26\n3 2025-07-26\n\n\n\n\n\n\n\n\n.\n\n\n\nThe reasons for this Odd R behaviour are nuanced and for another day. For now, think of it as dplyr R package is picking up the slack, and using context to infer it’s a column name and not an environmental variable/object.\n\n\n\n\nSelecting multiple columns\nSince we are able to select one column, can we select multiple (similar to a [Data[,2:5]] approach in base R)? We can, and they can be positioned anywhere within the data.frame:\n\nSubset <- Data |> select(bid, timepoint, Condition, Tcells, `CD8+`, `CD4+`)\n\nhead(Subset, 3)\n\n bid timepoint Condition Tcells CD8+ CD4+\n1 INF0052 0 Ctrl 0.2804264 0.2734826 0.6341164\n2 INF0100 0 Ctrl 0.6748298 0.3357696 0.6119112\n3 INF0100 4 Ctrl 0.6119129 0.2862104 0.6639621\n\n\nYou will notice that the order in which we selected the columns will dictate their position in the subsetted data.frame object:\n\nSubset <- Data |> select(bid, Tcells, `CD8+`, `CD4+`, timepoint, Condition, )\n\nhead(Subset, 3)\n\n bid Tcells CD8+ CD4+ timepoint Condition\n1 INF0052 0.2804264 0.2734826 0.6341164 0 Ctrl\n2 INF0100 0.6748298 0.3357696 0.6119112 0 Ctrl\n3 INF0100 0.6119129 0.2862104 0.6639621 4 Ctrl", "crumbs": [ "About", "Intro to R", - "03 - Inside a .FCS file" + "04 - Intro to Tidyverse" ] }, { - "objectID": "course/03_InsideFCSFile/index.html#early-metadata", - "href": "course/03_InsideFCSFile/index.html#early-metadata", - "title": "03 - Inside an FCS File", - "section": "Early Metadata", - "text": "Early Metadata\nWithin the initial portion, we are getting back metadata keywords related to where and how the particular file was acquired. Keywords of potential interest include:\n\n\n\n\n\n\nStart Time\n\n\n\nWhat time was the .fcs file acquired\n\n\n\n\nDescriptionList$`$BTIM`\n\n[1] \"13:55:29.85\"\n\n\n\n\n\n\n\n\n\nCytometer\n\n\n\nWhat type of cytometer was the .fcs file acquired on\n\n\n\n\nDescriptionList$`$CYT`\n\n[1] \"Aurora\"\n\n\n\n\n\n\n\n\n\n\n\nCytometer Serial Number\n\n\n\nManufacturer Serial Number of the Cytometer\n\n\n\n\nDescriptionList$`$CYTSN`\n\n[1] \"V0333\"\n\n\n\n\n\n\n\n\n\nFCS File Acquisition Date\n\n\n\nWhat was the date of acquisition\n\n\n\n\nDescriptionList$`$DATE`\n\n[1] \"04-Aug-2025\"\n\n\n\n\n\n\n\n\n\n\n\nAcquisition End Time\n\n\n\nWhat time was acquisition stopped\n\n\n\n\nDescriptionList$`$ETIM`\n\n[1] \"13:55:57.02\"\n\n\n\n\n\n\n\n\n\nFile Name\n\n\n\nName of the .fcs file\n\n\n\n\nDescriptionList$`$FIL`\n\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n\n\n\n\n\n\n\n\n\n\nOperator\n\n\n\nWho acquired the .fcs file\n\n\n\n\nDescriptionList$`$OP`\n\n[1] \"David Rach\"", + "objectID": "course/04_IntroToTidyverse/index.html#relocate", + "href": "course/04_IntroToTidyverse/index.html#relocate", + "title": "04 - Introduction to Tidyverse", + "section": "relocate", + "text": "relocate\nAlternatively, we occasionally want to move one column. While we could respecify the location using select(), specifying the names of all the other columns out in a line of code to just to rearrange one does not sound like a good use of time. For this reason, the second dplyr function we will be learning is the relocate() function.\nLooking at our Data object, let’s say we wanted to move the Tcells column from its current location to the second column position (right after the bid column). The line of code to do so would look like:\n\nData |> relocate(Tcells, .after=bid) |> head(3)\n\n bid Tcells timepoint Condition Date infant_sex ptype root\n1 INF0052 0.2804264 0 Ctrl 2025-07-26 Male HEU-hi 2098368\n2 INF0100 0.6748298 0 Ctrl 2025-07-26 Male HEU-lo 2020184\n3 INF0100 0.6119129 4 Ctrl 2025-07-26 Male HEU-lo 1155040\n singletsFSC singletsSSC singletsSSCB CD45 NotMonocytes nonDebris\n1 1894070 1666179 1537396 0.5952943 0.8820349 0.8627649\n2 1791890 1697083 1579098 0.9106762 0.9052256 0.8602660\n3 1033320 875465 845446 0.9705765 0.9845400 0.9578793\n lymphocytes live Dump+ Dump- Vd2+ Vd2- Va7.2+\n1 0.6420138 0.9020581 0.21090996 0.6911482 0.008120361 0.9918796 0.01448070\n2 0.2145848 0.8908981 0.06252775 0.8283703 0.007265620 0.9927344 0.01577499\n3 0.7403110 0.8757665 0.20023803 0.6755285 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Monocytes Debris CD45_count\n1 587573 0.11796509 0.13723513 915203\n2 308583 0.09477437 0.13973396 1438047\n3 607477 0.01545999 0.04212072 820570\n\n# |> head(3) is used only to make the website output visualization manageable :D\n\nSimilar to what we saw with select(), this approach can also be used for more than 1 column:\n\nData |> relocate(Tcells, Monocytes, .after=bid) |> head(3)\n\n bid Tcells Monocytes timepoint Condition Date infant_sex ptype\n1 INF0052 0.2804264 0.11796509 0 Ctrl 2025-07-26 Male HEU-hi\n2 INF0100 0.6748298 0.09477437 0 Ctrl 2025-07-26 Male HEU-lo\n3 INF0100 0.6119129 0.01545999 4 Ctrl 2025-07-26 Male HEU-lo\n root singletsFSC singletsSSC singletsSSCB CD45 NotMonocytes nonDebris\n1 2098368 1894070 1666179 1537396 0.5952943 0.8820349 0.8627649\n2 2020184 1791890 1697083 1579098 0.9106762 0.9052256 0.8602660\n3 1155040 1033320 875465 845446 0.9705765 0.9845400 0.9578793\n lymphocytes live Dump+ Dump- Vd2+ Vd2- Va7.2+\n1 0.6420138 0.9020581 0.21090996 0.6911482 0.008120361 0.9918796 0.01448070\n2 0.2145848 0.8908981 0.06252775 0.8283703 0.007265620 0.9927344 0.01577499\n3 0.7403110 0.8757665 0.20023803 0.6755285 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Debris CD45_count\n1 587573 0.13723513 915203\n2 308583 0.13973396 1438047\n3 607477 0.04212072 820570\n\n# |> head(3) is used only to make the website output visualization manageable :D\n\nWe can also modify the argument so that columns are placed before a certain column\n\nData |> relocate(Tcells, .before=Date) |> head(3)\n\n bid timepoint Condition Tcells Date infant_sex ptype root\n1 INF0052 0 Ctrl 0.2804264 2025-07-26 Male HEU-hi 2098368\n2 INF0100 0 Ctrl 0.6748298 2025-07-26 Male HEU-lo 2020184\n3 INF0100 4 Ctrl 0.6119129 2025-07-26 Male HEU-lo 1155040\n singletsFSC singletsSSC singletsSSCB CD45 NotMonocytes nonDebris\n1 1894070 1666179 1537396 0.5952943 0.8820349 0.8627649\n2 1791890 1697083 1579098 0.9106762 0.9052256 0.8602660\n3 1033320 875465 845446 0.9705765 0.9845400 0.9578793\n lymphocytes live Dump+ Dump- Vd2+ Vd2- Va7.2+\n1 0.6420138 0.9020581 0.21090996 0.6911482 0.008120361 0.9918796 0.01448070\n2 0.2145848 0.8908981 0.06252775 0.8283703 0.007265620 0.9927344 0.01577499\n3 0.7403110 0.8757665 0.20023803 0.6755285 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Monocytes Debris CD45_count\n1 587573 0.11796509 0.13723513 915203\n2 308583 0.09477437 0.13973396 1438047\n3 607477 0.01545999 0.04212072 820570\n\n# |> head(3) is used only to make the website output visualization manageable :D\n\nAnd as we might suspect, we could specify a column index location rather than using a column name.\n\nData |> relocate(Date, .before=1) |> head(3)\n\n Date bid timepoint Condition infant_sex ptype root singletsFSC\n1 2025-07-26 INF0052 0 Ctrl Male HEU-hi 2098368 1894070\n2 2025-07-26 INF0100 0 Ctrl Male HEU-lo 2020184 1791890\n3 2025-07-26 INF0100 4 Ctrl Male HEU-lo 1155040 1033320\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1666179 1537396 0.5952943 0.8820349 0.8627649 0.6420138\n2 1697083 1579098 0.9106762 0.9052256 0.8602660 0.2145848\n3 875465 845446 0.9705765 0.9845400 0.9578793 0.7403110\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9020581 0.21090996 0.6911482 0.2804264 0.008120361 0.9918796 0.01448070\n2 0.8908981 0.06252775 0.8283703 0.6748298 0.007265620 0.9927344 0.01577499\n3 0.8757665 0.20023803 0.6755285 0.6119129 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Monocytes Debris CD45_count\n1 587573 0.11796509 0.13723513 915203\n2 308583 0.09477437 0.13973396 1438047\n3 607477 0.01545999 0.04212072 820570\n\n# |> head(3) is used only to make the website output visualization manageable :D", "crumbs": [ "About", "Intro to R", - "03 - Inside a .FCS file" + "04 - Intro to Tidyverse" ] }, { - "objectID": "course/03_InsideFCSFile/index.html#detector-values", - "href": "course/03_InsideFCSFile/index.html#detector-values", - "title": "03 - Inside an FCS File", - "section": "Detector Values", - "text": "Detector Values\nThe next major stretch of keywords encode parameter values associated with the individual detectors for at the time of acquisition.\n\nDetectors <- DescriptionList[20:384]\nDetectors\n\n$`$P10B`\n[1] \"32\"\n\n$`$P10E`\n[1] \"0,0\"\n\n$`$P10N`\n[1] \"UV9-A\"\n\n$`$P10R`\n[1] \"4194304\"\n\n$`$P10TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P10V`\n[1] \"710\"\n\n$`$P11B`\n[1] \"32\"\n\n$`$P11E`\n[1] \"0,0\"\n\n$`$P11N`\n[1] \"UV10-A\"\n\n$`$P11R`\n[1] \"4194304\"\n\n$`$P11TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P11V`\n[1] \"377\"\n\n$`$P12B`\n[1] \"32\"\n\n$`$P12E`\n[1] \"0,0\"\n\n$`$P12N`\n[1] \"UV11-A\"\n\n$`$P12R`\n[1] \"4194304\"\n\n$`$P12TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P12V`\n[1] \"469\"\n\n$`$P13B`\n[1] \"32\"\n\n$`$P13E`\n[1] \"0,0\"\n\n$`$P13N`\n[1] \"UV12-A\"\n\n$`$P13R`\n[1] \"4194304\"\n\n$`$P13TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P13V`\n[1] \"434\"\n\n$`$P14B`\n[1] \"32\"\n\n$`$P14E`\n[1] \"0,0\"\n\n$`$P14N`\n[1] \"UV13-A\"\n\n$`$P14R`\n[1] \"4194304\"\n\n$`$P14TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P14V`\n[1] \"564\"\n\n$`$P15B`\n[1] \"32\"\n\n$`$P15E`\n[1] \"0,0\"\n\n$`$P15N`\n[1] \"UV14-A\"\n\n$`$P15R`\n[1] \"4194304\"\n\n$`$P15TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P15V`\n[1] \"975\"\n\n$`$P16B`\n[1] \"32\"\n\n$`$P16E`\n[1] \"0,0\"\n\n$`$P16N`\n[1] \"UV15-A\"\n\n$`$P16R`\n[1] \"4194304\"\n\n$`$P16TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P16V`\n[1] \"737\"\n\n$`$P17B`\n[1] \"32\"\n\n$`$P17E`\n[1] \"0,0\"\n\n$`$P17N`\n[1] \"UV16-A\"\n\n$`$P17R`\n[1] \"4194304\"\n\n$`$P17TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P17V`\n[1] \"1069\"\n\n$`$P18B`\n[1] \"32\"\n\n$`$P18E`\n[1] \"0,0\"\n\n$`$P18N`\n[1] \"SSC-H\"\n\n$`$P18R`\n[1] \"4194304\"\n\n$`$P18TYPE`\n[1] \"Side_Scatter\"\n\n$`$P18V`\n[1] \"334\"\n\n$`$P19B`\n[1] \"32\"\n\n$`$P19E`\n[1] \"0,0\"\n\n$`$P19N`\n[1] \"SSC-A\"\n\n$`$P19R`\n[1] \"4194304\"\n\n$`$P19TYPE`\n[1] \"Side_Scatter\"\n\n$`$P19V`\n[1] \"334\"\n\n$`$P1B`\n[1] \"32\"\n\n$`$P1E`\n[1] \"0,0\"\n\n$`$P1N`\n[1] \"Time\"\n\n$`$P1R`\n[1] \"272140\"\n\n$`$P1TYPE`\n[1] \"Time\"\n\n$`$P20B`\n[1] \"32\"\n\n$`$P20E`\n[1] \"0,0\"\n\n$`$P20N`\n[1] \"V1-A\"\n\n$`$P20R`\n[1] \"4194304\"\n\n$`$P20TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P20V`\n[1] \"352\"\n\n$`$P21B`\n[1] \"32\"\n\n$`$P21E`\n[1] \"0,0\"\n\n$`$P21N`\n[1] \"V2-A\"\n\n$`$P21R`\n[1] \"4194304\"\n\n$`$P21TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P21V`\n[1] \"412\"\n\n$`$P22B`\n[1] \"32\"\n\n$`$P22E`\n[1] \"0,0\"\n\n$`$P22N`\n[1] \"V3-A\"\n\n$`$P22R`\n[1] \"4194304\"\n\n$`$P22TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P22V`\n[1] \"304\"\n\n$`$P23B`\n[1] \"32\"\n\n$`$P23E`\n[1] \"0,0\"\n\n$`$P23N`\n[1] \"V4-A\"\n\n$`$P23R`\n[1] \"4194304\"\n\n$`$P23TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P23V`\n[1] \"217\"\n\n$`$P24B`\n[1] \"32\"\n\n$`$P24E`\n[1] \"0,0\"\n\n$`$P24N`\n[1] \"V5-A\"\n\n$`$P24R`\n[1] \"4194304\"\n\n$`$P24TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P24V`\n[1] \"257\"\n\n$`$P25B`\n[1] \"32\"\n\n$`$P25E`\n[1] \"0,0\"\n\n$`$P25N`\n[1] \"V6-A\"\n\n$`$P25R`\n[1] \"4194304\"\n\n$`$P25TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P25V`\n[1] \"218\"\n\n$`$P26B`\n[1] \"32\"\n\n$`$P26E`\n[1] \"0,0\"\n\n$`$P26N`\n[1] \"V7-A\"\n\n$`$P26R`\n[1] \"4194304\"\n\n$`$P26TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P26V`\n[1] \"303\"\n\n$`$P27B`\n[1] \"32\"\n\n$`$P27E`\n[1] \"0,0\"\n\n$`$P27N`\n[1] \"V8-A\"\n\n$`$P27R`\n[1] \"4194304\"\n\n$`$P27TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P27V`\n[1] \"461\"\n\n$`$P28B`\n[1] \"32\"\n\n$`$P28E`\n[1] \"0,0\"\n\n$`$P28N`\n[1] \"V9-A\"\n\n$`$P28R`\n[1] \"4194304\"\n\n$`$P28TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P28V`\n[1] \"320\"\n\n$`$P29B`\n[1] \"32\"\n\n$`$P29E`\n[1] \"0,0\"\n\n$`$P29N`\n[1] \"V10-A\"\n\n$`$P29R`\n[1] \"4194304\"\n\n$`$P29TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P29V`\n[1] \"359\"\n\n$`$P2B`\n[1] \"32\"\n\n$`$P2E`\n[1] \"0,0\"\n\n$`$P2N`\n[1] \"UV1-A\"\n\n$`$P2R`\n[1] \"4194304\"\n\n$`$P2TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P2V`\n[1] \"1008\"\n\n$`$P30B`\n[1] \"32\"\n\n$`$P30E`\n[1] \"0,0\"\n\n$`$P30N`\n[1] \"V11-A\"\n\n$`$P30R`\n[1] \"4194304\"\n\n$`$P30TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P30V`\n[1] \"271\"\n\n$`$P31B`\n[1] \"32\"\n\n$`$P31E`\n[1] \"0,0\"\n\n$`$P31N`\n[1] \"V12-A\"\n\n$`$P31R`\n[1] \"4194304\"\n\n$`$P31TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P31V`\n[1] \"234\"\n\n$`$P32B`\n[1] \"32\"\n\n$`$P32E`\n[1] \"0,0\"\n\n$`$P32N`\n[1] \"V13-A\"\n\n$`$P32R`\n[1] \"4194304\"\n\n$`$P32TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P32V`\n[1] \"236\"\n\n$`$P33B`\n[1] \"32\"\n\n$`$P33E`\n[1] \"0,0\"\n\n$`$P33N`\n[1] \"V14-A\"\n\n$`$P33R`\n[1] \"4194304\"\n\n$`$P33TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P33V`\n[1] \"318\"\n\n$`$P34B`\n[1] \"32\"\n\n$`$P34E`\n[1] \"0,0\"\n\n$`$P34N`\n[1] \"V15-A\"\n\n$`$P34R`\n[1] \"4194304\"\n\n$`$P34TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P34V`\n[1] \"602\"\n\n$`$P35B`\n[1] \"32\"\n\n$`$P35E`\n[1] \"0,0\"\n\n$`$P35N`\n[1] \"V16-A\"\n\n$`$P35R`\n[1] \"4194304\"\n\n$`$P35TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P35V`\n[1] \"372\"\n\n$`$P36B`\n[1] \"32\"\n\n$`$P36E`\n[1] \"0,0\"\n\n$`$P36N`\n[1] \"FSC-H\"\n\n$`$P36R`\n[1] \"4194304\"\n\n$`$P36TYPE`\n[1] \"Forward_Scatter\"\n\n$`$P36V`\n[1] \"55\"\n\n$`$P37B`\n[1] \"32\"\n\n$`$P37E`\n[1] \"0,0\"\n\n$`$P37N`\n[1] \"FSC-A\"\n\n$`$P37R`\n[1] \"4194304\"\n\n$`$P37TYPE`\n[1] \"Forward_Scatter\"\n\n$`$P37V`\n[1] \"55\"\n\n$`$P38B`\n[1] \"32\"\n\n$`$P38E`\n[1] \"0,0\"\n\n$`$P38N`\n[1] \"SSC-B-H\"\n\n$`$P38R`\n[1] \"4194304\"\n\n$`$P38TYPE`\n[1] \"Side_Scatter\"\n\n$`$P38V`\n[1] \"241\"\n\n$`$P39B`\n[1] \"32\"\n\n$`$P39E`\n[1] \"0,0\"\n\n$`$P39N`\n[1] \"SSC-B-A\"\n\n$`$P39R`\n[1] \"4194304\"\n\n$`$P39TYPE`\n[1] \"Side_Scatter\"\n\n$`$P39V`\n[1] \"241\"\n\n$`$P3B`\n[1] \"32\"\n\n$`$P3E`\n[1] \"0,0\"\n\n$`$P3N`\n[1] \"UV2-A\"\n\n$`$P3R`\n[1] \"4194304\"\n\n$`$P3TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P3V`\n[1] \"286\"\n\n$`$P40B`\n[1] \"32\"\n\n$`$P40E`\n[1] \"0,0\"\n\n$`$P40N`\n[1] \"B1-A\"\n\n$`$P40R`\n[1] \"4194304\"\n\n$`$P40TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P40V`\n[1] \"1013\"\n\n$`$P41B`\n[1] \"32\"\n\n$`$P41E`\n[1] \"0,0\"\n\n$`$P41N`\n[1] \"B2-A\"\n\n$`$P41R`\n[1] \"4194304\"\n\n$`$P41TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P41V`\n[1] \"483\"\n\n$`$P42B`\n[1] \"32\"\n\n$`$P42E`\n[1] \"0,0\"\n\n$`$P42N`\n[1] \"B3-A\"\n\n$`$P42R`\n[1] \"4194304\"\n\n$`$P42TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P42V`\n[1] \"471\"\n\n$`$P43B`\n[1] \"32\"\n\n$`$P43E`\n[1] \"0,0\"\n\n$`$P43N`\n[1] \"B4-A\"\n\n$`$P43R`\n[1] \"4194304\"\n\n$`$P43TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P43V`\n[1] \"473\"\n\n$`$P44B`\n[1] \"32\"\n\n$`$P44E`\n[1] \"0,0\"\n\n$`$P44N`\n[1] \"B5-A\"\n\n$`$P44R`\n[1] \"4194304\"\n\n$`$P44TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P44V`\n[1] \"467\"\n\n$`$P45B`\n[1] \"32\"\n\n$`$P45E`\n[1] \"0,0\"\n\n$`$P45N`\n[1] \"B6-A\"\n\n$`$P45R`\n[1] \"4194304\"\n\n$`$P45TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P45V`\n[1] \"284\"\n\n$`$P46B`\n[1] \"32\"\n\n$`$P46E`\n[1] \"0,0\"\n\n$`$P46N`\n[1] \"B7-A\"\n\n$`$P46R`\n[1] \"4194304\"\n\n$`$P46TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P46V`\n[1] \"531\"\n\n$`$P47B`\n[1] \"32\"\n\n$`$P47E`\n[1] \"0,0\"\n\n$`$P47N`\n[1] \"B8-A\"\n\n$`$P47R`\n[1] \"4194304\"\n\n$`$P47TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P47V`\n[1] \"432\"\n\n$`$P48B`\n[1] \"32\"\n\n$`$P48E`\n[1] \"0,0\"\n\n$`$P48N`\n[1] \"B9-A\"\n\n$`$P48R`\n[1] \"4194304\"\n\n$`$P48TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P48V`\n[1] \"675\"\n\n$`$P49B`\n[1] \"32\"\n\n$`$P49E`\n[1] \"0,0\"\n\n$`$P49N`\n[1] \"B10-A\"\n\n$`$P49R`\n[1] \"4194304\"\n\n$`$P49TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P49V`\n[1] \"490\"\n\n$`$P4B`\n[1] \"32\"\n\n$`$P4E`\n[1] \"0,0\"\n\n$`$P4N`\n[1] \"UV3-A\"\n\n$`$P4R`\n[1] \"4194304\"\n\n$`$P4TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P4V`\n[1] \"677\"\n\n$`$P50B`\n[1] \"32\"\n\n$`$P50E`\n[1] \"0,0\"\n\n$`$P50N`\n[1] \"B11-A\"\n\n$`$P50R`\n[1] \"4194304\"\n\n$`$P50TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P50V`\n[1] \"286\"\n\n$`$P51B`\n[1] \"32\"\n\n$`$P51E`\n[1] \"0,0\"\n\n$`$P51N`\n[1] \"B12-A\"\n\n$`$P51R`\n[1] \"4194304\"\n\n$`$P51TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P51V`\n[1] \"407\"\n\n$`$P52B`\n[1] \"32\"\n\n$`$P52E`\n[1] \"0,0\"\n\n$`$P52N`\n[1] \"B13-A\"\n\n$`$P52R`\n[1] \"4194304\"\n\n$`$P52TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P52V`\n[1] \"700\"\n\n$`$P53B`\n[1] \"32\"\n\n$`$P53E`\n[1] \"0,0\"\n\n$`$P53N`\n[1] \"B14-A\"\n\n$`$P53R`\n[1] \"4194304\"\n\n$`$P53TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P53V`\n[1] \"693\"\n\n$`$P54B`\n[1] \"32\"\n\n$`$P54E`\n[1] \"0,0\"\n\n$`$P54N`\n[1] \"R1-A\"\n\n$`$P54R`\n[1] \"4194304\"\n\n$`$P54TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P54V`\n[1] \"158\"\n\n$`$P55B`\n[1] \"32\"\n\n$`$P55E`\n[1] \"0,0\"\n\n$`$P55N`\n[1] \"R2-A\"\n\n$`$P55R`\n[1] \"4194304\"\n\n$`$P55TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P55V`\n[1] \"245\"\n\n$`$P56B`\n[1] \"32\"\n\n$`$P56E`\n[1] \"0,0\"\n\n$`$P56N`\n[1] \"R3-A\"\n\n$`$P56R`\n[1] \"4194304\"\n\n$`$P56TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P56V`\n[1] \"338\"\n\n$`$P57B`\n[1] \"32\"\n\n$`$P57E`\n[1] \"0,0\"\n\n$`$P57N`\n[1] \"R4-A\"\n\n$`$P57R`\n[1] \"4194304\"\n\n$`$P57TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P57V`\n[1] \"238\"\n\n$`$P58B`\n[1] \"32\"\n\n$`$P58E`\n[1] \"0,0\"\n\n$`$P58N`\n[1] \"R5-A\"\n\n$`$P58R`\n[1] \"4194304\"\n\n$`$P58TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P58V`\n[1] \"191\"\n\n$`$P59B`\n[1] \"32\"\n\n$`$P59E`\n[1] \"0,0\"\n\n$`$P59N`\n[1] \"R6-A\"\n\n$`$P59R`\n[1] \"4194304\"\n\n$`$P59TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P59V`\n[1] \"274\"\n\n$`$P5B`\n[1] \"32\"\n\n$`$P5E`\n[1] \"0,0\"\n\n$`$P5N`\n[1] \"UV4-A\"\n\n$`$P5R`\n[1] \"4194304\"\n\n$`$P5TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P5V`\n[1] \"1022\"\n\n$`$P60B`\n[1] \"32\"\n\n$`$P60E`\n[1] \"0,0\"\n\n$`$P60N`\n[1] \"R7-A\"\n\n$`$P60R`\n[1] \"4194304\"\n\n$`$P60TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P60V`\n[1] \"524\"\n\n$`$P61B`\n[1] \"32\"\n\n$`$P61E`\n[1] \"0,0\"\n\n$`$P61N`\n[1] \"R8-A\"\n\n$`$P61R`\n[1] \"4194304\"\n\n$`$P61TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P61V`\n[1] \"243\"\n\n$`$P6B`\n[1] \"32\"\n\n$`$P6E`\n[1] \"0,0\"\n\n$`$P6N`\n[1] \"UV5-A\"\n\n$`$P6R`\n[1] \"4194304\"\n\n$`$P6TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P6V`\n[1] \"616\"\n\n$`$P7B`\n[1] \"32\"\n\n$`$P7E`\n[1] \"0,0\"\n\n$`$P7N`\n[1] \"UV6-A\"\n\n$`$P7R`\n[1] \"4194304\"\n\n$`$P7TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P7V`\n[1] \"506\"\n\n$`$P8B`\n[1] \"32\"\n\n$`$P8E`\n[1] \"0,0\"\n\n$`$P8N`\n[1] \"UV7-A\"\n\n$`$P8R`\n[1] \"4194304\"\n\n$`$P8TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P8V`\n[1] \"661\"\n\n$`$P9B`\n[1] \"32\"\n\n$`$P9E`\n[1] \"0,0\"\n\n$`$P9N`\n[1] \"UV8-A\"\n\n$`$P9R`\n[1] \"4194304\"\n\n$`$P9TYPE`\n[1] \"Raw_Fluorescence\"\n\n$`$P9V`\n[1] \"514\"\n\n\nFortunately for all involved, there is a consistently repeating pattern for the keywords corresponding to each detector. We can see that here for $P7B, $P7E, $P7N, $P7R, $P7TYPE, $P7V\n\nWhen referencing to the Flow Cytometry Standard documentation, here are what the particular keyword letters mean:\n\n\n\n\n\n\nB\n\n\n\nNumber of bits reserved for parameter number n\n\n\n\n\nDescriptionList$`$P7B`\n\n[1] \"32\"\n\n\n\n\n\n\n\n\n\nE\n\n\n\nAmplification type for parameter n. \n\n\n\n\nDescriptionList$`$P7E`\n\n[1] \"0,0\"\n\n\n\n\n\n\n\n\n\n\n\nN\n\n\n\nShort Name for parameter n. \n\n\n\n\nDescriptionList$`$P7N`\n\n[1] \"UV6-A\"\n\n\n\n\n\n\n\n\n\nR\n\n\n\nRange for parameter number n. \n\n\n\n\nDescriptionList$`$P7R`\n\n[1] \"4194304\"\n\n\n\n\n\n\n\n\n\n\n\nTYPE\n\n\n\nDetector type for parameter n. \n\n\n\n\nDescriptionList$`$P7TYPE`\n\n[1] \"Raw_Fluorescence\"\n\n\n\n\n\n\n\n\n\nV\n\n\n\nDetector voltage for parameter n. \n\n\n\n\nDescriptionList$`$P7V`\n\n[1] \"506\"\n\n\n\n\n\nWhile not immediately obvious, understanding what these keywords encoded has proven useful for our core. In our case, we have built an automated InstrumentQC dashboard for all the instruments at our core.\n\n\n\nBy extracting out from our daily QC bead .fcs files the stored N (Detector Name) and V (Gain/Voltage) values for all the individual detectors, it allows us to plot Levey-Jennings Plots for our individual instruments, giving us usually around a months warning before an individual laser begins to fail. This helps with scheduling the Field-Service Engineer visit before it starts impacting the actual data.\n\n\n\nWhile most of the detectors keywords are similar (only changing there individual name and voltage) there are a couple exceptions.\nFor the FSC/SSC parameters, instead of Raw_Fluorescence value for Type, we see the corresponding Scatter value get return. This in term is what is used by various commercial softwares to show those axis as linear instead of biexponential when selected.\n\n\n\nThis is similarly the case for the Time parameter, where in addition to Type being set to Time, the range also appears different to Raw/Scatters value.", + "objectID": "course/04_IntroToTidyverse/index.html#rename", + "href": "course/04_IntroToTidyverse/index.html#rename", + "title": "04 - Introduction to Tidyverse", + "section": "rename", + "text": "rename\nAt this point, we are able to both move and select particular columns, allowing us to rearrange and subset a larger data.frame object however we want it to appear. However, as we encountered, some of the names contain special characters and spaces, requiring use of tick marks (``) to avoid issues. How can we change a column name?\nIn base R, we could change individual column names by assigning a new value with the assignment arrow to the corresponding column name index. For example, looking at our Subset object, wen could rename CD8+ as follows:\n\ncolnames(Subset)\n\n[1] \"bid\" \"Tcells\" \"CD8+\" \"CD4+\" \"timepoint\" \"Condition\"\n\ncolnames(Subset)[3]\n\n[1] \"CD8+\"\n\n\n\ncolnames(Subset)[3] <- \"CD8Positive\"\ncolnames(Subset)\n\n[1] \"bid\" \"Tcells\" \"CD8Positive\" \"CD4+\" \"timepoint\" \n[6] \"Condition\" \n\n\nWith the tidyverse, we can use the rename() function which removes the need to look up the column index number. The way we write the argument is placing within the parenthesis the old name to the right of the equals sign, with the new name to the left\n\nRenamed <- Subset |> rename(CD4_Positive = `CD4+`)\ncolnames(Renamed)\n\n[1] \"bid\" \"Tcells\" \"CD8Positive\" \"CD4_Positive\" \"timepoint\" \n[6] \"Condition\" \n\n\nIf we wanted to rename multiple column names at once, we would just need to include a comma between the individual rename arguments within the parenthesis.\n\nRenamed_Multiple <- Subset |> rename(specimen = bid, timepoint_months = timepoint, stimulation = Condition, CD4Positive=`CD4+`)\ncolnames(Renamed_Multiple)\n\n[1] \"specimen\" \"Tcells\" \"CD8Positive\" \"CD4Positive\" \n[5] \"timepoint_months\" \"stimulation\"", "crumbs": [ "About", "Intro to R", - "03 - Inside a .FCS file" + "04 - Intro to Tidyverse" ] }, { - "objectID": "course/03_InsideFCSFile/index.html#middle-metadata", - "href": "course/03_InsideFCSFile/index.html#middle-metadata", - "title": "03 - Inside an FCS File", - "section": "Middle Metadata", - "text": "Middle Metadata\nOnce we are out of the detector keywords, we find the last of the $Metadata associated keywords.\n\nDetectors <- DescriptionList[385:398]\nDetectors\n\n$`$PAR`\n[1] \"61\"\n\n$`$PROJ`\n[1] \"CellCounts4L_AB_05\"\n\n$`$SPILLOVER`\n UV1-A UV2-A UV3-A UV4-A UV5-A UV6-A UV7-A UV8-A UV9-A UV10-A UV11-A\n [1,] 1e+00 0 0 0 0 0 0 0 0 0 0\n [2,] 1e-06 1 0 0 0 0 0 0 0 0 0\n [3,] 0e+00 0 1 0 0 0 0 0 0 0 0\n [4,] 0e+00 0 0 1 0 0 0 0 0 0 0\n [5,] 0e+00 0 0 0 1 0 0 0 0 0 0\n [6,] 0e+00 0 0 0 0 1 0 0 0 0 0\n [7,] 0e+00 0 0 0 0 0 1 0 0 0 0\n [8,] 0e+00 0 0 0 0 0 0 1 0 0 0\n [9,] 0e+00 0 0 0 0 0 0 0 1 0 0\n[10,] 0e+00 0 0 0 0 0 0 0 0 1 0\n[11,] 0e+00 0 0 0 0 0 0 0 0 0 1\n[12,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[13,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[14,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[15,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[16,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[17,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[18,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[19,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[20,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[21,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[22,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[23,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[24,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[25,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[26,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[27,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[28,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[29,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[30,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[31,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[32,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[33,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[34,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[35,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[36,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[37,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[38,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[39,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[40,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[41,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[42,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[43,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[44,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[45,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[46,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[47,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[48,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[49,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[50,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[51,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[52,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[53,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[54,] 0e+00 0 0 0 0 0 0 0 0 0 0\n UV12-A UV13-A UV14-A UV15-A UV16-A V1-A V2-A V3-A V4-A V5-A V6-A V7-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 1 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 1 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 1 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 1 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 1 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 1 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 1 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 1 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 1 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 1 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 1 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 1\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0\n V8-A V9-A V10-A V11-A V12-A V13-A V14-A V15-A V16-A B1-A B2-A B3-A B4-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n B5-A B6-A B7-A B8-A B9-A B10-A B11-A B12-A B13-A B14-A R1-A R2-A R3-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n R4-A R5-A R6-A R7-A R8-A\n [1,] 0 0 0 0 0\n [2,] 0 0 0 0 0\n [3,] 0 0 0 0 0\n [4,] 0 0 0 0 0\n [5,] 0 0 0 0 0\n [6,] 0 0 0 0 0\n [7,] 0 0 0 0 0\n [8,] 0 0 0 0 0\n [9,] 0 0 0 0 0\n[10,] 0 0 0 0 0\n[11,] 0 0 0 0 0\n[12,] 0 0 0 0 0\n[13,] 0 0 0 0 0\n[14,] 0 0 0 0 0\n[15,] 0 0 0 0 0\n[16,] 0 0 0 0 0\n[17,] 0 0 0 0 0\n[18,] 0 0 0 0 0\n[19,] 0 0 0 0 0\n[20,] 0 0 0 0 0\n[21,] 0 0 0 0 0\n[22,] 0 0 0 0 0\n[23,] 0 0 0 0 0\n[24,] 0 0 0 0 0\n[25,] 0 0 0 0 0\n[26,] 0 0 0 0 0\n[27,] 0 0 0 0 0\n[28,] 0 0 0 0 0\n[29,] 0 0 0 0 0\n[30,] 0 0 0 0 0\n[31,] 0 0 0 0 0\n[32,] 0 0 0 0 0\n[33,] 0 0 0 0 0\n[34,] 0 0 0 0 0\n[35,] 0 0 0 0 0\n[36,] 0 0 0 0 0\n[37,] 0 0 0 0 0\n[38,] 0 0 0 0 0\n[39,] 0 0 0 0 0\n[40,] 0 0 0 0 0\n[41,] 0 0 0 0 0\n[42,] 0 0 0 0 0\n[43,] 0 0 0 0 0\n[44,] 0 0 0 0 0\n[45,] 0 0 0 0 0\n[46,] 0 0 0 0 0\n[47,] 0 0 0 0 0\n[48,] 0 0 0 0 0\n[49,] 0 0 0 0 0\n[50,] 1 0 0 0 0\n[51,] 0 1 0 0 0\n[52,] 0 0 1 0 0\n[53,] 0 0 0 1 0\n[54,] 0 0 0 0 1\n\n$`$TIMESTEP`\n[1] \"0.0001\"\n\n$`$TOT`\n[1] \"100\"\n\n$`$VOL`\n[1] \"30.31\"\n\n$`APPLY COMPENSATION`\n[1] \"FALSE\"\n\n$CHARSET\n[1] \"utf-8\"\n\n$CREATOR\n[1] \"SpectroFlo 3.3.0\"\n\n$FCSversion\n[1] \"3\"\n\n$FILENAME\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n$`FSC ASF`\n[1] \"1.21\"\n\n$GROUPNAME\n[1] \"ND050\"\n\n$GUID\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n\nAmong those of potential interest\n\n\n\n\n\n\nProj\n\n\n\nOften corresponding to the experiment file name\n\n\n\n\nDescriptionList$`$PROJ`\n\n[1] \"CellCounts4L_AB_05\"\n\n\n\n\n\n\n\n\n\nSpillover\n\n\n\nWhere the internal spillover matrix is stored (we will revisit during compensation)\n\n\n\n\nDescriptionList$`$SPILLOVER`\n\n UV1-A UV2-A UV3-A UV4-A UV5-A UV6-A UV7-A UV8-A UV9-A UV10-A UV11-A\n [1,] 1e+00 0 0 0 0 0 0 0 0 0 0\n [2,] 1e-06 1 0 0 0 0 0 0 0 0 0\n [3,] 0e+00 0 1 0 0 0 0 0 0 0 0\n [4,] 0e+00 0 0 1 0 0 0 0 0 0 0\n [5,] 0e+00 0 0 0 1 0 0 0 0 0 0\n [6,] 0e+00 0 0 0 0 1 0 0 0 0 0\n [7,] 0e+00 0 0 0 0 0 1 0 0 0 0\n [8,] 0e+00 0 0 0 0 0 0 1 0 0 0\n [9,] 0e+00 0 0 0 0 0 0 0 1 0 0\n[10,] 0e+00 0 0 0 0 0 0 0 0 1 0\n[11,] 0e+00 0 0 0 0 0 0 0 0 0 1\n[12,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[13,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[14,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[15,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[16,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[17,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[18,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[19,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[20,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[21,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[22,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[23,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[24,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[25,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[26,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[27,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[28,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[29,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[30,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[31,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[32,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[33,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[34,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[35,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[36,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[37,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[38,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[39,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[40,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[41,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[42,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[43,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[44,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[45,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[46,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[47,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[48,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[49,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[50,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[51,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[52,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[53,] 0e+00 0 0 0 0 0 0 0 0 0 0\n[54,] 0e+00 0 0 0 0 0 0 0 0 0 0\n UV12-A UV13-A UV14-A UV15-A UV16-A V1-A V2-A V3-A V4-A V5-A V6-A V7-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 1 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 1 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 1 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 1 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 1 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 1 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 1 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 1 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 1 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 1 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 1 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 1\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0\n V8-A V9-A V10-A V11-A V12-A V13-A V14-A V15-A V16-A B1-A B2-A B3-A B4-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[37,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n B5-A B6-A B7-A B8-A B9-A B10-A B11-A B12-A B13-A B14-A R1-A R2-A R3-A\n [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[10,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[11,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[12,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[13,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[14,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[15,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[16,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[17,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[18,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[19,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[20,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[21,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[22,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[23,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[24,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[25,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[26,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[27,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[28,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[29,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[30,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[31,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[32,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[33,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[34,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[35,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[36,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[37,] 1 0 0 0 0 0 0 0 0 0 0 0 0\n[38,] 0 1 0 0 0 0 0 0 0 0 0 0 0\n[39,] 0 0 1 0 0 0 0 0 0 0 0 0 0\n[40,] 0 0 0 1 0 0 0 0 0 0 0 0 0\n[41,] 0 0 0 0 1 0 0 0 0 0 0 0 0\n[42,] 0 0 0 0 0 1 0 0 0 0 0 0 0\n[43,] 0 0 0 0 0 0 1 0 0 0 0 0 0\n[44,] 0 0 0 0 0 0 0 1 0 0 0 0 0\n[45,] 0 0 0 0 0 0 0 0 1 0 0 0 0\n[46,] 0 0 0 0 0 0 0 0 0 1 0 0 0\n[47,] 0 0 0 0 0 0 0 0 0 0 1 0 0\n[48,] 0 0 0 0 0 0 0 0 0 0 0 1 0\n[49,] 0 0 0 0 0 0 0 0 0 0 0 0 1\n[50,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[51,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[52,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[53,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n[54,] 0 0 0 0 0 0 0 0 0 0 0 0 0\n R4-A R5-A R6-A R7-A R8-A\n [1,] 0 0 0 0 0\n [2,] 0 0 0 0 0\n [3,] 0 0 0 0 0\n [4,] 0 0 0 0 0\n [5,] 0 0 0 0 0\n [6,] 0 0 0 0 0\n [7,] 0 0 0 0 0\n [8,] 0 0 0 0 0\n [9,] 0 0 0 0 0\n[10,] 0 0 0 0 0\n[11,] 0 0 0 0 0\n[12,] 0 0 0 0 0\n[13,] 0 0 0 0 0\n[14,] 0 0 0 0 0\n[15,] 0 0 0 0 0\n[16,] 0 0 0 0 0\n[17,] 0 0 0 0 0\n[18,] 0 0 0 0 0\n[19,] 0 0 0 0 0\n[20,] 0 0 0 0 0\n[21,] 0 0 0 0 0\n[22,] 0 0 0 0 0\n[23,] 0 0 0 0 0\n[24,] 0 0 0 0 0\n[25,] 0 0 0 0 0\n[26,] 0 0 0 0 0\n[27,] 0 0 0 0 0\n[28,] 0 0 0 0 0\n[29,] 0 0 0 0 0\n[30,] 0 0 0 0 0\n[31,] 0 0 0 0 0\n[32,] 0 0 0 0 0\n[33,] 0 0 0 0 0\n[34,] 0 0 0 0 0\n[35,] 0 0 0 0 0\n[36,] 0 0 0 0 0\n[37,] 0 0 0 0 0\n[38,] 0 0 0 0 0\n[39,] 0 0 0 0 0\n[40,] 0 0 0 0 0\n[41,] 0 0 0 0 0\n[42,] 0 0 0 0 0\n[43,] 0 0 0 0 0\n[44,] 0 0 0 0 0\n[45,] 0 0 0 0 0\n[46,] 0 0 0 0 0\n[47,] 0 0 0 0 0\n[48,] 0 0 0 0 0\n[49,] 0 0 0 0 0\n[50,] 1 0 0 0 0\n[51,] 0 1 0 0 0\n[52,] 0 0 1 0 0\n[53,] 0 0 0 1 0\n[54,] 0 0 0 0 1\n\n\n\n\n\n\n\n\n\nTOT\n\n\n\nTotal events (in this case my downsampled 100 cells)\n\n\n\n\nDescriptionList$`$TOT`\n\n[1] \"100\"\n\n\n\n\n\n\n\n\n\nVolume\n\n\n\nVolume amount acquired during acquisition.\n\n\n\n\nDescriptionList$`$VOL`\n\n[1] \"30.31\"\n\n\n\n\n\n\n\n\n\nSoftware\n\n\n\nSoftware used and version\n\n\n\n\nDescriptionList$CREATOR\n\n[1] \"SpectroFlo 3.3.0\"\n\n\n\nYou will notice at this point, the keyword names including a “$” symbol have stopped, so tick marks are no longer required (except when there is a space in the name). The only $ remaining is being used as a selector for a particular item in the list.\n\nDetectors <- DescriptionList[390:398]\nDetectors\n\n$`$VOL`\n[1] \"30.31\"\n\n$`APPLY COMPENSATION`\n[1] \"FALSE\"\n\n$CHARSET\n[1] \"utf-8\"\n\n$CREATOR\n[1] \"SpectroFlo 3.3.0\"\n\n$FCSversion\n[1] \"3\"\n\n$FILENAME\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n$`FSC ASF`\n[1] \"1.21\"\n\n$GROUPNAME\n[1] \"ND050\"\n\n$GUID\n[1] \"CellCounts4L_AB_05-ND050-05.fcs\"\n\n\n\n\n\n\n\n\nFILENAME\n\n\n\nBasically the full file.path to the .fcs file of interest.\n\n\n\n\nDescriptionList$FILENAME\n\n[1] \"data/CellCounts4L_AB_05_ND050_05.fcs\"\n\n\n\n\n\n\n\n\n\nGROUPNAME\n\n\n\nThe Name assigned to the acquisition Group.\n\n\n\n\nDescriptionList$GROUPNAME\n\n[1] \"ND050\"", + "objectID": "course/04_IntroToTidyverse/index.html#pull", + "href": "course/04_IntroToTidyverse/index.html#pull", + "title": "04 - Introduction to Tidyverse", + "section": "pull", + "text": "pull\nSometimes, we may want to retrieve individual values present in a column, to use within either a vector or a list. We can do this using the pull() function, which will retrieve the column contents and strip the column formatting\n\nData |> pull(Date) |> head(5)\n\n[1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n\n\nThis can be useful when we are doing data exploration, and trying to determine how many unique variants might be present. For example, if we wanted to see what days individual samples were acquired, we could pull() the data and pass it to the unique() function:\n\nData |> pull(Date) |> unique()\n\n[1] \"2025-07-26\" \"2025-07-29\" \"2025-07-31\" \"2025-08-05\" \"2025-08-07\"\n[6] \"2025-08-22\" \"2025-08-28\" \"2025-08-30\"", "crumbs": [ "About", "Intro to R", - "03 - Inside a .FCS file" + "04 - Intro to Tidyverse" ] }, { - "objectID": "course/03_InsideFCSFile/index.html#laser-metadata", - "href": "course/03_InsideFCSFile/index.html#laser-metadata", - "title": "03 - Inside an FCS File", - "section": "Laser Metadata", - "text": "Laser Metadata\nNext up, there is a small stretch of keywords containing the values associated with the individual lasers as far as delays and area scaling factors for a particular day (also useful when plotted).\n\nDetectors <- DescriptionList[399:410]\nDetectors\n\n$LASER1ASF\n[1] \"1.09\"\n\n$LASER1DELAY\n[1] \"-19.525\"\n\n$LASER1NAME\n[1] \"Violet\"\n\n$LASER2ASF\n[1] \"1.14\"\n\n$LASER2DELAY\n[1] \"0\"\n\n$LASER2NAME\n[1] \"Blue\"\n\n$LASER3ASF\n[1] \"1.02\"\n\n$LASER3DELAY\n[1] \"20.15\"\n\n$LASER3NAME\n[1] \"Red\"\n\n$LASER4ASF\n[1] \"0.92\"\n\n$LASER4DELAY\n[1] \"40.725\"\n\n$LASER4NAME\n[1] \"UV\"", + "objectID": "course/04_IntroToTidyverse/index.html#filter-rows", + "href": "course/04_IntroToTidyverse/index.html#filter-rows", + "title": "04 - Introduction to Tidyverse", + "section": "filter (Rows)", + "text": "filter (Rows)\nSo far, we have been working with dplyr functions primarily used when working with and subsetting columns (including select(), pull(), rename() and relocate()). What if we wanted to work with rows of a data.frame? This is where the filter() function is used.\nThe Condition column in this Dataset appears to be indicating whether the samples were stimulated. Let’s see how many unique values are contained within that column\n\nData |> pull(Condition) |> unique() \n\n[1] \"Ctrl\" \"PPD\" \"SEB\" \n\n\nIn the case of this dataset, looks like the .fcs files where treated with either left alone, treated with PPD (Purified Protein Derrivative) or SEB. What if we wanted to subset only those treated with PPD?\nWithin filter(), we would specify the column name as the first argument, and ask that only values equal to (==) “PPD” be returned. Notice in this case, “” are needed, as we are asking for a matching character value.\n\nPPDOnly <- Data |> filter(Condition == \"PPD\")\nhead(PPDOnly, 5)\n\n bid timepoint Condition Date infant_sex ptype root singletsFSC\n1 INF0052 0 PPD 2025-07-26 Male HEU-hi 2363512 2136616\n2 INF0100 0 PPD 2025-07-26 Male HEU-lo 2049112 1821676\n3 INF0100 4 PPD 2025-07-26 Male HEU-lo 1063496 946587\n4 INF0100 9 PPD 2025-07-26 Male HEU-lo 788368 714198\n5 INF0179 0 PPD 2025-07-26 Male HU 1380336 1242311\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1875394 1732620 0.5873838 0.8619837 0.8429685 0.6408044\n2 1717636 1597085 0.9063081 0.9251961 0.8771889 0.2174284\n3 796056 767297 0.9709891 0.9848719 0.9556049 0.7313503\n4 626387 600011 0.9822803 0.9842139 0.8123041 0.6223228\n5 1047081 1000877 0.9470275 0.9575685 0.9134438 0.6996502\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9009254 0.20743228 0.6934931 0.2835676 0.007408209 0.9925918 0.01507057\n2 0.8929673 0.06181426 0.8311531 0.6735798 0.007137230 0.9928628 0.01671801\n3 0.8782307 0.20727202 0.6709587 0.5989873 0.005254643 0.9947454 0.01609790\n4 0.9566639 0.23164587 0.7250180 0.6489405 0.011935922 0.9880641 0.01855298\n5 0.8856898 0.33186111 0.5538287 0.4441538 0.004382972 0.9956170 0.01297237\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9775212 0.6340345 0.3434867 0.2744119 0.06907479 184930\n2 0.9761448 0.6145707 0.3615741 0.3312279 0.03034620 211987\n3 0.9786475 0.6559480 0.3226994 0.2912084 0.03149109 326378\n4 0.9695111 0.4306889 0.5388222 0.4908558 0.04796636 238021\n5 0.9826447 0.7499194 0.2327253 0.1850897 0.04763554 294549\n lymphocytes_count Monocytes Debris CD45_count\n1 652155 0.13801632 0.15703150 1017713\n2 314717 0.07480391 0.12281107 1447451\n3 544883 0.01512811 0.04439511 745037\n4 366784 0.01578611 0.18769586 589379\n5 663169 0.04243146 0.08655621 947858\n\n\nWhile this works, using “==” to match can glitch, especially with character values. Using the %in% operator is a better way of identifying and extracting only the rows whose Condition column contains “PPD”\n\nData |> filter(Condition %in% \"PPD\") |> head(5)\n\n bid timepoint Condition Date infant_sex ptype root singletsFSC\n1 INF0052 0 PPD 2025-07-26 Male HEU-hi 2363512 2136616\n2 INF0100 0 PPD 2025-07-26 Male HEU-lo 2049112 1821676\n3 INF0100 4 PPD 2025-07-26 Male HEU-lo 1063496 946587\n4 INF0100 9 PPD 2025-07-26 Male HEU-lo 788368 714198\n5 INF0179 0 PPD 2025-07-26 Male HU 1380336 1242311\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1875394 1732620 0.5873838 0.8619837 0.8429685 0.6408044\n2 1717636 1597085 0.9063081 0.9251961 0.8771889 0.2174284\n3 796056 767297 0.9709891 0.9848719 0.9556049 0.7313503\n4 626387 600011 0.9822803 0.9842139 0.8123041 0.6223228\n5 1047081 1000877 0.9470275 0.9575685 0.9134438 0.6996502\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9009254 0.20743228 0.6934931 0.2835676 0.007408209 0.9925918 0.01507057\n2 0.8929673 0.06181426 0.8311531 0.6735798 0.007137230 0.9928628 0.01671801\n3 0.8782307 0.20727202 0.6709587 0.5989873 0.005254643 0.9947454 0.01609790\n4 0.9566639 0.23164587 0.7250180 0.6489405 0.011935922 0.9880641 0.01855298\n5 0.8856898 0.33186111 0.5538287 0.4441538 0.004382972 0.9956170 0.01297237\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9775212 0.6340345 0.3434867 0.2744119 0.06907479 184930\n2 0.9761448 0.6145707 0.3615741 0.3312279 0.03034620 211987\n3 0.9786475 0.6559480 0.3226994 0.2912084 0.03149109 326378\n4 0.9695111 0.4306889 0.5388222 0.4908558 0.04796636 238021\n5 0.9826447 0.7499194 0.2327253 0.1850897 0.04763554 294549\n lymphocytes_count Monocytes Debris CD45_count\n1 652155 0.13801632 0.15703150 1017713\n2 314717 0.07480391 0.12281107 1447451\n3 544883 0.01512811 0.04439511 745037\n4 366784 0.01578611 0.18769586 589379\n5 663169 0.04243146 0.08655621 947858\n\n\nSimilar to what we saw for select(), we can grab rows that contain various values at once. We would just need to modify the second part of the argument. If we wanted to grab rows whose Condition column contained either PPD or SEB, we would need to provide that argument as a vector, placing both within c()/\n\nData |> filter(Condition %in% c(\"PPD\", \"SEB\")) |> head(5)\n\n bid timepoint Condition Date infant_sex ptype root singletsFSC\n1 INF0052 0 PPD 2025-07-26 Male HEU-hi 2363512 2136616\n2 INF0100 0 PPD 2025-07-26 Male HEU-lo 2049112 1821676\n3 INF0100 4 PPD 2025-07-26 Male HEU-lo 1063496 946587\n4 INF0100 9 PPD 2025-07-26 Male HEU-lo 788368 714198\n5 INF0179 0 PPD 2025-07-26 Male HU 1380336 1242311\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1875394 1732620 0.5873838 0.8619837 0.8429685 0.6408044\n2 1717636 1597085 0.9063081 0.9251961 0.8771889 0.2174284\n3 796056 767297 0.9709891 0.9848719 0.9556049 0.7313503\n4 626387 600011 0.9822803 0.9842139 0.8123041 0.6223228\n5 1047081 1000877 0.9470275 0.9575685 0.9134438 0.6996502\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9009254 0.20743228 0.6934931 0.2835676 0.007408209 0.9925918 0.01507057\n2 0.8929673 0.06181426 0.8311531 0.6735798 0.007137230 0.9928628 0.01671801\n3 0.8782307 0.20727202 0.6709587 0.5989873 0.005254643 0.9947454 0.01609790\n4 0.9566639 0.23164587 0.7250180 0.6489405 0.011935922 0.9880641 0.01855298\n5 0.8856898 0.33186111 0.5538287 0.4441538 0.004382972 0.9956170 0.01297237\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9775212 0.6340345 0.3434867 0.2744119 0.06907479 184930\n2 0.9761448 0.6145707 0.3615741 0.3312279 0.03034620 211987\n3 0.9786475 0.6559480 0.3226994 0.2912084 0.03149109 326378\n4 0.9695111 0.4306889 0.5388222 0.4908558 0.04796636 238021\n5 0.9826447 0.7499194 0.2327253 0.1850897 0.04763554 294549\n lymphocytes_count Monocytes Debris CD45_count\n1 652155 0.13801632 0.15703150 1017713\n2 314717 0.07480391 0.12281107 1447451\n3 544883 0.01512811 0.04439511 745037\n4 366784 0.01578611 0.18769586 589379\n5 663169 0.04243146 0.08655621 947858\n\n\nAlternatively, we could have set up the vector externally, and then provided it to filter()\n\nTheseConditions <- c(\"PPD\", \"SEB\")\nData |> filter(Condition %in% TheseConditions) |> head(5)\n\n bid timepoint Condition Date infant_sex ptype root singletsFSC\n1 INF0052 0 PPD 2025-07-26 Male HEU-hi 2363512 2136616\n2 INF0100 0 PPD 2025-07-26 Male HEU-lo 2049112 1821676\n3 INF0100 4 PPD 2025-07-26 Male HEU-lo 1063496 946587\n4 INF0100 9 PPD 2025-07-26 Male HEU-lo 788368 714198\n5 INF0179 0 PPD 2025-07-26 Male HU 1380336 1242311\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1875394 1732620 0.5873838 0.8619837 0.8429685 0.6408044\n2 1717636 1597085 0.9063081 0.9251961 0.8771889 0.2174284\n3 796056 767297 0.9709891 0.9848719 0.9556049 0.7313503\n4 626387 600011 0.9822803 0.9842139 0.8123041 0.6223228\n5 1047081 1000877 0.9470275 0.9575685 0.9134438 0.6996502\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9009254 0.20743228 0.6934931 0.2835676 0.007408209 0.9925918 0.01507057\n2 0.8929673 0.06181426 0.8311531 0.6735798 0.007137230 0.9928628 0.01671801\n3 0.8782307 0.20727202 0.6709587 0.5989873 0.005254643 0.9947454 0.01609790\n4 0.9566639 0.23164587 0.7250180 0.6489405 0.011935922 0.9880641 0.01855298\n5 0.8856898 0.33186111 0.5538287 0.4441538 0.004382972 0.9956170 0.01297237\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9775212 0.6340345 0.3434867 0.2744119 0.06907479 184930\n2 0.9761448 0.6145707 0.3615741 0.3312279 0.03034620 211987\n3 0.9786475 0.6559480 0.3226994 0.2912084 0.03149109 326378\n4 0.9695111 0.4306889 0.5388222 0.4908558 0.04796636 238021\n5 0.9826447 0.7499194 0.2327253 0.1850897 0.04763554 294549\n lymphocytes_count Monocytes Debris CD45_count\n1 652155 0.13801632 0.15703150 1017713\n2 314717 0.07480391 0.12281107 1447451\n3 544883 0.01512811 0.04439511 745037\n4 366784 0.01578611 0.18769586 589379\n5 663169 0.04243146 0.08655621 947858\n\n\nWhile this works when we have a limited number of variant condition values, what if had many more but only wanted to exclude one value? As we saw when learning about Conditionals, when we add a ! in front of a logical value, we get the opposite logical value returned\n\nIsThisASpectralInstrument <- TRUE\n\n!IsThisASpectralInstrument\n\n[1] FALSE\n\n\nIn the context of the dplyr package, we can use ! within the filter() to remove rows that contain a certain value\n\nSubset <- Data |> filter(!Condition %in% \"SEB\")\nSubset |> pull(Condition) |> unique()\n\n[1] \"Ctrl\" \"PPD\" \n\n\nLikewise, we can also use it with the select() to exclude columns we don’t want to include\n\nSubset <- Data |> select(!timepoint)\nSubset[1:3,]\n\n bid Condition Date infant_sex ptype root singletsFSC\n1 INF0052 Ctrl 2025-07-26 Male HEU-hi 2098368 1894070\n2 INF0100 Ctrl 2025-07-26 Male HEU-lo 2020184 1791890\n3 INF0100 Ctrl 2025-07-26 Male HEU-lo 1155040 1033320\n singletsSSC singletsSSCB CD45 NotMonocytes nonDebris lymphocytes\n1 1666179 1537396 0.5952943 0.8820349 0.8627649 0.6420138\n2 1697083 1579098 0.9106762 0.9052256 0.8602660 0.2145848\n3 875465 845446 0.9705765 0.9845400 0.9578793 0.7403110\n live Dump+ Dump- Tcells Vd2+ Vd2- Va7.2+\n1 0.9020581 0.21090996 0.6911482 0.2804264 0.008120361 0.9918796 0.01448070\n2 0.8908981 0.06252775 0.8283703 0.6748298 0.007265620 0.9927344 0.01577499\n3 0.8757665 0.20023803 0.6755285 0.6119129 0.004651313 0.9953487 0.01579402\n Va7.2- CD4+ CD4- CD8+ CD8- Tcells_count\n1 0.9773989 0.6341164 0.3432825 0.2734826 0.06979990 164771\n2 0.9769594 0.6119112 0.3650482 0.3357696 0.02927858 208241\n3 0.9795547 0.6639621 0.3155925 0.2862104 0.02938209 371723\n lymphocytes_count Monocytes Debris CD45_count\n1 587573 0.11796509 0.13723513 915203\n2 308583 0.09477437 0.13973396 1438047\n3 607477 0.01545999 0.04212072 820570", "crumbs": [ "About", "Intro to R", - "03 - Inside a .FCS file" + "04 - Intro to Tidyverse" ] }, { - "objectID": "course/03_InsideFCSFile/index.html#display", - "href": "course/03_InsideFCSFile/index.html#display", - "title": "03 - Inside an FCS File", - "section": "Display", - "text": "Display\nThen there is a stretch matching whether a particular detector needs to be displayed as linear (in the case of time and scatter) or as log (for individual detectors).\n\nDetectors <- DescriptionList[412:472]\nDetectors\n\n$P10DISPLAY\n[1] \"LOG\"\n\n$P11DISPLAY\n[1] \"LOG\"\n\n$P12DISPLAY\n[1] \"LOG\"\n\n$P13DISPLAY\n[1] \"LOG\"\n\n$P14DISPLAY\n[1] \"LOG\"\n\n$P15DISPLAY\n[1] \"LOG\"\n\n$P16DISPLAY\n[1] \"LOG\"\n\n$P17DISPLAY\n[1] \"LOG\"\n\n$P18DISPLAY\n[1] \"LIN\"\n\n$P19DISPLAY\n[1] \"LIN\"\n\n$P1DISPLAY\n[1] \"LOG\"\n\n$P20DISPLAY\n[1] \"LOG\"\n\n$P21DISPLAY\n[1] \"LOG\"\n\n$P22DISPLAY\n[1] \"LOG\"\n\n$P23DISPLAY\n[1] \"LOG\"\n\n$P24DISPLAY\n[1] \"LOG\"\n\n$P25DISPLAY\n[1] \"LOG\"\n\n$P26DISPLAY\n[1] \"LOG\"\n\n$P27DISPLAY\n[1] \"LOG\"\n\n$P28DISPLAY\n[1] \"LOG\"\n\n$P29DISPLAY\n[1] \"LOG\"\n\n$P2DISPLAY\n[1] \"LOG\"\n\n$P30DISPLAY\n[1] \"LOG\"\n\n$P31DISPLAY\n[1] \"LOG\"\n\n$P32DISPLAY\n[1] \"LOG\"\n\n$P33DISPLAY\n[1] \"LOG\"\n\n$P34DISPLAY\n[1] \"LOG\"\n\n$P35DISPLAY\n[1] \"LOG\"\n\n$P36DISPLAY\n[1] \"LIN\"\n\n$P37DISPLAY\n[1] \"LIN\"\n\n$P38DISPLAY\n[1] \"LIN\"\n\n$P39DISPLAY\n[1] \"LIN\"\n\n$P3DISPLAY\n[1] \"LOG\"\n\n$P40DISPLAY\n[1] \"LOG\"\n\n$P41DISPLAY\n[1] \"LOG\"\n\n$P42DISPLAY\n[1] \"LOG\"\n\n$P43DISPLAY\n[1] \"LOG\"\n\n$P44DISPLAY\n[1] \"LOG\"\n\n$P45DISPLAY\n[1] \"LOG\"\n\n$P46DISPLAY\n[1] \"LOG\"\n\n$P47DISPLAY\n[1] \"LOG\"\n\n$P48DISPLAY\n[1] \"LOG\"\n\n$P49DISPLAY\n[1] \"LOG\"\n\n$P4DISPLAY\n[1] \"LOG\"\n\n$P50DISPLAY\n[1] \"LOG\"\n\n$P51DISPLAY\n[1] \"LOG\"\n\n$P52DISPLAY\n[1] \"LOG\"\n\n$P53DISPLAY\n[1] \"LOG\"\n\n$P54DISPLAY\n[1] \"LOG\"\n\n$P55DISPLAY\n[1] \"LOG\"\n\n$P56DISPLAY\n[1] \"LOG\"\n\n$P57DISPLAY\n[1] \"LOG\"\n\n$P58DISPLAY\n[1] \"LOG\"\n\n$P59DISPLAY\n[1] \"LOG\"\n\n$P5DISPLAY\n[1] \"LOG\"\n\n$P60DISPLAY\n[1] \"LOG\"\n\n$P61DISPLAY\n[1] \"LOG\"\n\n$P6DISPLAY\n[1] \"LOG\"\n\n$P7DISPLAY\n[1] \"LOG\"\n\n$P8DISPLAY\n[1] \"LOG\"\n\n$P9DISPLAY\n[1] \"LOG\"\n\n\nAnd a few final keywords with threshold, window scaling and other user selected settings.\n\nDetectors <- DescriptionList[473:476]\nDetectors\n\n$THRESHOLD\n[1] \"(FSC,50000)\"\n\n$TUBENAME\n[1] \"05\"\n\n$USERSETTINGNAME\n[1] \"DTR_CellCounts\"\n\n$`WINDOW EXTENSION`\n[1] \"3\"", + "objectID": "course/04_IntroToTidyverse/index.html#mutate", + "href": "course/04_IntroToTidyverse/index.html#mutate", + "title": "04 - Introduction to Tidyverse", + "section": "mutate", + "text": "mutate\nAs we can see, with just these handful of functions, we have the building blocks to rearrange and subset a larger data.frame into a format that we prefer. But what if we wanted to alter the content of a column, or add new columns to an existing data.frame? This is where the mutate() function can be used.\nLet’s start by slimming down our current Data to a smaller workable example, highlighting the functions and pipes we learned about today\n\nTidyData <- Data |> filter(Condition %in% \"Ctrl\") |> filter(timepoint %in% \"0\") |>\n select(bid, timepoint, Condition, Date, Tcells_count, CD45_count) |>\n rename(specimen=bid, condition=Condition) |> relocate(Date, .after=specimen)\n\n\nTidyData\n\n specimen Date timepoint condition Tcells_count CD45_count\n1 INF0052 2025-07-26 0 Ctrl 164771 915203\n2 INF0100 2025-07-26 0 Ctrl 208241 1438047\n3 INF0179 2025-07-26 0 Ctrl 291777 940733\n4 INF0134 2025-07-29 0 Ctrl 127866 689676\n5 INF0148 2025-07-29 0 Ctrl 234335 1013985\n6 INF0191 2025-07-29 0 Ctrl 55780 715443\n7 INF0124 2025-07-31 0 Ctrl 70297 687720\n8 INF0149 2025-07-31 0 Ctrl 107900 857845\n9 INF0169 2025-07-31 0 Ctrl 75540 854594\n10 INF0019 2025-08-05 0 Ctrl 208055 873622\n11 INF0032 2025-08-05 0 Ctrl 361034 753064\n12 INF0180 2025-08-05 0 Ctrl 284958 1049663\n13 INF0155 2025-08-07 0 Ctrl 281626 1065048\n14 INF0158 2025-08-07 0 Ctrl 280913 1249338\n15 INF0159 2025-08-07 0 Ctrl 452551 1190219\n16 INF0013 2025-08-22 0 Ctrl 182751 836573\n17 INF0023 2025-08-22 0 Ctrl 218435 968035\n18 INF0030 2025-08-22 0 Ctrl 85521 732321\n19 INF0166 2025-08-28 0 Ctrl 225650 739495\n20 INF0199 2025-08-28 0 Ctrl 169736 1112176\n21 INF0207 2025-08-28 0 Ctrl 39055 905365\n22 INF0614 2025-08-30 0 Ctrl 224396 1569007\n23 INF0622 2025-08-30 0 Ctrl 161924 939307\n\n\nThe mutate() function can be used to modify existing columns, as well as to create new ones. For example, let’s derrive the proportion of T cells from the overall CD45 gate. To do so, within the parenthesis, we would specify a new column name, and then divide the original columns:\n\nTidyData <- TidyData |> mutate(Tcells_ProportionCD45 = Tcells_count / CD45_count)\nTidyData\n\n specimen Date timepoint condition Tcells_count CD45_count\n1 INF0052 2025-07-26 0 Ctrl 164771 915203\n2 INF0100 2025-07-26 0 Ctrl 208241 1438047\n3 INF0179 2025-07-26 0 Ctrl 291777 940733\n4 INF0134 2025-07-29 0 Ctrl 127866 689676\n5 INF0148 2025-07-29 0 Ctrl 234335 1013985\n6 INF0191 2025-07-29 0 Ctrl 55780 715443\n7 INF0124 2025-07-31 0 Ctrl 70297 687720\n8 INF0149 2025-07-31 0 Ctrl 107900 857845\n9 INF0169 2025-07-31 0 Ctrl 75540 854594\n10 INF0019 2025-08-05 0 Ctrl 208055 873622\n11 INF0032 2025-08-05 0 Ctrl 361034 753064\n12 INF0180 2025-08-05 0 Ctrl 284958 1049663\n13 INF0155 2025-08-07 0 Ctrl 281626 1065048\n14 INF0158 2025-08-07 0 Ctrl 280913 1249338\n15 INF0159 2025-08-07 0 Ctrl 452551 1190219\n16 INF0013 2025-08-22 0 Ctrl 182751 836573\n17 INF0023 2025-08-22 0 Ctrl 218435 968035\n18 INF0030 2025-08-22 0 Ctrl 85521 732321\n19 INF0166 2025-08-28 0 Ctrl 225650 739495\n20 INF0199 2025-08-28 0 Ctrl 169736 1112176\n21 INF0207 2025-08-28 0 Ctrl 39055 905365\n22 INF0614 2025-08-30 0 Ctrl 224396 1569007\n23 INF0622 2025-08-30 0 Ctrl 161924 939307\n Tcells_ProportionCD45\n1 0.18003765\n2 0.14480820\n3 0.31015921\n4 0.18540010\n5 0.23110302\n6 0.07796568\n7 0.10221747\n8 0.12578030\n9 0.08839285\n10 0.23815220\n11 0.47942008\n12 0.27147570\n13 0.26442564\n14 0.22484948\n15 0.38022498\n16 0.21845195\n17 0.22564783\n18 0.11678076\n19 0.30514067\n20 0.15261613\n21 0.04313730\n22 0.14301785\n23 0.17238666\n\n\nWe can see that we have many significant digits being returned. Let’s round this new column to 2 significant digits by applying the round() function\n\nTidyData <- TidyData |> mutate(TcellsRounded = round(Tcells_ProportionCD45, 2))\nTidyData \n\n specimen Date timepoint condition Tcells_count CD45_count\n1 INF0052 2025-07-26 0 Ctrl 164771 915203\n2 INF0100 2025-07-26 0 Ctrl 208241 1438047\n3 INF0179 2025-07-26 0 Ctrl 291777 940733\n4 INF0134 2025-07-29 0 Ctrl 127866 689676\n5 INF0148 2025-07-29 0 Ctrl 234335 1013985\n6 INF0191 2025-07-29 0 Ctrl 55780 715443\n7 INF0124 2025-07-31 0 Ctrl 70297 687720\n8 INF0149 2025-07-31 0 Ctrl 107900 857845\n9 INF0169 2025-07-31 0 Ctrl 75540 854594\n10 INF0019 2025-08-05 0 Ctrl 208055 873622\n11 INF0032 2025-08-05 0 Ctrl 361034 753064\n12 INF0180 2025-08-05 0 Ctrl 284958 1049663\n13 INF0155 2025-08-07 0 Ctrl 281626 1065048\n14 INF0158 2025-08-07 0 Ctrl 280913 1249338\n15 INF0159 2025-08-07 0 Ctrl 452551 1190219\n16 INF0013 2025-08-22 0 Ctrl 182751 836573\n17 INF0023 2025-08-22 0 Ctrl 218435 968035\n18 INF0030 2025-08-22 0 Ctrl 85521 732321\n19 INF0166 2025-08-28 0 Ctrl 225650 739495\n20 INF0199 2025-08-28 0 Ctrl 169736 1112176\n21 INF0207 2025-08-28 0 Ctrl 39055 905365\n22 INF0614 2025-08-30 0 Ctrl 224396 1569007\n23 INF0622 2025-08-30 0 Ctrl 161924 939307\n Tcells_ProportionCD45 TcellsRounded\n1 0.18003765 0.18\n2 0.14480820 0.14\n3 0.31015921 0.31\n4 0.18540010 0.19\n5 0.23110302 0.23\n6 0.07796568 0.08\n7 0.10221747 0.10\n8 0.12578030 0.13\n9 0.08839285 0.09\n10 0.23815220 0.24\n11 0.47942008 0.48\n12 0.27147570 0.27\n13 0.26442564 0.26\n14 0.22484948 0.22\n15 0.38022498 0.38\n16 0.21845195 0.22\n17 0.22564783 0.23\n18 0.11678076 0.12\n19 0.30514067 0.31\n20 0.15261613 0.15\n21 0.04313730 0.04\n22 0.14301785 0.14\n23 0.17238666 0.17", "crumbs": [ "About", "Intro to R", - "03 - Inside a .FCS file" + "04 - Intro to Tidyverse" ] }, { - "objectID": "course/03_InsideFCSFile/index.html#flowcore-parameters", - "href": "course/03_InsideFCSFile/index.html#flowcore-parameters", - "title": "03 - Inside an FCS File", - "section": "flowCore Parameters", - "text": "flowCore Parameters\nDepending on the arguments selected during read.FCS(), we might also encounter additional keywords that are added in by flowCore. For example, we do not see these keywords when “transformation” is set to FALSE.\n\nflowCoreCheck <- read.FCS(filename=firstfile,\n transformation = FALSE, truncate_max_range = FALSE)\n\nflowCoreCheck\n\nflowFrame object 'CellCounts4L_AB_05-ND050-05.fcs'\nwith 100 cells and 61 observables:\n name desc range minRange maxRange\n$P1 Time NA 272140 0 272139\n$P2 UV1-A NA 4194304 -111 4194303\n$P3 UV2-A NA 4194304 -111 4194303\n$P4 UV3-A NA 4194304 -111 4194303\n$P5 UV4-A NA 4194304 -111 4194303\n... ... ... ... ... ...\n$P57 R4-A NA 4194304 -111 4194303\n$P58 R5-A NA 4194304 -111 4194303\n$P59 R6-A NA 4194304 -111 4194303\n$P60 R7-A NA 4194304 -111 4194303\n$P61 R8-A NA 4194304 -111 4194303\n476 keywords are stored in the 'description' slot\n\n\n\nNoChange <- keyword(flowCoreCheck)\nDetectors <- NoChange [476:500]\nDetectors\n\n$`WINDOW EXTENSION`\n[1] \"3\"\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n$<NA>\nNULL\n\n\nBy contrast, if we had set “transformation” to TRUE:\n\nflowCoreCheck <- read.FCS(filename=firstfile,\n transformation = TRUE, truncate_max_range = FALSE)\n\nflowCoreCheck\n\nflowFrame object 'CellCounts4L_AB_05-ND050-05.fcs'\nwith 100 cells and 61 observables:\n name desc range minRange maxRange\n$P1 Time NA 272140 0 272139\n$P2 UV1-A NA 4194304 -111 4194303\n$P3 UV2-A NA 4194304 -111 4194303\n$P4 UV3-A NA 4194304 -111 4194303\n$P5 UV4-A NA 4194304 -111 4194303\n... ... ... ... ... ...\n$P57 R4-A NA 4194304 -111 4194303\n$P58 R5-A NA 4194304 -111 4194303\n$P59 R6-A NA 4194304 -111 4194303\n$P60 R7-A NA 4194304 -111 4194303\n$P61 R8-A NA 4194304 -111 4194303\n599 keywords are stored in the 'description' slot\n\n\n\nYesChange <- keyword(flowCoreCheck)\nDetectors <- YesChange [476:500]\nDetectors\n\n$`WINDOW EXTENSION`\n[1] \"3\"\n\n$transformation\n[1] \"applied\"\n\n$`flowCore_$P1Rmax`\n[1] \"272140\"\n\n$`flowCore_$P1Rmin`\n[1] \"0\"\n\n$`flowCore_$P2Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P2Rmin`\n[1] \"-111\"\n\n$`flowCore_$P3Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P3Rmin`\n[1] \"-111\"\n\n$`flowCore_$P4Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P4Rmin`\n[1] \"-111\"\n\n$`flowCore_$P5Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P5Rmin`\n[1] \"-111\"\n\n$`flowCore_$P6Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P6Rmin`\n[1] \"-111\"\n\n$`flowCore_$P7Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P7Rmin`\n[1] \"-111\"\n\n$`flowCore_$P8Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P8Rmin`\n[1] \"-26.3464946746826\"\n\n$`flowCore_$P9Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P9Rmin`\n[1] \"-111\"\n\n$`flowCore_$P10Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P10Rmin`\n[1] \"0\"\n\n$`flowCore_$P11Rmax`\n[1] \"4194304\"\n\n$`flowCore_$P11Rmin`\n[1] \"-111\"\n\n$`flowCore_$P12Rmax`\n[1] \"4194304\"\n\n\n\n\nFor some flow cytometry R packages, you will notice when opening their exported .fcs outputs in commercial software that these flowCore keywords have ended up integrated. It is likely somewhere in the package code the author forgot to add set transformation to FALSE, which is why we are seeing these flowCore keywords after the fact.", + "objectID": "course/04_IntroToTidyverse/index.html#arrange", + "href": "course/04_IntroToTidyverse/index.html#arrange", + "title": "04 - Introduction to Tidyverse", + "section": "arrange", + "text": "arrange\nAnd while we are here, let’s rearrange the rows so that they are descending based on the Tcell proportion. We can use this by using the desc() and arrange() functions from dplyr:\n\nTidyData <- TidyData |> arrange(desc(TcellsRounded))\n\nAnd let’s go ahead and filter() and identify the specimens that had more than 30% T cells as part of the overall CD45 gate (context, these samples were Cord Blood):\n\nTidyData |> filter(TcellsRounded > 0.3)\n\n specimen Date timepoint condition Tcells_count CD45_count\n1 INF0032 2025-08-05 0 Ctrl 361034 753064\n2 INF0159 2025-08-07 0 Ctrl 452551 1190219\n3 INF0179 2025-07-26 0 Ctrl 291777 940733\n4 INF0166 2025-08-28 0 Ctrl 225650 739495\n Tcells_ProportionCD45 TcellsRounded\n1 0.4794201 0.48\n2 0.3802250 0.38\n3 0.3101592 0.31\n4 0.3051407 0.31\n\n\nWhich is we had wanted to just retrieve the specimen IDs, we could add pull() after a new pipe argument.\n\nTidyData |> filter(TcellsRounded > 0.3) |> pull(specimen)\n\n[1] \"INF0032\" \"INF0159\" \"INF0179\" \"INF0166\"\n\n\nAnd finally, since I may want to send the data to a supervisor, let’s go ahead and export this “tidyed” version of our data.frame out to it’s own .csv file. Working within our project folder, this would look like this:\n\nNewName <- paste0(\"MyNewDataset\", \".csv\")\nStorageLocation <- file.path(\"data\", NewName)\nStorageLocation\n\n[1] \"data/MyNewDataset.csv\"\n\n\n\nwrite.csv(TidyData, StorageLocation, row.names=FALSE)", "crumbs": [ "About", "Intro to R", - "03 - Inside a .FCS file" + "04 - Intro to Tidyverse" ] }, - { - "objectID": "course/04_IntroToTidyverse/BonusContent.html", - "href": "course/04_IntroToTidyverse/BonusContent.html", - "title": "Bonus Content", - "section": "", - "text": "thefilepath <- file.path(\"data\", \"Dataset.csv\")\n\nthefilepath\n\n[1] \"data/Dataset.csv\"\nData <- read.csv(file=thefilepath, check.names=FALSE)\ncolnames(Data)\n\n [1] \"bid\" \"timepoint\" \"Condition\" \n [4] \"Date\" \"infant_sex\" \"ptype\" \n [7] \"root\" \"singletsFSC\" \"singletsSSC\" \n[10] \"singletsSSCB\" \"CD45\" \"NotMonocytes\" \n[13] \"nonDebris\" \"lymphocytes\" \"live\" \n[16] \"Dump+\" \"Dump-\" \"Tcells\" \n[19] \"Vd2+\" \"Vd2-\" \"Va7.2+\" \n[22] \"Va7.2-\" \"CD4+\" \"CD4-\" \n[25] \"CD8+\" \"CD8-\" \"Tcells_count\" \n[28] \"lymphocytes_count\" \"Monocytes\" \"Debris\" \n[31] \"CD45_count\"" - }, - { - "objectID": "course/04_IntroToTidyverse/BonusContent.html#pull", - "href": "course/04_IntroToTidyverse/BonusContent.html#pull", - "title": "Bonus Content", - "section": "Pull", - "text": "Pull" - }, - { - "objectID": "course/04_IntroToTidyverse/BonusContent.html#case-when", - "href": "course/04_IntroToTidyverse/BonusContent.html#case-when", - "title": "Bonus Content", - "section": "Case-When", - "text": "Case-When\nCase-when is an useful function, but may be a bit much to try to teach in the main segment. Basically, when the condition on the left side of the ~ is fulfilled, it will execute what is being specified on the right hand side.\nIn turn, we can combine these together by adding a “,”. I tend to use this mutate str_detect case_when combination when encountering messy data out in the while where I need to selectively change particular cell values in a consistent reproducible manner" - }, - { - "objectID": "course/04_IntroToTidyverse/BonusContent.html#selecting-columns-base-r", - "href": "course/04_IntroToTidyverse/BonusContent.html#selecting-columns-base-r", - "title": "Bonus Content", - "section": "Selecting Columns (Base R)", - "text": "Selecting Columns (Base R)\nAs we saw last week, there are multiple ways to select values from particular columns in base R. If we had wanted to retrieve the “Date” column, why not first identify its index position, and use [,] to extract the underlying data?\n\ncolnames(Data)\n\n [1] \"bid\" \"timepoint\" \"Condition\" \n [4] \"Date\" \"infant_sex\" \"ptype\" \n [7] \"root\" \"singletsFSC\" \"singletsSSC\" \n[10] \"singletsSSCB\" \"CD45\" \"NotMonocytes\" \n[13] \"nonDebris\" \"lymphocytes\" \"live\" \n[16] \"Dump+\" \"Dump-\" \"Tcells\" \n[19] \"Vd2+\" \"Vd2-\" \"Va7.2+\" \n[22] \"Va7.2-\" \"CD4+\" \"CD4-\" \n[25] \"CD8+\" \"CD8-\" \"Tcells_count\" \n[28] \"lymphocytes_count\" \"Monocytes\" \"Debris\" \n[31] \"CD45_count\" \n\n\n\ncolnames(Data)[4]\n\n[1] \"Date\"\n\n\n\nDataColumn <- Data[,4] # Column specified after the ,\nDataColumn\n\n [1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [6] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [11] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [16] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [21] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n [26] \"2025-07-26\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\"\n [31] \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\"\n [36] \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\"\n [41] \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-29\"\n [46] \"2025-07-29\" \"2025-07-29\" \"2025-07-29\" \"2025-07-31\" \"2025-07-31\"\n [51] \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\"\n [56] \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\"\n [61] \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\"\n [66] \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\"\n [71] \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\" \"2025-07-31\"\n [76] \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\"\n [81] \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\"\n [86] \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\"\n [91] \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-05\"\n [96] \"2025-08-05\" \"2025-08-05\" \"2025-08-05\" \"2025-08-07\" \"2025-08-07\"\n[101] \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\"\n[106] \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\"\n[111] \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\"\n[116] \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\"\n[121] \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-07\" \"2025-08-22\"\n[126] \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\"\n[131] \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\"\n[136] \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\"\n[141] \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\"\n[146] \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\" \"2025-08-22\"\n[151] \"2025-08-22\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\"\n[156] \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\"\n[161] \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\"\n[166] \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\"\n[171] \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-28\"\n[176] \"2025-08-28\" \"2025-08-28\" \"2025-08-28\" \"2025-08-30\" \"2025-08-30\"\n[181] \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\"\n[186] \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\"\n[191] \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\" \"2025-08-30\"\n[196] \"2025-08-30\"\n\n\nHowever, looking at the output, we see this looks like the values, not a column. Our suspicions are confirmed when running DataColumn\n\nstr(DataColumn)\n\n chr [1:196] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" ...\n\n\nThis is similarly the case when we use the $ accessor.\n\nDataColumn <- Data$Date\nstr(DataColumn)\n\n chr [1:196] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" \"2025-07-26\" ...\n\n\n\nhead(DataColumn, 3)\n\n[1] \"2025-07-26\" \"2025-07-26\" \"2025-07-26\"\n\n\nBy contrast, when selecting two columns, the structure is maintained.\n\nTwoColumns <- Data[,4:5]\n\nWhy is the data.frame column structure lost in base R when isolating a single data.frame column? And who thought to make it that convoluted? If we were an R course in early 2010s, we might go into an explanation, but fortunately, we don’t need to understand why, we have the dplyr R package to rescue us." - }, { "objectID": "course/05_GatingSets/Downsampling.html", "href": "course/05_GatingSets/Downsampling.html", diff --git a/docs/site_libs/bootstrap/bootstrap-8eaec6b9941db0f18eecf13b95a46332.min.css b/docs/site_libs/bootstrap/bootstrap-8eaec6b9941db0f18eecf13b95a46332.min.css index dac9a3f..19f9a75 100644 --- a/docs/site_libs/bootstrap/bootstrap-8eaec6b9941db0f18eecf13b95a46332.min.css +++ b/docs/site_libs/bootstrap/bootstrap-8eaec6b9941db0f18eecf13b95a46332.min.css @@ -1,12 +1,12 @@ -/*! - * Bootstrap v5.3.1 (https://getbootstrap.com/) - * Copyright 2011-2023 The Bootstrap Authors - * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE) - */:root,[data-bs-theme=light]{--bs-blue: #0d6efd;--bs-indigo: #6610f2;--bs-purple: #6f42c1;--bs-pink: #d63384;--bs-red: #dc3545;--bs-orange: #fd7e14;--bs-yellow: 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1rem;--bs-nav-link-padding-y: 0.5rem;--bs-nav-link-font-weight: ;--bs-nav-link-color: #0d6efd;--bs-nav-link-hover-color: rgb(10.4, 88, 202.4);--bs-nav-link-disabled-color: rgba(33, 37, 41, 0.75);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding-left:0;margin-bottom:0;list-style:none}.nav-link{display:block;padding:var(--bs-nav-link-padding-y) var(--bs-nav-link-padding-x);font-size:var(--bs-nav-link-font-size);font-weight:var(--bs-nav-link-font-weight);color:var(--bs-nav-link-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background:none;border:0;transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out}@media(prefers-reduced-motion: reduce){.nav-link{transition:none}}.nav-link:hover,.nav-link:focus{color:var(--bs-nav-link-hover-color)}.nav-link:focus-visible{outline:0;box-shadow:0 0 0 .25rem 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.offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:rgba(0,0,0,0) !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-xxl .offcanvas .offcanvas-header{display:none}.navbar-expand-xxl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}.navbar-expand{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand .navbar-nav .dropdown-menu{position:absolute}.navbar-expand .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand .navbar-nav-scroll{overflow:visible}.navbar-expand .navbar-collapse{display:flex !important;display:-webkit-flex 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ease;--bs-accordion-border-color: #dee2e6;--bs-accordion-border-width: 1px;--bs-accordion-border-radius: 0.25rem;--bs-accordion-inner-border-radius: calc(0.25rem - 1px);--bs-accordion-btn-padding-x: 1.25rem;--bs-accordion-btn-padding-y: 1rem;--bs-accordion-btn-color: #212529;--bs-accordion-btn-bg: #ffffff;--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23212529'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-icon-width: 1.25rem;--bs-accordion-btn-icon-transform: rotate(-180deg);--bs-accordion-btn-icon-transition: transform 0.2s ease-in-out;--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%285.2, 44, 101.2%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-focus-border-color: rgb(134, 182.5, 254);--bs-accordion-btn-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: rgb(5.2, 44, 101.2);--bs-accordion-active-bg: rgb(206.6, 226, 254.6)}.accordion-button{position:relative;display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;border-radius:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media(prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1*var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media(prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:first-of-type{border-top-left-radius:var(--bs-accordion-border-radius);border-top-right-radius:var(--bs-accordion-border-radius)}.accordion-item:first-of-type .accordion-button{border-top-left-radius:var(--bs-accordion-inner-border-radius);border-top-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:not(:first-of-type){border-top:0}.accordion-item:last-of-type{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-item:last-of-type .accordion-button.collapsed{border-bottom-right-radius:var(--bs-accordion-inner-border-radius);border-bottom-left-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0;border-radius:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme=dark] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%28109.8, 168, 253.8%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%28109.8, 168, 253.8%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: 0;--bs-breadcrumb-padding-y: 0;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color: rgba(33, 37, 41, 0.75);--bs-breadcrumb-item-padding-x: 0.5rem;--bs-breadcrumb-item-active-color: rgba(33, 37, 41, 0.75);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg);border-radius:var(--bs-breadcrumb-border-radius)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, ">") /* rtl: var(--bs-breadcrumb-divider, ">") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: 0.75rem;--bs-pagination-padding-y: 0.375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: #0d6efd;--bs-pagination-bg: #ffffff;--bs-pagination-border-width: 1px;--bs-pagination-border-color: #dee2e6;--bs-pagination-border-radius: 0.25rem;--bs-pagination-hover-color: rgb(10.4, 88, 202.4);--bs-pagination-hover-bg: #f8f9fa;--bs-pagination-hover-border-color: #dee2e6;--bs-pagination-focus-color: rgb(10.4, 88, 202.4);--bs-pagination-focus-bg: #e9ecef;--bs-pagination-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-pagination-active-color: #ffffff;--bs-pagination-active-bg: #0d6efd;--bs-pagination-active-border-color: #0d6efd;--bs-pagination-disabled-color: rgba(33, 37, 41, 0.75);--bs-pagination-disabled-bg: #e9ecef;--bs-pagination-disabled-border-color: #dee2e6;display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out}@media(prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(1px*-1)}.page-item:first-child .page-link{border-top-left-radius:var(--bs-pagination-border-radius);border-bottom-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-top-right-radius:var(--bs-pagination-border-radius);border-bottom-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: 0.75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: 0.5rem}.pagination-sm{--bs-pagination-padding-x: 0.5rem;--bs-pagination-padding-y: 0.25rem;--bs-pagination-font-size:0.875rem;--bs-pagination-border-radius: 0.2em}.badge{--bs-badge-padding-x: 0.65em;--bs-badge-padding-y: 0.35em;--bs-badge-font-size:0.75em;--bs-badge-font-weight: 700;--bs-badge-color: #ffffff;--bs-badge-border-radius: 0.25rem;display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:var(--bs-badge-border-radius)}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: 1px solid var(--bs-alert-border-color);--bs-alert-border-radius: 0.25rem;--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height: 1rem;--bs-progress-font-size:0.75rem;--bs-progress-bg: #e9ecef;--bs-progress-border-radius: 0.25rem;--bs-progress-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.075);--bs-progress-bar-color: #ffffff;--bs-progress-bar-bg: #0d6efd;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media(prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media(prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: #212529;--bs-list-group-bg: #ffffff;--bs-list-group-border-color: #dee2e6;--bs-list-group-border-width: 1px;--bs-list-group-border-radius: 0.25rem;--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: 0.5rem;--bs-list-group-action-color: rgba(33, 37, 41, 0.75);--bs-list-group-action-hover-color: #000;--bs-list-group-action-hover-bg: #f8f9fa;--bs-list-group-action-active-color: #212529;--bs-list-group-action-active-bg: #e9ecef;--bs-list-group-disabled-color: rgba(33, 37, 41, 0.75);--bs-list-group-disabled-bg: #ffffff;--bs-list-group-active-color: #ffffff;--bs-list-group-active-bg: #0d6efd;--bs-list-group-active-border-color: #0d6efd;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;border-radius:var(--bs-list-group-border-radius)}.list-group-numbered{list-style-type:none;counter-reset:section}.list-group-numbered>.list-group-item::before{content:counters(section, ".") ". ";counter-increment:section}.list-group-item-action{width:100%;color:var(--bs-list-group-action-color);text-align:inherit}.list-group-item-action:hover,.list-group-item-action:focus{z-index:1;color:var(--bs-list-group-action-hover-color);text-decoration:none;background-color:var(--bs-list-group-action-hover-bg)}.list-group-item-action:active{color:var(--bs-list-group-action-active-color);background-color:var(--bs-list-group-action-active-bg)}.list-group-item{position:relative;display:block;padding:var(--bs-list-group-item-padding-y) var(--bs-list-group-item-padding-x);color:var(--bs-list-group-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-list-group-bg);border:var(--bs-list-group-border-width) solid var(--bs-list-group-border-color)}.list-group-item:first-child{border-top-left-radius:inherit;border-top-right-radius:inherit}.list-group-item:last-child{border-bottom-right-radius:inherit;border-bottom-left-radius:inherit}.list-group-item.disabled,.list-group-item:disabled{color:var(--bs-list-group-disabled-color);pointer-events:none;background-color:var(--bs-list-group-disabled-bg)}.list-group-item.active{z-index:2;color:var(--bs-list-group-active-color);background-color:var(--bs-list-group-active-bg);border-color:var(--bs-list-group-active-border-color)}.list-group-item+.list-group-item{border-top-width:0}.list-group-item+.list-group-item.active{margin-top:calc(-1*var(--bs-list-group-border-width));border-top-width:var(--bs-list-group-border-width)}.list-group-horizontal{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal>.list-group-item.active{margin-top:0}.list-group-horizontal>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}@media(min-width: 576px){.list-group-horizontal-sm{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-sm>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-sm>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-sm>.list-group-item.active{margin-top:0}.list-group-horizontal-sm>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-sm>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 768px){.list-group-horizontal-md{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-md>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-md>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-md>.list-group-item.active{margin-top:0}.list-group-horizontal-md>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-md>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 992px){.list-group-horizontal-lg{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-lg>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-lg>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1200px){.list-group-horizontal-xl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1400px){.list-group-horizontal-xxl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xxl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xxl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xxl>.list-group-item.active{margin-top:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}.list-group-flush{border-radius:0}.list-group-flush>.list-group-item{border-width:0 0 var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-default{--bs-list-group-color: var(--bs-default-text-emphasis);--bs-list-group-bg: var(--bs-default-bg-subtle);--bs-list-group-border-color: var(--bs-default-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-default-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-default-border-subtle);--bs-list-group-active-color: var(--bs-default-bg-subtle);--bs-list-group-active-bg: var(--bs-default-text-emphasis);--bs-list-group-active-border-color: var(--bs-default-text-emphasis)}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23000'%3e%3cpath d='M.293.293a1 1 0 0 1 1.414 0L8 6.586 14.293.293a1 1 0 1 1 1.414 1.414L9.414 8l6.293 6.293a1 1 0 0 1-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 0 1-1.414-1.414L6.586 8 .293 1.707a1 1 0 0 1 0-1.414z'/%3e%3c/svg%3e");--bs-btn-close-opacity: 0.5;--bs-btn-close-hover-opacity: 0.75;--bs-btn-close-focus-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-btn-close-focus-opacity: 1;--bs-btn-close-disabled-opacity: 0.25;--bs-btn-close-white-filter: invert(1) grayscale(100%) brightness(200%);box-sizing:content-box;width:1em;height:1em;padding:.25em .25em;color:var(--bs-btn-close-color);background:rgba(0,0,0,0) var(--bs-btn-close-bg) center/1em auto no-repeat;border:0;border-radius:.25rem;opacity:var(--bs-btn-close-opacity)}.btn-close:hover{color:var(--bs-btn-close-color);text-decoration:none;opacity:var(--bs-btn-close-hover-opacity)}.btn-close:focus{outline:0;box-shadow:var(--bs-btn-close-focus-shadow);opacity:var(--bs-btn-close-focus-opacity)}.btn-close:disabled,.btn-close.disabled{pointer-events:none;user-select:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;-o-user-select:none;opacity:var(--bs-btn-close-disabled-opacity)}.btn-close-white{filter:var(--bs-btn-close-white-filter)}[data-bs-theme=dark] .btn-close{filter:var(--bs-btn-close-white-filter)}.toast{--bs-toast-zindex: 1090;--bs-toast-padding-x: 0.75rem;--bs-toast-padding-y: 0.5rem;--bs-toast-spacing: 1.5rem;--bs-toast-max-width: 350px;--bs-toast-font-size:0.875rem;--bs-toast-color: ;--bs-toast-bg: rgba(255, 255, 255, 0.85);--bs-toast-border-width: 1px;--bs-toast-border-color: rgba(0, 0, 0, 0.175);--bs-toast-border-radius: 0.25rem;--bs-toast-box-shadow: 0 0.5rem 1rem rgba(0, 0, 0, 0.15);--bs-toast-header-color: rgba(33, 37, 41, 0.75);--bs-toast-header-bg: rgba(255, 255, 255, 0.85);--bs-toast-header-border-color: rgba(0, 0, 0, 0.175);width:var(--bs-toast-max-width);max-width:100%;font-size:var(--bs-toast-font-size);color:var(--bs-toast-color);pointer-events:auto;background-color:var(--bs-toast-bg);background-clip:padding-box;border:var(--bs-toast-border-width) solid var(--bs-toast-border-color);box-shadow:var(--bs-toast-box-shadow);border-radius:var(--bs-toast-border-radius)}.toast.showing{opacity:0}.toast:not(.show){display:none}.toast-container{--bs-toast-zindex: 1090;position:absolute;z-index:var(--bs-toast-zindex);width:max-content;width:-webkit-max-content;width:-moz-max-content;width:-ms-max-content;width:-o-max-content;max-width:100%;pointer-events:none}.toast-container>:not(:last-child){margin-bottom:var(--bs-toast-spacing)}.toast-header{display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;padding:var(--bs-toast-padding-y) var(--bs-toast-padding-x);color:var(--bs-toast-header-color);background-color:var(--bs-toast-header-bg);background-clip:padding-box;border-bottom:var(--bs-toast-border-width) solid var(--bs-toast-header-border-color);border-top-left-radius:calc(var(--bs-toast-border-radius) - var(--bs-toast-border-width));border-top-right-radius:calc(var(--bs-toast-border-radius) - var(--bs-toast-border-width))}.toast-header .btn-close{margin-right:calc(-0.5*var(--bs-toast-padding-x));margin-left:var(--bs-toast-padding-x)}.toast-body{padding:var(--bs-toast-padding-x);word-wrap:break-word}.modal{--bs-modal-zindex: 1055;--bs-modal-width: 500px;--bs-modal-padding: 1rem;--bs-modal-margin: 0.5rem;--bs-modal-color: ;--bs-modal-bg: #ffffff;--bs-modal-border-color: rgba(0, 0, 0, 0.175);--bs-modal-border-width: 1px;--bs-modal-border-radius: 0.5rem;--bs-modal-box-shadow: 0 0.125rem 0.25rem rgba(0, 0, 0, 0.075);--bs-modal-inner-border-radius: calc(0.5rem - 1px);--bs-modal-header-padding-x: 1rem;--bs-modal-header-padding-y: 1rem;--bs-modal-header-padding: 1rem 1rem;--bs-modal-header-border-color: #dee2e6;--bs-modal-header-border-width: 1px;--bs-modal-title-line-height: 1.5;--bs-modal-footer-gap: 0.5rem;--bs-modal-footer-bg: ;--bs-modal-footer-border-color: #dee2e6;--bs-modal-footer-border-width: 1px;position:fixed;top:0;left:0;z-index:var(--bs-modal-zindex);display:none;width:100%;height:100%;overflow-x:hidden;overflow-y:auto;outline:0}.modal-dialog{position:relative;width:auto;margin:var(--bs-modal-margin);pointer-events:none}.modal.fade .modal-dialog{transition:transform .3s ease-out;transform:translate(0, -50px)}@media(prefers-reduced-motion: reduce){.modal.fade .modal-dialog{transition:none}}.modal.show .modal-dialog{transform:none}.modal.modal-static .modal-dialog{transform:scale(1.02)}.modal-dialog-scrollable{height:calc(100% - var(--bs-modal-margin)*2)}.modal-dialog-scrollable .modal-content{max-height:100%;overflow:hidden}.modal-dialog-scrollable .modal-body{overflow-y:auto}.modal-dialog-centered{display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;min-height:calc(100% - var(--bs-modal-margin)*2)}.modal-content{position:relative;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;width:100%;color:var(--bs-modal-color);pointer-events:auto;background-color:var(--bs-modal-bg);background-clip:padding-box;border:var(--bs-modal-border-width) solid var(--bs-modal-border-color);border-radius:var(--bs-modal-border-radius);outline:0}.modal-backdrop{--bs-backdrop-zindex: 1050;--bs-backdrop-bg: #000;--bs-backdrop-opacity: 0.5;position:fixed;top:0;left:0;z-index:var(--bs-backdrop-zindex);width:100vw;height:100vh;background-color:var(--bs-backdrop-bg)}.modal-backdrop.fade{opacity:0}.modal-backdrop.show{opacity:var(--bs-backdrop-opacity)}.modal-header{display:flex;display:-webkit-flex;flex-shrink:0;-webkit-flex-shrink:0;align-items:center;-webkit-align-items:center;justify-content:space-between;-webkit-justify-content:space-between;padding:var(--bs-modal-header-padding);border-bottom:var(--bs-modal-header-border-width) solid var(--bs-modal-header-border-color);border-top-left-radius:var(--bs-modal-inner-border-radius);border-top-right-radius:var(--bs-modal-inner-border-radius)}.modal-header .btn-close{padding:calc(var(--bs-modal-header-padding-y)*.5) calc(var(--bs-modal-header-padding-x)*.5);margin:calc(-0.5*var(--bs-modal-header-padding-y)) calc(-0.5*var(--bs-modal-header-padding-x)) calc(-0.5*var(--bs-modal-header-padding-y)) auto}.modal-title{margin-bottom:0;line-height:var(--bs-modal-title-line-height)}.modal-body{position:relative;flex:1 1 auto;-webkit-flex:1 1 auto;padding:var(--bs-modal-padding)}.modal-footer{display:flex;display:-webkit-flex;flex-shrink:0;-webkit-flex-shrink:0;flex-wrap:wrap;-webkit-flex-wrap:wrap;align-items:center;-webkit-align-items:center;justify-content:flex-end;-webkit-justify-content:flex-end;padding:calc(var(--bs-modal-padding) - var(--bs-modal-footer-gap)*.5);background-color:var(--bs-modal-footer-bg);border-top:var(--bs-modal-footer-border-width) solid var(--bs-modal-footer-border-color);border-bottom-right-radius:var(--bs-modal-inner-border-radius);border-bottom-left-radius:var(--bs-modal-inner-border-radius)}.modal-footer>*{margin:calc(var(--bs-modal-footer-gap)*.5)}@media(min-width: 576px){.modal{--bs-modal-margin: 1.75rem;--bs-modal-box-shadow: 0 0.5rem 1rem rgba(0, 0, 0, 0.15)}.modal-dialog{max-width:var(--bs-modal-width);margin-right:auto;margin-left:auto}.modal-sm{--bs-modal-width: 300px}}@media(min-width: 992px){.modal-lg,.modal-xl{--bs-modal-width: 800px}}@media(min-width: 1200px){.modal-xl{--bs-modal-width: 1140px}}.modal-fullscreen{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen .modal-content{height:100%;border:0;border-radius:0}.modal-fullscreen .modal-header,.modal-fullscreen .modal-footer{border-radius:0}.modal-fullscreen .modal-body{overflow-y:auto}@media(max-width: 575.98px){.modal-fullscreen-sm-down{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen-sm-down .modal-content{height:100%;border:0;border-radius:0}.modal-fullscreen-sm-down .modal-header,.modal-fullscreen-sm-down .modal-footer{border-radius:0}.modal-fullscreen-sm-down .modal-body{overflow-y:auto}}@media(max-width: 767.98px){.modal-fullscreen-md-down{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen-md-down .modal-content{height:100%;border:0;border-radius:0}.modal-fullscreen-md-down .modal-header,.modal-fullscreen-md-down .modal-footer{border-radius:0}.modal-fullscreen-md-down .modal-body{overflow-y:auto}}@media(max-width: 991.98px){.modal-fullscreen-lg-down{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen-lg-down .modal-content{height:100%;border:0;border-radius:0}.modal-fullscreen-lg-down .modal-header,.modal-fullscreen-lg-down .modal-footer{border-radius:0}.modal-fullscreen-lg-down .modal-body{overflow-y:auto}}@media(max-width: 1199.98px){.modal-fullscreen-xl-down{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen-xl-down .modal-content{height:100%;border:0;border-radius:0}.modal-fullscreen-xl-down .modal-header,.modal-fullscreen-xl-down .modal-footer{border-radius:0}.modal-fullscreen-xl-down .modal-body{overflow-y:auto}}@media(max-width: 1399.98px){.modal-fullscreen-xxl-down{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen-xxl-down .modal-content{height:100%;border:0;border-radius:0}.modal-fullscreen-xxl-down .modal-header,.modal-fullscreen-xxl-down .modal-footer{border-radius:0}.modal-fullscreen-xxl-down .modal-body{overflow-y:auto}}.tooltip{--bs-tooltip-zindex: 1080;--bs-tooltip-max-width: 200px;--bs-tooltip-padding-x: 0.5rem;--bs-tooltip-padding-y: 0.25rem;--bs-tooltip-margin: ;--bs-tooltip-font-size:0.875rem;--bs-tooltip-color: #ffffff;--bs-tooltip-bg: #000;--bs-tooltip-border-radius: 0.25rem;--bs-tooltip-opacity: 0.9;--bs-tooltip-arrow-width: 0.8rem;--bs-tooltip-arrow-height: 0.4rem;z-index:var(--bs-tooltip-zindex);display:block;margin:var(--bs-tooltip-margin);font-family:system-ui,-apple-system,"Segoe UI",Roboto,"Helvetica Neue","Noto Sans","Liberation Sans",Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol","Noto Color Emoji";font-style:normal;font-weight:400;line-height:1.5;text-align:left;text-align:start;text-decoration:none;text-shadow:none;text-transform:none;letter-spacing:normal;word-break:normal;white-space:normal;word-spacing:normal;line-break:auto;font-size:var(--bs-tooltip-font-size);word-wrap:break-word;opacity:0}.tooltip.show{opacity:var(--bs-tooltip-opacity)}.tooltip .tooltip-arrow{display:block;width:var(--bs-tooltip-arrow-width);height:var(--bs-tooltip-arrow-height)}.tooltip .tooltip-arrow::before{position:absolute;content:"";border-color:rgba(0,0,0,0);border-style:solid}.bs-tooltip-top .tooltip-arrow,.bs-tooltip-auto[data-popper-placement^=top] .tooltip-arrow{bottom:calc(-1*var(--bs-tooltip-arrow-height))}.bs-tooltip-top .tooltip-arrow::before,.bs-tooltip-auto[data-popper-placement^=top] .tooltip-arrow::before{top:-1px;border-width:var(--bs-tooltip-arrow-height) calc(var(--bs-tooltip-arrow-width)*.5) 0;border-top-color:var(--bs-tooltip-bg)}.bs-tooltip-end .tooltip-arrow,.bs-tooltip-auto[data-popper-placement^=right] .tooltip-arrow{left:calc(-1*var(--bs-tooltip-arrow-height));width:var(--bs-tooltip-arrow-height);height:var(--bs-tooltip-arrow-width)}.bs-tooltip-end .tooltip-arrow::before,.bs-tooltip-auto[data-popper-placement^=right] .tooltip-arrow::before{right:-1px;border-width:calc(var(--bs-tooltip-arrow-width)*.5) var(--bs-tooltip-arrow-height) calc(var(--bs-tooltip-arrow-width)*.5) 0;border-right-color:var(--bs-tooltip-bg)}.bs-tooltip-bottom .tooltip-arrow,.bs-tooltip-auto[data-popper-placement^=bottom] .tooltip-arrow{top:calc(-1*var(--bs-tooltip-arrow-height))}.bs-tooltip-bottom 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var(--bg-gradient-end, 180%)) rgb(13,165.2,245.2);color:#000}.bg-gradient-cyan-indigo{--bslib-color-fg: #000;--bslib-color-bg: rgb(48.6, 127.6, 240.8);background:linear-gradient(var(--bg-gradient-deg, 140deg), #0dcaf0 var(--bg-gradient-start, 36%), #6610f2 var(--bg-gradient-end, 180%)) rgb(48.6,127.6,240.8);color:#000}.bg-gradient-cyan-purple{--bslib-color-fg: #000;--bslib-color-bg: rgb(52.2, 147.6, 221.2);background:linear-gradient(var(--bg-gradient-deg, 140deg), #0dcaf0 var(--bg-gradient-start, 36%), #6f42c1 var(--bg-gradient-end, 180%)) rgb(52.2,147.6,221.2);color:#000}.bg-gradient-cyan-pink{--bslib-color-fg: #000;--bslib-color-bg: rgb(93.4, 141.6, 196.8);background:linear-gradient(var(--bg-gradient-deg, 140deg), #0dcaf0 var(--bg-gradient-start, 36%), #d63384 var(--bg-gradient-end, 180%)) rgb(93.4,141.6,196.8);color:#000}.bg-gradient-cyan-red{--bslib-color-fg: #000;--bslib-color-bg: rgb(95.8, 142.4, 171.6);background:linear-gradient(var(--bg-gradient-deg, 140deg), #0dcaf0 var(--bg-gradient-start, 36%), #dc3545 var(--bg-gradient-end, 180%)) rgb(95.8,142.4,171.6);color:#000}.bg-gradient-cyan-orange{--bslib-color-fg: #000;--bslib-color-bg: rgb(109, 171.6, 152);background:linear-gradient(var(--bg-gradient-deg, 140deg), #0dcaf0 var(--bg-gradient-start, 36%), #fd7e14 var(--bg-gradient-end, 180%)) rgb(109,171.6,152);color:#000}.bg-gradient-cyan-yellow{--bslib-color-fg: #000;--bslib-color-bg: rgb(109.8, 198.4, 146.8);background:linear-gradient(var(--bg-gradient-deg, 140deg), #0dcaf0 var(--bg-gradient-start, 36%), #ffc107 var(--bg-gradient-end, 180%)) rgb(109.8,198.4,146.8);color:#000}.bg-gradient-cyan-green{--bslib-color-fg: #000;--bslib-color-bg: rgb(17.8, 175.2, 177.6);background:linear-gradient(var(--bg-gradient-deg, 140deg), #0dcaf0 var(--bg-gradient-start, 36%), #198754 var(--bg-gradient-end, 180%)) rgb(17.8,175.2,177.6);color:#000}.bg-gradient-cyan-teal{--bslib-color-fg: #000;--bslib-color-bg: rgb(20.6, 201.6, 204.4);background:linear-gradient(var(--bg-gradient-deg, 140deg), #0dcaf0 var(--bg-gradient-start, 36%), #20c997 var(--bg-gradient-end, 180%)) rgb(20.6,201.6,204.4);color:#000}.tab-content>.tab-pane.html-fill-container{display:none}.tab-content>.active.html-fill-container{display:flex}.tab-content.html-fill-container{padding:0}.bslib-sidebar-layout{--bslib-sidebar-transition-duration: 500ms;--bslib-sidebar-transition-easing-x: cubic-bezier(0.8, 0.78, 0.22, 1.07);--bslib-sidebar-border: var(--bs-card-border-width, 1px) solid var(--bs-card-border-color, rgba(0, 0, 0, 0.175));--bslib-sidebar-border-radius: var(--bs-border-radius);--bslib-sidebar-vert-border: var(--bs-card-border-width, 1px) solid var(--bs-card-border-color, rgba(0, 0, 0, 0.175));--bslib-sidebar-bg: rgba(var(--bs-emphasis-color-rgb, 0, 0, 0), 0.05);--bslib-sidebar-fg: var(--bs-emphasis-color, black);--bslib-sidebar-main-fg: var(--bs-card-color, var(--bs-body-color));--bslib-sidebar-main-bg: var(--bs-card-bg, 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.sidebar-title{font-size:1.25rem;line-height:1.25;margin-top:0;margin-bottom:1rem;padding-bottom:1rem;border-bottom:var(--bslib-sidebar-border)}.bslib-sidebar-layout.sidebar-right{grid-template-columns:var(--bslib-sidebar-column-main) min(100% - var(--bslib-sidebar-icon-size),var(--bslib-sidebar-width, 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0}.bslib-sidebar-layout.sidebar-collapsed:not(.transitioning)>.sidebar>*{display:none}.bslib-sidebar-layout.sidebar-collapsed>.main{border-radius:inherit}.bslib-sidebar-layout.sidebar-collapsed:not(.sidebar-right)>.main{padding-left:var(--bslib-sidebar-padding-icon)}.bslib-sidebar-layout.sidebar-collapsed.sidebar-right>.main{padding-right:var(--bslib-sidebar-padding-icon)}.bslib-sidebar-layout.sidebar-collapsed>.collapse-toggle{color:var(--bslib-sidebar-main-fg);top:calc(var(--bslib-sidebar-overlap-counter, 0)*(var(--bslib-sidebar-icon-size) + var(--bslib-sidebar-padding)) + var(--bslib-sidebar-icon-size, 1rem)/2);right:calc(-2.5*var(--bslib-sidebar-icon-size) - var(--bs-card-border-width, 1px))}.bslib-sidebar-layout.sidebar-collapsed.sidebar-right>.collapse-toggle{left:calc(-2.5*var(--bslib-sidebar-icon-size) - var(--bs-card-border-width, 1px));right:unset}@media(min-width: 576px){.bslib-sidebar-layout.transitioning>.sidebar>.sidebar-content{display:none}}@media(max-width: 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100%}.bslib-sidebar-layout:not([data-bslib-sidebar-open=always]).sidebar-collapsed{grid-template-columns:0 100%}.bslib-sidebar-layout:not([data-bslib-sidebar-open=always]).sidebar-collapsed.sidebar-right{grid-template-columns:100% 0}.bslib-sidebar-layout:not([data-bslib-sidebar-open=always]):not(.sidebar-right)>.main{padding-left:var(--bslib-sidebar-padding-icon)}.bslib-sidebar-layout:not([data-bslib-sidebar-open=always]).sidebar-right>.main{padding-right:var(--bslib-sidebar-padding-icon)}.bslib-sidebar-layout:not([data-bslib-sidebar-open=always])>.main{opacity:0;transition:opacity var(--bslib-sidebar-transition-easing-x) var(--bslib-sidebar-transition-duration)}.bslib-sidebar-layout:not([data-bslib-sidebar-open=always]).sidebar-collapsed>.main{opacity:1}}.bslib-card{overflow:auto}.bslib-card .card-body+.card-body{padding-top:0}.bslib-card .card-body{overflow:auto}.bslib-card .card-body p{margin-top:0}.bslib-card .card-body p:last-child{margin-bottom:0}.bslib-card 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!important;z-index:1070}.bslib-full-screen-enter{display:none;position:absolute;bottom:var(--bslib-full-screen-enter-bottom, 0.2rem);right:var(--bslib-full-screen-enter-right, 0);top:var(--bslib-full-screen-enter-top);left:var(--bslib-full-screen-enter-left);color:var(--bslib-color-fg, var(--bs-card-color));background-color:var(--bslib-color-bg, var(--bs-card-bg, var(--bs-body-bg)));border:var(--bs-card-border-width) solid var(--bslib-color-fg, var(--bs-card-border-color));box-shadow:0 2px 4px rgba(0,0,0,.15);margin:.2rem .4rem;padding:.55rem !important;font-size:.8rem;cursor:pointer;opacity:.7;z-index:1070}.bslib-full-screen-enter:hover{opacity:1}.card[data-full-screen=false]:hover>*>.bslib-full-screen-enter{display:block}.bslib-has-full-screen .card:hover>*>.bslib-full-screen-enter{display:none}@media(max-width: 575.98px){.bslib-full-screen-enter{display:none !important}}.bslib-full-screen-exit{position:relative;top:1.35rem;font-size:.9rem;cursor:pointer;text-decoration:none;display:flex;float:right;margin-right:2.15rem;align-items:center;color:rgba(var(--bs-body-bg-rgb), 0.8)}.bslib-full-screen-exit:hover{color:rgba(var(--bs-body-bg-rgb), 1)}.bslib-full-screen-exit svg{margin-left:.5rem;font-size:1.5rem}#bslib-full-screen-overlay{position:fixed;inset:0;background-color:rgba(var(--bs-body-color-rgb), 0.6);backdrop-filter:blur(2px);-webkit-backdrop-filter:blur(2px);z-index:1069;animation:bslib-full-screen-overlay-enter 400ms cubic-bezier(0.6, 0.02, 0.65, 1) forwards}@keyframes bslib-full-screen-overlay-enter{0%{opacity:0}100%{opacity:1}}@media(min-width: 576px){.nav:not(.nav-hidden){display:flex !important;display:-webkit-flex !important}.nav:not(.nav-hidden):not(.nav-stacked):not(.flex-column){float:none !important}.nav:not(.nav-hidden):not(.nav-stacked):not(.flex-column)>.bslib-nav-spacer{margin-left:auto !important}.nav:not(.nav-hidden):not(.nav-stacked):not(.flex-column)>.form-inline{margin-top:auto;margin-bottom:auto}.nav:not(.nav-hidden).nav-stacked{flex-direction:column;-webkit-flex-direction:column;height:100%}.nav:not(.nav-hidden).nav-stacked>.bslib-nav-spacer{margin-top:auto !important}}:root{--bslib-page-sidebar-title-bg: white;--bslib-page-sidebar-title-color: #000}.bslib-page-title{background-color:var(--bslib-page-sidebar-title-bg);color:var(--bslib-page-sidebar-title-color);font-size:1.25rem;font-weight:300;padding:var(--bslib-spacer, 1rem);padding-left:1.5rem;margin-bottom:0;border-bottom:1px solid #dee2e6}.navbar+.container-fluid:has(>.tab-content>.tab-pane.active.html-fill-container),.navbar+.container-sm:has(>.tab-content>.tab-pane.active.html-fill-container),.navbar+.container-md:has(>.tab-content>.tab-pane.active.html-fill-container),.navbar+.container-lg:has(>.tab-content>.tab-pane.active.html-fill-container),.navbar+.container-xl:has(>.tab-content>.tab-pane.active.html-fill-container),.navbar+.container-xxl:has(>.tab-content>.tab-pane.active.html-fill-container){padding-left:0;padding-right:0}.navbar+.container-fluid>.tab-content>.tab-pane.active.html-fill-container,.navbar+.container-sm>.tab-content>.tab-pane.active.html-fill-container,.navbar+.container-md>.tab-content>.tab-pane.active.html-fill-container,.navbar+.container-lg>.tab-content>.tab-pane.active.html-fill-container,.navbar+.container-xl>.tab-content>.tab-pane.active.html-fill-container,.navbar+.container-xxl>.tab-content>.tab-pane.active.html-fill-container{padding:var(--bslib-spacer, 1rem);gap:var(--bslib-spacer, 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.offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:rgba(0,0,0,0) !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-xxl .offcanvas .offcanvas-header{display:none}.navbar-expand-xxl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}.navbar-expand{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand .navbar-nav .dropdown-menu{position:absolute}.navbar-expand .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand .navbar-nav-scroll{overflow:visible}.navbar-expand .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand .navbar-toggler{display:none}.navbar-expand .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:rgba(0,0,0,0) !important;border:0 !important;transform:none !important;transition:none}.navbar-expand .offcanvas .offcanvas-header{display:none}.navbar-expand .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}.navbar-dark,.navbar[data-bs-theme=dark]{--bs-navbar-color: rgb(89.25, 89.25, 89.25);--bs-navbar-hover-color: rgba(9.75, 82.5, 189.75, 0.8);--bs-navbar-disabled-color: rgba(89.25, 89.25, 89.25, 0.75);--bs-navbar-active-color: rgb(9.75, 82.5, 189.75);--bs-navbar-brand-color: rgb(89.25, 89.25, 89.25);--bs-navbar-brand-hover-color: rgb(9.75, 82.5, 189.75);--bs-navbar-toggler-border-color: rgba(89.25, 89.25, 89.25, 0);--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgb%2889.25, 89.25, 89.25%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}[data-bs-theme=dark] .navbar-toggler-icon{--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgb%2889.25, 89.25, 89.25%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}.card{--bs-card-spacer-y: 1rem;--bs-card-spacer-x: 1rem;--bs-card-title-spacer-y: 0.5rem;--bs-card-title-color: ;--bs-card-subtitle-color: ;--bs-card-border-width: 1px;--bs-card-border-color: rgba(0, 0, 0, 0.175);--bs-card-border-radius: 0.25rem;--bs-card-box-shadow: ;--bs-card-inner-border-radius: calc(0.25rem - 1px);--bs-card-cap-padding-y: 0.5rem;--bs-card-cap-padding-x: 1rem;--bs-card-cap-bg: rgba(52, 58, 64, 0.25);--bs-card-cap-color: ;--bs-card-height: ;--bs-card-color: ;--bs-card-bg: #ffffff;--bs-card-img-overlay-padding: 1rem;--bs-card-group-margin: 0.75rem;position:relative;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;min-width:0;height:var(--bs-card-height);color:var(--bs-body-color);word-wrap:break-word;background-color:var(--bs-card-bg);background-clip:border-box;border:var(--bs-card-border-width) solid var(--bs-card-border-color);border-radius:var(--bs-card-border-radius)}.card>hr{margin-right:0;margin-left:0}.card>.list-group{border-top:inherit;border-bottom:inherit}.card>.list-group:first-child{border-top-width:0;border-top-left-radius:var(--bs-card-inner-border-radius);border-top-right-radius:var(--bs-card-inner-border-radius)}.card>.list-group:last-child{border-bottom-width:0;border-bottom-right-radius:var(--bs-card-inner-border-radius);border-bottom-left-radius:var(--bs-card-inner-border-radius)}.card>.card-header+.list-group,.card>.list-group+.card-footer{border-top:0}.card-body{flex:1 1 auto;-webkit-flex:1 1 auto;padding:var(--bs-card-spacer-y) var(--bs-card-spacer-x);color:var(--bs-card-color)}.card-title{margin-bottom:var(--bs-card-title-spacer-y);color:var(--bs-card-title-color)}.card-subtitle{margin-top:calc(-0.5*var(--bs-card-title-spacer-y));margin-bottom:0;color:var(--bs-card-subtitle-color)}.card-text:last-child{margin-bottom:0}.card-link+.card-link{margin-left:var(--bs-card-spacer-x)}.card-header{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);margin-bottom:0;color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-bottom:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-header:first-child{border-radius:var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius) 0 0}.card-footer{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-top:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-footer:last-child{border-radius:0 0 var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius)}.card-header-tabs{margin-right:calc(-0.5*var(--bs-card-cap-padding-x));margin-bottom:calc(-1*var(--bs-card-cap-padding-y));margin-left:calc(-0.5*var(--bs-card-cap-padding-x));border-bottom:0}.card-header-tabs .nav-link.active{background-color:var(--bs-card-bg);border-bottom-color:var(--bs-card-bg)}.card-header-pills{margin-right:calc(-0.5*var(--bs-card-cap-padding-x));margin-left:calc(-0.5*var(--bs-card-cap-padding-x))}.card-img-overlay{position:absolute;top:0;right:0;bottom:0;left:0;padding:var(--bs-card-img-overlay-padding);border-radius:var(--bs-card-inner-border-radius)}.card-img,.card-img-top,.card-img-bottom{width:100%}.card-img,.card-img-top{border-top-left-radius:var(--bs-card-inner-border-radius);border-top-right-radius:var(--bs-card-inner-border-radius)}.card-img,.card-img-bottom{border-bottom-right-radius:var(--bs-card-inner-border-radius);border-bottom-left-radius:var(--bs-card-inner-border-radius)}.card-group>.card{margin-bottom:var(--bs-card-group-margin)}@media(min-width: 576px){.card-group{display:flex;display:-webkit-flex;flex-flow:row wrap;-webkit-flex-flow:row wrap}.card-group>.card{flex:1 0 0%;-webkit-flex:1 0 0%;margin-bottom:0}.card-group>.card+.card{margin-left:0;border-left:0}.card-group>.card:not(:last-child){border-top-right-radius:0;border-bottom-right-radius:0}.card-group>.card:not(:last-child) .card-img-top,.card-group>.card:not(:last-child) .card-header{border-top-right-radius:0}.card-group>.card:not(:last-child) .card-img-bottom,.card-group>.card:not(:last-child) .card-footer{border-bottom-right-radius:0}.card-group>.card:not(:first-child){border-top-left-radius:0;border-bottom-left-radius:0}.card-group>.card:not(:first-child) .card-img-top,.card-group>.card:not(:first-child) .card-header{border-top-left-radius:0}.card-group>.card:not(:first-child) .card-img-bottom,.card-group>.card:not(:first-child) .card-footer{border-bottom-left-radius:0}}.accordion{--bs-accordion-color: #212529;--bs-accordion-bg: #ffffff;--bs-accordion-transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out, border-radius 0.15s ease;--bs-accordion-border-color: #dee2e6;--bs-accordion-border-width: 1px;--bs-accordion-border-radius: 0.25rem;--bs-accordion-inner-border-radius: calc(0.25rem - 1px);--bs-accordion-btn-padding-x: 1.25rem;--bs-accordion-btn-padding-y: 1rem;--bs-accordion-btn-color: #212529;--bs-accordion-btn-bg: #ffffff;--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23212529'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-icon-width: 1.25rem;--bs-accordion-btn-icon-transform: rotate(-180deg);--bs-accordion-btn-icon-transition: transform 0.2s ease-in-out;--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%285.2, 44, 101.2%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-focus-border-color: rgb(134, 182.5, 254);--bs-accordion-btn-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: rgb(5.2, 44, 101.2);--bs-accordion-active-bg: rgb(206.6, 226, 254.6)}.accordion-button{position:relative;display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;border-radius:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media(prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1*var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media(prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:first-of-type{border-top-left-radius:var(--bs-accordion-border-radius);border-top-right-radius:var(--bs-accordion-border-radius)}.accordion-item:first-of-type .accordion-button{border-top-left-radius:var(--bs-accordion-inner-border-radius);border-top-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:not(:first-of-type){border-top:0}.accordion-item:last-of-type{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-item:last-of-type .accordion-button.collapsed{border-bottom-right-radius:var(--bs-accordion-inner-border-radius);border-bottom-left-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0;border-radius:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme=dark] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%28109.8, 168, 253.8%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='rgb%28109.8, 168, 253.8%29'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: 0;--bs-breadcrumb-padding-y: 0;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color: rgba(33, 37, 41, 0.75);--bs-breadcrumb-item-padding-x: 0.5rem;--bs-breadcrumb-item-active-color: rgba(33, 37, 41, 0.75);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg);border-radius:var(--bs-breadcrumb-border-radius)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, ">") /* rtl: var(--bs-breadcrumb-divider, ">") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: 0.75rem;--bs-pagination-padding-y: 0.375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: #0d6efd;--bs-pagination-bg: #ffffff;--bs-pagination-border-width: 1px;--bs-pagination-border-color: #dee2e6;--bs-pagination-border-radius: 0.25rem;--bs-pagination-hover-color: rgb(10.4, 88, 202.4);--bs-pagination-hover-bg: #f8f9fa;--bs-pagination-hover-border-color: #dee2e6;--bs-pagination-focus-color: rgb(10.4, 88, 202.4);--bs-pagination-focus-bg: #e9ecef;--bs-pagination-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-pagination-active-color: #ffffff;--bs-pagination-active-bg: #0d6efd;--bs-pagination-active-border-color: #0d6efd;--bs-pagination-disabled-color: rgba(33, 37, 41, 0.75);--bs-pagination-disabled-bg: #e9ecef;--bs-pagination-disabled-border-color: #dee2e6;display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out}@media(prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(1px*-1)}.page-item:first-child .page-link{border-top-left-radius:var(--bs-pagination-border-radius);border-bottom-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-top-right-radius:var(--bs-pagination-border-radius);border-bottom-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: 0.75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: 0.5rem}.pagination-sm{--bs-pagination-padding-x: 0.5rem;--bs-pagination-padding-y: 0.25rem;--bs-pagination-font-size:0.875rem;--bs-pagination-border-radius: 0.2em}.badge{--bs-badge-padding-x: 0.65em;--bs-badge-padding-y: 0.35em;--bs-badge-font-size:0.75em;--bs-badge-font-weight: 700;--bs-badge-color: #ffffff;--bs-badge-border-radius: 0.25rem;display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:var(--bs-badge-border-radius)}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: 1px solid var(--bs-alert-border-color);--bs-alert-border-radius: 0.25rem;--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height: 1rem;--bs-progress-font-size:0.75rem;--bs-progress-bg: #e9ecef;--bs-progress-border-radius: 0.25rem;--bs-progress-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.075);--bs-progress-bar-color: #ffffff;--bs-progress-bar-bg: #0d6efd;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media(prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media(prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: #212529;--bs-list-group-bg: #ffffff;--bs-list-group-border-color: #dee2e6;--bs-list-group-border-width: 1px;--bs-list-group-border-radius: 0.25rem;--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: 0.5rem;--bs-list-group-action-color: rgba(33, 37, 41, 0.75);--bs-list-group-action-hover-color: #000;--bs-list-group-action-hover-bg: #f8f9fa;--bs-list-group-action-active-color: #212529;--bs-list-group-action-active-bg: #e9ecef;--bs-list-group-disabled-color: rgba(33, 37, 41, 0.75);--bs-list-group-disabled-bg: #ffffff;--bs-list-group-active-color: #ffffff;--bs-list-group-active-bg: #0d6efd;--bs-list-group-active-border-color: #0d6efd;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;border-radius:var(--bs-list-group-border-radius)}.list-group-numbered{list-style-type:none;counter-reset:section}.list-group-numbered>.list-group-item::before{content:counters(section, ".") ". ";counter-increment:section}.list-group-item-action{width:100%;color:var(--bs-list-group-action-color);text-align:inherit}.list-group-item-action:hover,.list-group-item-action:focus{z-index:1;color:var(--bs-list-group-action-hover-color);text-decoration:none;background-color:var(--bs-list-group-action-hover-bg)}.list-group-item-action:active{color:var(--bs-list-group-action-active-color);background-color:var(--bs-list-group-action-active-bg)}.list-group-item{position:relative;display:block;padding:var(--bs-list-group-item-padding-y) var(--bs-list-group-item-padding-x);color:var(--bs-list-group-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-list-group-bg);border:var(--bs-list-group-border-width) solid var(--bs-list-group-border-color)}.list-group-item:first-child{border-top-left-radius:inherit;border-top-right-radius:inherit}.list-group-item:last-child{border-bottom-right-radius:inherit;border-bottom-left-radius:inherit}.list-group-item.disabled,.list-group-item:disabled{color:var(--bs-list-group-disabled-color);pointer-events:none;background-color:var(--bs-list-group-disabled-bg)}.list-group-item.active{z-index:2;color:var(--bs-list-group-active-color);background-color:var(--bs-list-group-active-bg);border-color:var(--bs-list-group-active-border-color)}.list-group-item+.list-group-item{border-top-width:0}.list-group-item+.list-group-item.active{margin-top:calc(-1*var(--bs-list-group-border-width));border-top-width:var(--bs-list-group-border-width)}.list-group-horizontal{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal>.list-group-item.active{margin-top:0}.list-group-horizontal>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}@media(min-width: 576px){.list-group-horizontal-sm{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-sm>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-sm>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-sm>.list-group-item.active{margin-top:0}.list-group-horizontal-sm>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-sm>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 768px){.list-group-horizontal-md{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-md>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-md>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-md>.list-group-item.active{margin-top:0}.list-group-horizontal-md>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-md>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 992px){.list-group-horizontal-lg{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-lg>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-lg>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1200px){.list-group-horizontal-xl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1400px){.list-group-horizontal-xxl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xxl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xxl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xxl>.list-group-item.active{margin-top:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}.list-group-flush{border-radius:0}.list-group-flush>.list-group-item{border-width:0 0 var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-default{--bs-list-group-color: var(--bs-default-text-emphasis);--bs-list-group-bg: var(--bs-default-bg-subtle);--bs-list-group-border-color: var(--bs-default-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-default-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-default-border-subtle);--bs-list-group-active-color: var(--bs-default-bg-subtle);--bs-list-group-active-bg: var(--bs-default-text-emphasis);--bs-list-group-active-border-color: var(--bs-default-text-emphasis)}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23000'%3e%3cpath d='M.293.293a1 1 0 0 1 1.414 0L8 6.586 14.293.293a1 1 0 1 1 1.414 1.414L9.414 8l6.293 6.293a1 1 0 0 1-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 0 1-1.414-1.414L6.586 8 .293 1.707a1 1 0 0 1 0-1.414z'/%3e%3c/svg%3e");--bs-btn-close-opacity: 0.5;--bs-btn-close-hover-opacity: 0.75;--bs-btn-close-focus-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-btn-close-focus-opacity: 1;--bs-btn-close-disabled-opacity: 0.25;--bs-btn-close-white-filter: invert(1) grayscale(100%) brightness(200%);box-sizing:content-box;width:1em;height:1em;padding:.25em .25em;color:var(--bs-btn-close-color);background:rgba(0,0,0,0) var(--bs-btn-close-bg) center/1em auto no-repeat;border:0;border-radius:.25rem;opacity:var(--bs-btn-close-opacity)}.btn-close:hover{color:var(--bs-btn-close-color);text-decoration:none;opacity:var(--bs-btn-close-hover-opacity)}.btn-close:focus{outline:0;box-shadow:var(--bs-btn-close-focus-shadow);opacity:var(--bs-btn-close-focus-opacity)}.btn-close:disabled,.btn-close.disabled{pointer-events:none;user-select:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;-o-user-select:none;opacity:var(--bs-btn-close-disabled-opacity)}.btn-close-white{filter:var(--bs-btn-close-white-filter)}[data-bs-theme=dark] .btn-close{filter:var(--bs-btn-close-white-filter)}.toast{--bs-toast-zindex: 1090;--bs-toast-padding-x: 0.75rem;--bs-toast-padding-y: 0.5rem;--bs-toast-spacing: 1.5rem;--bs-toast-max-width: 350px;--bs-toast-font-size:0.875rem;--bs-toast-color: ;--bs-toast-bg: rgba(255, 255, 255, 0.85);--bs-toast-border-width: 1px;--bs-toast-border-color: rgba(0, 0, 0, 0.175);--bs-toast-border-radius: 0.25rem;--bs-toast-box-shadow: 0 0.5rem 1rem rgba(0, 0, 0, 0.15);--bs-toast-header-color: rgba(33, 37, 41, 0.75);--bs-toast-header-bg: rgba(255, 255, 255, 0.85);--bs-toast-header-border-color: rgba(0, 0, 0, 0.175);width:var(--bs-toast-max-width);max-width:100%;font-size:var(--bs-toast-font-size);color:var(--bs-toast-color);pointer-events:auto;background-color:var(--bs-toast-bg);background-clip:padding-box;border:var(--bs-toast-border-width) solid var(--bs-toast-border-color);box-shadow:var(--bs-toast-box-shadow);border-radius:var(--bs-toast-border-radius)}.toast.showing{opacity:0}.toast:not(.show){display:none}.toast-container{--bs-toast-zindex: 1090;position:absolute;z-index:var(--bs-toast-zindex);width:max-content;width:-webkit-max-content;width:-moz-max-content;width:-ms-max-content;width:-o-max-content;max-width:100%;pointer-events:none}.toast-container>:not(:last-child){margin-bottom:var(--bs-toast-spacing)}.toast-header{display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;padding:var(--bs-toast-padding-y) var(--bs-toast-padding-x);color:var(--bs-toast-header-color);background-color:var(--bs-toast-header-bg);background-clip:padding-box;border-bottom:var(--bs-toast-border-width) solid var(--bs-toast-header-border-color);border-top-left-radius:calc(var(--bs-toast-border-radius) - var(--bs-toast-border-width));border-top-right-radius:calc(var(--bs-toast-border-radius) - var(--bs-toast-border-width))}.toast-header .btn-close{margin-right:calc(-0.5*var(--bs-toast-padding-x));margin-left:var(--bs-toast-padding-x)}.toast-body{padding:var(--bs-toast-padding-x);word-wrap:break-word}.modal{--bs-modal-zindex: 1055;--bs-modal-width: 500px;--bs-modal-padding: 1rem;--bs-modal-margin: 0.5rem;--bs-modal-color: ;--bs-modal-bg: #ffffff;--bs-modal-border-color: rgba(0, 0, 0, 0.175);--bs-modal-border-width: 1px;--bs-modal-border-radius: 0.5rem;--bs-modal-box-shadow: 0 0.125rem 0.25rem rgba(0, 0, 0, 0.075);--bs-modal-inner-border-radius: calc(0.5rem - 1px);--bs-modal-header-padding-x: 1rem;--bs-modal-header-padding-y: 1rem;--bs-modal-header-padding: 1rem 1rem;--bs-modal-header-border-color: #dee2e6;--bs-modal-header-border-width: 1px;--bs-modal-title-line-height: 1.5;--bs-modal-footer-gap: 0.5rem;--bs-modal-footer-bg: ;--bs-modal-footer-border-color: #dee2e6;--bs-modal-footer-border-width: 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;--quarto-scss-export-border-color-translucent: rgba(0, 0, 0, 0.175);--quarto-scss-export-component-active-bg: #0d6efd;--quarto-scss-export-component-active-color: #ffffff;--quarto-scss-export-focus-ring-color: rgba(13, 110, 253, 0.25);--quarto-scss-export-headings-font-family: ;--quarto-scss-export-headings-font-style: ;--quarto-scss-export-display-font-family: ;--quarto-scss-export-display-font-style: ;--quarto-scss-export-blockquote-footer-color: #6c757d;--quarto-scss-export-blockquote-border-color: #e9ecef;--quarto-scss-export-hr-bg-color: ;--quarto-scss-export-hr-height: ;--quarto-scss-export-hr-border-color: ;--quarto-scss-export-legend-font-weight: ;--quarto-scss-export-mark-bg: rgb(255, 242.6, 205.4);--quarto-scss-export-table-color: #212529;--quarto-scss-export-table-bg: #ffffff;--quarto-scss-export-table-accent-bg: transparent;--quarto-scss-export-table-th-font-weight: ;--quarto-scss-export-table-striped-color: #212529;--quarto-scss-export-table-striped-bg: rgba(0, 0, 0, 0.05);--quarto-scss-export-table-active-color: #212529;--quarto-scss-export-table-active-bg: rgba(0, 0, 0, 0.1);--quarto-scss-export-table-hover-color: #212529;--quarto-scss-export-table-hover-bg: rgba(0, 0, 0, 0.075);--quarto-scss-export-table-caption-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-input-btn-font-family: ;--quarto-scss-export-input-btn-focus-color: rgba(13, 110, 253, 0.25);--quarto-scss-export-btn-color: #212529;--quarto-scss-export-btn-font-family: ;--quarto-scss-export-btn-white-space: ;--quarto-scss-export-btn-link-color: #0d6efd;--quarto-scss-export-btn-link-hover-color: rgb(10.4, 88, 202.4);--quarto-scss-export-btn-link-disabled-color: #6c757d;--quarto-scss-export-form-text-font-style: ;--quarto-scss-export-form-text-font-weight: ;--quarto-scss-export-form-text-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-form-label-font-size: ;--quarto-scss-export-form-label-font-style: ;--quarto-scss-export-form-label-font-weight: ;--quarto-scss-export-form-label-color: ;--quarto-scss-export-input-font-family: ;--quarto-scss-export-input-disabled-color: ;--quarto-scss-export-input-disabled-bg: #e9ecef;--quarto-scss-export-input-disabled-border-color: ;--quarto-scss-export-input-color: #212529;--quarto-scss-export-input-focus-bg: #ffffff;--quarto-scss-export-input-focus-border-color: rgb(134, 182.5, 254);--quarto-scss-export-input-focus-color: #212529;--quarto-scss-export-input-placeholder-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-input-plaintext-color: #212529;--quarto-scss-export-form-check-label-color: ;--quarto-scss-export-form-check-transition: ;--quarto-scss-export-form-check-input-bg: #ffffff;--quarto-scss-export-form-check-input-focus-border: rgb(134, 182.5, 254);--quarto-scss-export-form-check-input-checked-color: #ffffff;--quarto-scss-export-form-check-input-checked-bg-color: #0d6efd;--quarto-scss-export-form-check-input-checked-border-color: #0d6efd;--quarto-scss-export-form-check-input-indeterminate-color: #ffffff;--quarto-scss-export-form-check-input-indeterminate-bg-color: #0d6efd;--quarto-scss-export-form-check-input-indeterminate-border-color: #0d6efd;--quarto-scss-export-form-switch-color: rgba(0, 0, 0, 0.25);--quarto-scss-export-form-switch-focus-color: rgb(134, 182.5, 254);--quarto-scss-export-form-switch-checked-color: #ffffff;--quarto-scss-export-input-group-addon-color: #212529;--quarto-scss-export-input-group-addon-bg: #f8f9fa;--quarto-scss-export-input-group-addon-border-color: #dee2e6;--quarto-scss-export-form-select-font-family: ;--quarto-scss-export-form-select-color: #212529;--quarto-scss-export-form-select-bg: #ffffff;--quarto-scss-export-form-select-disabled-color: ;--quarto-scss-export-form-select-disabled-bg: #e9ecef;--quarto-scss-export-form-select-disabled-border-color: ;--quarto-scss-export-form-select-indicator-color: #343a40;--quarto-scss-export-form-select-border-color: #dee2e6;--quarto-scss-export-form-select-focus-border-color: rgb(134, 182.5, 254);--quarto-scss-export-form-range-track-bg: #f8f9fa;--quarto-scss-export-form-range-thumb-bg: #0d6efd;--quarto-scss-export-form-range-thumb-active-bg: rgb(182.4, 211.5, 254.4);--quarto-scss-export-form-range-thumb-disabled-bg: rgba(33, 37, 41, 0.75);--quarto-scss-export-form-file-button-color: #212529;--quarto-scss-export-form-file-button-bg: #f8f9fa;--quarto-scss-export-form-file-button-hover-bg: #e9ecef;--quarto-scss-export-form-floating-label-disabled-color: #6c757d;--quarto-scss-export-form-feedback-font-style: ;--quarto-scss-export-form-feedback-valid-color: #198754;--quarto-scss-export-form-feedback-invalid-color: #dc3545;--quarto-scss-export-form-feedback-icon-valid-color: #198754;--quarto-scss-export-form-feedback-icon-invalid-color: #dc3545;--quarto-scss-export-form-valid-color: #198754;--quarto-scss-export-form-valid-border-color: #198754;--quarto-scss-export-form-invalid-color: #dc3545;--quarto-scss-export-form-invalid-border-color: #dc3545;--quarto-scss-export-nav-link-font-size: ;--quarto-scss-export-nav-link-font-weight: ;--quarto-scss-export-nav-link-color: #0d6efd;--quarto-scss-export-nav-link-hover-color: rgb(10.4, 88, 202.4);--quarto-scss-export-nav-link-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-nav-tabs-border-color: #dee2e6;--quarto-scss-export-nav-tabs-link-hover-border-color: #e9ecef #e9ecef #dee2e6;--quarto-scss-export-nav-tabs-link-active-color: #000;--quarto-scss-export-nav-tabs-link-active-bg: #ffffff;--quarto-scss-export-nav-pills-link-active-bg: #0d6efd;--quarto-scss-export-nav-pills-link-active-color: #ffffff;--quarto-scss-export-nav-underline-link-active-color: #000;--quarto-scss-export-navbar-padding-x: ;--quarto-scss-export-navbar-light-contrast: #000;--quarto-scss-export-navbar-dark-contrast: #000;--quarto-scss-export-navbar-light-icon-color: rgba(0, 0, 0, 0.75);--quarto-scss-export-navbar-dark-icon-color: rgba(0, 0, 0, 0.75);--quarto-scss-export-dropdown-color: #212529;--quarto-scss-export-dropdown-bg: #ffffff;--quarto-scss-export-dropdown-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-divider-bg: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-link-color: #212529;--quarto-scss-export-dropdown-link-hover-color: #212529;--quarto-scss-export-dropdown-link-hover-bg: #f8f9fa;--quarto-scss-export-dropdown-link-active-bg: #0d6efd;--quarto-scss-export-dropdown-link-active-color: #ffffff;--quarto-scss-export-dropdown-link-disabled-color: rgba(33, 37, 41, 0.5);--quarto-scss-export-dropdown-header-color: #6c757d;--quarto-scss-export-dropdown-dark-color: #dee2e6;--quarto-scss-export-dropdown-dark-bg: #343a40;--quarto-scss-export-dropdown-dark-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-dark-divider-bg: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-dark-box-shadow: ;--quarto-scss-export-dropdown-dark-link-color: #dee2e6;--quarto-scss-export-dropdown-dark-link-hover-color: #ffffff;--quarto-scss-export-dropdown-dark-link-hover-bg: rgba(255, 255, 255, 0.15);--quarto-scss-export-dropdown-dark-link-active-color: #ffffff;--quarto-scss-export-dropdown-dark-link-active-bg: #0d6efd;--quarto-scss-export-dropdown-dark-link-disabled-color: #adb5bd;--quarto-scss-export-dropdown-dark-header-color: #adb5bd;--quarto-scss-export-pagination-color: #0d6efd;--quarto-scss-export-pagination-bg: #ffffff;--quarto-scss-export-pagination-border-color: #dee2e6;--quarto-scss-export-pagination-focus-color: rgb(10.4, 88, 202.4);--quarto-scss-export-pagination-focus-bg: #e9ecef;--quarto-scss-export-pagination-hover-color: rgb(10.4, 88, 202.4);--quarto-scss-export-pagination-hover-bg: #f8f9fa;--quarto-scss-export-pagination-hover-border-color: #dee2e6;--quarto-scss-export-pagination-active-color: #ffffff;--quarto-scss-export-pagination-active-bg: #0d6efd;--quarto-scss-export-pagination-active-border-color: #0d6efd;--quarto-scss-export-pagination-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-pagination-disabled-bg: #e9ecef;--quarto-scss-export-pagination-disabled-border-color: #dee2e6;--quarto-scss-export-card-title-color: ;--quarto-scss-export-card-subtitle-color: ;--quarto-scss-export-card-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-card-box-shadow: ;--quarto-scss-export-card-cap-color: ;--quarto-scss-export-card-height: ;--quarto-scss-export-card-color: ;--quarto-scss-export-card-bg: #ffffff;--quarto-scss-export-accordion-color: #212529;--quarto-scss-export-accordion-bg: #ffffff;--quarto-scss-export-accordion-border-color: #dee2e6;--quarto-scss-export-accordion-button-color: #212529;--quarto-scss-export-accordion-button-bg: #ffffff;--quarto-scss-export-accordion-button-active-bg: rgb(206.6, 226, 254.6);--quarto-scss-export-accordion-button-active-color: rgb(5.2, 44, 101.2);--quarto-scss-export-accordion-button-focus-border-color: rgb(134, 182.5, 254);--quarto-scss-export-accordion-icon-color: #212529;--quarto-scss-export-accordion-icon-active-color: rgb(5.2, 44, 101.2);--quarto-scss-export-tooltip-color: #ffffff;--quarto-scss-export-tooltip-bg: #000;--quarto-scss-export-tooltip-margin: ;--quarto-scss-export-tooltip-arrow-color: ;--quarto-scss-export-form-feedback-tooltip-line-height: ;--quarto-scss-export-popover-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-popover-header-bg: #e9ecef;--quarto-scss-export-popover-body-color: #212529;--quarto-scss-export-popover-arrow-color: #ffffff;--quarto-scss-export-popover-arrow-outer-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-toast-color: ;--quarto-scss-export-toast-background-color: rgba(255, 255, 255, 0.85);--quarto-scss-export-toast-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-toast-header-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-toast-header-background-color: rgba(255, 255, 255, 0.85);--quarto-scss-export-toast-header-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-badge-color: #ffffff;--quarto-scss-export-modal-content-color: ;--quarto-scss-export-modal-content-bg: #ffffff;--quarto-scss-export-modal-content-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-modal-backdrop-bg: #000;--quarto-scss-export-modal-header-border-color: #dee2e6;--quarto-scss-export-modal-footer-bg: ;--quarto-scss-export-modal-footer-border-color: #dee2e6;--quarto-scss-export-progress-bg: #e9ecef;--quarto-scss-export-progress-bar-color: #ffffff;--quarto-scss-export-progress-bar-bg: #0d6efd;--quarto-scss-export-list-group-color: #212529;--quarto-scss-export-list-group-bg: #ffffff;--quarto-scss-export-list-group-border-color: #dee2e6;--quarto-scss-export-list-group-hover-bg: #f8f9fa;--quarto-scss-export-list-group-active-bg: #0d6efd;--quarto-scss-export-list-group-active-color: #ffffff;--quarto-scss-export-list-group-active-border-color: #0d6efd;--quarto-scss-export-list-group-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-list-group-disabled-bg: #ffffff;--quarto-scss-export-list-group-action-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-list-group-action-hover-color: #000;--quarto-scss-export-list-group-action-active-color: #212529;--quarto-scss-export-list-group-action-active-bg: #e9ecef;--quarto-scss-export-thumbnail-bg: #ffffff;--quarto-scss-export-thumbnail-border-color: #dee2e6;--quarto-scss-export-figure-caption-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-font-size: ;--quarto-scss-export-breadcrumb-bg: ;--quarto-scss-export-breadcrumb-divider-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-active-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-border-radius: ;--quarto-scss-export-carousel-control-color: #ffffff;--quarto-scss-export-carousel-indicator-active-bg: #ffffff;--quarto-scss-export-carousel-caption-color: #ffffff;--quarto-scss-export-carousel-dark-indicator-active-bg: #000;--quarto-scss-export-carousel-dark-caption-color: #000;--quarto-scss-export-btn-close-color: #000;--quarto-scss-export-offcanvas-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-offcanvas-bg-color: #ffffff;--quarto-scss-export-offcanvas-color: #212529;--quarto-scss-export-offcanvas-backdrop-bg: #000;--quarto-scss-export-code-color-dark: white;--quarto-scss-export-kbd-color: #ffffff;--quarto-scss-export-kbd-bg: #212529;--quarto-scss-export-nested-kbd-font-weight: ;--quarto-scss-export-pre-bg: #f8f9fa;--quarto-scss-export-pre-color: #000;--quarto-scss-export-bslib-sidebar-bg: rgba(var(--bs-emphasis-color-rgb, 0, 0, 0), 0.05);--quarto-scss-export-bslib-sidebar-toggle-bg: rgba(var(--bs-emphasis-color-rgb, 0, 0, 0), 0.1);--quarto-scss-export-bslib-page-sidebar-title-bg: white;--quarto-scss-export-bslib-page-sidebar-title-color: #000;--quarto-scss-export-sidebar-color: rgb(89.25, 89.25, 89.25);--quarto-scss-export-sidebar-hover-color: rgba(9.75, 82.5, 189.75, 0.8);--quarto-scss-export-sidebar-disabled-color: rgba(89.25, 89.25, 89.25, 0.75);--quarto-scss-export-valuebox-bg-primary: #0d6efd;--quarto-scss-export-valuebox-bg-secondary: #6c757d;--quarto-scss-export-valuebox-bg-success: #198754;--quarto-scss-export-valuebox-bg-info: #0dcaf0;--quarto-scss-export-valuebox-bg-warning: #ffc107;--quarto-scss-export-valuebox-bg-danger: #dc3545;--quarto-scss-export-valuebox-bg-light: #f8f9fa;--quarto-scss-export-valuebox-bg-dark: #212529;--quarto-scss-export-mermaid-bg-color: #ffffff;--quarto-scss-export-mermaid-edge-color: #6c757d;--quarto-scss-export-mermaid-node-fg-color: #212529;--quarto-scss-export-mermaid-fg-color: #212529;--quarto-scss-export-mermaid-fg-color--lighter: rgb(55.7432432432, 62.5, 69.2567567568);--quarto-scss-export-mermaid-fg-color--lightest: rgb(78.4864864865, 88, 97.5135135135);--quarto-scss-export-mermaid-label-bg-color: #ffffff;--quarto-scss-export-mermaid-label-fg-color: #0d6efd;--quarto-scss-export-mermaid-node-bg-color: rgba(13, 110, 253, 0.1);--quarto-scss-export-code-block-border-left-color: #dee2e6;--quarto-scss-export-callout-color-note: #0d6efd;--quarto-scss-export-callout-color-tip: #198754;--quarto-scss-export-callout-color-important: #dc3545;--quarto-scss-export-callout-color-caution: #fd7e14;--quarto-scss-export-callout-color-warning: #ffc107} \ No newline at end of file diff --git a/docs/site_libs/bootstrap/bootstrap-icons.css b/docs/site_libs/bootstrap/bootstrap-icons.css index 285e444..08ba797 100644 --- a/docs/site_libs/bootstrap/bootstrap-icons.css +++ b/docs/site_libs/bootstrap/bootstrap-icons.css @@ -1,2078 +1,2078 @@ -/*! - * Bootstrap Icons v1.11.1 (https://icons.getbootstrap.com/) - * Copyright 2019-2023 The Bootstrap Authors - * Licensed under MIT (https://github.com/twbs/icons/blob/main/LICENSE) - */ - -@font-face { - font-display: block; - font-family: "bootstrap-icons"; - src: -url("./bootstrap-icons.woff?2820a3852bdb9a5832199cc61cec4e65") format("woff"); -} - -.bi::before, -[class^="bi-"]::before, -[class*=" bi-"]::before { - display: inline-block; - font-family: bootstrap-icons !important; - font-style: normal; - font-weight: normal !important; - font-variant: normal; - text-transform: none; - line-height: 1; - vertical-align: -.125em; - -webkit-font-smoothing: antialiased; - -moz-osx-font-smoothing: grayscale; -} - -.bi-123::before { content: "\f67f"; } -.bi-alarm-fill::before { content: "\f101"; } -.bi-alarm::before { content: "\f102"; } -.bi-align-bottom::before { content: "\f103"; } -.bi-align-center::before { content: "\f104"; } -.bi-align-end::before { content: "\f105"; } -.bi-align-middle::before { content: "\f106"; } -.bi-align-start::before { content: "\f107"; } -.bi-align-top::before { content: "\f108"; } -.bi-alt::before { content: "\f109"; } -.bi-app-indicator::before { content: "\f10a"; } -.bi-app::before { content: "\f10b"; } -.bi-archive-fill::before { content: "\f10c"; } -.bi-archive::before { content: "\f10d"; } 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s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var fi={placement:"bottom",modifiers:[],strategy:"absolute"};function pi(){for(var t=arguments.length,e=new Array(t),i=0;iNumber.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(F.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...g(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=z.find(".dropdown-menu 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e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ei,Ti].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ii)?this:z.prev(this,Ii)[0]||z.next(this,Ii)[0]||z.findOne(Ii,t.delegateTarget.parentNode),o=qi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}N.on(document,Si,Ii,qi.dataApiKeydownHandler),N.on(document,Si,Pi,qi.dataApiKeydownHandler),N.on(document,Li,qi.clearMenus),N.on(document,Di,qi.clearMenus),N.on(document,Li,Ii,(function(t){t.preventDefault(),qi.getOrCreateInstance(this).toggle()})),m(qi);const Vi="backdrop",Ki="show",Qi=`mousedown.bs.${Vi}`,Xi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Yi={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Ui extends H{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Yi}static get NAME(){return Vi}show(t){if(!this._config.isVisible)return void g(t);this._append();const e=this._getElement();this._config.isAnimated&&d(e),e.classList.add(Ki),this._emulateAnimation((()=>{g(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),g(t)}))):g(t)}dispose(){this._isAppended&&(N.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=r(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),N.on(t,Qi,(()=>{g(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){_(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends H{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),N.off(document,Gi),N.on(document,Ji,(t=>this._handleFocusin(t))),N.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,N.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=z.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===tn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?tn:"forward")}}const on=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",rn=".sticky-top",an="padding-right",ln="margin-right";class cn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,an,(e=>e+t)),this._setElementAttributes(on,an,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,an),this._resetElementAttributes(on,an),this._resetElementAttributes(rn,ln)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&F.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=F.getDataAttribute(t,e);null!==i?(F.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(o(t))e(t);else for(const i of z.find(t,this._element))e(i)}}const hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",An="show",En="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends W{constructor(t,e){super(t,e),this._dialog=z.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||N.trigger(this._element,pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(wn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(N.trigger(this._element,dn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){N.off(window,hn),N.off(this._dialog,hn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Ui({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=z.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),d(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,N.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){N.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),N.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),N.on(this._element,bn,(t=>{N.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),N.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(N.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(En)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(En),this._queueCallback((()=>{this._element.classList.remove(En),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=p()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=p()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=On.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}N.on(document,yn,'[data-bs-toggle="modal"]',(function(t){const e=z.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),N.one(e,pn,(t=>{t.defaultPrevented||N.one(e,fn,(()=>{a(this)&&this.focus()}))}));const i=z.findOne(".modal.show");i&&On.getInstance(i).hide(),On.getOrCreateInstance(e).toggle(this)})),R(On),m(On);const xn=".bs.offcanvas",kn=".data-api",Ln=`load${xn}${kn}`,Sn="show",Dn="showing",$n="hiding",In=".offcanvas.show",Nn=`show${xn}`,Pn=`shown${xn}`,Mn=`hide${xn}`,jn=`hidePrevented${xn}`,Fn=`hidden${xn}`,Hn=`resize${xn}`,Wn=`click${xn}${kn}`,Bn=`keydown.dismiss${xn}`,zn={backdrop:!0,keyboard:!0,scroll:!1},Rn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class qn extends W{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||N.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),N.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(N.trigger(this._element,Mn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),N.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():N.trigger(this._element,jn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){N.on(this._element,Bn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():N.trigger(this._element,jn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}N.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=z.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),l(this))return;N.one(e,Fn,(()=>{a(this)&&this.focus()}));const i=z.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),N.on(window,Ln,(()=>{for(const t of z.find(In))qn.getOrCreateInstance(t).show()})),N.on(window,Hn,(()=>{for(const t of z.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),R(qn),m(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Yn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"
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")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=z.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?o(e)?this._putElementInTemplate(r(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return g(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const Zn=new Set(["sanitize","allowList","sanitizeFn"]),ts="fade",es="show",is=".modal",ns="hide.bs.modal",ss="hover",os="focus",rs={AUTO:"auto",TOP:"top",RIGHT:p()?"left":"right",BOTTOM:"bottom",LEFT:p()?"right":"left"},as={allowList:Vn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'',title:"",trigger:"hover focus"},ls={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class cs extends W{constructor(t,e){if(void 0===vi)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,e),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return as}static get DefaultType(){return ls}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),N.off(this._element.closest(is),ns,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=N.trigger(this._element,this.constructor.eventName("show")),e=(c(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),N.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.on(t,"mouseover",h);this._queueCallback((()=>{N.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!N.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.off(t,"mouseover",h);this._activeTrigger.click=!1,this._activeTrigger[os]=!1,this._activeTrigger[ss]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),N.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(ts,es),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(ts),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new Jn({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{".tooltip-inner":this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(ts)}_isShown(){return this.tip&&this.tip.classList.contains(es)}_createPopper(t){const e=g(this._config.placement,[this,t,this._element]),i=rs[e.toUpperCase()];return bi(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return g(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...g(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)N.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===ss?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===ss?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");N.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?os:ss]=!0,e._enter()})),N.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?os:ss]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},N.on(this._element.closest(is),ns,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=F.getDataAttributes(this._element);for(const t of Object.keys(e))Zn.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=cs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}m(cs);const hs={...cs.Default,content:"",offset:[0,8],placement:"right",template:'',trigger:"click"},ds={...cs.DefaultType,content:"(null|string|element|function)"};class us extends cs{static get Default(){return hs}static get DefaultType(){return ds}static get 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e=this._observableSections.get(t.target.hash);if(e){t.preventDefault();const i=this._rootElement||window,n=e.offsetTop-this._element.offsetTop;if(i.scrollTo)return void i.scrollTo({top:n,behavior:"smooth"});i.scrollTop=n}})))}_getNewObserver(){const t={root:this._rootElement,threshold:this._config.threshold,rootMargin:this._config.rootMargin};return new IntersectionObserver((t=>this._observerCallback(t)),t)}_observerCallback(t){const e=t=>this._targetLinks.get(`#${t.target.id}`),i=t=>{this._previousScrollData.visibleEntryTop=t.target.offsetTop,this._process(e(t))},n=(this._rootElement||document.documentElement).scrollTop,s=n>=this._previousScrollData.parentScrollTop;this._previousScrollData.parentScrollTop=n;for(const o of t){if(!o.isIntersecting){this._activeTarget=null,this._clearActiveClass(e(o));continue}const t=o.target.offsetTop>=this._previousScrollData.visibleEntryTop;if(s&&t){if(i(o),!n)return}else s||t||i(o)}}_initializeTargetsAndObservables(){this._targetLinks=new 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t.defaultInterval=t.interval,t}_addEventListeners(){this._config.keyboard&&N.on(this._element,ft,(t=>this._keydown(t))),"hover"===this._config.pause&&(N.on(this._element,pt,(()=>this.pause())),N.on(this._element,mt,(()=>this._maybeEnableCycle()))),this._config.touch&&st.isSupported()&&this._addTouchEventListeners()}_addTouchEventListeners(){for(const t of z.find(".carousel-item img",this._element))N.on(t,gt,(t=>t.preventDefault()));const t={leftCallback:()=>this._slide(this._directionToOrder(ct)),rightCallback:()=>this._slide(this._directionToOrder(ht)),endCallback:()=>{"hover"===this._config.pause&&(this.pause(),this.touchTimeout&&clearTimeout(this.touchTimeout),this.touchTimeout=setTimeout((()=>this._maybeEnableCycle()),500+this._config.interval))}};this._swipeHelper=new st(this._element,t)}_keydown(t){if(/input|textarea/i.test(t.target.tagName))return;const e=Tt[t.key];e&&(t.preventDefault(),this._slide(this._directionToOrder(e)))}_getItemIndex(t){return this._getItems().indexOf(t)}_setActiveIndicatorElement(t){if(!this._indicatorsElement)return;const e=z.findOne(wt,this._indicatorsElement);e.classList.remove(yt),e.removeAttribute("aria-current");const i=z.findOne(`[data-bs-slide-to="${t}"]`,this._indicatorsElement);i&&(i.classList.add(yt),i.setAttribute("aria-current","true"))}_updateInterval(){const t=this._activeElement||this._getActive();if(!t)return;const e=Number.parseInt(t.getAttribute("data-bs-interval"),10);this._config.interval=e||this._config.defaultInterval}_slide(t,e=null){if(this._isSliding)return;const i=this._getActive(),n=t===at,s=e||b(this._getItems(),i,n,this._config.wrap);if(s===i)return;const o=this._getItemIndex(s),r=e=>N.trigger(this._element,e,{relatedTarget:s,direction:this._orderToDirection(t),from:this._getItemIndex(i),to:o});if(r(dt).defaultPrevented)return;if(!i||!s)return;const a=Boolean(this._interval);this.pause(),this._isSliding=!0,this._setActiveIndicatorElement(o),this._activeElement=s;const l=n?"carousel-item-start":"carousel-item-end",c=n?"carousel-item-next":"carousel-item-prev";s.classList.add(c),d(s),i.classList.add(l),s.classList.add(l),this._queueCallback((()=>{s.classList.remove(l,c),s.classList.add(yt),i.classList.remove(yt,c,l),this._isSliding=!1,r(ut)}),i,this._isAnimated()),a&&this.cycle()}_isAnimated(){return this._element.classList.contains("slide")}_getActive(){return z.findOne(Et,this._element)}_getItems(){return z.find(At,this._element)}_clearInterval(){this._interval&&(clearInterval(this._interval),this._interval=null)}_directionToOrder(t){return p()?t===ct?lt:at:t===ct?at:lt}_orderToDirection(t){return p()?t===lt?ct:ht:t===lt?ht:ct}static jQueryInterface(t){return this.each((function(){const e=xt.getOrCreateInstance(this,t);if("number"!=typeof t){if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}else e.to(t)}))}}N.on(document,bt,"[data-bs-slide], 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i=`scroll${e[0].toUpperCase()+e.slice(1)}`;this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(Mt),this._element.classList.add(Pt,Nt),this._element.style[e]="",N.trigger(this._element,St)}),this._element,!0),this._element.style[e]=`${this._element[i]}px`}hide(){if(this._isTransitioning||!this._isShown())return;if(N.trigger(this._element,Dt).defaultPrevented)return;const t=this._getDimension();this._element.style[t]=`${this._element.getBoundingClientRect()[t]}px`,d(this._element),this._element.classList.add(Mt),this._element.classList.remove(Pt,Nt);for(const t of this._triggerArray){const e=z.getElementFromSelector(t);e&&!this._isShown(e)&&this._addAriaAndCollapsedClass([t],!1)}this._isTransitioning=!0,this._element.style[t]="",this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(Mt),this._element.classList.add(Pt),N.trigger(this._element,$t)}),this._element,!0)}_isShown(t=this._element){return 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J,Z="x"===y?zt:Vt,tt="x"===y?Rt:qt,et=A[w],it="y"===w?"height":"width",nt=et+g[Z],st=et-g[tt],ot=-1!==[zt,Vt].indexOf(_),rt=null!=(J=null==x?void 0:x[w])?J:0,at=ot?nt:et-E[it]-T[it]-rt+O.altAxis,lt=ot?et+E[it]+T[it]-rt-O.altAxis:st,ct=f&&ot?function(t,e,i){var n=Ne(t,e,i);return n>i?i:n}(at,et,lt):Ne(f?at:nt,et,f?lt:st);A[w]=ct,k[w]=ct-et}e.modifiersData[n]=k}},requiresIfExists:["offset"]};function di(t,e,i){void 0===i&&(i=!1);var n,s,o=me(e),r=me(e)&&function(t){var e=t.getBoundingClientRect(),i=we(e.width)/t.offsetWidth||1,n=we(e.height)/t.offsetHeight||1;return 1!==i||1!==n}(e),a=Le(e),l=Te(t,r,i),c={scrollLeft:0,scrollTop:0},h={x:0,y:0};return(o||!o&&!i)&&(("body"!==ue(e)||Ue(a))&&(c=(n=e)!==fe(n)&&me(n)?{scrollLeft:(s=n).scrollLeft,scrollTop:s.scrollTop}:Xe(n)),me(e)?((h=Te(e,!0)).x+=e.clientLeft,h.y+=e.clientTop):a&&(h.x=Ye(a))),{x:l.left+c.scrollLeft-h.x,y:l.top+c.scrollTop-h.y,width:l.width,height:l.height}}function ui(t){var e=new Map,i=new Set,n=[];function s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var fi={placement:"bottom",modifiers:[],strategy:"absolute"};function pi(){for(var t=arguments.length,e=new Array(t),i=0;iNumber.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(F.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...g(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=z.find(".dropdown-menu 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e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ei,Ti].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ii)?this:z.prev(this,Ii)[0]||z.next(this,Ii)[0]||z.findOne(Ii,t.delegateTarget.parentNode),o=qi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}N.on(document,Si,Ii,qi.dataApiKeydownHandler),N.on(document,Si,Pi,qi.dataApiKeydownHandler),N.on(document,Li,qi.clearMenus),N.on(document,Di,qi.clearMenus),N.on(document,Li,Ii,(function(t){t.preventDefault(),qi.getOrCreateInstance(this).toggle()})),m(qi);const Vi="backdrop",Ki="show",Qi=`mousedown.bs.${Vi}`,Xi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Yi={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Ui extends H{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Yi}static get NAME(){return Vi}show(t){if(!this._config.isVisible)return void g(t);this._append();const e=this._getElement();this._config.isAnimated&&d(e),e.classList.add(Ki),this._emulateAnimation((()=>{g(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),g(t)}))):g(t)}dispose(){this._isAppended&&(N.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=r(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),N.on(t,Qi,(()=>{g(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){_(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends H{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),N.off(document,Gi),N.on(document,Ji,(t=>this._handleFocusin(t))),N.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,N.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=z.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===tn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?tn:"forward")}}const on=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",rn=".sticky-top",an="padding-right",ln="margin-right";class cn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,an,(e=>e+t)),this._setElementAttributes(on,an,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,an),this._resetElementAttributes(on,an),this._resetElementAttributes(rn,ln)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&F.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=F.getDataAttribute(t,e);null!==i?(F.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(o(t))e(t);else for(const i of z.find(t,this._element))e(i)}}const hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",An="show",En="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends W{constructor(t,e){super(t,e),this._dialog=z.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||N.trigger(this._element,pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(wn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(N.trigger(this._element,dn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){N.off(window,hn),N.off(this._dialog,hn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Ui({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=z.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),d(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,N.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){N.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),N.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),N.on(this._element,bn,(t=>{N.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),N.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(N.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(En)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(En),this._queueCallback((()=>{this._element.classList.remove(En),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=p()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=p()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=On.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}N.on(document,yn,'[data-bs-toggle="modal"]',(function(t){const e=z.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),N.one(e,pn,(t=>{t.defaultPrevented||N.one(e,fn,(()=>{a(this)&&this.focus()}))}));const i=z.findOne(".modal.show");i&&On.getInstance(i).hide(),On.getOrCreateInstance(e).toggle(this)})),R(On),m(On);const xn=".bs.offcanvas",kn=".data-api",Ln=`load${xn}${kn}`,Sn="show",Dn="showing",$n="hiding",In=".offcanvas.show",Nn=`show${xn}`,Pn=`shown${xn}`,Mn=`hide${xn}`,jn=`hidePrevented${xn}`,Fn=`hidden${xn}`,Hn=`resize${xn}`,Wn=`click${xn}${kn}`,Bn=`keydown.dismiss${xn}`,zn={backdrop:!0,keyboard:!0,scroll:!1},Rn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class qn extends W{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||N.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),N.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(N.trigger(this._element,Mn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),N.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():N.trigger(this._element,jn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){N.on(this._element,Bn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():N.trigger(this._element,jn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}N.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=z.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),l(this))return;N.one(e,Fn,(()=>{a(this)&&this.focus()}));const i=z.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),N.on(window,Ln,(()=>{for(const t of z.find(In))qn.getOrCreateInstance(t).show()})),N.on(window,Hn,(()=>{for(const t of z.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),R(qn),m(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Yn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"
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")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=z.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?o(e)?this._putElementInTemplate(r(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return g(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const Zn=new Set(["sanitize","allowList","sanitizeFn"]),ts="fade",es="show",is=".modal",ns="hide.bs.modal",ss="hover",os="focus",rs={AUTO:"auto",TOP:"top",RIGHT:p()?"left":"right",BOTTOM:"bottom",LEFT:p()?"right":"left"},as={allowList:Vn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'',title:"",trigger:"hover focus"},ls={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class cs extends W{constructor(t,e){if(void 0===vi)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,e),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return as}static get DefaultType(){return ls}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),N.off(this._element.closest(is),ns,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=N.trigger(this._element,this.constructor.eventName("show")),e=(c(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),N.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.on(t,"mouseover",h);this._queueCallback((()=>{N.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!N.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.off(t,"mouseover",h);this._activeTrigger.click=!1,this._activeTrigger[os]=!1,this._activeTrigger[ss]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),N.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(ts,es),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(ts),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new Jn({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{".tooltip-inner":this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(ts)}_isShown(){return this.tip&&this.tip.classList.contains(es)}_createPopper(t){const e=g(this._config.placement,[this,t,this._element]),i=rs[e.toUpperCase()];return bi(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return g(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...g(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)N.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===ss?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===ss?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");N.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?os:ss]=!0,e._enter()})),N.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?os:ss]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},N.on(this._element.closest(is),ns,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=F.getDataAttributes(this._element);for(const t of Object.keys(e))Zn.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=cs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}m(cs);const hs={...cs.Default,content:"",offset:[0,8],placement:"right",template:'',trigger:"click"},ds={...cs.DefaultType,content:"(null|string|element|function)"};class us extends cs{static get Default(){return hs}static get DefaultType(){return ds}static get NAME(){return"popover"}_isWithContent(){return this._getTitle()||this._getContent()}_getContentForTemplate(){return{".popover-header":this._getTitle(),".popover-body":this._getContent()}}_getContent(){return this._resolvePossibleFunction(this._config.content)}static jQueryInterface(t){return this.each((function(){const e=us.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}m(us);const fs=".bs.scrollspy",ps=`activate${fs}`,ms=`click${fs}`,gs=`load${fs}.data-api`,_s="active",bs="[href]",vs=".nav-link",ys=`${vs}, .nav-item > ${vs}, .list-group-item`,ws={offset:null,rootMargin:"0px 0px -25%",smoothScroll:!1,target:null,threshold:[.1,.5,1]},As={offset:"(number|null)",rootMargin:"string",smoothScroll:"boolean",target:"element",threshold:"array"};class Es extends W{constructor(t,e){super(t,e),this._targetLinks=new Map,this._observableSections=new 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e=this._observableSections.get(t.target.hash);if(e){t.preventDefault();const i=this._rootElement||window,n=e.offsetTop-this._element.offsetTop;if(i.scrollTo)return void i.scrollTo({top:n,behavior:"smooth"});i.scrollTop=n}})))}_getNewObserver(){const t={root:this._rootElement,threshold:this._config.threshold,rootMargin:this._config.rootMargin};return new IntersectionObserver((t=>this._observerCallback(t)),t)}_observerCallback(t){const e=t=>this._targetLinks.get(`#${t.target.id}`),i=t=>{this._previousScrollData.visibleEntryTop=t.target.offsetTop,this._process(e(t))},n=(this._rootElement||document.documentElement).scrollTop,s=n>=this._previousScrollData.parentScrollTop;this._previousScrollData.parentScrollTop=n;for(const o of t){if(!o.isIntersecting){this._activeTarget=null,this._clearActiveClass(e(o));continue}const t=o.target.offsetTop>=this._previousScrollData.visibleEntryTop;if(s&&t){if(i(o),!n)return}else s||t||i(o)}}_initializeTargetsAndObservables(){this._targetLinks=new Map,this._observableSections=new Map;const t=z.find(bs,this._config.target);for(const e of t){if(!e.hash||l(e))continue;const t=z.findOne(decodeURI(e.hash),this._element);a(t)&&(this._targetLinks.set(decodeURI(e.hash),e),this._observableSections.set(e.hash,t))}}_process(t){this._activeTarget!==t&&(this._clearActiveClass(this._config.target),this._activeTarget=t,t.classList.add(_s),this._activateParents(t),N.trigger(this._element,ps,{relatedTarget:t}))}_activateParents(t){if(t.classList.contains("dropdown-item"))z.findOne(".dropdown-toggle",t.closest(".dropdown")).classList.add(_s);else for(const e of z.parents(t,".nav, .list-group"))for(const t of z.prev(e,ys))t.classList.add(_s)}_clearActiveClass(t){t.classList.remove(_s);const e=z.find(`${bs}.${_s}`,t);for(const t of e)t.classList.remove(_s)}static jQueryInterface(t){return this.each((function(){const e=Es.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}N.on(window,gs,(()=>{for(const t of z.find('[data-bs-spy="scroll"]'))Es.getOrCreateInstance(t)})),m(Es);const Ts=".bs.tab",Cs=`hide${Ts}`,Os=`hidden${Ts}`,xs=`show${Ts}`,ks=`shown${Ts}`,Ls=`click${Ts}`,Ss=`keydown${Ts}`,Ds=`load${Ts}`,$s="ArrowLeft",Is="ArrowRight",Ns="ArrowUp",Ps="ArrowDown",Ms="Home",js="End",Fs="active",Hs="fade",Ws="show",Bs=":not(.dropdown-toggle)",zs='[data-bs-toggle="tab"], [data-bs-toggle="pill"], [data-bs-toggle="list"]',Rs=`.nav-link${Bs}, .list-group-item${Bs}, [role="tab"]${Bs}, ${zs}`,qs=`.${Fs}[data-bs-toggle="tab"], .${Fs}[data-bs-toggle="pill"], .${Fs}[data-bs-toggle="list"]`;class Vs extends W{constructor(t){super(t),this._parent=this._element.closest('.list-group, .nav, [role="tablist"]'),this._parent&&(this._setInitialAttributes(this._parent,this._getChildren()),N.on(this._element,Ss,(t=>this._keydown(t))))}static get NAME(){return"tab"}show(){const t=this._element;if(this._elemIsActive(t))return;const 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R(ro),m(ro),{Alert:Q,Button:Y,Carousel:xt,Collapse:Bt,Dropdown:qi,Modal:On,Offcanvas:qn,Popover:us,ScrollSpy:Es,Tab:Vs,Toast:ro,Tooltip:cs}})); //# sourceMappingURL=bootstrap.bundle.min.js.map \ No newline at end of file diff --git a/docs/site_libs/clipboard/clipboard.min.js b/docs/site_libs/clipboard/clipboard.min.js index 1103f81..9f97edb 100644 --- a/docs/site_libs/clipboard/clipboard.min.js +++ b/docs/site_libs/clipboard/clipboard.min.js @@ -1,7 +1,7 @@ -/*! - * clipboard.js v2.0.11 - * https://clipboardjs.com/ - * - * Licensed MIT © Zeno Rocha - */ +/*! + * clipboard.js v2.0.11 + * https://clipboardjs.com/ + * + * Licensed MIT © Zeno Rocha + */ !function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return b}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),r=n.n(e);function c(t){try{return document.execCommand(t)}catch(t){return}}var a=function(t){t=r()(t);return c("cut"),t};function o(t,e){var n,o,t=(n=t,o="rtl"===document.documentElement.getAttribute("dir"),(t=document.createElement("textarea")).style.fontSize="12pt",t.style.border="0",t.style.padding="0",t.style.margin="0",t.style.position="absolute",t.style[o?"right":"left"]="-9999px",o=window.pageYOffset||document.documentElement.scrollTop,t.style.top="".concat(o,"px"),t.setAttribute("readonly",""),t.value=n,t);return e.container.appendChild(t),e=r()(t),c("copy"),t.remove(),e}var f=function(t){var e=1.container-fluid.crosstalk-bscols{margin-left:auto;margin-right:auto}.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column{display:inline-block;padding-right:12px;vertical-align:top}@media only screen and (max-width: 480px){.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column{display:block;padding-right:inherit}}.crosstalk-input{margin-bottom:15px}.crosstalk-input .control-label{margin-bottom:0;vertical-align:middle}.crosstalk-input input[type="checkbox"]{margin:4px 0 0;margin-top:1px;line-height:normal}.crosstalk-input .checkbox{position:relative;display:block;margin-top:10px;margin-bottom:10px}.crosstalk-input .checkbox>label{padding-left:20px;margin-bottom:0;font-weight:400;cursor:pointer}.crosstalk-input .checkbox input[type="checkbox"],.crosstalk-input .checkbox-inline input[type="checkbox"]{position:absolute;margin-top:2px;margin-left:-20px}.crosstalk-input .checkbox+.checkbox{margin-top:-5px}.crosstalk-input .checkbox-inline{position:relative;display:inline-block;padding-left:20px;margin-bottom:0;font-weight:400;vertical-align:middle;cursor:pointer}.crosstalk-input .checkbox-inline+.checkbox-inline{margin-top:0;margin-left:10px} +.container-fluid.crosstalk-bscols{margin-left:-30px;margin-right:-30px;white-space:normal}body>.container-fluid.crosstalk-bscols{margin-left:auto;margin-right:auto}.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column{display:inline-block;padding-right:12px;vertical-align:top}@media only screen and (max-width: 480px){.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column{display:block;padding-right:inherit}}.crosstalk-input{margin-bottom:15px}.crosstalk-input .control-label{margin-bottom:0;vertical-align:middle}.crosstalk-input input[type="checkbox"]{margin:4px 0 0;margin-top:1px;line-height:normal}.crosstalk-input .checkbox{position:relative;display:block;margin-top:10px;margin-bottom:10px}.crosstalk-input .checkbox>label{padding-left:20px;margin-bottom:0;font-weight:400;cursor:pointer}.crosstalk-input .checkbox input[type="checkbox"],.crosstalk-input .checkbox-inline input[type="checkbox"]{position:absolute;margin-top:2px;margin-left:-20px}.crosstalk-input .checkbox+.checkbox{margin-top:-5px}.crosstalk-input .checkbox-inline{position:relative;display:inline-block;padding-left:20px;margin-bottom:0;font-weight:400;vertical-align:middle;cursor:pointer}.crosstalk-input .checkbox-inline+.checkbox-inline{margin-top:0;margin-left:10px} diff --git a/docs/site_libs/crosstalk-1.2.2/js/crosstalk.js b/docs/site_libs/crosstalk-1.2.2/js/crosstalk.js index fd9eb53..6bab151 100644 --- a/docs/site_libs/crosstalk-1.2.2/js/crosstalk.js +++ b/docs/site_libs/crosstalk-1.2.2/js/crosstalk.js @@ -1,1474 +1,1474 @@ -(function(){function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o b) { - return 1; - } -} - -/** - * @private - */ - -var FilterSet = function () { - function FilterSet() { - _classCallCheck(this, FilterSet); - - this.reset(); - } - - _createClass(FilterSet, [{ - key: "reset", - value: function reset() { - // Key: handle ID, Value: array of selected keys, or null - this._handles = {}; - // Key: key string, Value: count of handles that include it - this._keys = {}; - this._value = null; - this._activeHandles = 0; - } - }, { - key: "update", - value: function update(handleId, keys) { - if (keys !== null) { - keys = keys.slice(0); // clone before sorting - keys.sort(naturalComparator); - } - - var _diffSortedLists = (0, _util.diffSortedLists)(this._handles[handleId], keys), - added = _diffSortedLists.added, - removed = _diffSortedLists.removed; - - this._handles[handleId] = keys; - - for (var i = 0; i < added.length; i++) { - this._keys[added[i]] = (this._keys[added[i]] || 0) + 1; - } - for (var _i = 0; _i < removed.length; _i++) { - this._keys[removed[_i]]--; - } - - this._updateValue(keys); - } - - /** - * @param {string[]} keys Sorted array of strings that indicate - * a superset of possible keys. - * @private - */ - - }, { - key: "_updateValue", - value: function _updateValue() { - var keys = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : this._allKeys; - - var handleCount = Object.keys(this._handles).length; - if (handleCount === 0) { - this._value = null; - } else { - this._value = []; - for (var i = 0; i < keys.length; i++) { - var count = this._keys[keys[i]]; - if (count === handleCount) { - this._value.push(keys[i]); - } - } - } - } - }, { - key: "clear", - value: function clear(handleId) { - if (typeof this._handles[handleId] === "undefined") { - return; - } - - var keys = this._handles[handleId]; - if (!keys) { - keys = []; - } - - for (var i = 0; i < keys.length; i++) { - this._keys[keys[i]]--; - } - delete this._handles[handleId]; - - this._updateValue(); - } - }, { - key: "value", - get: function get() { - return this._value; - } - }, { - key: "_allKeys", - get: function get() { - var allKeys = Object.keys(this._keys); - allKeys.sort(naturalComparator); - return allKeys; - } - }]); - - return FilterSet; -}(); - -exports.default = FilterSet; - -},{"./util":11}],4:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; - -exports.default = group; - -var _var2 = require("./var"); - -var _var3 = _interopRequireDefault(_var2); - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -// Use a global so that multiple copies of crosstalk.js can be loaded and still -// have groups behave as singletons across all copies. -global.__crosstalk_groups = global.__crosstalk_groups || {}; -var groups = global.__crosstalk_groups; - -function group(groupName) { - if (groupName && typeof groupName === "string") { - if (!groups.hasOwnProperty(groupName)) { - groups[groupName] = new Group(groupName); - } - return groups[groupName]; - } else if ((typeof groupName === "undefined" ? "undefined" : _typeof(groupName)) === "object" && groupName._vars && groupName.var) { - // Appears to already be a group object - return groupName; - } else if (Array.isArray(groupName) && groupName.length == 1 && typeof groupName[0] === "string") { - return group(groupName[0]); - } else { - throw new Error("Invalid groupName argument"); - } -} - -var Group = function () { - function Group(name) { - _classCallCheck(this, Group); - - this.name = name; - this._vars = {}; - } - - _createClass(Group, [{ - key: "var", - value: function _var(name) { - if (!name || typeof name !== "string") { - throw new Error("Invalid var name"); - } - - if (!this._vars.hasOwnProperty(name)) this._vars[name] = new _var3.default(this, name); - return this._vars[name]; - } - }, { - key: "has", - value: function has(name) { - if (!name || typeof name !== "string") { - throw new Error("Invalid var name"); - } - - return this._vars.hasOwnProperty(name); - } - }]); - - return Group; -}(); - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./var":12}],5:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _group = require("./group"); - -var _group2 = _interopRequireDefault(_group); - -var _selection = require("./selection"); - -var _filter = require("./filter"); - -var _input = require("./input"); - -require("./input_selectize"); - -require("./input_checkboxgroup"); - -require("./input_slider"); - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -var defaultGroup = (0, _group2.default)("default"); - -function var_(name) { - return defaultGroup.var(name); -} - -function has(name) { - return defaultGroup.has(name); -} - -if (global.Shiny) { - global.Shiny.addCustomMessageHandler("update-client-value", function (message) { - if (typeof message.group === "string") { - (0, _group2.default)(message.group).var(message.name).set(message.value); - } else { - var_(message.name).set(message.value); - } - }); -} - -var crosstalk = { - group: _group2.default, - var: var_, - has: has, - SelectionHandle: _selection.SelectionHandle, - FilterHandle: _filter.FilterHandle, - bind: _input.bind -}; - -/** - * @namespace crosstalk - */ -exports.default = crosstalk; - -global.crosstalk = crosstalk; - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./group":4,"./input":6,"./input_checkboxgroup":7,"./input_selectize":8,"./input_slider":9,"./selection":10}],6:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); -exports.register = register; -exports.bind = bind; -var $ = global.jQuery; - -var bindings = {}; - -function register(reg) { - bindings[reg.className] = reg; - if (global.document && global.document.readyState !== "complete") { - $(function () { - bind(); - }); - } else if (global.document) { - setTimeout(bind, 100); - } -} - -function bind() { - Object.keys(bindings).forEach(function (className) { - var binding = bindings[className]; - $("." + binding.className).not(".crosstalk-input-bound").each(function (i, el) { - bindInstance(binding, el); - }); - }); -} - -// Escape jQuery identifier -function $escape(val) { - return val.replace(/([!"#$%&'()*+,./:;<=>?@[\\\]^`{|}~])/g, "\\$1"); -} - -function bindEl(el) { - var $el = $(el); - Object.keys(bindings).forEach(function (className) { - if ($el.hasClass(className) && !$el.hasClass("crosstalk-input-bound")) { - var binding = bindings[className]; - bindInstance(binding, el); - } - }); -} - -function bindInstance(binding, el) { - var jsonEl = $(el).find("script[type='application/json'][data-for='" + $escape(el.id) + "']"); - var data = JSON.parse(jsonEl[0].innerText); - - var instance = binding.factory(el, data); - $(el).data("crosstalk-instance", instance); - $(el).addClass("crosstalk-input-bound"); -} - -if (global.Shiny) { - var inputBinding = new global.Shiny.InputBinding(); - var _$ = global.jQuery; - _$.extend(inputBinding, { - find: function find(scope) { - return _$(scope).find(".crosstalk-input"); - }, - initialize: function initialize(el) { - if (!_$(el).hasClass("crosstalk-input-bound")) { - bindEl(el); - } - }, - getId: function getId(el) { - return el.id; - }, - getValue: function getValue(el) {}, - setValue: function setValue(el, value) {}, - receiveMessage: function receiveMessage(el, data) {}, - subscribe: function subscribe(el, callback) { - _$(el).data("crosstalk-instance").resume(); - }, - unsubscribe: function unsubscribe(el) { - _$(el).data("crosstalk-instance").suspend(); - } - }); - global.Shiny.inputBindings.register(inputBinding, "crosstalk.inputBinding"); -} - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{}],7:[function(require,module,exports){ -(function (global){ -"use strict"; - -var _input = require("./input"); - -var input = _interopRequireWildcard(_input); - -var _filter = require("./filter"); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -var $ = global.jQuery; - -input.register({ - className: "crosstalk-input-checkboxgroup", - - factory: function factory(el, data) { - /* - * map: {"groupA": ["keyA", "keyB", ...], ...} - * group: "ct-groupname" - */ - var ctHandle = new _filter.FilterHandle(data.group); - - var lastKnownKeys = void 0; - var $el = $(el); - $el.on("change", "input[type='checkbox']", function () { - var checked = $el.find("input[type='checkbox']:checked"); - if (checked.length === 0) { - lastKnownKeys = null; - ctHandle.clear(); - } else { - var keys = {}; - checked.each(function () { - data.map[this.value].forEach(function (key) { - keys[key] = true; - }); - }); - var keyArray = Object.keys(keys); - keyArray.sort(); - lastKnownKeys = keyArray; - ctHandle.set(keyArray); - } - }); - - return { - suspend: function suspend() { - ctHandle.clear(); - }, - resume: function resume() { - if (lastKnownKeys) ctHandle.set(lastKnownKeys); - } - }; - } -}); - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./input":6}],8:[function(require,module,exports){ -(function (global){ -"use strict"; - -var _input = require("./input"); - -var input = _interopRequireWildcard(_input); - -var _util = require("./util"); - -var util = _interopRequireWildcard(_util); - -var _filter = require("./filter"); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -var $ = global.jQuery; - -input.register({ - className: "crosstalk-input-select", - - factory: function factory(el, data) { - /* - * items: {value: [...], label: [...]} - * map: {"groupA": ["keyA", "keyB", ...], ...} - * group: "ct-groupname" - */ - - var first = [{ value: "", label: "(All)" }]; - var items = util.dataframeToD3(data.items); - var opts = { - options: first.concat(items), - valueField: "value", - labelField: "label", - searchField: "label" - }; - - var select = $(el).find("select")[0]; - - var selectize = $(select).selectize(opts)[0].selectize; - - var ctHandle = new _filter.FilterHandle(data.group); - - var lastKnownKeys = void 0; - selectize.on("change", function () { - if (selectize.items.length === 0) { - lastKnownKeys = null; - ctHandle.clear(); - } else { - var keys = {}; - selectize.items.forEach(function (group) { - data.map[group].forEach(function (key) { - keys[key] = true; - }); - }); - var keyArray = Object.keys(keys); - keyArray.sort(); - lastKnownKeys = keyArray; - ctHandle.set(keyArray); - } - }); - - return { - suspend: function suspend() { - ctHandle.clear(); - }, - resume: function resume() { - if (lastKnownKeys) ctHandle.set(lastKnownKeys); - } - }; - } -}); - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./input":6,"./util":11}],9:[function(require,module,exports){ -(function (global){ -"use strict"; - -var _slicedToArray = function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i["return"]) _i["return"](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError("Invalid attempt to destructure non-iterable instance"); } }; }(); - -var _input = require("./input"); - -var input = _interopRequireWildcard(_input); - -var _filter = require("./filter"); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -var $ = global.jQuery; -var strftime = global.strftime; - -input.register({ - className: "crosstalk-input-slider", - - factory: function factory(el, data) { - /* - * map: {"groupA": ["keyA", "keyB", ...], ...} - * group: "ct-groupname" - */ - var ctHandle = new _filter.FilterHandle(data.group); - - var opts = {}; - var $el = $(el).find("input"); - var dataType = $el.data("data-type"); - var timeFormat = $el.data("time-format"); - var round = $el.data("round"); - var timeFormatter = void 0; - - // Set up formatting functions - if (dataType === "date") { - timeFormatter = strftime.utc(); - opts.prettify = function (num) { - return timeFormatter(timeFormat, new Date(num)); - }; - } else if (dataType === "datetime") { - var timezone = $el.data("timezone"); - if (timezone) timeFormatter = strftime.timezone(timezone);else timeFormatter = strftime; - - opts.prettify = function (num) { - return timeFormatter(timeFormat, new Date(num)); - }; - } else if (dataType === "number") { - if (typeof round !== "undefined") opts.prettify = function (num) { - var factor = Math.pow(10, round); - return Math.round(num * factor) / factor; - }; - } - - $el.ionRangeSlider(opts); - - function getValue() { - var result = $el.data("ionRangeSlider").result; - - // Function for converting numeric value from slider to appropriate type. - var convert = void 0; - var dataType = $el.data("data-type"); - if (dataType === "date") { - convert = function convert(val) { - return formatDateUTC(new Date(+val)); - }; - } else if (dataType === "datetime") { - convert = function convert(val) { - // Convert ms to s - return +val / 1000; - }; - } else { - convert = function convert(val) { - return +val; - }; - } - - if ($el.data("ionRangeSlider").options.type === "double") { - return [convert(result.from), convert(result.to)]; - } else { - return convert(result.from); - } - } - - var lastKnownKeys = null; - - $el.on("change.crosstalkSliderInput", function (event) { - if (!$el.data("updating") && !$el.data("animating")) { - var _getValue = getValue(), - _getValue2 = _slicedToArray(_getValue, 2), - from = _getValue2[0], - to = _getValue2[1]; - - var keys = []; - for (var i = 0; i < data.values.length; i++) { - var val = data.values[i]; - if (val >= from && val <= to) { - keys.push(data.keys[i]); - } - } - keys.sort(); - ctHandle.set(keys); - lastKnownKeys = keys; - } - }); - - // let $el = $(el); - // $el.on("change", "input[type="checkbox"]", function() { - // let checked = $el.find("input[type="checkbox"]:checked"); - // if (checked.length === 0) { - // ctHandle.clear(); - // } else { - // let keys = {}; - // checked.each(function() { - // data.map[this.value].forEach(function(key) { - // keys[key] = true; - // }); - // }); - // let keyArray = Object.keys(keys); - // keyArray.sort(); - // ctHandle.set(keyArray); - // } - // }); - - return { - suspend: function suspend() { - ctHandle.clear(); - }, - resume: function resume() { - if (lastKnownKeys) ctHandle.set(lastKnownKeys); - } - }; - } -}); - -// Convert a number to a string with leading zeros -function padZeros(n, digits) { - var str = n.toString(); - while (str.length < digits) { - str = "0" + str; - }return str; -} - -// Given a Date object, return a string in yyyy-mm-dd format, using the -// UTC date. This may be a day off from the date in the local time zone. -function formatDateUTC(date) { - if (date instanceof Date) { - return date.getUTCFullYear() + "-" + padZeros(date.getUTCMonth() + 1, 2) + "-" + padZeros(date.getUTCDate(), 2); - } else { - return null; - } -} - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./input":6}],10:[function(require,module,exports){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); -exports.SelectionHandle = undefined; - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _events = require("./events"); - -var _events2 = _interopRequireDefault(_events); - -var _group = require("./group"); - -var _group2 = _interopRequireDefault(_group); - -var _util = require("./util"); - -var util = _interopRequireWildcard(_util); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -/** - * Use this class to read and write (and listen for changes to) the selection - * for a Crosstalk group. This is intended to be used for linked brushing. - * - * If two (or more) `SelectionHandle` instances in the same webpage share the - * same group name, they will share the same state. Setting the selection using - * one `SelectionHandle` instance will result in the `value` property instantly - * changing across the others, and `"change"` event listeners on all instances - * (including the one that initiated the sending) will fire. - * - * @param {string} [group] - The name of the Crosstalk group, or if none, - * null or undefined (or any other falsy value). This can be changed later - * via the [SelectionHandle#setGroup](#setGroup) method. - * @param {Object} [extraInfo] - An object whose properties will be copied to - * the event object whenever an event is emitted. - */ -var SelectionHandle = exports.SelectionHandle = function () { - function SelectionHandle() { - var group = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : null; - var extraInfo = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : null; - - _classCallCheck(this, SelectionHandle); - - this._eventRelay = new _events2.default(); - this._emitter = new util.SubscriptionTracker(this._eventRelay); - - // Name of the group we're currently tracking, if any. Can change over time. - this._group = null; - // The Var we're currently tracking, if any. Can change over time. - this._var = null; - // The event handler subscription we currently have on var.on("change"). - this._varOnChangeSub = null; - - this._extraInfo = util.extend({ sender: this }, extraInfo); - - this.setGroup(group); - } - - /** - * Changes the Crosstalk group membership of this SelectionHandle. The group - * being switched away from (if any) will not have its selection value - * modified as a result of calling `setGroup`, even if this handle was the - * most recent handle to set the selection of the group. - * - * The group being switched to (if any) will also not have its selection value - * modified as a result of calling `setGroup`. If you want to set the - * selection value of the new group, call `set` explicitly. - * - * @param {string} group - The name of the Crosstalk group, or null (or - * undefined) to clear the group. - */ - - - _createClass(SelectionHandle, [{ - key: "setGroup", - value: function setGroup(group) { - var _this = this; - - // If group is unchanged, do nothing - if (this._group === group) return; - // Treat null, undefined, and other falsy values the same - if (!this._group && !group) return; - - if (this._var) { - this._var.off("change", this._varOnChangeSub); - this._var = null; - this._varOnChangeSub = null; - } - - this._group = group; - - if (group) { - this._var = (0, _group2.default)(group).var("selection"); - var sub = this._var.on("change", function (e) { - _this._eventRelay.trigger("change", e, _this); - }); - this._varOnChangeSub = sub; - } - } - - /** - * Retrieves the current selection for the group represented by this - * `SelectionHandle`. - * - * - If no selection is active, then this value will be falsy. - * - If a selection is active, but no data points are selected, then this - * value will be an empty array. - * - If a selection is active, and data points are selected, then the keys - * of the selected data points will be present in the array. - */ - - }, { - key: "_mergeExtraInfo", - - - /** - * Combines the given `extraInfo` (if any) with the handle's default - * `_extraInfo` (if any). - * @private - */ - value: function _mergeExtraInfo(extraInfo) { - // Important incidental effect: shallow clone is returned - return util.extend({}, this._extraInfo ? this._extraInfo : null, extraInfo ? extraInfo : null); - } - - /** - * Overwrites the current selection for the group, and raises the `"change"` - * event among all of the group's '`SelectionHandle` instances (including - * this one). - * - * @fires SelectionHandle#change - * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see - * {@link SelectionHandle#value}). - * @param {Object} [extraInfo] - Extra properties to be included on the event - * object that's passed to listeners (in addition to any options that were - * passed into the `SelectionHandle` constructor). - */ - - }, { - key: "set", - value: function set(selectedKeys, extraInfo) { - if (this._var) this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo)); - } - - /** - * Overwrites the current selection for the group, and raises the `"change"` - * event among all of the group's '`SelectionHandle` instances (including - * this one). - * - * @fires SelectionHandle#change - * @param {Object} [extraInfo] - Extra properties to be included on the event - * object that's passed to listeners (in addition to any that were passed - * into the `SelectionHandle` constructor). - */ - - }, { - key: "clear", - value: function clear(extraInfo) { - if (this._var) this.set(void 0, this._mergeExtraInfo(extraInfo)); - } - - /** - * Subscribes to events on this `SelectionHandle`. - * - * @param {string} eventType - Indicates the type of events to listen to. - * Currently, only `"change"` is supported. - * @param {SelectionHandle~listener} listener - The callback function that - * will be invoked when the event occurs. - * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel - * this subscription. - */ - - }, { - key: "on", - value: function on(eventType, listener) { - return this._emitter.on(eventType, listener); - } - - /** - * Cancels event subscriptions created by {@link SelectionHandle#on}. - * - * @param {string} eventType - The type of event to unsubscribe. - * @param {string|SelectionHandle~listener} listener - Either the callback - * function previously passed into {@link SelectionHandle#on}, or the - * string that was returned from {@link SelectionHandle#on}. - */ - - }, { - key: "off", - value: function off(eventType, listener) { - return this._emitter.off(eventType, listener); - } - - /** - * Shuts down the `SelectionHandle` object. - * - * Removes all event listeners that were added through this handle. - */ - - }, { - key: "close", - value: function close() { - this._emitter.removeAllListeners(); - this.setGroup(null); - } - }, { - key: "value", - get: function get() { - return this._var ? this._var.get() : null; - } - }]); - - return SelectionHandle; -}(); - -/** - * @callback SelectionHandle~listener - * @param {Object} event - An object containing details of the event. For - * `"change"` events, this includes the properties `value` (the new - * value of the selection, or `undefined` if no selection is active), - * `oldValue` (the previous value of the selection), and `sender` (the - * `SelectionHandle` instance that made the change). - */ - -/** - * @event SelectionHandle#change - * @type {object} - * @property {object} value - The new value of the selection, or `undefined` - * if no selection is active. - * @property {object} oldValue - The previous value of the selection. - * @property {SelectionHandle} sender - The `SelectionHandle` instance that - * changed the value. - */ - -},{"./events":1,"./group":4,"./util":11}],11:[function(require,module,exports){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; - -exports.extend = extend; -exports.checkSorted = checkSorted; -exports.diffSortedLists = diffSortedLists; -exports.dataframeToD3 = dataframeToD3; - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -function extend(target) { - for (var _len = arguments.length, sources = Array(_len > 1 ? _len - 1 : 0), _key = 1; _key < _len; _key++) { - sources[_key - 1] = arguments[_key]; - } - - for (var i = 0; i < sources.length; i++) { - var src = sources[i]; - if (typeof src === "undefined" || src === null) continue; - - for (var key in src) { - if (src.hasOwnProperty(key)) { - target[key] = src[key]; - } - } - } - return target; -} - -function checkSorted(list) { - for (var i = 1; i < list.length; i++) { - if (list[i] <= list[i - 1]) { - throw new Error("List is not sorted or contains duplicate"); - } - } -} - -function diffSortedLists(a, b) { - var i_a = 0; - var i_b = 0; - - if (!a) a = []; - if (!b) b = []; - - var a_only = []; - var b_only = []; - - checkSorted(a); - checkSorted(b); - - while (i_a < a.length && i_b < b.length) { - if (a[i_a] === b[i_b]) { - i_a++; - i_b++; - } else if (a[i_a] < b[i_b]) { - a_only.push(a[i_a++]); - } else { - b_only.push(b[i_b++]); - } - } - - if (i_a < a.length) a_only = a_only.concat(a.slice(i_a)); - if (i_b < b.length) b_only = b_only.concat(b.slice(i_b)); - return { - removed: a_only, - added: b_only - }; -} - -// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... } -// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ] -function dataframeToD3(df) { - var names = []; - var length = void 0; - for (var name in df) { - if (df.hasOwnProperty(name)) names.push(name); - if (_typeof(df[name]) !== "object" || typeof df[name].length === "undefined") { - throw new Error("All fields must be arrays"); - } else if (typeof length !== "undefined" && length !== df[name].length) { - throw new Error("All fields must be arrays of the same length"); - } - length = df[name].length; - } - var results = []; - var item = void 0; - for (var row = 0; row < length; row++) { - item = {}; - for (var col = 0; col < names.length; col++) { - item[names[col]] = df[names[col]][row]; - } - results.push(item); - } - return results; -} - -/** - * Keeps track of all event listener additions/removals and lets all active - * listeners be removed with a single operation. - * - * @private - */ - -var SubscriptionTracker = exports.SubscriptionTracker = function () { - function SubscriptionTracker(emitter) { - _classCallCheck(this, SubscriptionTracker); - - this._emitter = emitter; - this._subs = {}; - } - - _createClass(SubscriptionTracker, [{ - key: "on", - value: function on(eventType, listener) { - var sub = this._emitter.on(eventType, listener); - this._subs[sub] = eventType; - return sub; - } - }, { - key: "off", - value: function off(eventType, listener) { - var sub = this._emitter.off(eventType, listener); - if (sub) { - delete this._subs[sub]; - } - return sub; - } - }, { - key: "removeAllListeners", - value: function removeAllListeners() { - var _this = this; - - var current_subs = this._subs; - this._subs = {}; - Object.keys(current_subs).forEach(function (sub) { - _this._emitter.off(current_subs[sub], sub); - }); - } - }]); - - return SubscriptionTracker; -}(); - -},{}],12:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _events = require("./events"); - -var _events2 = _interopRequireDefault(_events); - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -var Var = function () { - function Var(group, name, /*optional*/value) { - _classCallCheck(this, Var); - - this._group = group; - this._name = name; - this._value = value; - this._events = new _events2.default(); - } - - _createClass(Var, [{ - key: "get", - value: function get() { - return this._value; - } - }, { - key: "set", - value: function set(value, /*optional*/event) { - if (this._value === value) { - // Do nothing; the value hasn't changed - return; - } - var oldValue = this._value; - this._value = value; - // Alert JavaScript listeners that the value has changed - var evt = {}; - if (event && (typeof event === "undefined" ? "undefined" : _typeof(event)) === "object") { - for (var k in event) { - if (event.hasOwnProperty(k)) evt[k] = event[k]; - } - } - evt.oldValue = oldValue; - evt.value = value; - this._events.trigger("change", evt, this); - - // TODO: Make this extensible, to let arbitrary back-ends know that - // something has changed - if (global.Shiny && global.Shiny.onInputChange) { - global.Shiny.onInputChange(".clientValue-" + (this._group.name !== null ? this._group.name + "-" : "") + this._name, typeof value === "undefined" ? null : value); - } - } - }, { - key: "on", - value: function on(eventType, listener) { - return this._events.on(eventType, listener); - } - }, { - key: "off", - value: function off(eventType, listener) { - return this._events.off(eventType, listener); - } - }]); - - return Var; -}(); - -exports.default = Var; - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./events":1}]},{},[5]) -//# sourceMappingURL=crosstalk.js.map +(function(){function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o b) { + return 1; + } +} + +/** + * @private + */ + +var FilterSet = function () { + function FilterSet() { + _classCallCheck(this, FilterSet); + + this.reset(); + } + + _createClass(FilterSet, [{ + key: "reset", + value: function reset() { + // Key: handle ID, Value: array of selected keys, or null + this._handles = {}; + // Key: key string, Value: count of handles that include it + this._keys = {}; + this._value = null; + this._activeHandles = 0; + } + }, { + key: "update", + value: function update(handleId, keys) { + if (keys !== null) { + keys = keys.slice(0); // clone before sorting + keys.sort(naturalComparator); + } + + var _diffSortedLists = (0, _util.diffSortedLists)(this._handles[handleId], keys), + added = _diffSortedLists.added, + removed = _diffSortedLists.removed; + + this._handles[handleId] = keys; + + for (var i = 0; i < added.length; i++) { + this._keys[added[i]] = (this._keys[added[i]] || 0) + 1; + } + for (var _i = 0; _i < removed.length; _i++) { + this._keys[removed[_i]]--; + } + + this._updateValue(keys); + } + + /** + * @param {string[]} keys Sorted array of strings that indicate + * a superset of possible keys. + * @private + */ + + }, { + key: "_updateValue", + value: function _updateValue() { + var keys = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : this._allKeys; + + var handleCount = Object.keys(this._handles).length; + if (handleCount === 0) { + this._value = null; + } else { + this._value = []; + for (var i = 0; i < keys.length; i++) { + var count = this._keys[keys[i]]; + if (count === handleCount) { + this._value.push(keys[i]); + } + } + } + } + }, { + key: "clear", + value: function clear(handleId) { + if (typeof this._handles[handleId] === "undefined") { + return; + } + + var keys = this._handles[handleId]; + if (!keys) { + keys = []; + } + + for (var i = 0; i < keys.length; i++) { + this._keys[keys[i]]--; + } + delete this._handles[handleId]; + + this._updateValue(); + } + }, { + key: "value", + get: function get() { + return this._value; + } + }, { + key: "_allKeys", + get: function get() { + var allKeys = Object.keys(this._keys); + allKeys.sort(naturalComparator); + return allKeys; + } + }]); + + return FilterSet; +}(); + +exports.default = FilterSet; + +},{"./util":11}],4:[function(require,module,exports){ +(function (global){ +"use strict"; + +Object.defineProperty(exports, "__esModule", { + value: true +}); + +var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); + +var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; + +exports.default = group; + +var _var2 = require("./var"); + +var _var3 = _interopRequireDefault(_var2); + +function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } + +function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } + +// Use a global so that multiple copies of crosstalk.js can be loaded and still +// have groups behave as singletons across all copies. +global.__crosstalk_groups = global.__crosstalk_groups || {}; +var groups = global.__crosstalk_groups; + +function group(groupName) { + if (groupName && typeof groupName === "string") { + if (!groups.hasOwnProperty(groupName)) { + groups[groupName] = new Group(groupName); + } + return groups[groupName]; + } else if ((typeof groupName === "undefined" ? "undefined" : _typeof(groupName)) === "object" && groupName._vars && groupName.var) { + // Appears to already be a group object + return groupName; + } else if (Array.isArray(groupName) && groupName.length == 1 && typeof groupName[0] === "string") { + return group(groupName[0]); + } else { + throw new Error("Invalid groupName argument"); + } +} + +var Group = function () { + function Group(name) { + _classCallCheck(this, Group); + + this.name = name; + this._vars = {}; + } + + _createClass(Group, [{ + key: "var", + value: function _var(name) { + if (!name || typeof name !== "string") { + throw new Error("Invalid var name"); + } + + if (!this._vars.hasOwnProperty(name)) this._vars[name] = new _var3.default(this, name); + return this._vars[name]; + } + }, { + key: "has", + value: function has(name) { + if (!name || typeof name !== "string") { + throw new Error("Invalid var name"); + } + + return this._vars.hasOwnProperty(name); + } + }]); + + return Group; +}(); + +}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) + +},{"./var":12}],5:[function(require,module,exports){ +(function (global){ +"use strict"; + +Object.defineProperty(exports, "__esModule", { + value: true +}); + +var _group = require("./group"); + +var _group2 = _interopRequireDefault(_group); + +var _selection = require("./selection"); + +var _filter = require("./filter"); + +var _input = require("./input"); + +require("./input_selectize"); + +require("./input_checkboxgroup"); + +require("./input_slider"); + +function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } + +var defaultGroup = (0, _group2.default)("default"); + +function var_(name) { + return defaultGroup.var(name); +} + +function has(name) { + return defaultGroup.has(name); +} + +if (global.Shiny) { + global.Shiny.addCustomMessageHandler("update-client-value", function (message) { + if (typeof message.group === "string") { + (0, _group2.default)(message.group).var(message.name).set(message.value); + } else { + var_(message.name).set(message.value); + } + }); +} + +var crosstalk = { + group: _group2.default, + var: var_, + has: has, + SelectionHandle: _selection.SelectionHandle, + FilterHandle: _filter.FilterHandle, + bind: _input.bind +}; + +/** + * @namespace crosstalk + */ +exports.default = crosstalk; + +global.crosstalk = crosstalk; + +}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) + +},{"./filter":2,"./group":4,"./input":6,"./input_checkboxgroup":7,"./input_selectize":8,"./input_slider":9,"./selection":10}],6:[function(require,module,exports){ +(function (global){ +"use strict"; + +Object.defineProperty(exports, "__esModule", { + value: true +}); +exports.register = register; +exports.bind = bind; +var $ = global.jQuery; + +var bindings = {}; + +function register(reg) { + bindings[reg.className] = reg; + if (global.document && global.document.readyState !== "complete") { + $(function () { + bind(); + }); + } else if (global.document) { + setTimeout(bind, 100); + } +} + +function bind() { + Object.keys(bindings).forEach(function (className) { + var binding = bindings[className]; + $("." + binding.className).not(".crosstalk-input-bound").each(function (i, el) { + bindInstance(binding, el); + }); + }); +} + +// Escape jQuery identifier +function $escape(val) { + return val.replace(/([!"#$%&'()*+,./:;<=>?@[\\\]^`{|}~])/g, "\\$1"); +} + +function bindEl(el) { + var $el = $(el); + Object.keys(bindings).forEach(function (className) { + if ($el.hasClass(className) && !$el.hasClass("crosstalk-input-bound")) { + var binding = bindings[className]; + bindInstance(binding, el); + } + }); +} + +function bindInstance(binding, el) { + var jsonEl = $(el).find("script[type='application/json'][data-for='" + $escape(el.id) + "']"); + var data = JSON.parse(jsonEl[0].innerText); + + var instance = binding.factory(el, data); + $(el).data("crosstalk-instance", instance); + $(el).addClass("crosstalk-input-bound"); +} + +if (global.Shiny) { + var inputBinding = new global.Shiny.InputBinding(); + var _$ = global.jQuery; + _$.extend(inputBinding, { + find: function find(scope) { + return _$(scope).find(".crosstalk-input"); + }, + initialize: function initialize(el) { + if (!_$(el).hasClass("crosstalk-input-bound")) { + bindEl(el); + } + }, + getId: function getId(el) { + return el.id; + }, + getValue: function getValue(el) {}, + setValue: function setValue(el, value) {}, + receiveMessage: function receiveMessage(el, data) {}, + subscribe: function subscribe(el, callback) { + _$(el).data("crosstalk-instance").resume(); + }, + unsubscribe: function unsubscribe(el) { + _$(el).data("crosstalk-instance").suspend(); + } + }); + global.Shiny.inputBindings.register(inputBinding, "crosstalk.inputBinding"); +} + +}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) + +},{}],7:[function(require,module,exports){ +(function (global){ +"use strict"; + +var _input = require("./input"); + +var input = _interopRequireWildcard(_input); + +var _filter = require("./filter"); + +function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } + +var $ = global.jQuery; + +input.register({ + className: "crosstalk-input-checkboxgroup", + + factory: function factory(el, data) { + /* + * map: {"groupA": ["keyA", "keyB", ...], ...} + * group: "ct-groupname" + */ + var ctHandle = new _filter.FilterHandle(data.group); + + var lastKnownKeys = void 0; + var $el = $(el); + $el.on("change", "input[type='checkbox']", function () { + var checked = $el.find("input[type='checkbox']:checked"); + if (checked.length === 0) { + lastKnownKeys = null; + ctHandle.clear(); + } else { + var keys = {}; + checked.each(function () { + data.map[this.value].forEach(function (key) { + keys[key] = true; + }); + }); + var keyArray = Object.keys(keys); + keyArray.sort(); + lastKnownKeys = keyArray; + ctHandle.set(keyArray); + } + }); + + return { + suspend: function suspend() { + ctHandle.clear(); + }, + resume: function resume() { + if (lastKnownKeys) ctHandle.set(lastKnownKeys); + } + }; + } +}); + +}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) + +},{"./filter":2,"./input":6}],8:[function(require,module,exports){ +(function (global){ +"use strict"; + +var _input = require("./input"); + +var input = _interopRequireWildcard(_input); + +var _util = require("./util"); + +var util = _interopRequireWildcard(_util); + +var _filter = require("./filter"); + +function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } + +var $ = global.jQuery; + +input.register({ + className: "crosstalk-input-select", + + factory: function factory(el, data) { + /* + * items: {value: [...], label: [...]} + * map: {"groupA": ["keyA", "keyB", ...], ...} + * group: "ct-groupname" + */ + + var first = [{ value: "", label: "(All)" }]; + var items = util.dataframeToD3(data.items); + var opts = { + options: first.concat(items), + valueField: "value", + labelField: "label", + searchField: "label" + }; + + var select = $(el).find("select")[0]; + + var selectize = $(select).selectize(opts)[0].selectize; + + var ctHandle = new _filter.FilterHandle(data.group); + + var lastKnownKeys = void 0; + selectize.on("change", function () { + if (selectize.items.length === 0) { + lastKnownKeys = null; + ctHandle.clear(); + } else { + var keys = {}; + selectize.items.forEach(function (group) { + data.map[group].forEach(function (key) { + keys[key] = true; + }); + }); + var keyArray = Object.keys(keys); + keyArray.sort(); + lastKnownKeys = keyArray; + ctHandle.set(keyArray); + } + }); + + return { + suspend: function suspend() { + ctHandle.clear(); + }, + resume: function resume() { + if (lastKnownKeys) ctHandle.set(lastKnownKeys); + } + }; + } +}); + +}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) + +},{"./filter":2,"./input":6,"./util":11}],9:[function(require,module,exports){ +(function (global){ +"use strict"; + +var _slicedToArray = function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i["return"]) _i["return"](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError("Invalid attempt to destructure non-iterable instance"); } }; }(); + +var _input = require("./input"); + +var input = _interopRequireWildcard(_input); + +var _filter = require("./filter"); + +function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } + +var $ = global.jQuery; +var strftime = global.strftime; + +input.register({ + className: "crosstalk-input-slider", + + factory: function factory(el, data) { + /* + * map: {"groupA": ["keyA", "keyB", ...], ...} + * group: "ct-groupname" + */ + var ctHandle = new _filter.FilterHandle(data.group); + + var opts = {}; + var $el = $(el).find("input"); + var dataType = $el.data("data-type"); + var timeFormat = $el.data("time-format"); + var round = $el.data("round"); + var timeFormatter = void 0; + + // Set up formatting functions + if (dataType === "date") { + timeFormatter = strftime.utc(); + opts.prettify = function (num) { + return timeFormatter(timeFormat, new Date(num)); + }; + } else if (dataType === "datetime") { + var timezone = $el.data("timezone"); + if (timezone) timeFormatter = strftime.timezone(timezone);else timeFormatter = strftime; + + opts.prettify = function (num) { + return timeFormatter(timeFormat, new Date(num)); + }; + } else if (dataType === "number") { + if (typeof round !== "undefined") opts.prettify = function (num) { + var factor = Math.pow(10, round); + return Math.round(num * factor) / factor; + }; + } + + $el.ionRangeSlider(opts); + + function getValue() { + var result = $el.data("ionRangeSlider").result; + + // Function for converting numeric value from slider to appropriate type. + var convert = void 0; + var dataType = $el.data("data-type"); + if (dataType === "date") { + convert = function convert(val) { + return formatDateUTC(new Date(+val)); + }; + } else if (dataType === "datetime") { + convert = function convert(val) { + // Convert ms to s + return +val / 1000; + }; + } else { + convert = function convert(val) { + return +val; + }; + } + + if ($el.data("ionRangeSlider").options.type === "double") { + return [convert(result.from), convert(result.to)]; + } else { + return convert(result.from); + } + } + + var lastKnownKeys = null; + + $el.on("change.crosstalkSliderInput", function (event) { + if (!$el.data("updating") && !$el.data("animating")) { + var _getValue = getValue(), + _getValue2 = _slicedToArray(_getValue, 2), + from = _getValue2[0], + to = _getValue2[1]; + + var keys = []; + for (var i = 0; i < data.values.length; i++) { + var val = data.values[i]; + if (val >= from && val <= to) { + keys.push(data.keys[i]); + } + } + keys.sort(); + ctHandle.set(keys); + lastKnownKeys = keys; + } + }); + + // let $el = $(el); + // $el.on("change", "input[type="checkbox"]", function() { + // let checked = $el.find("input[type="checkbox"]:checked"); + // if (checked.length === 0) { + // ctHandle.clear(); + // } else { + // let keys = {}; + // checked.each(function() { + // data.map[this.value].forEach(function(key) { + // keys[key] = true; + // }); + // }); + // let keyArray = Object.keys(keys); + // keyArray.sort(); + // ctHandle.set(keyArray); + // } + // }); + + return { + suspend: function suspend() { + ctHandle.clear(); + }, + resume: function resume() { + if (lastKnownKeys) ctHandle.set(lastKnownKeys); + } + }; + } +}); + +// Convert a number to a string with leading zeros +function padZeros(n, digits) { + var str = n.toString(); + while (str.length < digits) { + str = "0" + str; + }return str; +} + +// Given a Date object, return a string in yyyy-mm-dd format, using the +// UTC date. This may be a day off from the date in the local time zone. +function formatDateUTC(date) { + if (date instanceof Date) { + return date.getUTCFullYear() + "-" + padZeros(date.getUTCMonth() + 1, 2) + "-" + padZeros(date.getUTCDate(), 2); + } else { + return null; + } +} + +}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) + +},{"./filter":2,"./input":6}],10:[function(require,module,exports){ +"use strict"; + +Object.defineProperty(exports, "__esModule", { + value: true +}); +exports.SelectionHandle = undefined; + +var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); + +var _events = require("./events"); + +var _events2 = _interopRequireDefault(_events); + +var _group = require("./group"); + +var _group2 = _interopRequireDefault(_group); + +var _util = require("./util"); + +var util = _interopRequireWildcard(_util); + +function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } + +function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } + +function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } + +/** + * Use this class to read and write (and listen for changes to) the selection + * for a Crosstalk group. This is intended to be used for linked brushing. + * + * If two (or more) `SelectionHandle` instances in the same webpage share the + * same group name, they will share the same state. Setting the selection using + * one `SelectionHandle` instance will result in the `value` property instantly + * changing across the others, and `"change"` event listeners on all instances + * (including the one that initiated the sending) will fire. + * + * @param {string} [group] - The name of the Crosstalk group, or if none, + * null or undefined (or any other falsy value). This can be changed later + * via the [SelectionHandle#setGroup](#setGroup) method. + * @param {Object} [extraInfo] - An object whose properties will be copied to + * the event object whenever an event is emitted. + */ +var SelectionHandle = exports.SelectionHandle = function () { + function SelectionHandle() { + var group = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : null; + var extraInfo = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : null; + + _classCallCheck(this, SelectionHandle); + + this._eventRelay = new _events2.default(); + this._emitter = new util.SubscriptionTracker(this._eventRelay); + + // Name of the group we're currently tracking, if any. Can change over time. + this._group = null; + // The Var we're currently tracking, if any. Can change over time. + this._var = null; + // The event handler subscription we currently have on var.on("change"). + this._varOnChangeSub = null; + + this._extraInfo = util.extend({ sender: this }, extraInfo); + + this.setGroup(group); + } + + /** + * Changes the Crosstalk group membership of this SelectionHandle. The group + * being switched away from (if any) will not have its selection value + * modified as a result of calling `setGroup`, even if this handle was the + * most recent handle to set the selection of the group. + * + * The group being switched to (if any) will also not have its selection value + * modified as a result of calling `setGroup`. If you want to set the + * selection value of the new group, call `set` explicitly. + * + * @param {string} group - The name of the Crosstalk group, or null (or + * undefined) to clear the group. + */ + + + _createClass(SelectionHandle, [{ + key: "setGroup", + value: function setGroup(group) { + var _this = this; + + // If group is unchanged, do nothing + if (this._group === group) return; + // Treat null, undefined, and other falsy values the same + if (!this._group && !group) return; + + if (this._var) { + this._var.off("change", this._varOnChangeSub); + this._var = null; + this._varOnChangeSub = null; + } + + this._group = group; + + if (group) { + this._var = (0, _group2.default)(group).var("selection"); + var sub = this._var.on("change", function (e) { + _this._eventRelay.trigger("change", e, _this); + }); + this._varOnChangeSub = sub; + } + } + + /** + * Retrieves the current selection for the group represented by this + * `SelectionHandle`. + * + * - If no selection is active, then this value will be falsy. + * - If a selection is active, but no data points are selected, then this + * value will be an empty array. + * - If a selection is active, and data points are selected, then the keys + * of the selected data points will be present in the array. + */ + + }, { + key: "_mergeExtraInfo", + + + /** + * Combines the given `extraInfo` (if any) with the handle's default + * `_extraInfo` (if any). + * @private + */ + value: function _mergeExtraInfo(extraInfo) { + // Important incidental effect: shallow clone is returned + return util.extend({}, this._extraInfo ? this._extraInfo : null, extraInfo ? extraInfo : null); + } + + /** + * Overwrites the current selection for the group, and raises the `"change"` + * event among all of the group's '`SelectionHandle` instances (including + * this one). + * + * @fires SelectionHandle#change + * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see + * {@link SelectionHandle#value}). + * @param {Object} [extraInfo] - Extra properties to be included on the event + * object that's passed to listeners (in addition to any options that were + * passed into the `SelectionHandle` constructor). + */ + + }, { + key: "set", + value: function set(selectedKeys, extraInfo) { + if (this._var) this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo)); + } + + /** + * Overwrites the current selection for the group, and raises the `"change"` + * event among all of the group's '`SelectionHandle` instances (including + * this one). + * + * @fires SelectionHandle#change + * @param {Object} [extraInfo] - Extra properties to be included on the event + * object that's passed to listeners (in addition to any that were passed + * into the `SelectionHandle` constructor). + */ + + }, { + key: "clear", + value: function clear(extraInfo) { + if (this._var) this.set(void 0, this._mergeExtraInfo(extraInfo)); + } + + /** + * Subscribes to events on this `SelectionHandle`. + * + * @param {string} eventType - Indicates the type of events to listen to. + * Currently, only `"change"` is supported. + * @param {SelectionHandle~listener} listener - The callback function that + * will be invoked when the event occurs. + * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel + * this subscription. + */ + + }, { + key: "on", + value: function on(eventType, listener) { + return this._emitter.on(eventType, listener); + } + + /** + * Cancels event subscriptions created by {@link SelectionHandle#on}. + * + * @param {string} eventType - The type of event to unsubscribe. + * @param {string|SelectionHandle~listener} listener - Either the callback + * function previously passed into {@link SelectionHandle#on}, or the + * string that was returned from {@link SelectionHandle#on}. + */ + + }, { + key: "off", + value: function off(eventType, listener) { + return this._emitter.off(eventType, listener); + } + + /** + * Shuts down the `SelectionHandle` object. + * + * Removes all event listeners that were added through this handle. + */ + + }, { + key: "close", + value: function close() { + this._emitter.removeAllListeners(); + this.setGroup(null); + } + }, { + key: "value", + get: function get() { + return this._var ? this._var.get() : null; + } + }]); + + return SelectionHandle; +}(); + +/** + * @callback SelectionHandle~listener + * @param {Object} event - An object containing details of the event. For + * `"change"` events, this includes the properties `value` (the new + * value of the selection, or `undefined` if no selection is active), + * `oldValue` (the previous value of the selection), and `sender` (the + * `SelectionHandle` instance that made the change). + */ + +/** + * @event SelectionHandle#change + * @type {object} + * @property {object} value - The new value of the selection, or `undefined` + * if no selection is active. + * @property {object} oldValue - The previous value of the selection. + * @property {SelectionHandle} sender - The `SelectionHandle` instance that + * changed the value. + */ + +},{"./events":1,"./group":4,"./util":11}],11:[function(require,module,exports){ +"use strict"; + +Object.defineProperty(exports, "__esModule", { + value: true +}); + +var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); + +var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; + +exports.extend = extend; +exports.checkSorted = checkSorted; +exports.diffSortedLists = diffSortedLists; +exports.dataframeToD3 = dataframeToD3; + +function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } + +function extend(target) { + for (var _len = arguments.length, sources = Array(_len > 1 ? _len - 1 : 0), _key = 1; _key < _len; _key++) { + sources[_key - 1] = arguments[_key]; + } + + for (var i = 0; i < sources.length; i++) { + var src = sources[i]; + if (typeof src === "undefined" || src === null) continue; + + for (var key in src) { + if (src.hasOwnProperty(key)) { + target[key] = src[key]; + } + } + } + return target; +} + +function checkSorted(list) { + for (var i = 1; i < list.length; i++) { + if (list[i] <= list[i - 1]) { + throw new Error("List is not sorted or contains duplicate"); + } + } +} + +function diffSortedLists(a, b) { + var i_a = 0; + var i_b = 0; + + if (!a) a = []; + if (!b) b = []; + + var a_only = []; + var b_only = []; + + checkSorted(a); + checkSorted(b); + + while (i_a < a.length && i_b < b.length) { + if (a[i_a] === b[i_b]) { + i_a++; + i_b++; + } else if (a[i_a] < b[i_b]) { + a_only.push(a[i_a++]); + } else { + b_only.push(b[i_b++]); + } + } + + if (i_a < a.length) a_only = a_only.concat(a.slice(i_a)); + if (i_b < b.length) b_only = b_only.concat(b.slice(i_b)); + return { + removed: a_only, + added: b_only + }; +} + +// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... } +// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ] +function dataframeToD3(df) { + var names = []; + var length = void 0; + for (var name in df) { + if (df.hasOwnProperty(name)) names.push(name); + if (_typeof(df[name]) !== "object" || typeof df[name].length === "undefined") { + throw new Error("All fields must be arrays"); + } else if (typeof length !== "undefined" && length !== df[name].length) { + throw new Error("All fields must be arrays of the same length"); + } + length = df[name].length; + } + var results = []; + var item = void 0; + for (var row = 0; row < length; row++) { + item = {}; + for (var col = 0; col < names.length; col++) { + item[names[col]] = df[names[col]][row]; + } + results.push(item); + } + return results; +} + +/** + * Keeps track of all event listener additions/removals and lets all active + * listeners be removed with a single operation. + * + * @private + */ + +var SubscriptionTracker = exports.SubscriptionTracker = function () { + function SubscriptionTracker(emitter) { + _classCallCheck(this, SubscriptionTracker); + + this._emitter = emitter; + this._subs = {}; + } + + _createClass(SubscriptionTracker, [{ + key: "on", + value: function on(eventType, listener) { + var sub = this._emitter.on(eventType, listener); + this._subs[sub] = eventType; + return sub; + } + }, { + key: "off", + value: function off(eventType, listener) { + var sub = this._emitter.off(eventType, listener); + if (sub) { + delete this._subs[sub]; + } + return sub; + } + }, { + key: "removeAllListeners", + value: function removeAllListeners() { + var _this = this; + + var current_subs = this._subs; + this._subs = {}; + Object.keys(current_subs).forEach(function (sub) { + _this._emitter.off(current_subs[sub], sub); + }); + } + }]); + + return SubscriptionTracker; +}(); + +},{}],12:[function(require,module,exports){ +(function (global){ +"use strict"; + +Object.defineProperty(exports, "__esModule", { + value: true +}); + +var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; + +var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); + +var _events = require("./events"); + +var _events2 = _interopRequireDefault(_events); + +function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } + +function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } + +var Var = function () { + function Var(group, name, /*optional*/value) { + _classCallCheck(this, Var); + + this._group = group; + this._name = name; + this._value = value; + this._events = new _events2.default(); + } + + _createClass(Var, [{ + key: "get", + value: function get() { + return this._value; + } + }, { + key: "set", + value: function set(value, /*optional*/event) { + if (this._value === value) { + // Do nothing; the value hasn't changed + return; + } + var oldValue = this._value; + this._value = value; + // Alert JavaScript listeners that the value has changed + var evt = {}; + if (event && (typeof event === "undefined" ? "undefined" : _typeof(event)) === "object") { + for (var k in event) { + if (event.hasOwnProperty(k)) evt[k] = event[k]; + } + } + evt.oldValue = oldValue; + evt.value = value; + this._events.trigger("change", evt, this); + + // TODO: Make this extensible, to let arbitrary back-ends know that + // something has changed + if (global.Shiny && global.Shiny.onInputChange) { + global.Shiny.onInputChange(".clientValue-" + (this._group.name !== null ? this._group.name + "-" : "") + this._name, typeof value === "undefined" ? null : value); + } + } + }, { + key: "on", + value: function on(eventType, listener) { + return this._events.on(eventType, listener); + } + }, { + key: "off", + value: function off(eventType, listener) { + return this._events.off(eventType, listener); + } + }]); + + return Var; +}(); + +exports.default = Var; + +}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) + +},{"./events":1}]},{},[5]) +//# sourceMappingURL=crosstalk.js.map diff --git a/docs/site_libs/crosstalk-1.2.2/js/crosstalk.js.map b/docs/site_libs/crosstalk-1.2.2/js/crosstalk.js.map index cff94f0..a89b39c 100644 --- a/docs/site_libs/crosstalk-1.2.2/js/crosstalk.js.map +++ b/docs/site_libs/crosstalk-1.2.2/js/crosstalk.js.map @@ -1,37 +1,37 @@ -{ - "version": 3, - "sources": [ - "node_modules/browser-pack/_prelude.js", - "javascript/src/events.js", - "javascript/src/filter.js", - "javascript/src/filterset.js", - "javascript/src/group.js", - "javascript/src/index.js", - "javascript/src/input.js", - "javascript/src/input_checkboxgroup.js", - "javascript/src/input_selectize.js", - "javascript/src/input_slider.js", - "javascript/src/selection.js", - "javascript/src/util.js", - "javascript/src/var.js" - ], - "names": [], - "mappings": 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- "file": "generated.js", - "sourceRoot": "", - "sourcesContent": [ - "(function(){function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require==\"function\"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error(\"Cannot find module '\"+o+\"'\");throw f.code=\"MODULE_NOT_FOUND\",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require==\"function\"&&require;for(var o=0;o {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Combine the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Close the handle. This clears this handle's contribution to the filter set,\n * and unsubscribes all event listeners.\n */\n close() {\n this._emitter.removeAllListeners();\n this.clear();\n this.setGroup(null);\n }\n\n /**\n * Clear this handle's contribution to the filter set.\n *\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n clear(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.clear(this._id);\n this._onChange(extraInfo);\n }\n\n /**\n * Set this handle's contribution to the filter set. This array should consist\n * of the keys of the rows that _should_ be displayed; any keys that are not\n * present in the array will be considered _filtered out_. Note that multiple\n * `FilterHandle` instances in the group may each contribute an array of keys,\n * and only those keys that appear in _all_ of the arrays make it through the\n * filter.\n *\n * @param {string[]} keys - Empty array, or array of keys. To clear the\n * filter, don't pass an empty array; instead, use the\n * {@link FilterHandle#clear} method.\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n set(keys, extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.update(this._id, keys);\n this._onChange(extraInfo);\n }\n\n /**\n * @return {string[]|null} - Either: 1) an array of keys that made it through\n * all of the `FilterHandle` instances, or, 2) `null`, which means no filter\n * is being applied (all data should be displayed).\n */\n get filteredKeys() {\n return this._filterSet ? this._filterSet.value : null;\n }\n\n /**\n * Subscribe to events on this `FilterHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {FilterHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link FilterHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancel event subscriptions created by {@link FilterHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|FilterHandle~listener} listener - Either the callback\n * function previously passed into {@link FilterHandle#on}, or the\n * string that was returned from {@link FilterHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n _onChange(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterVar.set(this._filterSet.value, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * @callback FilterHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the filter set, or `null` if no filter set is active),\n * `oldValue` (the previous value of the filter set), and `sender` (the\n * `FilterHandle` instance that made the change).\n */\n\n}\n\n/**\n * @event FilterHandle#change\n * @type {object}\n * @property {object} value - The new value of the filter set, or `null`\n * if no filter set is active.\n * @property {object} oldValue - The previous value of the filter set.\n * @property {FilterHandle} sender - The `FilterHandle` instance that\n * changed the value.\n */\n", - "import { diffSortedLists } from \"./util\";\n\nfunction naturalComparator(a, b) {\n if (a === b) {\n return 0;\n } else if (a < b) {\n return -1;\n } else if (a > b) {\n return 1;\n }\n}\n\n/**\n * @private\n */\nexport default class FilterSet {\n constructor() {\n this.reset();\n }\n\n reset() {\n // Key: handle ID, Value: array of selected keys, or null\n this._handles = {};\n // Key: key string, Value: count of handles that include it\n this._keys = {};\n this._value = null;\n this._activeHandles = 0;\n }\n\n get value() {\n return this._value;\n }\n\n update(handleId, keys) {\n if (keys !== null) {\n keys = keys.slice(0); // clone before sorting\n keys.sort(naturalComparator);\n }\n\n let {added, removed} = diffSortedLists(this._handles[handleId], keys);\n this._handles[handleId] = keys;\n\n for (let i = 0; i < added.length; i++) {\n this._keys[added[i]] = (this._keys[added[i]] || 0) + 1;\n }\n for (let i = 0; i < removed.length; i++) {\n this._keys[removed[i]]--;\n }\n\n this._updateValue(keys);\n }\n\n /**\n * @param {string[]} keys Sorted array of strings that indicate\n * a superset of possible keys.\n * @private\n */\n _updateValue(keys = this._allKeys) {\n let handleCount = Object.keys(this._handles).length;\n if (handleCount === 0) {\n this._value = null;\n } else {\n this._value = [];\n for (let i = 0; i < keys.length; i++) {\n let count = this._keys[keys[i]];\n if (count === handleCount) {\n this._value.push(keys[i]);\n }\n }\n }\n }\n\n clear(handleId) {\n if (typeof(this._handles[handleId]) === \"undefined\") {\n return;\n }\n\n let keys = this._handles[handleId];\n if (!keys) {\n keys = [];\n }\n\n for (let i = 0; i < keys.length; i++) {\n this._keys[keys[i]]--;\n }\n delete this._handles[handleId];\n\n this._updateValue();\n }\n\n get _allKeys() {\n let allKeys = Object.keys(this._keys);\n allKeys.sort(naturalComparator);\n return allKeys;\n }\n}\n", - "import Var from \"./var\";\n\n// Use a global so that multiple copies of crosstalk.js can be loaded and still\n// have groups behave as singletons across all copies.\nglobal.__crosstalk_groups = global.__crosstalk_groups || {};\nlet groups = global.__crosstalk_groups;\n\nexport default function group(groupName) {\n if (groupName && typeof(groupName) === \"string\") {\n if (!groups.hasOwnProperty(groupName)) {\n groups[groupName] = new Group(groupName);\n }\n return groups[groupName];\n } else if (typeof(groupName) === \"object\" && groupName._vars && groupName.var) {\n // Appears to already be a group object\n return groupName;\n } else if (Array.isArray(groupName) &&\n groupName.length == 1 &&\n typeof(groupName[0]) === \"string\") {\n return group(groupName[0]);\n } else {\n throw new Error(\"Invalid groupName argument\");\n }\n}\n\nclass Group {\n constructor(name) {\n this.name = name;\n this._vars = {};\n }\n\n var(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n if (!this._vars.hasOwnProperty(name))\n this._vars[name] = new Var(this, name);\n return this._vars[name];\n }\n\n has(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n return this._vars.hasOwnProperty(name);\n }\n}\n", - "import group from \"./group\";\nimport { SelectionHandle } from \"./selection\";\nimport { FilterHandle } from \"./filter\";\nimport { bind } from \"./input\";\nimport \"./input_selectize\";\nimport \"./input_checkboxgroup\";\nimport \"./input_slider\";\n\nconst defaultGroup = group(\"default\");\n\nfunction var_(name) {\n return defaultGroup.var(name);\n}\n\nfunction has(name) {\n return defaultGroup.has(name);\n}\n\nif (global.Shiny) {\n global.Shiny.addCustomMessageHandler(\"update-client-value\", function(message) {\n if (typeof(message.group) === \"string\") {\n group(message.group).var(message.name).set(message.value);\n } else {\n var_(message.name).set(message.value);\n }\n });\n}\n\nconst crosstalk = {\n group: group,\n var: var_,\n has: has,\n SelectionHandle: SelectionHandle,\n FilterHandle: FilterHandle,\n bind: bind\n};\n\n/**\n * @namespace crosstalk\n */\nexport default crosstalk;\nglobal.crosstalk = crosstalk;\n", - "let $ = global.jQuery;\n\nlet bindings = {};\n\nexport function register(reg) {\n bindings[reg.className] = reg;\n if (global.document && global.document.readyState !== \"complete\") {\n $(() => {\n bind();\n });\n } else if (global.document) {\n setTimeout(bind, 100);\n }\n}\n\nexport function bind() {\n Object.keys(bindings).forEach(function(className) {\n let binding = bindings[className];\n $(\".\" + binding.className).not(\".crosstalk-input-bound\").each(function(i, el) {\n bindInstance(binding, el);\n });\n });\n}\n\n// Escape jQuery identifier\nfunction $escape(val) {\n return val.replace(/([!\"#$%&'()*+,./:;<=>?@[\\\\\\]^`{|}~])/g, \"\\\\$1\");\n}\n\nfunction bindEl(el) {\n let $el = $(el);\n Object.keys(bindings).forEach(function(className) {\n if ($el.hasClass(className) && !$el.hasClass(\"crosstalk-input-bound\")) {\n let binding = bindings[className];\n bindInstance(binding, el);\n }\n });\n}\n\nfunction bindInstance(binding, el) {\n let jsonEl = $(el).find(\"script[type='application/json'][data-for='\" + $escape(el.id) + \"']\");\n let data = JSON.parse(jsonEl[0].innerText);\n\n let instance = binding.factory(el, data);\n $(el).data(\"crosstalk-instance\", instance);\n $(el).addClass(\"crosstalk-input-bound\");\n}\n\nif (global.Shiny) {\n let inputBinding = new global.Shiny.InputBinding();\n let $ = global.jQuery;\n $.extend(inputBinding, {\n find: function(scope) {\n return $(scope).find(\".crosstalk-input\");\n },\n initialize: function(el) {\n if (!$(el).hasClass(\"crosstalk-input-bound\")) {\n bindEl(el);\n }\n },\n getId: function(el) {\n return el.id;\n },\n getValue: function(el) {\n\n },\n setValue: function(el, value) {\n\n },\n receiveMessage: function(el, data) {\n\n },\n subscribe: function(el, callback) {\n $(el).data(\"crosstalk-instance\").resume();\n },\n unsubscribe: function(el) {\n $(el).data(\"crosstalk-instance\").suspend();\n }\n });\n global.Shiny.inputBindings.register(inputBinding, \"crosstalk.inputBinding\");\n}\n", - "import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-checkboxgroup\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n let $el = $(el);\n $el.on(\"change\", \"input[type='checkbox']\", function() {\n let checked = $el.find(\"input[type='checkbox']:checked\");\n if (checked.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n checked.each(function() {\n data.map[this.value].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n", - "import * as input from \"./input\";\nimport * as util from \"./util\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-select\",\n\n factory: function(el, data) {\n /*\n * items: {value: [...], label: [...]}\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n\n let first = [{value: \"\", label: \"(All)\"}];\n let items = util.dataframeToD3(data.items);\n let opts = {\n options: first.concat(items),\n valueField: \"value\",\n labelField: \"label\",\n searchField: \"label\"\n };\n\n let select = $(el).find(\"select\")[0];\n\n let selectize = $(select).selectize(opts)[0].selectize;\n\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n selectize.on(\"change\", function() {\n if (selectize.items.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n selectize.items.forEach(function(group) {\n data.map[group].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n", - "import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\nlet strftime = global.strftime;\n\ninput.register({\n className: \"crosstalk-input-slider\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let opts = {};\n let $el = $(el).find(\"input\");\n let dataType = $el.data(\"data-type\");\n let timeFormat = $el.data(\"time-format\");\n let round = $el.data(\"round\");\n let timeFormatter;\n\n // Set up formatting functions\n if (dataType === \"date\") {\n timeFormatter = strftime.utc();\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n\n } else if (dataType === \"datetime\") {\n let timezone = $el.data(\"timezone\");\n if (timezone)\n timeFormatter = strftime.timezone(timezone);\n else\n timeFormatter = strftime;\n\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n } else if (dataType === \"number\") {\n if (typeof round !== \"undefined\")\n opts.prettify = function(num) {\n let factor = Math.pow(10, round);\n return Math.round(num * factor) / factor;\n };\n }\n\n $el.ionRangeSlider(opts);\n\n function getValue() {\n let result = $el.data(\"ionRangeSlider\").result;\n\n // Function for converting numeric value from slider to appropriate type.\n let convert;\n let dataType = $el.data(\"data-type\");\n if (dataType === \"date\") {\n convert = function(val) {\n return formatDateUTC(new Date(+val));\n };\n } else if (dataType === \"datetime\") {\n convert = function(val) {\n // Convert ms to s\n return +val / 1000;\n };\n } else {\n convert = function(val) { return +val; };\n }\n\n if ($el.data(\"ionRangeSlider\").options.type === \"double\") {\n return [convert(result.from), convert(result.to)];\n } else {\n return convert(result.from);\n }\n }\n\n let lastKnownKeys = null;\n\n $el.on(\"change.crosstalkSliderInput\", function(event) {\n if (!$el.data(\"updating\") && !$el.data(\"animating\")) {\n let [from, to] = getValue();\n let keys = [];\n for (let i = 0; i < data.values.length; i++) {\n let val = data.values[i];\n if (val >= from && val <= to) {\n keys.push(data.keys[i]);\n }\n }\n keys.sort();\n ctHandle.set(keys);\n lastKnownKeys = keys;\n }\n });\n\n\n // let $el = $(el);\n // $el.on(\"change\", \"input[type=\"checkbox\"]\", function() {\n // let checked = $el.find(\"input[type=\"checkbox\"]:checked\");\n // if (checked.length === 0) {\n // ctHandle.clear();\n // } else {\n // let keys = {};\n // checked.each(function() {\n // data.map[this.value].forEach(function(key) {\n // keys[key] = true;\n // });\n // });\n // let keyArray = Object.keys(keys);\n // keyArray.sort();\n // ctHandle.set(keyArray);\n // }\n // });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n\n\n// Convert a number to a string with leading zeros\nfunction padZeros(n, digits) {\n let str = n.toString();\n while (str.length < digits)\n str = \"0\" + str;\n return str;\n}\n\n// Given a Date object, return a string in yyyy-mm-dd format, using the\n// UTC date. This may be a day off from the date in the local time zone.\nfunction formatDateUTC(date) {\n if (date instanceof Date) {\n return date.getUTCFullYear() + \"-\" +\n padZeros(date.getUTCMonth()+1, 2) + \"-\" +\n padZeros(date.getUTCDate(), 2);\n\n } else {\n return null;\n }\n}\n", - "import Events from \"./events\";\nimport grp from \"./group\";\nimport * as util from \"./util\";\n\n/**\n * Use this class to read and write (and listen for changes to) the selection\n * for a Crosstalk group. This is intended to be used for linked brushing.\n *\n * If two (or more) `SelectionHandle` instances in the same webpage share the\n * same group name, they will share the same state. Setting the selection using\n * one `SelectionHandle` instance will result in the `value` property instantly\n * changing across the others, and `\"change\"` event listeners on all instances\n * (including the one that initiated the sending) will fire.\n *\n * @param {string} [group] - The name of the Crosstalk group, or if none,\n * null or undefined (or any other falsy value). This can be changed later\n * via the [SelectionHandle#setGroup](#setGroup) method.\n * @param {Object} [extraInfo] - An object whose properties will be copied to\n * the event object whenever an event is emitted.\n */\nexport class SelectionHandle {\n\n constructor(group = null, extraInfo = null) {\n this._eventRelay = new Events();\n this._emitter = new util.SubscriptionTracker(this._eventRelay);\n\n // Name of the group we're currently tracking, if any. Can change over time.\n this._group = null;\n // The Var we're currently tracking, if any. Can change over time.\n this._var = null;\n // The event handler subscription we currently have on var.on(\"change\").\n this._varOnChangeSub = null;\n\n this._extraInfo = util.extend({ sender: this }, extraInfo);\n\n this.setGroup(group);\n }\n\n /**\n * Changes the Crosstalk group membership of this SelectionHandle. The group\n * being switched away from (if any) will not have its selection value\n * modified as a result of calling `setGroup`, even if this handle was the\n * most recent handle to set the selection of the group.\n *\n * The group being switched to (if any) will also not have its selection value\n * modified as a result of calling `setGroup`. If you want to set the\n * selection value of the new group, call `set` explicitly.\n *\n * @param {string} group - The name of the Crosstalk group, or null (or\n * undefined) to clear the group.\n */\n setGroup(group) {\n // If group is unchanged, do nothing\n if (this._group === group)\n return;\n // Treat null, undefined, and other falsy values the same\n if (!this._group && !group)\n return;\n\n if (this._var) {\n this._var.off(\"change\", this._varOnChangeSub);\n this._var = null;\n this._varOnChangeSub = null;\n }\n\n this._group = group;\n\n if (group) {\n this._var = grp(group).var(\"selection\");\n let sub = this._var.on(\"change\", (e) => {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Retrieves the current selection for the group represented by this\n * `SelectionHandle`.\n *\n * - If no selection is active, then this value will be falsy.\n * - If a selection is active, but no data points are selected, then this\n * value will be an empty array.\n * - If a selection is active, and data points are selected, then the keys\n * of the selected data points will be present in the array.\n */\n get value() {\n return this._var ? this._var.get() : null;\n }\n\n /**\n * Combines the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n // Important incidental effect: shallow clone is returned\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see\n * {@link SelectionHandle#value}).\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `SelectionHandle` constructor).\n */\n set(selectedKeys, extraInfo) {\n if (this._var)\n this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any that were passed\n * into the `SelectionHandle` constructor).\n */\n clear(extraInfo) {\n if (this._var)\n this.set(void 0, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Subscribes to events on this `SelectionHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {SelectionHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancels event subscriptions created by {@link SelectionHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|SelectionHandle~listener} listener - Either the callback\n * function previously passed into {@link SelectionHandle#on}, or the\n * string that was returned from {@link SelectionHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n /**\n * Shuts down the `SelectionHandle` object.\n *\n * Removes all event listeners that were added through this handle.\n */\n close() {\n this._emitter.removeAllListeners();\n this.setGroup(null);\n }\n}\n\n/**\n * @callback SelectionHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the selection, or `undefined` if no selection is active),\n * `oldValue` (the previous value of the selection), and `sender` (the\n * `SelectionHandle` instance that made the change).\n */\n\n/**\n * @event SelectionHandle#change\n * @type {object}\n * @property {object} value - The new value of the selection, or `undefined`\n * if no selection is active.\n * @property {object} oldValue - The previous value of the selection.\n * @property {SelectionHandle} sender - The `SelectionHandle` instance that\n * changed the value.\n */\n", - "export function extend(target, ...sources) {\n for (let i = 0; i < sources.length; i++) {\n let src = sources[i];\n if (typeof(src) === \"undefined\" || src === null)\n continue;\n\n for (let key in src) {\n if (src.hasOwnProperty(key)) {\n target[key] = src[key];\n }\n }\n }\n return target;\n}\n\nexport function checkSorted(list) {\n for (let i = 1; i < list.length; i++) {\n if (list[i] <= list[i-1]) {\n throw new Error(\"List is not sorted or contains duplicate\");\n }\n }\n}\n\nexport function diffSortedLists(a, b) {\n let i_a = 0;\n let i_b = 0;\n\n if (!a) a = [];\n if (!b) b = [];\n\n let a_only = [];\n let b_only = [];\n\n checkSorted(a);\n checkSorted(b);\n\n while (i_a < a.length && i_b < b.length) {\n if (a[i_a] === b[i_b]) {\n i_a++;\n i_b++;\n } else if (a[i_a] < b[i_b]) {\n a_only.push(a[i_a++]);\n } else {\n b_only.push(b[i_b++]);\n }\n }\n\n if (i_a < a.length)\n a_only = a_only.concat(a.slice(i_a));\n if (i_b < b.length)\n b_only = b_only.concat(b.slice(i_b));\n return {\n removed: a_only,\n added: b_only\n };\n}\n\n// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... }\n// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ]\nexport function dataframeToD3(df) {\n let names = [];\n let length;\n for (let name in df) {\n if (df.hasOwnProperty(name))\n names.push(name);\n if (typeof(df[name]) !== \"object\" || typeof(df[name].length) === \"undefined\") {\n throw new Error(\"All fields must be arrays\");\n } else if (typeof(length) !== \"undefined\" && length !== df[name].length) {\n throw new Error(\"All fields must be arrays of the same length\");\n }\n length = df[name].length;\n }\n let results = [];\n let item;\n for (let row = 0; row < length; row++) {\n item = {};\n for (let col = 0; col < names.length; col++) {\n item[names[col]] = df[names[col]][row];\n }\n results.push(item);\n }\n return results;\n}\n\n/**\n * Keeps track of all event listener additions/removals and lets all active\n * listeners be removed with a single operation.\n *\n * @private\n */\nexport class SubscriptionTracker {\n constructor(emitter) {\n this._emitter = emitter;\n this._subs = {};\n }\n\n on(eventType, listener) {\n let sub = this._emitter.on(eventType, listener);\n this._subs[sub] = eventType;\n return sub;\n }\n\n off(eventType, listener) {\n let sub = this._emitter.off(eventType, listener);\n if (sub) {\n delete this._subs[sub];\n }\n return sub;\n }\n\n removeAllListeners() {\n let current_subs = this._subs;\n this._subs = {};\n Object.keys(current_subs).forEach((sub) => {\n this._emitter.off(current_subs[sub], sub);\n });\n }\n}\n", - "import Events from \"./events\";\n\nexport default class Var {\n constructor(group, name, /*optional*/ value) {\n this._group = group;\n this._name = name;\n this._value = value;\n this._events = new Events();\n }\n\n get() {\n return this._value;\n }\n\n set(value, /*optional*/ event) {\n if (this._value === value) {\n // Do nothing; the value hasn't changed\n return;\n }\n let oldValue = this._value;\n this._value = value;\n // Alert JavaScript listeners that the value has changed\n let evt = {};\n if (event && typeof(event) === \"object\") {\n for (let k in event) {\n if (event.hasOwnProperty(k))\n evt[k] = event[k];\n }\n }\n evt.oldValue = oldValue;\n evt.value = value;\n this._events.trigger(\"change\", evt, this);\n\n // TODO: Make this extensible, to let arbitrary back-ends know that\n // something has changed\n if (global.Shiny && global.Shiny.onInputChange) {\n global.Shiny.onInputChange(\n \".clientValue-\" +\n (this._group.name !== null ? this._group.name + \"-\" : \"\") +\n this._name,\n typeof(value) === \"undefined\" ? null : value\n );\n }\n }\n\n on(eventType, listener) {\n return this._events.on(eventType, listener);\n }\n\n off(eventType, listener) {\n return this._events.off(eventType, listener);\n }\n}\n" - ] +{ + "version": 3, + "sources": [ + "node_modules/browser-pack/_prelude.js", + "javascript/src/events.js", + "javascript/src/filter.js", + "javascript/src/filterset.js", + "javascript/src/group.js", + "javascript/src/index.js", + "javascript/src/input.js", + "javascript/src/input_checkboxgroup.js", + "javascript/src/input_selectize.js", + "javascript/src/input_slider.js", + "javascript/src/selection.js", + "javascript/src/util.js", + "javascript/src/var.js" + ], + "names": [], + "mappings": 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+ "file": "generated.js", + "sourceRoot": "", + "sourcesContent": [ + "(function(){function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require==\"function\"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error(\"Cannot find module '\"+o+\"'\");throw f.code=\"MODULE_NOT_FOUND\",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require==\"function\"&&require;for(var o=0;o {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Combine the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Close the handle. This clears this handle's contribution to the filter set,\n * and unsubscribes all event listeners.\n */\n close() {\n this._emitter.removeAllListeners();\n this.clear();\n this.setGroup(null);\n }\n\n /**\n * Clear this handle's contribution to the filter set.\n *\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n clear(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.clear(this._id);\n this._onChange(extraInfo);\n }\n\n /**\n * Set this handle's contribution to the filter set. This array should consist\n * of the keys of the rows that _should_ be displayed; any keys that are not\n * present in the array will be considered _filtered out_. Note that multiple\n * `FilterHandle` instances in the group may each contribute an array of keys,\n * and only those keys that appear in _all_ of the arrays make it through the\n * filter.\n *\n * @param {string[]} keys - Empty array, or array of keys. To clear the\n * filter, don't pass an empty array; instead, use the\n * {@link FilterHandle#clear} method.\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n set(keys, extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.update(this._id, keys);\n this._onChange(extraInfo);\n }\n\n /**\n * @return {string[]|null} - Either: 1) an array of keys that made it through\n * all of the `FilterHandle` instances, or, 2) `null`, which means no filter\n * is being applied (all data should be displayed).\n */\n get filteredKeys() {\n return this._filterSet ? this._filterSet.value : null;\n }\n\n /**\n * Subscribe to events on this `FilterHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {FilterHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link FilterHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancel event subscriptions created by {@link FilterHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|FilterHandle~listener} listener - Either the callback\n * function previously passed into {@link FilterHandle#on}, or the\n * string that was returned from {@link FilterHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n _onChange(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterVar.set(this._filterSet.value, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * @callback FilterHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the filter set, or `null` if no filter set is active),\n * `oldValue` (the previous value of the filter set), and `sender` (the\n * `FilterHandle` instance that made the change).\n */\n\n}\n\n/**\n * @event FilterHandle#change\n * @type {object}\n * @property {object} value - The new value of the filter set, or `null`\n * if no filter set is active.\n * @property {object} oldValue - The previous value of the filter set.\n * @property {FilterHandle} sender - The `FilterHandle` instance that\n * changed the value.\n */\n", + "import { diffSortedLists } from \"./util\";\n\nfunction naturalComparator(a, b) {\n if (a === b) {\n return 0;\n } else if (a < b) {\n return -1;\n } else if (a > b) {\n return 1;\n }\n}\n\n/**\n * @private\n */\nexport default class FilterSet {\n constructor() {\n this.reset();\n }\n\n reset() {\n // Key: handle ID, Value: array of selected keys, or null\n this._handles = {};\n // Key: key string, Value: count of handles that include it\n this._keys = {};\n this._value = null;\n this._activeHandles = 0;\n }\n\n get value() {\n return this._value;\n }\n\n update(handleId, keys) {\n if (keys !== null) {\n keys = keys.slice(0); // clone before sorting\n keys.sort(naturalComparator);\n }\n\n let {added, removed} = diffSortedLists(this._handles[handleId], keys);\n this._handles[handleId] = keys;\n\n for (let i = 0; i < added.length; i++) {\n this._keys[added[i]] = (this._keys[added[i]] || 0) + 1;\n }\n for (let i = 0; i < removed.length; i++) {\n this._keys[removed[i]]--;\n }\n\n this._updateValue(keys);\n }\n\n /**\n * @param {string[]} keys Sorted array of strings that indicate\n * a superset of possible keys.\n * @private\n */\n _updateValue(keys = this._allKeys) {\n let handleCount = Object.keys(this._handles).length;\n if (handleCount === 0) {\n this._value = null;\n } else {\n this._value = [];\n for (let i = 0; i < keys.length; i++) {\n let count = this._keys[keys[i]];\n if (count === handleCount) {\n this._value.push(keys[i]);\n }\n }\n }\n }\n\n clear(handleId) {\n if (typeof(this._handles[handleId]) === \"undefined\") {\n return;\n }\n\n let keys = this._handles[handleId];\n if (!keys) {\n keys = [];\n }\n\n for (let i = 0; i < keys.length; i++) {\n this._keys[keys[i]]--;\n }\n delete this._handles[handleId];\n\n this._updateValue();\n }\n\n get _allKeys() {\n let allKeys = Object.keys(this._keys);\n allKeys.sort(naturalComparator);\n return allKeys;\n }\n}\n", + "import Var from \"./var\";\n\n// Use a global so that multiple copies of crosstalk.js can be loaded and still\n// have groups behave as singletons across all copies.\nglobal.__crosstalk_groups = global.__crosstalk_groups || {};\nlet groups = global.__crosstalk_groups;\n\nexport default function group(groupName) {\n if (groupName && typeof(groupName) === \"string\") {\n if (!groups.hasOwnProperty(groupName)) {\n groups[groupName] = new Group(groupName);\n }\n return groups[groupName];\n } else if (typeof(groupName) === \"object\" && groupName._vars && groupName.var) {\n // Appears to already be a group object\n return groupName;\n } else if (Array.isArray(groupName) &&\n groupName.length == 1 &&\n typeof(groupName[0]) === \"string\") {\n return group(groupName[0]);\n } else {\n throw new Error(\"Invalid groupName argument\");\n }\n}\n\nclass Group {\n constructor(name) {\n this.name = name;\n this._vars = {};\n }\n\n var(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n if (!this._vars.hasOwnProperty(name))\n this._vars[name] = new Var(this, name);\n return this._vars[name];\n }\n\n has(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n return this._vars.hasOwnProperty(name);\n }\n}\n", + "import group from \"./group\";\nimport { SelectionHandle } from \"./selection\";\nimport { FilterHandle } from \"./filter\";\nimport { bind } from \"./input\";\nimport \"./input_selectize\";\nimport \"./input_checkboxgroup\";\nimport \"./input_slider\";\n\nconst defaultGroup = group(\"default\");\n\nfunction var_(name) {\n return defaultGroup.var(name);\n}\n\nfunction has(name) {\n return defaultGroup.has(name);\n}\n\nif (global.Shiny) {\n global.Shiny.addCustomMessageHandler(\"update-client-value\", function(message) {\n if (typeof(message.group) === \"string\") {\n group(message.group).var(message.name).set(message.value);\n } else {\n var_(message.name).set(message.value);\n }\n });\n}\n\nconst crosstalk = {\n group: group,\n var: var_,\n has: has,\n SelectionHandle: SelectionHandle,\n FilterHandle: FilterHandle,\n bind: bind\n};\n\n/**\n * @namespace crosstalk\n */\nexport default crosstalk;\nglobal.crosstalk = crosstalk;\n", + "let $ = global.jQuery;\n\nlet bindings = {};\n\nexport function register(reg) {\n bindings[reg.className] = reg;\n if (global.document && global.document.readyState !== \"complete\") {\n $(() => {\n bind();\n });\n } else if (global.document) {\n setTimeout(bind, 100);\n }\n}\n\nexport function bind() {\n Object.keys(bindings).forEach(function(className) {\n let binding = bindings[className];\n $(\".\" + binding.className).not(\".crosstalk-input-bound\").each(function(i, el) {\n bindInstance(binding, el);\n });\n });\n}\n\n// Escape jQuery identifier\nfunction $escape(val) {\n return val.replace(/([!\"#$%&'()*+,./:;<=>?@[\\\\\\]^`{|}~])/g, \"\\\\$1\");\n}\n\nfunction bindEl(el) {\n let $el = $(el);\n Object.keys(bindings).forEach(function(className) {\n if ($el.hasClass(className) && !$el.hasClass(\"crosstalk-input-bound\")) {\n let binding = bindings[className];\n bindInstance(binding, el);\n }\n });\n}\n\nfunction bindInstance(binding, el) {\n let jsonEl = $(el).find(\"script[type='application/json'][data-for='\" + $escape(el.id) + \"']\");\n let data = JSON.parse(jsonEl[0].innerText);\n\n let instance = binding.factory(el, data);\n $(el).data(\"crosstalk-instance\", instance);\n $(el).addClass(\"crosstalk-input-bound\");\n}\n\nif (global.Shiny) {\n let inputBinding = new global.Shiny.InputBinding();\n let $ = global.jQuery;\n $.extend(inputBinding, {\n find: function(scope) {\n return $(scope).find(\".crosstalk-input\");\n },\n initialize: function(el) {\n if (!$(el).hasClass(\"crosstalk-input-bound\")) {\n bindEl(el);\n }\n },\n getId: function(el) {\n return el.id;\n },\n getValue: function(el) {\n\n },\n setValue: function(el, value) {\n\n },\n receiveMessage: function(el, data) {\n\n },\n subscribe: function(el, callback) {\n $(el).data(\"crosstalk-instance\").resume();\n },\n unsubscribe: function(el) {\n $(el).data(\"crosstalk-instance\").suspend();\n }\n });\n global.Shiny.inputBindings.register(inputBinding, \"crosstalk.inputBinding\");\n}\n", + "import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-checkboxgroup\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n let $el = $(el);\n $el.on(\"change\", \"input[type='checkbox']\", function() {\n let checked = $el.find(\"input[type='checkbox']:checked\");\n if (checked.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n checked.each(function() {\n data.map[this.value].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n", + "import * as input from \"./input\";\nimport * as util from \"./util\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-select\",\n\n factory: function(el, data) {\n /*\n * items: {value: [...], label: [...]}\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n\n let first = [{value: \"\", label: \"(All)\"}];\n let items = util.dataframeToD3(data.items);\n let opts = {\n options: first.concat(items),\n valueField: \"value\",\n labelField: \"label\",\n searchField: \"label\"\n };\n\n let select = $(el).find(\"select\")[0];\n\n let selectize = $(select).selectize(opts)[0].selectize;\n\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n selectize.on(\"change\", function() {\n if (selectize.items.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n selectize.items.forEach(function(group) {\n data.map[group].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n", + "import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\nlet strftime = global.strftime;\n\ninput.register({\n className: \"crosstalk-input-slider\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let opts = {};\n let $el = $(el).find(\"input\");\n let dataType = $el.data(\"data-type\");\n let timeFormat = $el.data(\"time-format\");\n let round = $el.data(\"round\");\n let timeFormatter;\n\n // Set up formatting functions\n if (dataType === \"date\") {\n timeFormatter = strftime.utc();\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n\n } else if (dataType === \"datetime\") {\n let timezone = $el.data(\"timezone\");\n if (timezone)\n timeFormatter = strftime.timezone(timezone);\n else\n timeFormatter = strftime;\n\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n } else if (dataType === \"number\") {\n if (typeof round !== \"undefined\")\n opts.prettify = function(num) {\n let factor = Math.pow(10, round);\n return Math.round(num * factor) / factor;\n };\n }\n\n $el.ionRangeSlider(opts);\n\n function getValue() {\n let result = $el.data(\"ionRangeSlider\").result;\n\n // Function for converting numeric value from slider to appropriate type.\n let convert;\n let dataType = $el.data(\"data-type\");\n if (dataType === \"date\") {\n convert = function(val) {\n return formatDateUTC(new Date(+val));\n };\n } else if (dataType === \"datetime\") {\n convert = function(val) {\n // Convert ms to s\n return +val / 1000;\n };\n } else {\n convert = function(val) { return +val; };\n }\n\n if ($el.data(\"ionRangeSlider\").options.type === \"double\") {\n return [convert(result.from), convert(result.to)];\n } else {\n return convert(result.from);\n }\n }\n\n let lastKnownKeys = null;\n\n $el.on(\"change.crosstalkSliderInput\", function(event) {\n if (!$el.data(\"updating\") && !$el.data(\"animating\")) {\n let [from, to] = getValue();\n let keys = [];\n for (let i = 0; i < data.values.length; i++) {\n let val = data.values[i];\n if (val >= from && val <= to) {\n keys.push(data.keys[i]);\n }\n }\n keys.sort();\n ctHandle.set(keys);\n lastKnownKeys = keys;\n }\n });\n\n\n // let $el = $(el);\n // $el.on(\"change\", \"input[type=\"checkbox\"]\", function() {\n // let checked = $el.find(\"input[type=\"checkbox\"]:checked\");\n // if (checked.length === 0) {\n // ctHandle.clear();\n // } else {\n // let keys = {};\n // checked.each(function() {\n // data.map[this.value].forEach(function(key) {\n // keys[key] = true;\n // });\n // });\n // let keyArray = Object.keys(keys);\n // keyArray.sort();\n // ctHandle.set(keyArray);\n // }\n // });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n\n\n// Convert a number to a string with leading zeros\nfunction padZeros(n, digits) {\n let str = n.toString();\n while (str.length < digits)\n str = \"0\" + str;\n return str;\n}\n\n// Given a Date object, return a string in yyyy-mm-dd format, using the\n// UTC date. This may be a day off from the date in the local time zone.\nfunction formatDateUTC(date) {\n if (date instanceof Date) {\n return date.getUTCFullYear() + \"-\" +\n padZeros(date.getUTCMonth()+1, 2) + \"-\" +\n padZeros(date.getUTCDate(), 2);\n\n } else {\n return null;\n }\n}\n", + "import Events from \"./events\";\nimport grp from \"./group\";\nimport * as util from \"./util\";\n\n/**\n * Use this class to read and write (and listen for changes to) the selection\n * for a Crosstalk group. This is intended to be used for linked brushing.\n *\n * If two (or more) `SelectionHandle` instances in the same webpage share the\n * same group name, they will share the same state. Setting the selection using\n * one `SelectionHandle` instance will result in the `value` property instantly\n * changing across the others, and `\"change\"` event listeners on all instances\n * (including the one that initiated the sending) will fire.\n *\n * @param {string} [group] - The name of the Crosstalk group, or if none,\n * null or undefined (or any other falsy value). This can be changed later\n * via the [SelectionHandle#setGroup](#setGroup) method.\n * @param {Object} [extraInfo] - An object whose properties will be copied to\n * the event object whenever an event is emitted.\n */\nexport class SelectionHandle {\n\n constructor(group = null, extraInfo = null) {\n this._eventRelay = new Events();\n this._emitter = new util.SubscriptionTracker(this._eventRelay);\n\n // Name of the group we're currently tracking, if any. Can change over time.\n this._group = null;\n // The Var we're currently tracking, if any. Can change over time.\n this._var = null;\n // The event handler subscription we currently have on var.on(\"change\").\n this._varOnChangeSub = null;\n\n this._extraInfo = util.extend({ sender: this }, extraInfo);\n\n this.setGroup(group);\n }\n\n /**\n * Changes the Crosstalk group membership of this SelectionHandle. The group\n * being switched away from (if any) will not have its selection value\n * modified as a result of calling `setGroup`, even if this handle was the\n * most recent handle to set the selection of the group.\n *\n * The group being switched to (if any) will also not have its selection value\n * modified as a result of calling `setGroup`. If you want to set the\n * selection value of the new group, call `set` explicitly.\n *\n * @param {string} group - The name of the Crosstalk group, or null (or\n * undefined) to clear the group.\n */\n setGroup(group) {\n // If group is unchanged, do nothing\n if (this._group === group)\n return;\n // Treat null, undefined, and other falsy values the same\n if (!this._group && !group)\n return;\n\n if (this._var) {\n this._var.off(\"change\", this._varOnChangeSub);\n this._var = null;\n this._varOnChangeSub = null;\n }\n\n this._group = group;\n\n if (group) {\n this._var = grp(group).var(\"selection\");\n let sub = this._var.on(\"change\", (e) => {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Retrieves the current selection for the group represented by this\n * `SelectionHandle`.\n *\n * - If no selection is active, then this value will be falsy.\n * - If a selection is active, but no data points are selected, then this\n * value will be an empty array.\n * - If a selection is active, and data points are selected, then the keys\n * of the selected data points will be present in the array.\n */\n get value() {\n return this._var ? this._var.get() : null;\n }\n\n /**\n * Combines the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n // Important incidental effect: shallow clone is returned\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see\n * {@link SelectionHandle#value}).\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `SelectionHandle` constructor).\n */\n set(selectedKeys, extraInfo) {\n if (this._var)\n this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any that were passed\n * into the `SelectionHandle` constructor).\n */\n clear(extraInfo) {\n if (this._var)\n this.set(void 0, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Subscribes to events on this `SelectionHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {SelectionHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancels event subscriptions created by {@link SelectionHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|SelectionHandle~listener} listener - Either the callback\n * function previously passed into {@link SelectionHandle#on}, or the\n * string that was returned from {@link SelectionHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n /**\n * Shuts down the `SelectionHandle` object.\n *\n * Removes all event listeners that were added through this handle.\n */\n close() {\n this._emitter.removeAllListeners();\n this.setGroup(null);\n }\n}\n\n/**\n * @callback SelectionHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the selection, or `undefined` if no selection is active),\n * `oldValue` (the previous value of the selection), and `sender` (the\n * `SelectionHandle` instance that made the change).\n */\n\n/**\n * @event SelectionHandle#change\n * @type {object}\n * @property {object} value - The new value of the selection, or `undefined`\n * if no selection is active.\n * @property {object} oldValue - The previous value of the selection.\n * @property {SelectionHandle} sender - The `SelectionHandle` instance that\n * changed the value.\n */\n", + "export function extend(target, ...sources) {\n for (let i = 0; i < sources.length; i++) {\n let src = sources[i];\n if (typeof(src) === \"undefined\" || src === null)\n continue;\n\n for (let key in src) {\n if (src.hasOwnProperty(key)) {\n target[key] = src[key];\n }\n }\n }\n return target;\n}\n\nexport function checkSorted(list) {\n for (let i = 1; i < list.length; i++) {\n if (list[i] <= list[i-1]) {\n throw new Error(\"List is not sorted or contains duplicate\");\n }\n }\n}\n\nexport function diffSortedLists(a, b) {\n let i_a = 0;\n let i_b = 0;\n\n if (!a) a = [];\n if (!b) b = [];\n\n let a_only = [];\n let b_only = [];\n\n checkSorted(a);\n checkSorted(b);\n\n while (i_a < a.length && i_b < b.length) {\n if (a[i_a] === b[i_b]) {\n i_a++;\n i_b++;\n } else if (a[i_a] < b[i_b]) {\n a_only.push(a[i_a++]);\n } else {\n b_only.push(b[i_b++]);\n }\n }\n\n if (i_a < a.length)\n a_only = a_only.concat(a.slice(i_a));\n if (i_b < b.length)\n b_only = b_only.concat(b.slice(i_b));\n return {\n removed: a_only,\n added: b_only\n };\n}\n\n// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... }\n// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ]\nexport function dataframeToD3(df) {\n let names = [];\n let length;\n for (let name in df) {\n if (df.hasOwnProperty(name))\n names.push(name);\n if (typeof(df[name]) !== \"object\" || typeof(df[name].length) === \"undefined\") {\n throw new Error(\"All fields must be arrays\");\n } else if (typeof(length) !== \"undefined\" && length !== df[name].length) {\n throw new Error(\"All fields must be arrays of the same length\");\n }\n length = df[name].length;\n }\n let results = [];\n let item;\n for (let row = 0; row < length; row++) {\n item = {};\n for (let col = 0; col < names.length; col++) {\n item[names[col]] = df[names[col]][row];\n }\n results.push(item);\n }\n return results;\n}\n\n/**\n * Keeps track of all event listener additions/removals and lets all active\n * listeners be removed with a single operation.\n *\n * @private\n */\nexport class SubscriptionTracker {\n constructor(emitter) {\n this._emitter = emitter;\n this._subs = {};\n }\n\n on(eventType, listener) {\n let sub = this._emitter.on(eventType, listener);\n this._subs[sub] = eventType;\n return sub;\n }\n\n off(eventType, listener) {\n let sub = this._emitter.off(eventType, listener);\n if (sub) {\n delete this._subs[sub];\n }\n return sub;\n }\n\n removeAllListeners() {\n let current_subs = this._subs;\n this._subs = {};\n Object.keys(current_subs).forEach((sub) => {\n this._emitter.off(current_subs[sub], sub);\n });\n }\n}\n", + "import Events from \"./events\";\n\nexport default class Var {\n constructor(group, name, /*optional*/ value) {\n this._group = group;\n this._name = name;\n this._value = value;\n this._events = new Events();\n }\n\n get() {\n return this._value;\n }\n\n set(value, /*optional*/ event) {\n if (this._value === value) {\n // Do nothing; the value hasn't changed\n return;\n }\n let oldValue = this._value;\n this._value = value;\n // Alert JavaScript listeners that the value has changed\n let evt = {};\n if (event && typeof(event) === \"object\") {\n for (let k in event) {\n if (event.hasOwnProperty(k))\n evt[k] = event[k];\n }\n }\n evt.oldValue = oldValue;\n evt.value = value;\n this._events.trigger(\"change\", evt, this);\n\n // TODO: Make this extensible, to let arbitrary back-ends know that\n // something has changed\n if (global.Shiny && global.Shiny.onInputChange) {\n global.Shiny.onInputChange(\n \".clientValue-\" +\n (this._group.name !== null ? this._group.name + \"-\" : \"\") +\n this._name,\n typeof(value) === \"undefined\" ? null : value\n );\n }\n }\n\n on(eventType, listener) {\n return this._events.on(eventType, listener);\n }\n\n off(eventType, listener) {\n return this._events.off(eventType, listener);\n }\n}\n" + ] } \ No newline at end of file diff --git a/docs/site_libs/crosstalk-1.2.2/js/crosstalk.min.js b/docs/site_libs/crosstalk-1.2.2/js/crosstalk.min.js index b7ec0ac..b5caff2 100644 --- a/docs/site_libs/crosstalk-1.2.2/js/crosstalk.min.js +++ b/docs/site_libs/crosstalk-1.2.2/js/crosstalk.min.js @@ -1,2 +1,2 @@ -!function o(u,a,l){function s(n,e){if(!a[n]){if(!u[n]){var t="function"==typeof require&&require;if(!e&&t)return t(n,!0);if(f)return f(n,!0);var r=new Error("Cannot find module '"+n+"'");throw r.code="MODULE_NOT_FOUND",r}var i=a[n]={exports:{}};u[n][0].call(i.exports,function(e){var t=u[n][1][e];return s(t||e)},i,i.exports,o,u,a,l)}return a[n].exports}for(var f="function"==typeof require&&require,e=0;e?@[\\\]^`{|}~])/g,"\\$1")+"']"),r=JSON.parse(n[0].innerText),i=e.factory(t,r);o(t).data("crosstalk-instance",i),o(t).addClass("crosstalk-input-bound")}if(t.Shiny){var e=new t.Shiny.InputBinding,u=t.jQuery;u.extend(e,{find:function(e){return u(e).find(".crosstalk-input")},initialize:function(e){var t,n;u(e).hasClass("crosstalk-input-bound")||(n=o(t=e),Object.keys(r).forEach(function(e){n.hasClass(e)&&!n.hasClass("crosstalk-input-bound")&&i(r[e],t)}))},getId:function(e){return 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t.default=e,t}var f=e.jQuery;t.register({className:"crosstalk-input-select",factory:function(e,n){var t=l.dataframeToD3(n.items),r={options:[{value:"",label:"(All)"}].concat(t),valueField:"value",labelField:"label",searchField:"label"},i=f(e).find("select")[0],o=f(i).selectize(r)[0].selectize,u=new s.FilterHandle(n.group),a=void 0;return o.on("change",function(){if(0===o.items.length)a=null,u.clear();else{var t={};o.items.forEach(function(e){n.map[e].forEach(function(e){t[e]=!0})});var e=Object.keys(t);e.sort(),a=e,u.set(e)}}),{suspend:function(){u.clear()},resume:function(){a&&u.set(a)}}}})}).call(this,"undefined"!=typeof global?global:"undefined"!=typeof self?self:"undefined"!=typeof window?window:{})},{"./filter":2,"./input":6,"./util":11}],9:[function(n,e,t){(function(e){"use strict";var d=function(e,t){if(Array.isArray(e))return e;if(Symbol.iterator in Object(e))return function(e,t){var n=[],r=!0,i=!1,o=void 0;try{for(var 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look reasonable without Bootstrap */ -.crosstalk-input { - margin-bottom: 15px; /* a la .form-group */ - .control-label { - margin-bottom: 0; - vertical-align: middle; - } - input[type="checkbox"] { - margin: 4px 0 0; - margin-top: 1px; - line-height: normal; - } - .checkbox { - position: relative; - display: block; - margin-top: 10px; - margin-bottom: 10px; - } - .checkbox > label{ - padding-left: 20px; - margin-bottom: 0; - font-weight: 400; - cursor: pointer; - } - .checkbox input[type="checkbox"], - .checkbox-inline input[type="checkbox"] { - position: absolute; - margin-top: 2px; - margin-left: -20px; - } - .checkbox + .checkbox { - margin-top: -5px; - } - .checkbox-inline { - position: relative; - display: inline-block; - padding-left: 20px; - margin-bottom: 0; - font-weight: 400; - vertical-align: middle; - cursor: pointer; - } - .checkbox-inline + .checkbox-inline { - margin-top: 0; - margin-left: 10px; - } -} +/* Adjust margins outwards, so column contents line up with the edges of the + parent of container-fluid. */ +.container-fluid.crosstalk-bscols { + margin-left: -30px; + margin-right: -30px; + white-space: normal; +} + +/* But don't adjust the margins outwards if we're directly under the body, + i.e. we were the top-level of something at the console. */ +body > .container-fluid.crosstalk-bscols { + margin-left: auto; + margin-right: auto; +} + +.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column { + display: inline-block; + padding-right: 12px; + vertical-align: top; +} + +@media only screen and (max-width:480px) { + .crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column { + display: block; + padding-right: inherit; + } +} + +/* Relevant BS3 styles to make filter_checkbox() look reasonable without Bootstrap */ +.crosstalk-input { + margin-bottom: 15px; /* a la .form-group */ + .control-label { + margin-bottom: 0; + vertical-align: middle; + } + input[type="checkbox"] { + margin: 4px 0 0; + margin-top: 1px; + line-height: normal; + } + .checkbox { + position: relative; + display: block; + margin-top: 10px; + margin-bottom: 10px; + } + .checkbox > label{ + padding-left: 20px; + margin-bottom: 0; + font-weight: 400; + cursor: pointer; + } + .checkbox input[type="checkbox"], + .checkbox-inline input[type="checkbox"] { + position: absolute; + margin-top: 2px; + margin-left: -20px; + } + .checkbox + .checkbox { + margin-top: -5px; + } + .checkbox-inline { + position: relative; + display: inline-block; + padding-left: 20px; + margin-bottom: 0; + font-weight: 400; + vertical-align: middle; + cursor: pointer; + } + .checkbox-inline + .checkbox-inline { + margin-top: 0; + margin-left: 10px; + } +} diff --git a/docs/site_libs/htmltools-fill-0.5.9/fill.css b/docs/site_libs/htmltools-fill-0.5.9/fill.css index 841ea9d..6a688e0 100644 --- a/docs/site_libs/htmltools-fill-0.5.9/fill.css +++ b/docs/site_libs/htmltools-fill-0.5.9/fill.css @@ -1,21 +1,21 @@ -@layer htmltools { - .html-fill-container { - display: flex; - flex-direction: column; - /* Prevent the container from expanding vertically or horizontally beyond its - parent's constraints. */ - min-height: 0; - min-width: 0; - } - .html-fill-container > .html-fill-item { - /* Fill items can grow and shrink freely within - available vertical space in fillable container */ - flex: 1 1 auto; - min-height: 0; - min-width: 0; - } - .html-fill-container > :not(.html-fill-item) { - /* Prevent shrinking or growing of non-fill items */ - flex: 0 0 auto; - } -} +@layer htmltools { + .html-fill-container { + display: flex; + flex-direction: column; + /* Prevent the container from expanding vertically or horizontally beyond its + parent's constraints. */ + min-height: 0; + min-width: 0; + } + .html-fill-container > .html-fill-item { + /* Fill items can grow and shrink freely within + available vertical space in fillable container */ + flex: 1 1 auto; + min-height: 0; + min-width: 0; + } + .html-fill-container > :not(.html-fill-item) { + /* Prevent shrinking or growing of non-fill items */ + flex: 0 0 auto; + } +} diff --git a/docs/site_libs/htmlwidgets-1.6.4/htmlwidgets.js b/docs/site_libs/htmlwidgets-1.6.4/htmlwidgets.js index 1067d02..b0dd358 100644 --- a/docs/site_libs/htmlwidgets-1.6.4/htmlwidgets.js +++ b/docs/site_libs/htmlwidgets-1.6.4/htmlwidgets.js @@ -1,901 +1,901 @@ -(function() { - // If window.HTMLWidgets is already defined, then use it; otherwise create a - // new object. This allows preceding code to set options that affect the - // initialization process (though none currently exist). - window.HTMLWidgets = window.HTMLWidgets || {}; - - // See if we're running in a viewer pane. If not, we're in a web browser. - var viewerMode = window.HTMLWidgets.viewerMode = - /\bviewer_pane=1\b/.test(window.location); - - // See if we're running in Shiny mode. If not, it's a static document. - // Note that static widgets can appear in both Shiny and static modes, but - // obviously, Shiny widgets can only appear in Shiny apps/documents. - var shinyMode = window.HTMLWidgets.shinyMode = - typeof(window.Shiny) !== "undefined" && !!window.Shiny.outputBindings; - - // We can't count on jQuery being available, so we implement our own - // version if necessary. - function querySelectorAll(scope, selector) { - if (typeof(jQuery) !== "undefined" && scope instanceof jQuery) { - return scope.find(selector); - } - if (scope.querySelectorAll) { - return scope.querySelectorAll(selector); - } - } - - function asArray(value) { - if (value === null) - return []; - if ($.isArray(value)) - return value; - return [value]; - } - - // Implement jQuery's extend - function extend(target /*, ... */) { - if (arguments.length == 1) { - return target; - } - for (var i = 1; i < arguments.length; i++) { - var source = arguments[i]; - for (var prop in source) { - if (source.hasOwnProperty(prop)) { - target[prop] = source[prop]; - } - } - } - return target; - } - - // IE8 doesn't support Array.forEach. - function forEach(values, callback, thisArg) { - if (values.forEach) { - values.forEach(callback, thisArg); - } else { - for (var i = 0; i < values.length; i++) { - callback.call(thisArg, values[i], i, values); - } - } - } - - // Replaces the specified method with the return value of funcSource. - // - // Note that funcSource should not BE the new method, it should be a function - // that RETURNS the new method. funcSource receives a single argument that is - // the overridden method, it can be called from the new method. The overridden - // method can be called like a regular function, it has the target permanently - // bound to it so "this" will work correctly. - function overrideMethod(target, methodName, funcSource) { - var superFunc = target[methodName] || function() {}; - var superFuncBound = function() { - return superFunc.apply(target, arguments); - }; - target[methodName] = funcSource(superFuncBound); - } - - // Add a method to delegator that, when invoked, calls - // delegatee.methodName. If there is no such method on - // the delegatee, but there was one on delegator before - // delegateMethod was called, then the original version - // is invoked instead. - // For example: - // - // var a = { - // method1: function() { console.log('a1'); } - // method2: function() { console.log('a2'); } - // }; - // var b = { - // method1: function() { console.log('b1'); } - // }; - // delegateMethod(a, b, "method1"); - // delegateMethod(a, b, "method2"); - // a.method1(); - // a.method2(); - // - // The output would be "b1", "a2". - function delegateMethod(delegator, delegatee, methodName) { - var inherited = delegator[methodName]; - delegator[methodName] = function() { - var target = delegatee; - var method = delegatee[methodName]; - - // The method doesn't exist on the delegatee. Instead, - // call the method on the delegator, if it exists. - if (!method) { - target = delegator; - method = inherited; - } - - if (method) { - return method.apply(target, arguments); - } - }; - } - - // Implement a vague facsimilie of jQuery's data method - function elementData(el, name, value) { - if (arguments.length == 2) { - return el["htmlwidget_data_" + name]; - } else if (arguments.length == 3) { - el["htmlwidget_data_" + name] = value; - return el; - } else { - throw new Error("Wrong number of arguments for elementData: " + - arguments.length); - } - } - - // http://stackoverflow.com/questions/3446170/escape-string-for-use-in-javascript-regex - function escapeRegExp(str) { - return str.replace(/[\-\[\]\/\{\}\(\)\*\+\?\.\\\^\$\|]/g, "\\$&"); - } - - function hasClass(el, className) { - var re = new RegExp("\\b" + escapeRegExp(className) + "\\b"); - return re.test(el.className); - } - - // elements - array (or array-like object) of HTML elements - // className - class name to test for - // include - if true, only return elements with given className; - // if false, only return elements *without* given className - function filterByClass(elements, className, include) { - var results = []; - for (var i = 0; i < elements.length; i++) { - if (hasClass(elements[i], className) == include) - results.push(elements[i]); - } - return results; - } - - function on(obj, eventName, func) { - if (obj.addEventListener) { - obj.addEventListener(eventName, func, false); - } else if (obj.attachEvent) { - obj.attachEvent(eventName, func); - } - } - - function off(obj, eventName, func) { - if (obj.removeEventListener) - obj.removeEventListener(eventName, func, false); - else if (obj.detachEvent) { - obj.detachEvent(eventName, func); - } - } - - // Translate array of values to top/right/bottom/left, as usual with - // the "padding" CSS property - // https://developer.mozilla.org/en-US/docs/Web/CSS/padding - function unpackPadding(value) { - if (typeof(value) === "number") - value = [value]; - if (value.length === 1) { - return {top: value[0], right: value[0], bottom: value[0], left: value[0]}; - } - if (value.length === 2) { - return {top: value[0], right: value[1], bottom: value[0], left: value[1]}; - } - if (value.length === 3) { - return {top: value[0], right: value[1], bottom: value[2], left: value[1]}; - } - if (value.length === 4) { - return {top: value[0], right: value[1], bottom: value[2], left: value[3]}; - } - } - - // Convert an unpacked padding object to a CSS value - function paddingToCss(paddingObj) { - return paddingObj.top + "px " + paddingObj.right + "px " + paddingObj.bottom + "px " + paddingObj.left + "px"; - } - - // Makes a number suitable for CSS - function px(x) { - if (typeof(x) === "number") - return x + "px"; - else - return x; - } - - // Retrieves runtime widget sizing information for an element. - // The return value is either null, or an object with fill, padding, - // defaultWidth, defaultHeight fields. - function sizingPolicy(el) { - var sizingEl = document.querySelector("script[data-for='" + el.id + "'][type='application/htmlwidget-sizing']"); - if (!sizingEl) - return null; - var sp = JSON.parse(sizingEl.textContent || sizingEl.text || "{}"); - if (viewerMode) { - return sp.viewer; - } else { - return sp.browser; - } - } - - // @param tasks Array of strings (or falsy value, in which case no-op). - // Each element must be a valid JavaScript expression that yields a - // function. Or, can be an array of objects with "code" and "data" - // properties; in this case, the "code" property should be a string - // of JS that's an expr that yields a function, and "data" should be - // an object that will be added as an additional argument when that - // function is called. - // @param target The object that will be "this" for each function - // execution. - // @param args Array of arguments to be passed to the functions. (The - // same arguments will be passed to all functions.) - function evalAndRun(tasks, target, args) { - if (tasks) { - forEach(tasks, function(task) { - var theseArgs = args; - if (typeof(task) === "object") { - theseArgs = theseArgs.concat([task.data]); - task = task.code; - } - var taskFunc = tryEval(task); - if (typeof(taskFunc) !== "function") { - throw new Error("Task must be a function! Source:\n" + task); - } - taskFunc.apply(target, theseArgs); - }); - } - } - - // Attempt eval() both with and without enclosing in parentheses. - // Note that enclosing coerces a function declaration into - // an expression that eval() can parse - // (otherwise, a SyntaxError is thrown) - function tryEval(code) { - var result = null; - try { - result = eval("(" + code + ")"); - } catch(error) { - if (!(error instanceof SyntaxError)) { - throw error; - } - try { - result = eval(code); - } catch(e) { - if (e instanceof SyntaxError) { - throw error; - } else { - throw e; - } - } - } - return result; - } - - function initSizing(el) { - var sizing = sizingPolicy(el); - if (!sizing) - return; - - var cel = document.getElementById("htmlwidget_container"); - if (!cel) - return; - - if (typeof(sizing.padding) !== "undefined") { - document.body.style.margin = "0"; - document.body.style.padding = paddingToCss(unpackPadding(sizing.padding)); - } - - if (sizing.fill) { - document.body.style.overflow = "hidden"; - document.body.style.width = "100%"; - document.body.style.height = "100%"; - document.documentElement.style.width = "100%"; - document.documentElement.style.height = "100%"; - cel.style.position = "absolute"; - var pad = unpackPadding(sizing.padding); - cel.style.top = pad.top + "px"; - cel.style.right = pad.right + "px"; - cel.style.bottom = pad.bottom + "px"; - cel.style.left = pad.left + "px"; - el.style.width = "100%"; - el.style.height = "100%"; - - return { - getWidth: function() { return cel.getBoundingClientRect().width; }, - getHeight: function() { return cel.getBoundingClientRect().height; } - }; - - } else { - el.style.width = px(sizing.width); - el.style.height = px(sizing.height); - - return { - getWidth: function() { return cel.getBoundingClientRect().width; }, - getHeight: function() { return cel.getBoundingClientRect().height; } - }; - } - } - - // Default implementations for methods - var defaults = { - find: function(scope) { - return querySelectorAll(scope, "." + this.name); - }, - renderError: function(el, err) { - var $el = $(el); - - this.clearError(el); - - // Add all these error classes, as Shiny does - var errClass = "shiny-output-error"; - if (err.type !== null) { - // use the classes of the error condition as CSS class names - errClass = errClass + " " + $.map(asArray(err.type), function(type) { - return errClass + "-" + type; - }).join(" "); - } - errClass = errClass + " htmlwidgets-error"; - - // Is el inline or block? If inline or inline-block, just display:none it - // and add an inline error. - var display = $el.css("display"); - $el.data("restore-display-mode", display); - - if (display === "inline" || display === "inline-block") { - $el.hide(); - if (err.message !== "") { - var errorSpan = $("").addClass(errClass); - errorSpan.text(err.message); - $el.after(errorSpan); - } - } else if (display === "block") { - // If block, add an error just after the el, set visibility:none on the - // el, and position the error to be on top of the el. - // Mark it with a unique ID and CSS class so we can remove it later. - $el.css("visibility", "hidden"); - if (err.message !== "") { - var errorDiv = $("
    ").addClass(errClass).css("position", "absolute") - .css("top", el.offsetTop) - .css("left", el.offsetLeft) - // setting width can push out the page size, forcing otherwise - // unnecessary scrollbars to appear and making it impossible for - // the element to shrink; so use max-width instead - .css("maxWidth", el.offsetWidth) - .css("height", el.offsetHeight); - errorDiv.text(err.message); - $el.after(errorDiv); - - // Really dumb way to keep the size/position of the error in sync with - // the parent element as the window is resized or whatever. - var intId = setInterval(function() { - if (!errorDiv[0].parentElement) { - clearInterval(intId); - return; - } - errorDiv - .css("top", el.offsetTop) - .css("left", el.offsetLeft) - .css("maxWidth", el.offsetWidth) - .css("height", el.offsetHeight); - }, 500); - } - } - }, - clearError: function(el) { - var $el = $(el); - var display = $el.data("restore-display-mode"); - $el.data("restore-display-mode", null); - - if (display === "inline" || display === "inline-block") { - if (display) - $el.css("display", display); - $(el.nextSibling).filter(".htmlwidgets-error").remove(); - } else if (display === "block"){ - $el.css("visibility", "inherit"); - $(el.nextSibling).filter(".htmlwidgets-error").remove(); - } - }, - sizing: {} - }; - - // Called by widget bindings to register a new type of widget. The definition - // object can contain the following properties: - // - name (required) - A string indicating the binding name, which will be - // used by default as the CSS classname to look for. - // - initialize (optional) - A function(el) that will be called once per - // widget element; if a value is returned, it will be passed as the third - // value to renderValue. - // - renderValue (required) - A function(el, data, initValue) that will be - // called with data. Static contexts will cause this to be called once per - // element; Shiny apps will cause this to be called multiple times per - // element, as the data changes. - window.HTMLWidgets.widget = function(definition) { - if (!definition.name) { - throw new Error("Widget must have a name"); - } - if (!definition.type) { - throw new Error("Widget must have a type"); - } - // Currently we only support output widgets - if (definition.type !== "output") { - throw new Error("Unrecognized widget type '" + definition.type + "'"); - } - // TODO: Verify that .name is a valid CSS classname - - // Support new-style instance-bound definitions. Old-style class-bound - // definitions have one widget "object" per widget per type/class of - // widget; the renderValue and resize methods on such widget objects - // take el and instance arguments, because the widget object can't - // store them. New-style instance-bound definitions have one widget - // object per widget instance; the definition that's passed in doesn't - // provide renderValue or resize methods at all, just the single method - // factory(el, width, height) - // which returns an object that has renderValue(x) and resize(w, h). - // This enables a far more natural programming style for the widget - // author, who can store per-instance state using either OO-style - // instance fields or functional-style closure variables (I guess this - // is in contrast to what can only be called C-style pseudo-OO which is - // what we required before). - if (definition.factory) { - definition = createLegacyDefinitionAdapter(definition); - } - - if (!definition.renderValue) { - throw new Error("Widget must have a renderValue function"); - } - - // For static rendering (non-Shiny), use a simple widget registration - // scheme. We also use this scheme for Shiny apps/documents that also - // contain static widgets. - window.HTMLWidgets.widgets = window.HTMLWidgets.widgets || []; - // Merge defaults into the definition; don't mutate the original definition. - var staticBinding = extend({}, defaults, definition); - overrideMethod(staticBinding, "find", function(superfunc) { - return function(scope) { - var results = superfunc(scope); - // Filter out Shiny outputs, we only want the static kind - return filterByClass(results, "html-widget-output", false); - }; - }); - window.HTMLWidgets.widgets.push(staticBinding); - - if (shinyMode) { - // Shiny is running. Register the definition with an output binding. - // The definition itself will not be the output binding, instead - // we will make an output binding object that delegates to the - // definition. This is because we foolishly used the same method - // name (renderValue) for htmlwidgets definition and Shiny bindings - // but they actually have quite different semantics (the Shiny - // bindings receive data that includes lots of metadata that it - // strips off before calling htmlwidgets renderValue). We can't - // just ignore the difference because in some widgets it's helpful - // to call this.renderValue() from inside of resize(), and if - // we're not delegating, then that call will go to the Shiny - // version instead of the htmlwidgets version. - - // Merge defaults with definition, without mutating either. - var bindingDef = extend({}, defaults, definition); - - // This object will be our actual Shiny binding. - var shinyBinding = new Shiny.OutputBinding(); - - // With a few exceptions, we'll want to simply use the bindingDef's - // version of methods if they are available, otherwise fall back to - // Shiny's defaults. NOTE: If Shiny's output bindings gain additional - // methods in the future, and we want them to be overrideable by - // HTMLWidget binding definitions, then we'll need to add them to this - // list. - delegateMethod(shinyBinding, bindingDef, "getId"); - delegateMethod(shinyBinding, bindingDef, "onValueChange"); - delegateMethod(shinyBinding, bindingDef, "onValueError"); - delegateMethod(shinyBinding, bindingDef, "renderError"); - delegateMethod(shinyBinding, bindingDef, "clearError"); - delegateMethod(shinyBinding, bindingDef, "showProgress"); - - // The find, renderValue, and resize are handled differently, because we - // want to actually decorate the behavior of the bindingDef methods. - - shinyBinding.find = function(scope) { - var results = bindingDef.find(scope); - - // Only return elements that are Shiny outputs, not static ones - var dynamicResults = results.filter(".html-widget-output"); - - // It's possible that whatever caused Shiny to think there might be - // new dynamic outputs, also caused there to be new static outputs. - // Since there might be lots of different htmlwidgets bindings, we - // schedule execution for later--no need to staticRender multiple - // times. - if (results.length !== dynamicResults.length) - scheduleStaticRender(); - - return dynamicResults; - }; - - // Wrap renderValue to handle initialization, which unfortunately isn't - // supported natively by Shiny at the time of this writing. - - shinyBinding.renderValue = function(el, data) { - Shiny.renderDependencies(data.deps); - // Resolve strings marked as javascript literals to objects - if (!(data.evals instanceof Array)) data.evals = [data.evals]; - for (var i = 0; data.evals && i < data.evals.length; i++) { - window.HTMLWidgets.evaluateStringMember(data.x, data.evals[i]); - } - if (!bindingDef.renderOnNullValue) { - if (data.x === null) { - el.style.visibility = "hidden"; - return; - } else { - el.style.visibility = "inherit"; - } - } - if (!elementData(el, "initialized")) { - initSizing(el); - - elementData(el, "initialized", true); - if (bindingDef.initialize) { - var rect = el.getBoundingClientRect(); - var result = bindingDef.initialize(el, rect.width, rect.height); - elementData(el, "init_result", result); - } - } - bindingDef.renderValue(el, data.x, elementData(el, "init_result")); - evalAndRun(data.jsHooks.render, elementData(el, "init_result"), [el, data.x]); - }; - - // Only override resize if bindingDef implements it - if (bindingDef.resize) { - shinyBinding.resize = function(el, width, height) { - // Shiny can call resize before initialize/renderValue have been - // called, which doesn't make sense for widgets. - if (elementData(el, "initialized")) { - bindingDef.resize(el, width, height, elementData(el, "init_result")); - } - }; - } - - Shiny.outputBindings.register(shinyBinding, bindingDef.name); - } - }; - - var scheduleStaticRenderTimerId = null; - function scheduleStaticRender() { - if (!scheduleStaticRenderTimerId) { - scheduleStaticRenderTimerId = setTimeout(function() { - scheduleStaticRenderTimerId = null; - window.HTMLWidgets.staticRender(); - }, 1); - } - } - - // Render static widgets after the document finishes loading - // Statically render all elements that are of this widget's class - window.HTMLWidgets.staticRender = function() { - var bindings = window.HTMLWidgets.widgets || []; - forEach(bindings, function(binding) { - var matches = binding.find(document.documentElement); - forEach(matches, function(el) { - var sizeObj = initSizing(el, binding); - - var getSize = function(el) { - if (sizeObj) { - return {w: sizeObj.getWidth(), h: sizeObj.getHeight()} - } else { - var rect = el.getBoundingClientRect(); - return {w: rect.width, h: rect.height} - } - }; - - if (hasClass(el, "html-widget-static-bound")) - return; - el.className = el.className + " html-widget-static-bound"; - - var initResult; - if (binding.initialize) { - var size = getSize(el); - initResult = binding.initialize(el, size.w, size.h); - elementData(el, "init_result", initResult); - } - - if (binding.resize) { - var lastSize = getSize(el); - var resizeHandler = function(e) { - var size = getSize(el); - if (size.w === 0 && size.h === 0) - return; - if (size.w === lastSize.w && size.h === lastSize.h) - return; - lastSize = size; - binding.resize(el, size.w, size.h, initResult); - }; - - on(window, "resize", resizeHandler); - - // This is needed for cases where we're running in a Shiny - // app, but the widget itself is not a Shiny output, but - // rather a simple static widget. One example of this is - // an rmarkdown document that has runtime:shiny and widget - // that isn't in a render function. Shiny only knows to - // call resize handlers for Shiny outputs, not for static - // widgets, so we do it ourselves. - if (window.jQuery) { - window.jQuery(document).on( - "shown.htmlwidgets shown.bs.tab.htmlwidgets shown.bs.collapse.htmlwidgets", - resizeHandler - ); - window.jQuery(document).on( - "hidden.htmlwidgets hidden.bs.tab.htmlwidgets hidden.bs.collapse.htmlwidgets", - resizeHandler - ); - } - - // This is needed for the specific case of ioslides, which - // flips slides between display:none and display:block. - // Ideally we would not have to have ioslide-specific code - // here, but rather have ioslides raise a generic event, - // but the rmarkdown package just went to CRAN so the - // window to getting that fixed may be long. - if (window.addEventListener) { - // It's OK to limit this to window.addEventListener - // browsers because ioslides itself only supports - // such browsers. - on(document, "slideenter", resizeHandler); - on(document, "slideleave", resizeHandler); - } - } - - var scriptData = document.querySelector("script[data-for='" + el.id + "'][type='application/json']"); - if (scriptData) { - var data = JSON.parse(scriptData.textContent || scriptData.text); - // Resolve strings marked as javascript literals to objects - if (!(data.evals instanceof Array)) data.evals = [data.evals]; - for (var k = 0; data.evals && k < data.evals.length; k++) { - window.HTMLWidgets.evaluateStringMember(data.x, data.evals[k]); - } - binding.renderValue(el, data.x, initResult); - evalAndRun(data.jsHooks.render, initResult, [el, data.x]); - } - }); - }); - - invokePostRenderHandlers(); - } - - - function has_jQuery3() { - if (!window.jQuery) { - return false; - } - var $version = window.jQuery.fn.jquery; - var $major_version = parseInt($version.split(".")[0]); - return $major_version >= 3; - } - - /* - / Shiny 1.4 bumped jQuery from 1.x to 3.x which means jQuery's - / on-ready handler (i.e., $(fn)) is now asyncronous (i.e., it now - / really means $(setTimeout(fn)). - / https://jquery.com/upgrade-guide/3.0/#breaking-change-document-ready-handlers-are-now-asynchronous - / - / Since Shiny uses $() to schedule initShiny, shiny>=1.4 calls initShiny - / one tick later than it did before, which means staticRender() is - / called renderValue() earlier than (advanced) widget authors might be expecting. - / https://github.com/rstudio/shiny/issues/2630 - / - / For a concrete example, leaflet has some methods (e.g., updateBounds) - / which reference Shiny methods registered in initShiny (e.g., setInputValue). - / Since leaflet is privy to this life-cycle, it knows to use setTimeout() to - / delay execution of those methods (until Shiny methods are ready) - / https://github.com/rstudio/leaflet/blob/18ec981/javascript/src/index.js#L266-L268 - / - / Ideally widget authors wouldn't need to use this setTimeout() hack that - / leaflet uses to call Shiny methods on a staticRender(). In the long run, - / the logic initShiny should be broken up so that method registration happens - / right away, but binding happens later. - */ - function maybeStaticRenderLater() { - if (shinyMode && has_jQuery3()) { - window.jQuery(window.HTMLWidgets.staticRender); - } else { - window.HTMLWidgets.staticRender(); - } - } - - if (document.addEventListener) { - document.addEventListener("DOMContentLoaded", function() { - document.removeEventListener("DOMContentLoaded", arguments.callee, false); - maybeStaticRenderLater(); - }, false); - } else if (document.attachEvent) { - document.attachEvent("onreadystatechange", function() { - if (document.readyState === "complete") { - document.detachEvent("onreadystatechange", arguments.callee); - maybeStaticRenderLater(); - } - }); - } - - - window.HTMLWidgets.getAttachmentUrl = function(depname, key) { - // If no key, default to the first item - if (typeof(key) === "undefined") - key = 1; - - var link = document.getElementById(depname + "-" + key + "-attachment"); - if (!link) { - throw new Error("Attachment " + depname + "/" + key + " not found in document"); - } - return link.getAttribute("href"); - }; - - window.HTMLWidgets.dataframeToD3 = function(df) { - var names = []; - var length; - for (var name in df) { - if (df.hasOwnProperty(name)) - names.push(name); - if (typeof(df[name]) !== "object" || typeof(df[name].length) === "undefined") { - throw new Error("All fields must be arrays"); - } else if (typeof(length) !== "undefined" && length !== df[name].length) { - throw new Error("All fields must be arrays of the same length"); - } - length = df[name].length; - } - var results = []; - var item; - for (var row = 0; row < length; row++) { - item = {}; - for (var col = 0; col < names.length; col++) { - item[names[col]] = df[names[col]][row]; - } - results.push(item); - } - return results; - }; - - window.HTMLWidgets.transposeArray2D = function(array) { - if (array.length === 0) return array; - var newArray = array[0].map(function(col, i) { - return array.map(function(row) { - return row[i] - }) - }); - return newArray; - }; - // Split value at splitChar, but allow splitChar to be escaped - // using escapeChar. Any other characters escaped by escapeChar - // will be included as usual (including escapeChar itself). - function splitWithEscape(value, splitChar, escapeChar) { - var results = []; - var escapeMode = false; - var currentResult = ""; - for (var pos = 0; pos < value.length; pos++) { - if (!escapeMode) { - if (value[pos] === splitChar) { - results.push(currentResult); - currentResult = ""; - } else if (value[pos] === escapeChar) { - escapeMode = true; - } else { - currentResult += value[pos]; - } - } else { - currentResult += value[pos]; - escapeMode = false; - } - } - if (currentResult !== "") { - results.push(currentResult); - } - return results; - } - // Function authored by Yihui/JJ Allaire - window.HTMLWidgets.evaluateStringMember = function(o, member) { - var parts = splitWithEscape(member, '.', '\\'); - for (var i = 0, l = parts.length; i < l; i++) { - var part = parts[i]; - // part may be a character or 'numeric' member name - if (o !== null && typeof o === "object" && part in o) { - if (i == (l - 1)) { // if we are at the end of the line then evalulate - if (typeof o[part] === "string") - o[part] = tryEval(o[part]); - } else { // otherwise continue to next embedded object - o = o[part]; - } - } - } - }; - - // Retrieve the HTMLWidget instance (i.e. the return value of an - // HTMLWidget binding's initialize() or factory() function) - // associated with an element, or null if none. - window.HTMLWidgets.getInstance = function(el) { - return elementData(el, "init_result"); - }; - - // Finds the first element in the scope that matches the selector, - // and returns the HTMLWidget instance (i.e. the return value of - // an HTMLWidget binding's initialize() or factory() function) - // associated with that element, if any. If no element matches the - // selector, or the first matching element has no HTMLWidget - // instance associated with it, then null is returned. - // - // The scope argument is optional, and defaults to window.document. - window.HTMLWidgets.find = function(scope, selector) { - if (arguments.length == 1) { - selector = scope; - scope = document; - } - - var el = scope.querySelector(selector); - if (el === null) { - return null; - } else { - return window.HTMLWidgets.getInstance(el); - } - }; - - // Finds all elements in the scope that match the selector, and - // returns the HTMLWidget instances (i.e. the return values of - // an HTMLWidget binding's initialize() or factory() function) - // associated with the elements, in an array. If elements that - // match the selector don't have an associated HTMLWidget - // instance, the returned array will contain nulls. - // - // The scope argument is optional, and defaults to window.document. - window.HTMLWidgets.findAll = function(scope, selector) { - if (arguments.length == 1) { - selector = scope; - scope = document; - } - - var nodes = scope.querySelectorAll(selector); - var results = []; - for (var i = 0; i < nodes.length; i++) { - results.push(window.HTMLWidgets.getInstance(nodes[i])); - } - return results; - }; - - var postRenderHandlers = []; - function invokePostRenderHandlers() { - while (postRenderHandlers.length) { - var handler = postRenderHandlers.shift(); - if (handler) { - handler(); - } - } - } - - // Register the given callback function to be invoked after the - // next time static widgets are rendered. - window.HTMLWidgets.addPostRenderHandler = function(callback) { - postRenderHandlers.push(callback); - }; - - // Takes a new-style instance-bound definition, and returns an - // old-style class-bound definition. This saves us from having - // to rewrite all the logic in this file to accomodate both - // types of definitions. - function createLegacyDefinitionAdapter(defn) { - var result = { - name: defn.name, - type: defn.type, - initialize: function(el, width, height) { - return defn.factory(el, width, height); - }, - renderValue: function(el, x, instance) { - return instance.renderValue(x); - }, - resize: function(el, width, height, instance) { - return instance.resize(width, height); - } - }; - - if (defn.find) - result.find = defn.find; - if (defn.renderError) - result.renderError = defn.renderError; - if (defn.clearError) - result.clearError = defn.clearError; - - return result; - } -})(); +(function() { + // If window.HTMLWidgets is already defined, then use it; otherwise create a + // new object. This allows preceding code to set options that affect the + // initialization process (though none currently exist). + window.HTMLWidgets = window.HTMLWidgets || {}; + + // See if we're running in a viewer pane. If not, we're in a web browser. + var viewerMode = window.HTMLWidgets.viewerMode = + /\bviewer_pane=1\b/.test(window.location); + + // See if we're running in Shiny mode. If not, it's a static document. + // Note that static widgets can appear in both Shiny and static modes, but + // obviously, Shiny widgets can only appear in Shiny apps/documents. + var shinyMode = window.HTMLWidgets.shinyMode = + typeof(window.Shiny) !== "undefined" && !!window.Shiny.outputBindings; + + // We can't count on jQuery being available, so we implement our own + // version if necessary. + function querySelectorAll(scope, selector) { + if (typeof(jQuery) !== "undefined" && scope instanceof jQuery) { + return scope.find(selector); + } + if (scope.querySelectorAll) { + return scope.querySelectorAll(selector); + } + } + + function asArray(value) { + if (value === null) + return []; + if ($.isArray(value)) + return value; + return [value]; + } + + // Implement jQuery's extend + function extend(target /*, ... */) { + if (arguments.length == 1) { + return target; + } + for (var i = 1; i < arguments.length; i++) { + var source = arguments[i]; + for (var prop in source) { + if (source.hasOwnProperty(prop)) { + target[prop] = source[prop]; + } + } + } + return target; + } + + // IE8 doesn't support Array.forEach. + function forEach(values, callback, thisArg) { + if (values.forEach) { + values.forEach(callback, thisArg); + } else { + for (var i = 0; i < values.length; i++) { + callback.call(thisArg, values[i], i, values); + } + } + } + + // Replaces the specified method with the return value of funcSource. + // + // Note that funcSource should not BE the new method, it should be a function + // that RETURNS the new method. funcSource receives a single argument that is + // the overridden method, it can be called from the new method. The overridden + // method can be called like a regular function, it has the target permanently + // bound to it so "this" will work correctly. + function overrideMethod(target, methodName, funcSource) { + var superFunc = target[methodName] || function() {}; + var superFuncBound = function() { + return superFunc.apply(target, arguments); + }; + target[methodName] = funcSource(superFuncBound); + } + + // Add a method to delegator that, when invoked, calls + // delegatee.methodName. If there is no such method on + // the delegatee, but there was one on delegator before + // delegateMethod was called, then the original version + // is invoked instead. + // For example: + // + // var a = { + // method1: function() { console.log('a1'); } + // method2: function() { console.log('a2'); } + // }; + // var b = { + // method1: function() { console.log('b1'); } + // }; + // delegateMethod(a, b, "method1"); + // delegateMethod(a, b, "method2"); + // a.method1(); + // a.method2(); + // + // The output would be "b1", "a2". + function delegateMethod(delegator, delegatee, methodName) { + var inherited = delegator[methodName]; + delegator[methodName] = function() { + var target = delegatee; + var method = delegatee[methodName]; + + // The method doesn't exist on the delegatee. Instead, + // call the method on the delegator, if it exists. + if (!method) { + target = delegator; + method = inherited; + } + + if (method) { + return method.apply(target, arguments); + } + }; + } + + // Implement a vague facsimilie of jQuery's data method + function elementData(el, name, value) { + if (arguments.length == 2) { + return el["htmlwidget_data_" + name]; + } else if (arguments.length == 3) { + el["htmlwidget_data_" + name] = value; + return el; + } else { + throw new Error("Wrong number of arguments for elementData: " + + arguments.length); + } + } + + // http://stackoverflow.com/questions/3446170/escape-string-for-use-in-javascript-regex + function escapeRegExp(str) { + return str.replace(/[\-\[\]\/\{\}\(\)\*\+\?\.\\\^\$\|]/g, "\\$&"); + } + + function hasClass(el, className) { + var re = new RegExp("\\b" + escapeRegExp(className) + "\\b"); + return re.test(el.className); + } + + // elements - array (or array-like object) of HTML elements + // className - class name to test for + // include - if true, only return elements with given className; + // if false, only return elements *without* given className + function filterByClass(elements, className, include) { + var results = []; + for (var i = 0; i < elements.length; i++) { + if (hasClass(elements[i], className) == include) + results.push(elements[i]); + } + return results; + } + + function on(obj, eventName, func) { + if (obj.addEventListener) { + obj.addEventListener(eventName, func, false); + } else if (obj.attachEvent) { + obj.attachEvent(eventName, func); + } + } + + function off(obj, eventName, func) { + if (obj.removeEventListener) + obj.removeEventListener(eventName, func, false); + else if (obj.detachEvent) { + obj.detachEvent(eventName, func); + } + } + + // Translate array of values to top/right/bottom/left, as usual with + // the "padding" CSS property + // https://developer.mozilla.org/en-US/docs/Web/CSS/padding + function unpackPadding(value) { + if (typeof(value) === "number") + value = [value]; + if (value.length === 1) { + return {top: value[0], right: value[0], bottom: value[0], left: value[0]}; + } + if (value.length === 2) { + return {top: value[0], right: value[1], bottom: value[0], left: value[1]}; + } + if (value.length === 3) { + return {top: value[0], right: value[1], bottom: value[2], left: value[1]}; + } + if (value.length === 4) { + return {top: value[0], right: value[1], bottom: value[2], left: value[3]}; + } + } + + // Convert an unpacked padding object to a CSS value + function paddingToCss(paddingObj) { + return paddingObj.top + "px " + paddingObj.right + "px " + paddingObj.bottom + "px " + paddingObj.left + "px"; + } + + // Makes a number suitable for CSS + function px(x) { + if (typeof(x) === "number") + return x + "px"; + else + return x; + } + + // Retrieves runtime widget sizing information for an element. + // The return value is either null, or an object with fill, padding, + // defaultWidth, defaultHeight fields. + function sizingPolicy(el) { + var sizingEl = document.querySelector("script[data-for='" + el.id + "'][type='application/htmlwidget-sizing']"); + if (!sizingEl) + return null; + var sp = JSON.parse(sizingEl.textContent || sizingEl.text || "{}"); + if (viewerMode) { + return sp.viewer; + } else { + return sp.browser; + } + } + + // @param tasks Array of strings (or falsy value, in which case no-op). + // Each element must be a valid JavaScript expression that yields a + // function. Or, can be an array of objects with "code" and "data" + // properties; in this case, the "code" property should be a string + // of JS that's an expr that yields a function, and "data" should be + // an object that will be added as an additional argument when that + // function is called. + // @param target The object that will be "this" for each function + // execution. + // @param args Array of arguments to be passed to the functions. (The + // same arguments will be passed to all functions.) + function evalAndRun(tasks, target, args) { + if (tasks) { + forEach(tasks, function(task) { + var theseArgs = args; + if (typeof(task) === "object") { + theseArgs = theseArgs.concat([task.data]); + task = task.code; + } + var taskFunc = tryEval(task); + if (typeof(taskFunc) !== "function") { + throw new Error("Task must be a function! Source:\n" + task); + } + taskFunc.apply(target, theseArgs); + }); + } + } + + // Attempt eval() both with and without enclosing in parentheses. + // Note that enclosing coerces a function declaration into + // an expression that eval() can parse + // (otherwise, a SyntaxError is thrown) + function tryEval(code) { + var result = null; + try { + result = eval("(" + code + ")"); + } catch(error) { + if (!(error instanceof SyntaxError)) { + throw error; + } + try { + result = eval(code); + } catch(e) { + if (e instanceof SyntaxError) { + throw error; + } else { + throw e; + } + } + } + return result; + } + + function initSizing(el) { + var sizing = sizingPolicy(el); + if (!sizing) + return; + + var cel = document.getElementById("htmlwidget_container"); + if (!cel) + return; + + if (typeof(sizing.padding) !== "undefined") { + document.body.style.margin = "0"; + document.body.style.padding = paddingToCss(unpackPadding(sizing.padding)); + } + + if (sizing.fill) { + document.body.style.overflow = "hidden"; + document.body.style.width = "100%"; + document.body.style.height = "100%"; + document.documentElement.style.width = "100%"; + document.documentElement.style.height = "100%"; + cel.style.position = "absolute"; + var pad = unpackPadding(sizing.padding); + cel.style.top = pad.top + "px"; + cel.style.right = pad.right + "px"; + cel.style.bottom = pad.bottom + "px"; + cel.style.left = pad.left + "px"; + el.style.width = "100%"; + el.style.height = "100%"; + + return { + getWidth: function() { return cel.getBoundingClientRect().width; }, + getHeight: function() { return cel.getBoundingClientRect().height; } + }; + + } else { + el.style.width = px(sizing.width); + el.style.height = px(sizing.height); + + return { + getWidth: function() { return cel.getBoundingClientRect().width; }, + getHeight: function() { return cel.getBoundingClientRect().height; } + }; + } + } + + // Default implementations for methods + var defaults = { + find: function(scope) { + return querySelectorAll(scope, "." + this.name); + }, + renderError: function(el, err) { + var $el = $(el); + + this.clearError(el); + + // Add all these error classes, as Shiny does + var errClass = "shiny-output-error"; + if (err.type !== null) { + // use the classes of the error condition as CSS class names + errClass = errClass + " " + $.map(asArray(err.type), function(type) { + return errClass + "-" + type; + }).join(" "); + } + errClass = errClass + " htmlwidgets-error"; + + // Is el inline or block? If inline or inline-block, just display:none it + // and add an inline error. + var display = $el.css("display"); + $el.data("restore-display-mode", display); + + if (display === "inline" || display === "inline-block") { + $el.hide(); + if (err.message !== "") { + var errorSpan = $("").addClass(errClass); + errorSpan.text(err.message); + $el.after(errorSpan); + } + } else if (display === "block") { + // If block, add an error just after the el, set visibility:none on the + // el, and position the error to be on top of the el. + // Mark it with a unique ID and CSS class so we can remove it later. + $el.css("visibility", "hidden"); + if (err.message !== "") { + var errorDiv = $("
    ").addClass(errClass).css("position", "absolute") + .css("top", el.offsetTop) + .css("left", el.offsetLeft) + // setting width can push out the page size, forcing otherwise + // unnecessary scrollbars to appear and making it impossible for + // the element to shrink; so use max-width instead + .css("maxWidth", el.offsetWidth) + .css("height", el.offsetHeight); + errorDiv.text(err.message); + $el.after(errorDiv); + + // Really dumb way to keep the size/position of the error in sync with + // the parent element as the window is resized or whatever. + var intId = setInterval(function() { + if (!errorDiv[0].parentElement) { + clearInterval(intId); + return; + } + errorDiv + .css("top", el.offsetTop) + .css("left", el.offsetLeft) + .css("maxWidth", el.offsetWidth) + .css("height", el.offsetHeight); + }, 500); + } + } + }, + clearError: function(el) { + var $el = $(el); + var display = $el.data("restore-display-mode"); + $el.data("restore-display-mode", null); + + if (display === "inline" || display === "inline-block") { + if (display) + $el.css("display", display); + $(el.nextSibling).filter(".htmlwidgets-error").remove(); + } else if (display === "block"){ + $el.css("visibility", "inherit"); + $(el.nextSibling).filter(".htmlwidgets-error").remove(); + } + }, + sizing: {} + }; + + // Called by widget bindings to register a new type of widget. The definition + // object can contain the following properties: + // - name (required) - A string indicating the binding name, which will be + // used by default as the CSS classname to look for. + // - initialize (optional) - A function(el) that will be called once per + // widget element; if a value is returned, it will be passed as the third + // value to renderValue. + // - renderValue (required) - A function(el, data, initValue) that will be + // called with data. Static contexts will cause this to be called once per + // element; Shiny apps will cause this to be called multiple times per + // element, as the data changes. + window.HTMLWidgets.widget = function(definition) { + if (!definition.name) { + throw new Error("Widget must have a name"); + } + if (!definition.type) { + throw new Error("Widget must have a type"); + } + // Currently we only support output widgets + if (definition.type !== "output") { + throw new Error("Unrecognized widget type '" + definition.type + "'"); + } + // TODO: Verify that .name is a valid CSS classname + + // Support new-style instance-bound definitions. Old-style class-bound + // definitions have one widget "object" per widget per type/class of + // widget; the renderValue and resize methods on such widget objects + // take el and instance arguments, because the widget object can't + // store them. New-style instance-bound definitions have one widget + // object per widget instance; the definition that's passed in doesn't + // provide renderValue or resize methods at all, just the single method + // factory(el, width, height) + // which returns an object that has renderValue(x) and resize(w, h). + // This enables a far more natural programming style for the widget + // author, who can store per-instance state using either OO-style + // instance fields or functional-style closure variables (I guess this + // is in contrast to what can only be called C-style pseudo-OO which is + // what we required before). + if (definition.factory) { + definition = createLegacyDefinitionAdapter(definition); + } + + if (!definition.renderValue) { + throw new Error("Widget must have a renderValue function"); + } + + // For static rendering (non-Shiny), use a simple widget registration + // scheme. We also use this scheme for Shiny apps/documents that also + // contain static widgets. + window.HTMLWidgets.widgets = window.HTMLWidgets.widgets || []; + // Merge defaults into the definition; don't mutate the original definition. + var staticBinding = extend({}, defaults, definition); + overrideMethod(staticBinding, "find", function(superfunc) { + return function(scope) { + var results = superfunc(scope); + // Filter out Shiny outputs, we only want the static kind + return filterByClass(results, "html-widget-output", false); + }; + }); + window.HTMLWidgets.widgets.push(staticBinding); + + if (shinyMode) { + // Shiny is running. Register the definition with an output binding. + // The definition itself will not be the output binding, instead + // we will make an output binding object that delegates to the + // definition. This is because we foolishly used the same method + // name (renderValue) for htmlwidgets definition and Shiny bindings + // but they actually have quite different semantics (the Shiny + // bindings receive data that includes lots of metadata that it + // strips off before calling htmlwidgets renderValue). We can't + // just ignore the difference because in some widgets it's helpful + // to call this.renderValue() from inside of resize(), and if + // we're not delegating, then that call will go to the Shiny + // version instead of the htmlwidgets version. + + // Merge defaults with definition, without mutating either. + var bindingDef = extend({}, defaults, definition); + + // This object will be our actual Shiny binding. + var shinyBinding = new Shiny.OutputBinding(); + + // With a few exceptions, we'll want to simply use the bindingDef's + // version of methods if they are available, otherwise fall back to + // Shiny's defaults. NOTE: If Shiny's output bindings gain additional + // methods in the future, and we want them to be overrideable by + // HTMLWidget binding definitions, then we'll need to add them to this + // list. + delegateMethod(shinyBinding, bindingDef, "getId"); + delegateMethod(shinyBinding, bindingDef, "onValueChange"); + delegateMethod(shinyBinding, bindingDef, "onValueError"); + delegateMethod(shinyBinding, bindingDef, "renderError"); + delegateMethod(shinyBinding, bindingDef, "clearError"); + delegateMethod(shinyBinding, bindingDef, "showProgress"); + + // The find, renderValue, and resize are handled differently, because we + // want to actually decorate the behavior of the bindingDef methods. + + shinyBinding.find = function(scope) { + var results = bindingDef.find(scope); + + // Only return elements that are Shiny outputs, not static ones + var dynamicResults = results.filter(".html-widget-output"); + + // It's possible that whatever caused Shiny to think there might be + // new dynamic outputs, also caused there to be new static outputs. + // Since there might be lots of different htmlwidgets bindings, we + // schedule execution for later--no need to staticRender multiple + // times. + if (results.length !== dynamicResults.length) + scheduleStaticRender(); + + return dynamicResults; + }; + + // Wrap renderValue to handle initialization, which unfortunately isn't + // supported natively by Shiny at the time of this writing. + + shinyBinding.renderValue = function(el, data) { + Shiny.renderDependencies(data.deps); + // Resolve strings marked as javascript literals to objects + if (!(data.evals instanceof Array)) data.evals = [data.evals]; + for (var i = 0; data.evals && i < data.evals.length; i++) { + window.HTMLWidgets.evaluateStringMember(data.x, data.evals[i]); + } + if (!bindingDef.renderOnNullValue) { + if (data.x === null) { + el.style.visibility = "hidden"; + return; + } else { + el.style.visibility = "inherit"; + } + } + if (!elementData(el, "initialized")) { + initSizing(el); + + elementData(el, "initialized", true); + if (bindingDef.initialize) { + var rect = el.getBoundingClientRect(); + var result = bindingDef.initialize(el, rect.width, rect.height); + elementData(el, "init_result", result); + } + } + bindingDef.renderValue(el, data.x, elementData(el, "init_result")); + evalAndRun(data.jsHooks.render, elementData(el, "init_result"), [el, data.x]); + }; + + // Only override resize if bindingDef implements it + if (bindingDef.resize) { + shinyBinding.resize = function(el, width, height) { + // Shiny can call resize before initialize/renderValue have been + // called, which doesn't make sense for widgets. + if (elementData(el, "initialized")) { + bindingDef.resize(el, width, height, elementData(el, "init_result")); + } + }; + } + + Shiny.outputBindings.register(shinyBinding, bindingDef.name); + } + }; + + var scheduleStaticRenderTimerId = null; + function scheduleStaticRender() { + if (!scheduleStaticRenderTimerId) { + scheduleStaticRenderTimerId = setTimeout(function() { + scheduleStaticRenderTimerId = null; + window.HTMLWidgets.staticRender(); + }, 1); + } + } + + // Render static widgets after the document finishes loading + // Statically render all elements that are of this widget's class + window.HTMLWidgets.staticRender = function() { + var bindings = window.HTMLWidgets.widgets || []; + forEach(bindings, function(binding) { + var matches = binding.find(document.documentElement); + forEach(matches, function(el) { + var sizeObj = initSizing(el, binding); + + var getSize = function(el) { + if (sizeObj) { + return {w: sizeObj.getWidth(), h: sizeObj.getHeight()} + } else { + var rect = el.getBoundingClientRect(); + return {w: rect.width, h: rect.height} + } + }; + + if (hasClass(el, "html-widget-static-bound")) + return; + el.className = el.className + " html-widget-static-bound"; + + var initResult; + if (binding.initialize) { + var size = getSize(el); + initResult = binding.initialize(el, size.w, size.h); + elementData(el, "init_result", initResult); + } + + if (binding.resize) { + var lastSize = getSize(el); + var resizeHandler = function(e) { + var size = getSize(el); + if (size.w === 0 && size.h === 0) + return; + if (size.w === lastSize.w && size.h === lastSize.h) + return; + lastSize = size; + binding.resize(el, size.w, size.h, initResult); + }; + + on(window, "resize", resizeHandler); + + // This is needed for cases where we're running in a Shiny + // app, but the widget itself is not a Shiny output, but + // rather a simple static widget. One example of this is + // an rmarkdown document that has runtime:shiny and widget + // that isn't in a render function. Shiny only knows to + // call resize handlers for Shiny outputs, not for static + // widgets, so we do it ourselves. + if (window.jQuery) { + window.jQuery(document).on( + "shown.htmlwidgets shown.bs.tab.htmlwidgets shown.bs.collapse.htmlwidgets", + resizeHandler + ); + window.jQuery(document).on( + "hidden.htmlwidgets hidden.bs.tab.htmlwidgets hidden.bs.collapse.htmlwidgets", + resizeHandler + ); + } + + // This is needed for the specific case of ioslides, which + // flips slides between display:none and display:block. + // Ideally we would not have to have ioslide-specific code + // here, but rather have ioslides raise a generic event, + // but the rmarkdown package just went to CRAN so the + // window to getting that fixed may be long. + if (window.addEventListener) { + // It's OK to limit this to window.addEventListener + // browsers because ioslides itself only supports + // such browsers. + on(document, "slideenter", resizeHandler); + on(document, "slideleave", resizeHandler); + } + } + + var scriptData = document.querySelector("script[data-for='" + el.id + "'][type='application/json']"); + if (scriptData) { + var data = JSON.parse(scriptData.textContent || scriptData.text); + // Resolve strings marked as javascript literals to objects + if (!(data.evals instanceof Array)) data.evals = [data.evals]; + for (var k = 0; data.evals && k < data.evals.length; k++) { + window.HTMLWidgets.evaluateStringMember(data.x, data.evals[k]); + } + binding.renderValue(el, data.x, initResult); + evalAndRun(data.jsHooks.render, initResult, [el, data.x]); + } + }); + }); + + invokePostRenderHandlers(); + } + + + function has_jQuery3() { + if (!window.jQuery) { + return false; + } + var $version = window.jQuery.fn.jquery; + var $major_version = parseInt($version.split(".")[0]); + return $major_version >= 3; + } + + /* + / Shiny 1.4 bumped jQuery from 1.x to 3.x which means jQuery's + / on-ready handler (i.e., $(fn)) is now asyncronous (i.e., it now + / really means $(setTimeout(fn)). + / https://jquery.com/upgrade-guide/3.0/#breaking-change-document-ready-handlers-are-now-asynchronous + / + / Since Shiny uses $() to schedule initShiny, shiny>=1.4 calls initShiny + / one tick later than it did before, which means staticRender() is + / called renderValue() earlier than (advanced) widget authors might be expecting. + / https://github.com/rstudio/shiny/issues/2630 + / + / For a concrete example, leaflet has some methods (e.g., updateBounds) + / which reference Shiny methods registered in initShiny (e.g., setInputValue). + / Since leaflet is privy to this life-cycle, it knows to use setTimeout() to + / delay execution of those methods (until Shiny methods are ready) + / https://github.com/rstudio/leaflet/blob/18ec981/javascript/src/index.js#L266-L268 + / + / Ideally widget authors wouldn't need to use this setTimeout() hack that + / leaflet uses to call Shiny methods on a staticRender(). In the long run, + / the logic initShiny should be broken up so that method registration happens + / right away, but binding happens later. + */ + function maybeStaticRenderLater() { + if (shinyMode && has_jQuery3()) { + window.jQuery(window.HTMLWidgets.staticRender); + } else { + window.HTMLWidgets.staticRender(); + } + } + + if (document.addEventListener) { + document.addEventListener("DOMContentLoaded", function() { + document.removeEventListener("DOMContentLoaded", arguments.callee, false); + maybeStaticRenderLater(); + }, false); + } else if (document.attachEvent) { + document.attachEvent("onreadystatechange", function() { + if (document.readyState === "complete") { + document.detachEvent("onreadystatechange", arguments.callee); + maybeStaticRenderLater(); + } + }); + } + + + window.HTMLWidgets.getAttachmentUrl = function(depname, key) { + // If no key, default to the first item + if (typeof(key) === "undefined") + key = 1; + + var link = document.getElementById(depname + "-" + key + "-attachment"); + if (!link) { + throw new Error("Attachment " + depname + "/" + key + " not found in document"); + } + return link.getAttribute("href"); + }; + + window.HTMLWidgets.dataframeToD3 = function(df) { + var names = []; + var length; + for (var name in df) { + if (df.hasOwnProperty(name)) + names.push(name); + if (typeof(df[name]) !== "object" || typeof(df[name].length) === "undefined") { + throw new Error("All fields must be arrays"); + } else if (typeof(length) !== "undefined" && length !== df[name].length) { + throw new Error("All fields must be arrays of the same length"); + } + length = df[name].length; + } + var results = []; + var item; + for (var row = 0; row < length; row++) { + item = {}; + for (var col = 0; col < names.length; col++) { + item[names[col]] = df[names[col]][row]; + } + results.push(item); + } + return results; + }; + + window.HTMLWidgets.transposeArray2D = function(array) { + if (array.length === 0) return array; + var newArray = array[0].map(function(col, i) { + return array.map(function(row) { + return row[i] + }) + }); + return newArray; + }; + // Split value at splitChar, but allow splitChar to be escaped + // using escapeChar. Any other characters escaped by escapeChar + // will be included as usual (including escapeChar itself). + function splitWithEscape(value, splitChar, escapeChar) { + var results = []; + var escapeMode = false; + var currentResult = ""; + for (var pos = 0; pos < value.length; pos++) { + if (!escapeMode) { + if (value[pos] === splitChar) { + results.push(currentResult); + currentResult = ""; + } else if (value[pos] === escapeChar) { + escapeMode = true; + } else { + currentResult += value[pos]; + } + } else { + currentResult += value[pos]; + escapeMode = false; + } + } + if (currentResult !== "") { + results.push(currentResult); + } + return results; + } + // Function authored by Yihui/JJ Allaire + window.HTMLWidgets.evaluateStringMember = function(o, member) { + var parts = splitWithEscape(member, '.', '\\'); + for (var i = 0, l = parts.length; i < l; i++) { + var part = parts[i]; + // part may be a character or 'numeric' member name + if (o !== null && typeof o === "object" && part in o) { + if (i == (l - 1)) { // if we are at the end of the line then evalulate + if (typeof o[part] === "string") + o[part] = tryEval(o[part]); + } else { // otherwise continue to next embedded object + o = o[part]; + } + } + } + }; + + // Retrieve the HTMLWidget instance (i.e. the return value of an + // HTMLWidget binding's initialize() or factory() function) + // associated with an element, or null if none. + window.HTMLWidgets.getInstance = function(el) { + return elementData(el, "init_result"); + }; + + // Finds the first element in the scope that matches the selector, + // and returns the HTMLWidget instance (i.e. the return value of + // an HTMLWidget binding's initialize() or factory() function) + // associated with that element, if any. If no element matches the + // selector, or the first matching element has no HTMLWidget + // instance associated with it, then null is returned. + // + // The scope argument is optional, and defaults to window.document. + window.HTMLWidgets.find = function(scope, selector) { + if (arguments.length == 1) { + selector = scope; + scope = document; + } + + var el = scope.querySelector(selector); + if (el === null) { + return null; + } else { + return window.HTMLWidgets.getInstance(el); + } + }; + + // Finds all elements in the scope that match the selector, and + // returns the HTMLWidget instances (i.e. the return values of + // an HTMLWidget binding's initialize() or factory() function) + // associated with the elements, in an array. If elements that + // match the selector don't have an associated HTMLWidget + // instance, the returned array will contain nulls. + // + // The scope argument is optional, and defaults to window.document. + window.HTMLWidgets.findAll = function(scope, selector) { + if (arguments.length == 1) { + selector = scope; + scope = document; + } + + var nodes = scope.querySelectorAll(selector); + var results = []; + for (var i = 0; i < nodes.length; i++) { + results.push(window.HTMLWidgets.getInstance(nodes[i])); + } + return results; + }; + + var postRenderHandlers = []; + function invokePostRenderHandlers() { + while (postRenderHandlers.length) { + var handler = postRenderHandlers.shift(); + if (handler) { + handler(); + } + } + } + + // Register the given callback function to be invoked after the + // next time static widgets are rendered. + window.HTMLWidgets.addPostRenderHandler = function(callback) { + postRenderHandlers.push(callback); + }; + + // Takes a new-style instance-bound definition, and returns an + // old-style class-bound definition. This saves us from having + // to rewrite all the logic in this file to accomodate both + // types of definitions. + function createLegacyDefinitionAdapter(defn) { + var result = { + name: defn.name, + type: defn.type, + initialize: function(el, width, height) { + return defn.factory(el, width, height); + }, + renderValue: function(el, x, instance) { + return instance.renderValue(x); + }, + resize: function(el, width, height, instance) { + return instance.resize(width, height); + } + }; + + if (defn.find) + result.find = defn.find; + if (defn.renderError) + result.renderError = defn.renderError; + if (defn.clearError) + result.clearError = defn.clearError; + + return result; + } +})(); diff --git a/docs/site_libs/jquery-3.5.1/jquery-AUTHORS.txt b/docs/site_libs/jquery-3.5.1/jquery-AUTHORS.txt index 06df1a5..dcc2a36 100644 --- a/docs/site_libs/jquery-3.5.1/jquery-AUTHORS.txt +++ b/docs/site_libs/jquery-3.5.1/jquery-AUTHORS.txt @@ -1,357 +1,357 @@ -Authors ordered by first contribution. - -John Resig -Gilles van den Hoven -Michael Geary -Stefan Petre -Yehuda Katz -Corey Jewett -Klaus Hartl -Franck Marcia -Jörn Zaefferer -Paul Bakaus -Brandon Aaron -Mike Alsup -Dave Methvin -Ed Engelhardt -Sean Catchpole -Paul Mclanahan -David Serduke -Richard D. Worth -Scott González -Ariel Flesler -Cheah Chu Yeow -Andrew Chalkley -Fabio Buffoni -Stefan Bauckmeier  -Jon Evans -TJ Holowaychuk -Riccardo De Agostini -Michael Bensoussan -Louis-Rémi Babé -Robert Katić -Damian Janowski -Anton Kovalyov -Dušan B. Jovanovic -Earle Castledine -Rich Dougherty -Kim Dalsgaard -Andrea Giammarchi -Fabian Jakobs -Mark Gibson -Karl Swedberg -Justin Meyer -Ben Alman -James Padolsey -David Petersen -Batiste Bieler -Jake Archibald -Alexander Farkas -Filipe Fortes -Rick Waldron -Neeraj Singh -Paul Irish -Iraê Carvalho -Matt Curry -Michael Monteleone -Noah Sloan -Tom Viner -J. Ryan Stinnett -Douglas Neiner -Adam J. Sontag -Heungsub Lee -Dave Reed -Carl Fürstenberg -Jacob Wright -Ralph Whitbeck -unknown -temp01 -Colin Snover -Jared Grippe -Ryan W Tenney -Alex Sexton -Pinhook -Ron Otten -Jephte Clain -Anton Matzneller -Dan Heberden -Henri Wiechers -Russell Holbrook -Julian Aubourg -Gianni Alessandro Chiappetta -Scott Jehl -James Burke -Jonas Pfenniger -Xavi Ramirez -Sylvester Keil -Brandon Sterne -Mathias Bynens -Lee Carpenter -Timmy Willison <4timmywil@gmail.com> -Corey Frang -Digitalxero -David Murdoch -Josh Varner -Charles McNulty -Jordan Boesch -Jess Thrysoee -Michael Murray -Alexis Abril -Rob Morgan -John Firebaugh -Sam Bisbee -Gilmore Davidson -Brian Brennan -Xavier Montillet -Daniel Pihlstrom -Sahab Yazdani -avaly -Scott Hughes -Mike Sherov -Greg Hazel -Schalk Neethling -Denis Knauf -Timo Tijhof -Steen Nielsen -Anton Ryzhov -Shi Chuan -Matt Mueller -Berker Peksag -Toby Brain -Justin -Daniel Herman -Oleg Gaidarenko -Rock Hymas -Richard Gibson -Rafaël Blais Masson -cmc3cn <59194618@qq.com> -Joe Presbrey -Sindre Sorhus -Arne de Bree -Vladislav Zarakovsky -Andrew E Monat -Oskari -Joao Henrique de Andrade Bruni -tsinha -Dominik D. Geyer -Matt Farmer -Trey Hunner -Jason Moon -Jeffery To -Kris Borchers -Vladimir Zhuravlev -Jacob Thornton -Chad Killingsworth -Vitya Muhachev -Nowres Rafid -David Benjamin -Alan Plum -Uri Gilad -Chris Faulkner -Marcel Greter -Elijah Manor -Daniel Chatfield -Daniel Gálvez -Nikita Govorov -Wesley Walser -Mike Pennisi -Matthias Jäggli -Devin Cooper -Markus Staab -Dave Riddle -Callum Macrae -Jonathan Sampson -Benjamin Truyman -Jay Merrifield -James Huston -Sai Lung Wong -Erick Ruiz de Chávez -David Bonner -Allen J Schmidt Jr -Akintayo Akinwunmi -MORGAN -Ismail Khair -Carl Danley -Mike Petrovich -Greg Lavallee -Tom H Fuertes -Roland Eckl -Yiming He -David Fox -Bennett Sorbo -Paul Ramos -Rod Vagg -Sebastian Burkhard -Zachary Adam Kaplan -Adam Coulombe -nanto_vi -nanto -Danil Somsikov -Ryunosuke SATO -Diego Tres -Jean Boussier -Andrew Plummer -Mark Raddatz -Pascal Borreli -Isaac Z. Schlueter -Karl Sieburg -Nguyen Phuc Lam -Dmitry Gusev -Steven Benner -Li Xudong -Michał Gołębiowski-Owczarek -Renato Oliveira dos Santos -Frederic Junod -Tom H Fuertes -Mitch Foley -ros3cin -Kyle Robinson Young -John Paul -Jason Bedard -Chris Talkington -Eddie Monge -Terry Jones -Jason Merino -Dan Burzo -Jeremy Dunck -Chris Price -Guy Bedford -njhamann -Goare Mao -Amey Sakhadeo -Mike Sidorov -Anthony Ryan -Lihan Li -George Kats -Dongseok Paeng -Ronny Springer -Ilya Kantor -Marian Sollmann -Chris Antaki -David Hong -Jakob Stoeck -Christopher Jones -Forbes Lindesay -S. Andrew Sheppard -Leonardo Balter -Rodrigo Rosenfeld Rosas -Daniel Husar -Philip Jägenstedt -John Hoven -Roman Reiß -Benjy Cui -Christian Kosmowski -David Corbacho -Liang Peng -TJ VanToll -Aurelio De Rosa -Senya Pugach -Dan Hart -Nazar Mokrynskyi -Benjamin Tan -Amit Merchant -Jason Bedard -Veaceslav Grimalschi -Richard McDaniel -Arthur Verschaeve -Shivaji Varma -Ben Toews -Bin Xin -Neftaly Hernandez -T.J. Crowder -Nicolas HENRY -Frederic Hemberger -Victor Homyakov -Aditya Raghavan -Anne-Gaelle Colom -Leonardo Braga -George Mauer -Stephen Edgar -Thomas Tortorini -Jörn Wagner -Jon Hester -Colin Frick -Winston Howes -Alexander O'Mara -Chris Rebert -Bastian Buchholz -Mu Haibao -Calvin Metcalf -Arthur Stolyar -Gabriel Schulhof -Gilad Peleg -Julian Alexander Murillo -Kevin Kirsche -Martin Naumann -Yongwoo Jeon -John-David Dalton -Marek Lewandowski -Bruno Pérel -Daniel Nill -Reed Loden -Sean Henderson -Gary Ye -Richard Kraaijenhagen -Connor Atherton -Christian Grete -Tom von Clef -Liza Ramo -Joelle Fleurantin -Steve Mao -Jon Dufresne -Jae Sung Park -Josh Soref -Saptak Sengupta -Henry Wong -Jun Sun -Martijn W. van der Lee -Devin Wilson -Damian Senn -Zack Hall -Vitaliy Terziev -Todor Prikumov -Bernhard M. Wiedemann -Jha Naman -Alexander Lisianoi -William Robinet -Joe Trumbull -Alexander K -Ralin Chimev -Felipe Sateler -Christophe Tafani-Dereeper -Manoj Kumar -David Broder-Rodgers -Alex Louden -Alex Padilla -karan-96 -南漂一卒 -Erik Lax -Boom Lee -Andreas Solleder -Pierre Spring -Shashanka Nataraj -CDAGaming -Matan Kotler-Berkowitz <205matan@gmail.com> -Jordan Beland -Henry Zhu -Nilton Cesar -basil.belokon -Andrey Meshkov -tmybr11 -Luis Emilio Velasco Sanchez -Ed S -Bert Zhang -Sébastien Règne -wartmanm <3869625+wartmanm@users.noreply.github.com> -Siddharth Dungarwal -abnud1 -Andrei Fangli -Marja Hölttä -buddh4 -Hoang -Wonseop Kim -Pat O'Callaghan -JuanMa Ruiz -Ahmed.S.ElAfifi -Sean Robinson -Christian Oliff +Authors ordered by first contribution. + +John Resig +Gilles van den Hoven +Michael Geary +Stefan Petre +Yehuda Katz +Corey Jewett +Klaus Hartl +Franck Marcia +Jörn Zaefferer +Paul Bakaus +Brandon Aaron +Mike Alsup +Dave Methvin +Ed Engelhardt +Sean Catchpole +Paul Mclanahan +David Serduke +Richard D. Worth +Scott González +Ariel Flesler +Cheah Chu Yeow +Andrew Chalkley +Fabio Buffoni +Stefan Bauckmeier  +Jon Evans +TJ Holowaychuk +Riccardo De Agostini +Michael Bensoussan +Louis-Rémi Babé +Robert Katić +Damian Janowski +Anton Kovalyov +Dušan B. Jovanovic +Earle Castledine +Rich Dougherty +Kim Dalsgaard +Andrea Giammarchi +Fabian Jakobs +Mark Gibson +Karl Swedberg +Justin Meyer +Ben Alman +James Padolsey +David Petersen +Batiste Bieler +Jake Archibald +Alexander Farkas +Filipe Fortes +Rick Waldron +Neeraj Singh +Paul Irish +Iraê Carvalho +Matt Curry +Michael Monteleone +Noah Sloan +Tom Viner +J. Ryan Stinnett +Douglas Neiner +Adam J. Sontag +Heungsub Lee +Dave Reed +Carl Fürstenberg +Jacob Wright +Ralph Whitbeck +unknown +temp01 +Colin Snover +Jared Grippe +Ryan W Tenney +Alex Sexton +Pinhook +Ron Otten +Jephte Clain +Anton Matzneller +Dan Heberden +Henri Wiechers +Russell Holbrook +Julian Aubourg +Gianni Alessandro Chiappetta +Scott Jehl +James Burke +Jonas Pfenniger +Xavi Ramirez +Sylvester Keil +Brandon Sterne +Mathias Bynens +Lee Carpenter +Timmy Willison <4timmywil@gmail.com> +Corey Frang +Digitalxero +David Murdoch +Josh Varner +Charles McNulty +Jordan Boesch +Jess Thrysoee +Michael Murray +Alexis Abril +Rob Morgan +John Firebaugh +Sam Bisbee +Gilmore Davidson +Brian Brennan +Xavier Montillet +Daniel Pihlstrom +Sahab Yazdani +avaly +Scott Hughes +Mike Sherov +Greg Hazel +Schalk Neethling +Denis Knauf +Timo Tijhof +Steen Nielsen +Anton Ryzhov +Shi Chuan +Matt Mueller +Berker Peksag +Toby Brain +Justin +Daniel Herman +Oleg Gaidarenko +Rock Hymas +Richard Gibson +Rafaël Blais Masson +cmc3cn <59194618@qq.com> +Joe Presbrey +Sindre Sorhus +Arne de Bree +Vladislav Zarakovsky +Andrew E Monat +Oskari +Joao Henrique de Andrade Bruni +tsinha +Dominik D. Geyer +Matt Farmer +Trey Hunner +Jason Moon +Jeffery To +Kris Borchers +Vladimir Zhuravlev +Jacob Thornton +Chad Killingsworth +Vitya Muhachev +Nowres Rafid +David Benjamin +Alan Plum +Uri Gilad +Chris Faulkner +Marcel Greter +Elijah Manor +Daniel Chatfield +Daniel Gálvez +Nikita Govorov +Wesley Walser +Mike Pennisi +Matthias Jäggli +Devin Cooper +Markus Staab +Dave Riddle +Callum Macrae +Jonathan Sampson +Benjamin Truyman +Jay Merrifield +James Huston +Sai Lung Wong +Erick Ruiz de Chávez +David Bonner +Allen J Schmidt Jr +Akintayo Akinwunmi +MORGAN +Ismail Khair +Carl Danley +Mike Petrovich +Greg Lavallee +Tom H Fuertes +Roland Eckl +Yiming He +David Fox +Bennett Sorbo +Paul Ramos +Rod Vagg +Sebastian Burkhard +Zachary Adam Kaplan +Adam Coulombe +nanto_vi +nanto +Danil Somsikov +Ryunosuke SATO +Diego Tres +Jean Boussier +Andrew Plummer +Mark Raddatz +Pascal Borreli +Isaac Z. Schlueter +Karl Sieburg +Nguyen Phuc Lam +Dmitry Gusev +Steven Benner +Li Xudong +Michał Gołębiowski-Owczarek +Renato Oliveira dos Santos +Frederic Junod +Tom H Fuertes +Mitch Foley +ros3cin +Kyle Robinson Young +John Paul +Jason Bedard +Chris Talkington +Eddie Monge +Terry Jones +Jason Merino +Dan Burzo +Jeremy Dunck +Chris Price +Guy Bedford +njhamann +Goare Mao +Amey Sakhadeo +Mike Sidorov +Anthony Ryan +Lihan Li +George Kats +Dongseok Paeng +Ronny Springer +Ilya Kantor +Marian Sollmann +Chris Antaki +David Hong +Jakob Stoeck +Christopher Jones +Forbes Lindesay +S. Andrew Sheppard +Leonardo Balter +Rodrigo Rosenfeld Rosas +Daniel Husar +Philip Jägenstedt +John Hoven +Roman Reiß +Benjy Cui +Christian Kosmowski +David Corbacho +Liang Peng +TJ VanToll +Aurelio De Rosa +Senya Pugach +Dan Hart +Nazar Mokrynskyi +Benjamin Tan +Amit Merchant +Jason Bedard +Veaceslav Grimalschi +Richard McDaniel +Arthur Verschaeve +Shivaji Varma +Ben Toews +Bin Xin +Neftaly Hernandez +T.J. Crowder +Nicolas HENRY +Frederic Hemberger +Victor Homyakov +Aditya Raghavan +Anne-Gaelle Colom +Leonardo Braga +George Mauer +Stephen Edgar +Thomas Tortorini +Jörn Wagner +Jon Hester +Colin Frick +Winston Howes +Alexander O'Mara +Chris Rebert +Bastian Buchholz +Mu Haibao +Calvin Metcalf +Arthur Stolyar +Gabriel Schulhof +Gilad Peleg +Julian Alexander Murillo +Kevin Kirsche +Martin Naumann +Yongwoo Jeon +John-David Dalton +Marek Lewandowski +Bruno Pérel +Daniel Nill +Reed Loden +Sean Henderson +Gary Ye +Richard Kraaijenhagen +Connor Atherton +Christian Grete +Tom von Clef +Liza Ramo +Joelle Fleurantin +Steve Mao +Jon Dufresne +Jae Sung Park +Josh Soref +Saptak Sengupta +Henry Wong +Jun Sun +Martijn W. van der Lee +Devin Wilson +Damian Senn +Zack Hall +Vitaliy Terziev +Todor Prikumov +Bernhard M. Wiedemann +Jha Naman +Alexander Lisianoi +William Robinet +Joe Trumbull +Alexander K +Ralin Chimev +Felipe Sateler +Christophe Tafani-Dereeper +Manoj Kumar +David Broder-Rodgers +Alex Louden +Alex Padilla +karan-96 +南漂一卒 +Erik Lax +Boom Lee +Andreas Solleder +Pierre Spring +Shashanka Nataraj +CDAGaming +Matan Kotler-Berkowitz <205matan@gmail.com> +Jordan Beland +Henry Zhu +Nilton Cesar +basil.belokon +Andrey Meshkov +tmybr11 +Luis Emilio Velasco Sanchez +Ed S +Bert Zhang +Sébastien Règne +wartmanm <3869625+wartmanm@users.noreply.github.com> +Siddharth Dungarwal +abnud1 +Andrei Fangli +Marja Hölttä +buddh4 +Hoang +Wonseop Kim +Pat O'Callaghan +JuanMa Ruiz +Ahmed.S.ElAfifi +Sean Robinson +Christian Oliff diff --git a/docs/site_libs/jquery-3.5.1/jquery.js b/docs/site_libs/jquery-3.5.1/jquery.js index 5093733..5546015 100644 --- a/docs/site_libs/jquery-3.5.1/jquery.js +++ b/docs/site_libs/jquery-3.5.1/jquery.js @@ -1,10872 +1,10872 @@ -/*! - * jQuery JavaScript Library v3.5.1 - * https://jquery.com/ - * - * Includes Sizzle.js - * https://sizzlejs.com/ - * - * Copyright JS Foundation and other contributors - * Released under the MIT license - * https://jquery.org/license - * - * Date: 2020-05-04T22:49Z - */ -( function( global, factory ) { - - "use strict"; - - if ( typeof module === "object" && typeof module.exports === "object" ) { - - // For CommonJS and CommonJS-like environments where a proper `window` - // is present, execute the factory and get jQuery. - // For environments that do not have a `window` with a `document` - // (such as Node.js), expose a factory as module.exports. - // This accentuates the need for the creation of a real `window`. - // e.g. var jQuery = require("jquery")(window); - // See ticket #14549 for more info. - module.exports = global.document ? - factory( global, true ) : - function( w ) { - if ( !w.document ) { - throw new Error( "jQuery requires a window with a document" ); - } - return factory( w ); - }; - } else { - factory( global ); - } - -// Pass this if window is not defined yet -} )( typeof window !== "undefined" ? window : this, function( window, noGlobal ) { - -// Edge <= 12 - 13+, Firefox <=18 - 45+, IE 10 - 11, Safari 5.1 - 9+, iOS 6 - 9.1 -// throw exceptions when non-strict code (e.g., ASP.NET 4.5) accesses strict mode -// arguments.callee.caller (trac-13335). But as of jQuery 3.0 (2016), strict mode should be common -// enough that all such attempts are guarded in a try block. -"use strict"; - -var arr = []; - -var getProto = Object.getPrototypeOf; - -var slice = arr.slice; - -var flat = arr.flat ? function( array ) { - return arr.flat.call( array ); -} : function( array ) { - return arr.concat.apply( [], array ); -}; - - -var push = arr.push; - -var indexOf = arr.indexOf; - -var class2type = {}; - -var toString = class2type.toString; - -var hasOwn = class2type.hasOwnProperty; - -var fnToString = hasOwn.toString; - -var ObjectFunctionString = fnToString.call( Object ); - -var support = {}; - -var isFunction = function isFunction( obj ) { - - // Support: Chrome <=57, Firefox <=52 - // In some browsers, typeof returns "function" for HTML elements - // (i.e., `typeof document.createElement( "object" ) === "function"`). - // We don't want to classify *any* DOM node as a function. - return typeof obj === "function" && typeof obj.nodeType !== "number"; - }; - - -var isWindow = function isWindow( obj ) { - return obj != null && obj === obj.window; - }; - - -var document = window.document; - - - - var preservedScriptAttributes = { - type: true, - src: true, - nonce: true, - noModule: true - }; - - function DOMEval( code, node, doc ) { - doc = doc || document; - - var i, val, - script = doc.createElement( "script" ); - - script.text = code; - if ( node ) { - for ( i in preservedScriptAttributes ) { - - // Support: Firefox 64+, Edge 18+ - // Some browsers don't support the "nonce" property on scripts. - // On the other hand, just using `getAttribute` is not enough as - // the `nonce` attribute is reset to an empty string whenever it - // becomes browsing-context connected. - // See https://github.com/whatwg/html/issues/2369 - // See https://html.spec.whatwg.org/#nonce-attributes - // The `node.getAttribute` check was added for the sake of - // `jQuery.globalEval` so that it can fake a nonce-containing node - // via an object. - val = node[ i ] || node.getAttribute && node.getAttribute( i ); - if ( val ) { - script.setAttribute( i, val ); - } - } - } - doc.head.appendChild( script ).parentNode.removeChild( script ); - } - - -function toType( obj ) { - if ( obj == null ) { - return obj + ""; - } - - // Support: Android <=2.3 only (functionish RegExp) - return typeof obj === "object" || typeof obj === "function" ? - class2type[ toString.call( obj ) ] || "object" : - typeof obj; -} -/* global Symbol */ -// Defining this global in .eslintrc.json would create a danger of using the global -// unguarded in another place, it seems safer to define global only for this module - - - -var - version = "3.5.1", - - // Define a local copy of jQuery - jQuery = function( selector, context ) { - - // The jQuery object is actually just the init constructor 'enhanced' - // Need init if jQuery is called (just allow error to be thrown if not included) - return new jQuery.fn.init( selector, context ); - }; - -jQuery.fn = jQuery.prototype = { - - // The current version of jQuery being used - jquery: version, - - constructor: jQuery, - - // The default length of a jQuery object is 0 - length: 0, - - toArray: function() { - return slice.call( this ); - }, - - // Get the Nth element in the matched element set OR - // Get the whole matched element set as a clean array - get: function( num ) { - - // Return all the elements in a clean array - if ( num == null ) { - return slice.call( this ); - } - - // Return just the one element from the set - return num < 0 ? this[ num + this.length ] : this[ num ]; - }, - - // Take an array of elements and push it onto the stack - // (returning the new matched element set) - pushStack: function( elems ) { - - // Build a new jQuery matched element set - var ret = jQuery.merge( this.constructor(), elems ); - - // Add the old object onto the stack (as a reference) - ret.prevObject = this; - - // Return the newly-formed element set - return ret; - }, - - // Execute a callback for every element in the matched set. - each: function( callback ) { - return jQuery.each( this, callback ); - }, - - map: function( callback ) { - return this.pushStack( jQuery.map( this, function( elem, i ) { - return callback.call( elem, i, elem ); - } ) ); - }, - - slice: function() { - return this.pushStack( slice.apply( this, arguments ) ); - }, - - first: function() { - return this.eq( 0 ); - }, - - last: function() { - return this.eq( -1 ); - }, - - even: function() { - return this.pushStack( jQuery.grep( this, function( _elem, i ) { - return ( i + 1 ) % 2; - } ) ); - }, - - odd: function() { - return this.pushStack( jQuery.grep( this, function( _elem, i ) { - return i % 2; - } ) ); - }, - - eq: function( i ) { - var len = this.length, - j = +i + ( i < 0 ? len : 0 ); - return this.pushStack( j >= 0 && j < len ? [ this[ j ] ] : [] ); - }, - - end: function() { - return this.prevObject || this.constructor(); - }, - - // For internal use only. - // Behaves like an Array's method, not like a jQuery method. - push: push, - sort: arr.sort, - splice: arr.splice -}; - -jQuery.extend = jQuery.fn.extend = function() { - var options, name, src, copy, copyIsArray, clone, - target = arguments[ 0 ] || {}, - i = 1, - length = arguments.length, - deep = false; - - // Handle a deep copy situation - if ( typeof target === "boolean" ) { - deep = target; - - // Skip the boolean and the target - target = arguments[ i ] || {}; - i++; - } - - // Handle case when target is a string or something (possible in deep copy) - if ( typeof target !== "object" && !isFunction( target ) ) { - target = {}; - } - - // Extend jQuery itself if only one argument is passed - if ( i === length ) { - target = this; - i--; - } - - for ( ; i < length; i++ ) { - - // Only deal with non-null/undefined values - if ( ( options = arguments[ i ] ) != null ) { - - // Extend the base object - for ( name in options ) { - copy = options[ name ]; - - // Prevent Object.prototype pollution - // Prevent never-ending loop - if ( name === "__proto__" || target === copy ) { - continue; - } - - // Recurse if we're merging plain objects or arrays - if ( deep && copy && ( jQuery.isPlainObject( copy ) || - ( copyIsArray = Array.isArray( copy ) ) ) ) { - src = target[ name ]; - - // Ensure proper type for the source value - if ( copyIsArray && !Array.isArray( src ) ) { - clone = []; - } else if ( !copyIsArray && !jQuery.isPlainObject( src ) ) { - clone = {}; - } else { - clone = src; - } - copyIsArray = false; - - // Never move original objects, clone them - target[ name ] = jQuery.extend( deep, clone, copy ); - - // Don't bring in undefined values - } else if ( copy !== undefined ) { - target[ name ] = copy; - } - } - } - } - - // Return the modified object - return target; -}; - -jQuery.extend( { - - // Unique for each copy of jQuery on the page - expando: "jQuery" + ( version + Math.random() ).replace( /\D/g, "" ), - - // Assume jQuery is ready without the ready module - isReady: true, - - error: function( msg ) { - throw new Error( msg ); - }, - - noop: function() {}, - - isPlainObject: function( obj ) { - var proto, Ctor; - - // Detect obvious negatives - // Use toString instead of jQuery.type to catch host objects - if ( !obj || toString.call( obj ) !== "[object Object]" ) { - return false; - } - - proto = getProto( obj ); - - // Objects with no prototype (e.g., `Object.create( null )`) are plain - if ( !proto ) { - return true; - } - - // Objects with prototype are plain iff they were constructed by a global Object function - Ctor = hasOwn.call( proto, "constructor" ) && proto.constructor; - return typeof Ctor === "function" && fnToString.call( Ctor ) === ObjectFunctionString; - }, - - isEmptyObject: function( obj ) { - var name; - - for ( name in obj ) { - return false; - } - return true; - }, - - // Evaluates a script in a provided context; falls back to the global one - // if not specified. - globalEval: function( code, options, doc ) { - DOMEval( code, { nonce: options && options.nonce }, doc ); - }, - - each: function( obj, callback ) { - var length, i = 0; - - if ( isArrayLike( obj ) ) { - length = obj.length; - for ( ; i < length; i++ ) { - if ( callback.call( obj[ i ], i, obj[ i ] ) === false ) { - break; - } - } - } else { - for ( i in obj ) { - if ( callback.call( obj[ i ], i, obj[ i ] ) === false ) { - break; - } - } - } - - return obj; - }, - - // results is for internal usage only - makeArray: function( arr, results ) { - var ret = results || []; - - if ( arr != null ) { - if ( isArrayLike( Object( arr ) ) ) { - jQuery.merge( ret, - typeof arr === "string" ? - [ arr ] : arr - ); - } else { - push.call( ret, arr ); - } - } - - return ret; - }, - - inArray: function( elem, arr, i ) { - return arr == null ? -1 : indexOf.call( arr, elem, i ); - }, - - // Support: Android <=4.0 only, PhantomJS 1 only - // push.apply(_, arraylike) throws on ancient WebKit - merge: function( first, second ) { - var len = +second.length, - j = 0, - i = first.length; - - for ( ; j < len; j++ ) { - first[ i++ ] = second[ j ]; - } - - first.length = i; - - return first; - }, - - grep: function( elems, callback, invert ) { - var callbackInverse, - matches = [], - i = 0, - length = elems.length, - callbackExpect = !invert; - - // Go through the array, only saving the items - // that pass the validator function - for ( ; i < length; i++ ) { - callbackInverse = !callback( elems[ i ], i ); - if ( callbackInverse !== callbackExpect ) { - matches.push( elems[ i ] ); - } - } - - return matches; - }, - - // arg is for internal usage only - map: function( elems, callback, arg ) { - var length, value, - i = 0, - ret = []; - - // Go through the array, translating each of the items to their new values - if ( isArrayLike( elems ) ) { - length = elems.length; - for ( ; i < length; i++ ) { - value = callback( elems[ i ], i, arg ); - - if ( value != null ) { - ret.push( value ); - } - } - - // Go through every key on the object, - } else { - for ( i in elems ) { - value = callback( elems[ i ], i, arg ); - - if ( value != null ) { - ret.push( value ); - } - } - } - - // Flatten any nested arrays - return flat( ret ); - }, - - // A global GUID counter for objects - guid: 1, - - // jQuery.support is not used in Core but other projects attach their - // properties to it so it needs to exist. - support: support -} ); - -if ( typeof Symbol === "function" ) { - jQuery.fn[ Symbol.iterator ] = arr[ Symbol.iterator ]; -} - -// Populate the class2type map -jQuery.each( "Boolean Number String Function Array Date RegExp Object Error Symbol".split( " " ), -function( _i, name ) { - class2type[ "[object " + name + "]" ] = name.toLowerCase(); -} ); - -function isArrayLike( obj ) { - - // Support: real iOS 8.2 only (not reproducible in simulator) - // `in` check used to prevent JIT error (gh-2145) - // hasOwn isn't used here due to false negatives - // regarding Nodelist length in IE - var length = !!obj && "length" in obj && obj.length, - type = toType( obj ); - - if ( isFunction( obj ) || isWindow( obj ) ) { - return false; - } - - return type === "array" || length === 0 || - typeof length === "number" && length > 0 && ( length - 1 ) in obj; -} -var Sizzle = -/*! - * Sizzle CSS Selector Engine v2.3.5 - * https://sizzlejs.com/ - * - * Copyright JS Foundation and other contributors - * Released under the MIT license - * https://js.foundation/ - * - * Date: 2020-03-14 - */ -( function( window ) { -var i, - support, - Expr, - getText, - isXML, - tokenize, - compile, - select, - outermostContext, - sortInput, - hasDuplicate, - - // Local document vars - setDocument, - document, - docElem, - documentIsHTML, - rbuggyQSA, - rbuggyMatches, - matches, - contains, - - // Instance-specific data - expando = "sizzle" + 1 * new Date(), - preferredDoc = window.document, - dirruns = 0, - done = 0, - classCache = createCache(), - tokenCache = createCache(), - compilerCache = createCache(), - nonnativeSelectorCache = createCache(), - sortOrder = function( a, b ) { - if ( a === b ) { - hasDuplicate = true; - } - return 0; - }, - - // Instance methods - hasOwn = ( {} ).hasOwnProperty, - arr = [], - pop = arr.pop, - pushNative = arr.push, - push = arr.push, - slice = arr.slice, - - // Use a stripped-down indexOf as it's faster than native - // https://jsperf.com/thor-indexof-vs-for/5 - indexOf = function( list, elem ) { - var i = 0, - len = list.length; - for ( ; i < len; i++ ) { - if ( list[ i ] === elem ) { - return i; - } - } - return -1; - }, - - booleans = "checked|selected|async|autofocus|autoplay|controls|defer|disabled|hidden|" + - "ismap|loop|multiple|open|readonly|required|scoped", - - // Regular expressions - - // http://www.w3.org/TR/css3-selectors/#whitespace - whitespace = "[\\x20\\t\\r\\n\\f]", - - // https://www.w3.org/TR/css-syntax-3/#ident-token-diagram - identifier = "(?:\\\\[\\da-fA-F]{1,6}" + whitespace + - "?|\\\\[^\\r\\n\\f]|[\\w-]|[^\0-\\x7f])+", - - // Attribute selectors: http://www.w3.org/TR/selectors/#attribute-selectors - attributes = "\\[" + whitespace + "*(" + identifier + ")(?:" + whitespace + - - // Operator (capture 2) - "*([*^$|!~]?=)" + whitespace + - - // "Attribute values must be CSS identifiers [capture 5] - // or strings [capture 3 or capture 4]" - "*(?:'((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\"|(" + identifier + "))|)" + - whitespace + "*\\]", - - pseudos = ":(" + identifier + ")(?:\\((" + - - // To reduce the number of selectors needing tokenize in the preFilter, prefer arguments: - // 1. quoted (capture 3; capture 4 or capture 5) - "('((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\")|" + - - // 2. simple (capture 6) - "((?:\\\\.|[^\\\\()[\\]]|" + attributes + ")*)|" + - - // 3. anything else (capture 2) - ".*" + - ")\\)|)", - - // Leading and non-escaped trailing whitespace, capturing some non-whitespace characters preceding the latter - rwhitespace = new RegExp( whitespace + "+", "g" ), - rtrim = new RegExp( "^" + whitespace + "+|((?:^|[^\\\\])(?:\\\\.)*)" + - whitespace + "+$", "g" ), - - rcomma = new RegExp( "^" + whitespace + "*," + whitespace + "*" ), - rcombinators = new RegExp( "^" + whitespace + "*([>+~]|" + whitespace + ")" + whitespace + - "*" ), - rdescend = new RegExp( whitespace + "|>" ), - - rpseudo = new RegExp( pseudos ), - ridentifier = new RegExp( "^" + identifier + "$" ), - - matchExpr = { - "ID": new RegExp( "^#(" + identifier + ")" ), - "CLASS": new RegExp( "^\\.(" + identifier + ")" ), - "TAG": new RegExp( "^(" + identifier + "|[*])" ), - "ATTR": new RegExp( "^" + attributes ), - "PSEUDO": new RegExp( "^" + pseudos ), - "CHILD": new RegExp( "^:(only|first|last|nth|nth-last)-(child|of-type)(?:\\(" + - whitespace + "*(even|odd|(([+-]|)(\\d*)n|)" + whitespace + "*(?:([+-]|)" + - whitespace + "*(\\d+)|))" + whitespace + "*\\)|)", "i" ), - "bool": new RegExp( "^(?:" + booleans + ")$", "i" ), - - // For use in libraries implementing .is() - // We use this for POS matching in `select` - "needsContext": new RegExp( "^" + whitespace + - "*[>+~]|:(even|odd|eq|gt|lt|nth|first|last)(?:\\(" + whitespace + - "*((?:-\\d)?\\d*)" + whitespace + "*\\)|)(?=[^-]|$)", "i" ) - }, - - rhtml = /HTML$/i, - rinputs = /^(?:input|select|textarea|button)$/i, - rheader = /^h\d$/i, - - rnative = /^[^{]+\{\s*\[native \w/, - - // Easily-parseable/retrievable ID or TAG or CLASS selectors - rquickExpr = /^(?:#([\w-]+)|(\w+)|\.([\w-]+))$/, - - rsibling = /[+~]/, - - // CSS escapes - // http://www.w3.org/TR/CSS21/syndata.html#escaped-characters - runescape = new RegExp( "\\\\[\\da-fA-F]{1,6}" + whitespace + "?|\\\\([^\\r\\n\\f])", "g" ), - funescape = function( escape, nonHex ) { - var high = "0x" + escape.slice( 1 ) - 0x10000; - - return nonHex ? - - // Strip the backslash prefix from a non-hex escape sequence - nonHex : - - // Replace a hexadecimal escape sequence with the encoded Unicode code point - // Support: IE <=11+ - // For values outside the Basic Multilingual Plane (BMP), manually construct a - // surrogate pair - high < 0 ? - String.fromCharCode( high + 0x10000 ) : - String.fromCharCode( high >> 10 | 0xD800, high & 0x3FF | 0xDC00 ); - }, - - // CSS string/identifier serialization - // https://drafts.csswg.org/cssom/#common-serializing-idioms - rcssescape = /([\0-\x1f\x7f]|^-?\d)|^-$|[^\0-\x1f\x7f-\uFFFF\w-]/g, - fcssescape = function( ch, asCodePoint ) { - if ( asCodePoint ) { - - // U+0000 NULL becomes U+FFFD REPLACEMENT CHARACTER - if ( ch === "\0" ) { - return "\uFFFD"; - } - - // Control characters and (dependent upon position) numbers get escaped as code points - return ch.slice( 0, -1 ) + "\\" + - ch.charCodeAt( ch.length - 1 ).toString( 16 ) + " "; - } - - // Other potentially-special ASCII characters get backslash-escaped - return "\\" + ch; - }, - - // Used for iframes - // See setDocument() - // Removing the function wrapper causes a "Permission Denied" - // error in IE - unloadHandler = function() { - setDocument(); - }, - - inDisabledFieldset = addCombinator( - function( elem ) { - return elem.disabled === true && elem.nodeName.toLowerCase() === "fieldset"; - }, - { dir: "parentNode", next: "legend" } - ); - -// Optimize for push.apply( _, NodeList ) -try { - push.apply( - ( arr = slice.call( preferredDoc.childNodes ) ), - preferredDoc.childNodes - ); - - // Support: Android<4.0 - // Detect silently failing push.apply - // eslint-disable-next-line no-unused-expressions - arr[ preferredDoc.childNodes.length ].nodeType; -} catch ( e ) { - push = { apply: arr.length ? - - // Leverage slice if possible - function( target, els ) { - pushNative.apply( target, slice.call( els ) ); - } : - - // Support: IE<9 - // Otherwise append directly - function( target, els ) { - var j = target.length, - i = 0; - - // Can't trust NodeList.length - while ( ( target[ j++ ] = els[ i++ ] ) ) {} - target.length = j - 1; - } - }; -} - -function Sizzle( selector, context, results, seed ) { - var m, i, elem, nid, match, groups, newSelector, - newContext = context && context.ownerDocument, - - // nodeType defaults to 9, since context defaults to document - nodeType = context ? context.nodeType : 9; - - results = results || []; - - // Return early from calls with invalid selector or context - if ( typeof selector !== "string" || !selector || - nodeType !== 1 && nodeType !== 9 && nodeType !== 11 ) { - - return results; - } - - // Try to shortcut find operations (as opposed to filters) in HTML documents - if ( !seed ) { - setDocument( context ); - context = context || document; - - if ( documentIsHTML ) { - - // If the selector is sufficiently simple, try using a "get*By*" DOM method - // (excepting DocumentFragment context, where the methods don't exist) - if ( nodeType !== 11 && ( match = rquickExpr.exec( selector ) ) ) { - - // ID selector - if ( ( m = match[ 1 ] ) ) { - - // Document context - if ( nodeType === 9 ) { - if ( ( elem = context.getElementById( m ) ) ) { - - // Support: IE, Opera, Webkit - // TODO: identify versions - // getElementById can match elements by name instead of ID - if ( elem.id === m ) { - results.push( elem ); - return results; - } - } else { - return results; - } - - // Element context - } else { - - // Support: IE, Opera, Webkit - // TODO: identify versions - // getElementById can match elements by name instead of ID - if ( newContext && ( elem = newContext.getElementById( m ) ) && - contains( context, elem ) && - elem.id === m ) { - - results.push( elem ); - return results; - } - } - - // Type selector - } else if ( match[ 2 ] ) { - push.apply( results, context.getElementsByTagName( selector ) ); - return results; - - // Class selector - } else if ( ( m = match[ 3 ] ) && support.getElementsByClassName && - context.getElementsByClassName ) { - - push.apply( results, context.getElementsByClassName( m ) ); - return results; - } - } - - // Take advantage of querySelectorAll - if ( support.qsa && - !nonnativeSelectorCache[ selector + " " ] && - ( !rbuggyQSA || !rbuggyQSA.test( selector ) ) && - - // Support: IE 8 only - // Exclude object elements - ( nodeType !== 1 || context.nodeName.toLowerCase() !== "object" ) ) { - - newSelector = selector; - newContext = context; - - // qSA considers elements outside a scoping root when evaluating child or - // descendant combinators, which is not what we want. - // In such cases, we work around the behavior by prefixing every selector in the - // list with an ID selector referencing the scope context. - // The technique has to be used as well when a leading combinator is used - // as such selectors are not recognized by querySelectorAll. - // Thanks to Andrew Dupont for this technique. - if ( nodeType === 1 && - ( rdescend.test( selector ) || rcombinators.test( selector ) ) ) { - - // Expand context for sibling selectors - newContext = rsibling.test( selector ) && testContext( context.parentNode ) || - context; - - // We can use :scope instead of the ID hack if the browser - // supports it & if we're not changing the context. - if ( newContext !== context || !support.scope ) { - - // Capture the context ID, setting it first if necessary - if ( ( nid = context.getAttribute( "id" ) ) ) { - nid = nid.replace( rcssescape, fcssescape ); - } else { - context.setAttribute( "id", ( nid = expando ) ); - } - } - - // Prefix every selector in the list - groups = tokenize( selector ); - i = groups.length; - while ( i-- ) { - groups[ i ] = ( nid ? "#" + nid : ":scope" ) + " " + - toSelector( groups[ i ] ); - } - newSelector = groups.join( "," ); - } - - try { - push.apply( results, - newContext.querySelectorAll( newSelector ) - ); - return results; - } catch ( qsaError ) { - nonnativeSelectorCache( selector, true ); - } finally { - if ( nid === expando ) { - context.removeAttribute( "id" ); - } - } - } - } - } - - // All others - return select( selector.replace( rtrim, "$1" ), context, results, seed ); -} - -/** - * Create key-value caches of limited size - * @returns {function(string, object)} Returns the Object data after storing it on itself with - * property name the (space-suffixed) string and (if the cache is larger than Expr.cacheLength) - * deleting the oldest entry - */ -function createCache() { - var keys = []; - - function cache( key, value ) { - - // Use (key + " ") to avoid collision with native prototype properties (see Issue #157) - if ( keys.push( key + " " ) > Expr.cacheLength ) { - - // Only keep the most recent entries - delete cache[ keys.shift() ]; - } - return ( cache[ key + " " ] = value ); - } - return cache; -} - -/** - * Mark a function for special use by Sizzle - * @param {Function} fn The function to mark - */ -function markFunction( fn ) { - fn[ expando ] = true; - return fn; -} - -/** - * Support testing using an element - * @param {Function} fn Passed the created element and returns a boolean result - */ -function assert( fn ) { - var el = document.createElement( "fieldset" ); - - try { - return !!fn( el ); - } catch ( e ) { - return false; - } finally { - - // Remove from its parent by default - if ( el.parentNode ) { - el.parentNode.removeChild( el ); - } - - // release memory in IE - el = null; - } -} - -/** - * Adds the same handler for all of the specified attrs - * @param {String} attrs Pipe-separated list of attributes - * @param {Function} handler The method that will be applied - */ -function addHandle( attrs, handler ) { - var arr = attrs.split( "|" ), - i = arr.length; - - while ( i-- ) { - Expr.attrHandle[ arr[ i ] ] = handler; - } -} - -/** - * Checks document order of two siblings - * @param {Element} a - * @param {Element} b - * @returns {Number} Returns less than 0 if a precedes b, greater than 0 if a follows b - */ -function siblingCheck( a, b ) { - var cur = b && a, - diff = cur && a.nodeType === 1 && b.nodeType === 1 && - a.sourceIndex - b.sourceIndex; - - // Use IE sourceIndex if available on both nodes - if ( diff ) { - return diff; - } - - // Check if b follows a - if ( cur ) { - while ( ( cur = cur.nextSibling ) ) { - if ( cur === b ) { - return -1; - } - } - } - - return a ? 1 : -1; -} - -/** - * Returns a function to use in pseudos for input types - * @param {String} type - */ -function createInputPseudo( type ) { - return function( elem ) { - var name = elem.nodeName.toLowerCase(); - return name === "input" && elem.type === type; - }; -} - -/** - * Returns a function to use in pseudos for buttons - * @param {String} type - */ -function createButtonPseudo( type ) { - return function( elem ) { - var name = elem.nodeName.toLowerCase(); - return ( name === "input" || name === "button" ) && elem.type === type; - }; -} - -/** - * Returns a function to use in pseudos for :enabled/:disabled - * @param {Boolean} disabled true for :disabled; false for :enabled - */ -function createDisabledPseudo( disabled ) { - - // Known :disabled false positives: fieldset[disabled] > legend:nth-of-type(n+2) :can-disable - return function( elem ) { - - // Only certain elements can match :enabled or :disabled - // https://html.spec.whatwg.org/multipage/scripting.html#selector-enabled - // https://html.spec.whatwg.org/multipage/scripting.html#selector-disabled - if ( "form" in elem ) { - - // Check for inherited disabledness on relevant non-disabled elements: - // * listed form-associated elements in a disabled fieldset - // https://html.spec.whatwg.org/multipage/forms.html#category-listed - // https://html.spec.whatwg.org/multipage/forms.html#concept-fe-disabled - // * option elements in a disabled optgroup - // https://html.spec.whatwg.org/multipage/forms.html#concept-option-disabled - // All such elements have a "form" property. - if ( elem.parentNode && elem.disabled === false ) { - - // Option elements defer to a parent optgroup if present - if ( "label" in elem ) { - if ( "label" in elem.parentNode ) { - return elem.parentNode.disabled === disabled; - } else { - return elem.disabled === disabled; - } - } - - // Support: IE 6 - 11 - // Use the isDisabled shortcut property to check for disabled fieldset ancestors - return elem.isDisabled === disabled || - - // Where there is no isDisabled, check manually - /* jshint -W018 */ - elem.isDisabled !== !disabled && - inDisabledFieldset( elem ) === disabled; - } - - return elem.disabled === disabled; - - // Try to winnow out elements that can't be disabled before trusting the disabled property. - // Some victims get caught in our net (label, legend, menu, track), but it shouldn't - // even exist on them, let alone have a boolean value. - } else if ( "label" in elem ) { - return elem.disabled === disabled; - } - - // Remaining elements are neither :enabled nor :disabled - return false; - }; -} - -/** - * Returns a function to use in pseudos for positionals - * @param {Function} fn - */ -function createPositionalPseudo( fn ) { - return markFunction( function( argument ) { - argument = +argument; - return markFunction( function( seed, matches ) { - var j, - matchIndexes = fn( [], seed.length, argument ), - i = matchIndexes.length; - - // Match elements found at the specified indexes - while ( i-- ) { - if ( seed[ ( j = matchIndexes[ i ] ) ] ) { - seed[ j ] = !( matches[ j ] = seed[ j ] ); - } - } - } ); - } ); -} - -/** - * Checks a node for validity as a Sizzle context - * @param {Element|Object=} context - * @returns {Element|Object|Boolean} The input node if acceptable, otherwise a falsy value - */ -function testContext( context ) { - return context && typeof context.getElementsByTagName !== "undefined" && context; -} - -// Expose support vars for convenience -support = Sizzle.support = {}; - -/** - * Detects XML nodes - * @param {Element|Object} elem An element or a document - * @returns {Boolean} True iff elem is a non-HTML XML node - */ -isXML = Sizzle.isXML = function( elem ) { - var namespace = elem.namespaceURI, - docElem = ( elem.ownerDocument || elem ).documentElement; - - // Support: IE <=8 - // Assume HTML when documentElement doesn't yet exist, such as inside loading iframes - // https://bugs.jquery.com/ticket/4833 - return !rhtml.test( namespace || docElem && docElem.nodeName || "HTML" ); -}; - -/** - * Sets document-related variables once based on the current document - * @param {Element|Object} [doc] An element or document object to use to set the document - * @returns {Object} Returns the current document - */ -setDocument = Sizzle.setDocument = function( node ) { - var hasCompare, subWindow, - doc = node ? node.ownerDocument || node : preferredDoc; - - // Return early if doc is invalid or already selected - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( doc == document || doc.nodeType !== 9 || !doc.documentElement ) { - return document; - } - - // Update global variables - document = doc; - docElem = document.documentElement; - documentIsHTML = !isXML( document ); - - // Support: IE 9 - 11+, Edge 12 - 18+ - // Accessing iframe documents after unload throws "permission denied" errors (jQuery #13936) - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( preferredDoc != document && - ( subWindow = document.defaultView ) && subWindow.top !== subWindow ) { - - // Support: IE 11, Edge - if ( subWindow.addEventListener ) { - subWindow.addEventListener( "unload", unloadHandler, false ); - - // Support: IE 9 - 10 only - } else if ( subWindow.attachEvent ) { - subWindow.attachEvent( "onunload", unloadHandler ); - } - } - - // Support: IE 8 - 11+, Edge 12 - 18+, Chrome <=16 - 25 only, Firefox <=3.6 - 31 only, - // Safari 4 - 5 only, Opera <=11.6 - 12.x only - // IE/Edge & older browsers don't support the :scope pseudo-class. - // Support: Safari 6.0 only - // Safari 6.0 supports :scope but it's an alias of :root there. - support.scope = assert( function( el ) { - docElem.appendChild( el ).appendChild( document.createElement( "div" ) ); - return typeof el.querySelectorAll !== "undefined" && - !el.querySelectorAll( ":scope fieldset div" ).length; - } ); - - /* Attributes - ---------------------------------------------------------------------- */ - - // Support: IE<8 - // Verify that getAttribute really returns attributes and not properties - // (excepting IE8 booleans) - support.attributes = assert( function( el ) { - el.className = "i"; - return !el.getAttribute( "className" ); - } ); - - /* getElement(s)By* - ---------------------------------------------------------------------- */ - - // Check if getElementsByTagName("*") returns only elements - support.getElementsByTagName = assert( function( el ) { - el.appendChild( document.createComment( "" ) ); - return !el.getElementsByTagName( "*" ).length; - } ); - - // Support: IE<9 - support.getElementsByClassName = rnative.test( document.getElementsByClassName ); - - // Support: IE<10 - // Check if getElementById returns elements by name - // The broken getElementById methods don't pick up programmatically-set names, - // so use a roundabout getElementsByName test - support.getById = assert( function( el ) { - docElem.appendChild( el ).id = expando; - return !document.getElementsByName || !document.getElementsByName( expando ).length; - } ); - - // ID filter and find - if ( support.getById ) { - Expr.filter[ "ID" ] = function( id ) { - var attrId = id.replace( runescape, funescape ); - return function( elem ) { - return elem.getAttribute( "id" ) === attrId; - }; - }; - Expr.find[ "ID" ] = function( id, context ) { - if ( typeof context.getElementById !== "undefined" && documentIsHTML ) { - var elem = context.getElementById( id ); - return elem ? [ elem ] : []; - } - }; - } else { - Expr.filter[ "ID" ] = function( id ) { - var attrId = id.replace( runescape, funescape ); - return function( elem ) { - var node = typeof elem.getAttributeNode !== "undefined" && - elem.getAttributeNode( "id" ); - return node && node.value === attrId; - }; - }; - - // Support: IE 6 - 7 only - // getElementById is not reliable as a find shortcut - Expr.find[ "ID" ] = function( id, context ) { - if ( typeof context.getElementById !== "undefined" && documentIsHTML ) { - var node, i, elems, - elem = context.getElementById( id ); - - if ( elem ) { - - // Verify the id attribute - node = elem.getAttributeNode( "id" ); - if ( node && node.value === id ) { - return [ elem ]; - } - - // Fall back on getElementsByName - elems = context.getElementsByName( id ); - i = 0; - while ( ( elem = elems[ i++ ] ) ) { - node = elem.getAttributeNode( "id" ); - if ( node && node.value === id ) { - return [ elem ]; - } - } - } - - return []; - } - }; - } - - // Tag - Expr.find[ "TAG" ] = support.getElementsByTagName ? - function( tag, context ) { - if ( typeof context.getElementsByTagName !== "undefined" ) { - return context.getElementsByTagName( tag ); - - // DocumentFragment nodes don't have gEBTN - } else if ( support.qsa ) { - return context.querySelectorAll( tag ); - } - } : - - function( tag, context ) { - var elem, - tmp = [], - i = 0, - - // By happy coincidence, a (broken) gEBTN appears on DocumentFragment nodes too - results = context.getElementsByTagName( tag ); - - // Filter out possible comments - if ( tag === "*" ) { - while ( ( elem = results[ i++ ] ) ) { - if ( elem.nodeType === 1 ) { - tmp.push( elem ); - } - } - - return tmp; - } - return results; - }; - - // Class - Expr.find[ "CLASS" ] = support.getElementsByClassName && function( className, context ) { - if ( typeof context.getElementsByClassName !== "undefined" && documentIsHTML ) { - return context.getElementsByClassName( className ); - } - }; - - /* QSA/matchesSelector - ---------------------------------------------------------------------- */ - - // QSA and matchesSelector support - - // matchesSelector(:active) reports false when true (IE9/Opera 11.5) - rbuggyMatches = []; - - // qSa(:focus) reports false when true (Chrome 21) - // We allow this because of a bug in IE8/9 that throws an error - // whenever `document.activeElement` is accessed on an iframe - // So, we allow :focus to pass through QSA all the time to avoid the IE error - // See https://bugs.jquery.com/ticket/13378 - rbuggyQSA = []; - - if ( ( support.qsa = rnative.test( document.querySelectorAll ) ) ) { - - // Build QSA regex - // Regex strategy adopted from Diego Perini - assert( function( el ) { - - var input; - - // Select is set to empty string on purpose - // This is to test IE's treatment of not explicitly - // setting a boolean content attribute, - // since its presence should be enough - // https://bugs.jquery.com/ticket/12359 - docElem.appendChild( el ).innerHTML = "" + - ""; - - // Support: IE8, Opera 11-12.16 - // Nothing should be selected when empty strings follow ^= or $= or *= - // The test attribute must be unknown in Opera but "safe" for WinRT - // https://msdn.microsoft.com/en-us/library/ie/hh465388.aspx#attribute_section - if ( el.querySelectorAll( "[msallowcapture^='']" ).length ) { - rbuggyQSA.push( "[*^$]=" + whitespace + "*(?:''|\"\")" ); - } - - // Support: IE8 - // Boolean attributes and "value" are not treated correctly - if ( !el.querySelectorAll( "[selected]" ).length ) { - rbuggyQSA.push( "\\[" + whitespace + "*(?:value|" + booleans + ")" ); - } - - // Support: Chrome<29, Android<4.4, Safari<7.0+, iOS<7.0+, PhantomJS<1.9.8+ - if ( !el.querySelectorAll( "[id~=" + expando + "-]" ).length ) { - rbuggyQSA.push( "~=" ); - } - - // Support: IE 11+, Edge 15 - 18+ - // IE 11/Edge don't find elements on a `[name='']` query in some cases. - // Adding a temporary attribute to the document before the selection works - // around the issue. - // Interestingly, IE 10 & older don't seem to have the issue. - input = document.createElement( "input" ); - input.setAttribute( "name", "" ); - el.appendChild( input ); - if ( !el.querySelectorAll( "[name='']" ).length ) { - rbuggyQSA.push( "\\[" + whitespace + "*name" + whitespace + "*=" + - whitespace + "*(?:''|\"\")" ); - } - - // Webkit/Opera - :checked should return selected option elements - // http://www.w3.org/TR/2011/REC-css3-selectors-20110929/#checked - // IE8 throws error here and will not see later tests - if ( !el.querySelectorAll( ":checked" ).length ) { - rbuggyQSA.push( ":checked" ); - } - - // Support: Safari 8+, iOS 8+ - // https://bugs.webkit.org/show_bug.cgi?id=136851 - // In-page `selector#id sibling-combinator selector` fails - if ( !el.querySelectorAll( "a#" + expando + "+*" ).length ) { - rbuggyQSA.push( ".#.+[+~]" ); - } - - // Support: Firefox <=3.6 - 5 only - // Old Firefox doesn't throw on a badly-escaped identifier. - el.querySelectorAll( "\\\f" ); - rbuggyQSA.push( "[\\r\\n\\f]" ); - } ); - - assert( function( el ) { - el.innerHTML = "" + - ""; - - // Support: Windows 8 Native Apps - // The type and name attributes are restricted during .innerHTML assignment - var input = document.createElement( "input" ); - input.setAttribute( "type", "hidden" ); - el.appendChild( input ).setAttribute( "name", "D" ); - - // Support: IE8 - // Enforce case-sensitivity of name attribute - if ( el.querySelectorAll( "[name=d]" ).length ) { - rbuggyQSA.push( "name" + whitespace + "*[*^$|!~]?=" ); - } - - // FF 3.5 - :enabled/:disabled and hidden elements (hidden elements are still enabled) - // IE8 throws error here and will not see later tests - if ( el.querySelectorAll( ":enabled" ).length !== 2 ) { - rbuggyQSA.push( ":enabled", ":disabled" ); - } - - // Support: IE9-11+ - // IE's :disabled selector does not pick up the children of disabled fieldsets - docElem.appendChild( el ).disabled = true; - if ( el.querySelectorAll( ":disabled" ).length !== 2 ) { - rbuggyQSA.push( ":enabled", ":disabled" ); - } - - // Support: Opera 10 - 11 only - // Opera 10-11 does not throw on post-comma invalid pseudos - el.querySelectorAll( "*,:x" ); - rbuggyQSA.push( ",.*:" ); - } ); - } - - if ( ( support.matchesSelector = rnative.test( ( matches = docElem.matches || - docElem.webkitMatchesSelector || - docElem.mozMatchesSelector || - docElem.oMatchesSelector || - docElem.msMatchesSelector ) ) ) ) { - - assert( function( el ) { - - // Check to see if it's possible to do matchesSelector - // on a disconnected node (IE 9) - support.disconnectedMatch = matches.call( el, "*" ); - - // This should fail with an exception - // Gecko does not error, returns false instead - matches.call( el, "[s!='']:x" ); - rbuggyMatches.push( "!=", pseudos ); - } ); - } - - rbuggyQSA = rbuggyQSA.length && new RegExp( rbuggyQSA.join( "|" ) ); - rbuggyMatches = rbuggyMatches.length && new RegExp( rbuggyMatches.join( "|" ) ); - - /* Contains - ---------------------------------------------------------------------- */ - hasCompare = rnative.test( docElem.compareDocumentPosition ); - - // Element contains another - // Purposefully self-exclusive - // As in, an element does not contain itself - contains = hasCompare || rnative.test( docElem.contains ) ? - function( a, b ) { - var adown = a.nodeType === 9 ? a.documentElement : a, - bup = b && b.parentNode; - return a === bup || !!( bup && bup.nodeType === 1 && ( - adown.contains ? - adown.contains( bup ) : - a.compareDocumentPosition && a.compareDocumentPosition( bup ) & 16 - ) ); - } : - function( a, b ) { - if ( b ) { - while ( ( b = b.parentNode ) ) { - if ( b === a ) { - return true; - } - } - } - return false; - }; - - /* Sorting - ---------------------------------------------------------------------- */ - - // Document order sorting - sortOrder = hasCompare ? - function( a, b ) { - - // Flag for duplicate removal - if ( a === b ) { - hasDuplicate = true; - return 0; - } - - // Sort on method existence if only one input has compareDocumentPosition - var compare = !a.compareDocumentPosition - !b.compareDocumentPosition; - if ( compare ) { - return compare; - } - - // Calculate position if both inputs belong to the same document - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - compare = ( a.ownerDocument || a ) == ( b.ownerDocument || b ) ? - a.compareDocumentPosition( b ) : - - // Otherwise we know they are disconnected - 1; - - // Disconnected nodes - if ( compare & 1 || - ( !support.sortDetached && b.compareDocumentPosition( a ) === compare ) ) { - - // Choose the first element that is related to our preferred document - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( a == document || a.ownerDocument == preferredDoc && - contains( preferredDoc, a ) ) { - return -1; - } - - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( b == document || b.ownerDocument == preferredDoc && - contains( preferredDoc, b ) ) { - return 1; - } - - // Maintain original order - return sortInput ? - ( indexOf( sortInput, a ) - indexOf( sortInput, b ) ) : - 0; - } - - return compare & 4 ? -1 : 1; - } : - function( a, b ) { - - // Exit early if the nodes are identical - if ( a === b ) { - hasDuplicate = true; - return 0; - } - - var cur, - i = 0, - aup = a.parentNode, - bup = b.parentNode, - ap = [ a ], - bp = [ b ]; - - // Parentless nodes are either documents or disconnected - if ( !aup || !bup ) { - - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - /* eslint-disable eqeqeq */ - return a == document ? -1 : - b == document ? 1 : - /* eslint-enable eqeqeq */ - aup ? -1 : - bup ? 1 : - sortInput ? - ( indexOf( sortInput, a ) - indexOf( sortInput, b ) ) : - 0; - - // If the nodes are siblings, we can do a quick check - } else if ( aup === bup ) { - return siblingCheck( a, b ); - } - - // Otherwise we need full lists of their ancestors for comparison - cur = a; - while ( ( cur = cur.parentNode ) ) { - ap.unshift( cur ); - } - cur = b; - while ( ( cur = cur.parentNode ) ) { - bp.unshift( cur ); - } - - // Walk down the tree looking for a discrepancy - while ( ap[ i ] === bp[ i ] ) { - i++; - } - - return i ? - - // Do a sibling check if the nodes have a common ancestor - siblingCheck( ap[ i ], bp[ i ] ) : - - // Otherwise nodes in our document sort first - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - /* eslint-disable eqeqeq */ - ap[ i ] == preferredDoc ? -1 : - bp[ i ] == preferredDoc ? 1 : - /* eslint-enable eqeqeq */ - 0; - }; - - return document; -}; - -Sizzle.matches = function( expr, elements ) { - return Sizzle( expr, null, null, elements ); -}; - -Sizzle.matchesSelector = function( elem, expr ) { - setDocument( elem ); - - if ( support.matchesSelector && documentIsHTML && - !nonnativeSelectorCache[ expr + " " ] && - ( !rbuggyMatches || !rbuggyMatches.test( expr ) ) && - ( !rbuggyQSA || !rbuggyQSA.test( expr ) ) ) { - - try { - var ret = matches.call( elem, expr ); - - // IE 9's matchesSelector returns false on disconnected nodes - if ( ret || support.disconnectedMatch || - - // As well, disconnected nodes are said to be in a document - // fragment in IE 9 - elem.document && elem.document.nodeType !== 11 ) { - return ret; - } - } catch ( e ) { - nonnativeSelectorCache( expr, true ); - } - } - - return Sizzle( expr, document, null, [ elem ] ).length > 0; -}; - -Sizzle.contains = function( context, elem ) { - - // Set document vars if needed - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( ( context.ownerDocument || context ) != document ) { - setDocument( context ); - } - return contains( context, elem ); -}; - -Sizzle.attr = function( elem, name ) { - - // Set document vars if needed - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( ( elem.ownerDocument || elem ) != document ) { - setDocument( elem ); - } - - var fn = Expr.attrHandle[ name.toLowerCase() ], - - // Don't get fooled by Object.prototype properties (jQuery #13807) - val = fn && hasOwn.call( Expr.attrHandle, name.toLowerCase() ) ? - fn( elem, name, !documentIsHTML ) : - undefined; - - return val !== undefined ? - val : - support.attributes || !documentIsHTML ? - elem.getAttribute( name ) : - ( val = elem.getAttributeNode( name ) ) && val.specified ? - val.value : - null; -}; - -Sizzle.escape = function( sel ) { - return ( sel + "" ).replace( rcssescape, fcssescape ); -}; - -Sizzle.error = function( msg ) { - throw new Error( "Syntax error, unrecognized expression: " + msg ); -}; - -/** - * Document sorting and removing duplicates - * @param {ArrayLike} results - */ -Sizzle.uniqueSort = function( results ) { - var elem, - duplicates = [], - j = 0, - i = 0; - - // Unless we *know* we can detect duplicates, assume their presence - hasDuplicate = !support.detectDuplicates; - sortInput = !support.sortStable && results.slice( 0 ); - results.sort( sortOrder ); - - if ( hasDuplicate ) { - while ( ( elem = results[ i++ ] ) ) { - if ( elem === results[ i ] ) { - j = duplicates.push( i ); - } - } - while ( j-- ) { - results.splice( duplicates[ j ], 1 ); - } - } - - // Clear input after sorting to release objects - // See https://github.com/jquery/sizzle/pull/225 - sortInput = null; - - return results; -}; - -/** - * Utility function for retrieving the text value of an array of DOM nodes - * @param {Array|Element} elem - */ -getText = Sizzle.getText = function( elem ) { - var node, - ret = "", - i = 0, - nodeType = elem.nodeType; - - if ( !nodeType ) { - - // If no nodeType, this is expected to be an array - while ( ( node = elem[ i++ ] ) ) { - - // Do not traverse comment nodes - ret += getText( node ); - } - } else if ( nodeType === 1 || nodeType === 9 || nodeType === 11 ) { - - // Use textContent for elements - // innerText usage removed for consistency of new lines (jQuery #11153) - if ( typeof elem.textContent === "string" ) { - return elem.textContent; - } else { - - // Traverse its children - for ( elem = elem.firstChild; elem; elem = elem.nextSibling ) { - ret += getText( elem ); - } - } - } else if ( nodeType === 3 || nodeType === 4 ) { - return elem.nodeValue; - } - - // Do not include comment or processing instruction nodes - - return ret; -}; - -Expr = Sizzle.selectors = { - - // Can be adjusted by the user - cacheLength: 50, - - createPseudo: markFunction, - - match: matchExpr, - - attrHandle: {}, - - find: {}, - - relative: { - ">": { dir: "parentNode", first: true }, - " ": { dir: "parentNode" }, - "+": { dir: "previousSibling", first: true }, - "~": { dir: "previousSibling" } - }, - - preFilter: { - "ATTR": function( match ) { - match[ 1 ] = match[ 1 ].replace( runescape, funescape ); - - // Move the given value to match[3] whether quoted or unquoted - match[ 3 ] = ( match[ 3 ] || match[ 4 ] || - match[ 5 ] || "" ).replace( runescape, funescape ); - - if ( match[ 2 ] === "~=" ) { - match[ 3 ] = " " + match[ 3 ] + " "; - } - - return match.slice( 0, 4 ); - }, - - "CHILD": function( match ) { - - /* matches from matchExpr["CHILD"] - 1 type (only|nth|...) - 2 what (child|of-type) - 3 argument (even|odd|\d*|\d*n([+-]\d+)?|...) - 4 xn-component of xn+y argument ([+-]?\d*n|) - 5 sign of xn-component - 6 x of xn-component - 7 sign of y-component - 8 y of y-component - */ - match[ 1 ] = match[ 1 ].toLowerCase(); - - if ( match[ 1 ].slice( 0, 3 ) === "nth" ) { - - // nth-* requires argument - if ( !match[ 3 ] ) { - Sizzle.error( match[ 0 ] ); - } - - // numeric x and y parameters for Expr.filter.CHILD - // remember that false/true cast respectively to 0/1 - match[ 4 ] = +( match[ 4 ] ? - match[ 5 ] + ( match[ 6 ] || 1 ) : - 2 * ( match[ 3 ] === "even" || match[ 3 ] === "odd" ) ); - match[ 5 ] = +( ( match[ 7 ] + match[ 8 ] ) || match[ 3 ] === "odd" ); - - // other types prohibit arguments - } else if ( match[ 3 ] ) { - Sizzle.error( match[ 0 ] ); - } - - return match; - }, - - "PSEUDO": function( match ) { - var excess, - unquoted = !match[ 6 ] && match[ 2 ]; - - if ( matchExpr[ "CHILD" ].test( match[ 0 ] ) ) { - return null; - } - - // Accept quoted arguments as-is - if ( match[ 3 ] ) { - match[ 2 ] = match[ 4 ] || match[ 5 ] || ""; - - // Strip excess characters from unquoted arguments - } else if ( unquoted && rpseudo.test( unquoted ) && - - // Get excess from tokenize (recursively) - ( excess = tokenize( unquoted, true ) ) && - - // advance to the next closing parenthesis - ( excess = unquoted.indexOf( ")", unquoted.length - excess ) - unquoted.length ) ) { - - // excess is a negative index - match[ 0 ] = match[ 0 ].slice( 0, excess ); - match[ 2 ] = unquoted.slice( 0, excess ); - } - - // Return only captures needed by the pseudo filter method (type and argument) - return match.slice( 0, 3 ); - } - }, - - filter: { - - "TAG": function( nodeNameSelector ) { - var nodeName = nodeNameSelector.replace( runescape, funescape ).toLowerCase(); - return nodeNameSelector === "*" ? - function() { - return true; - } : - function( elem ) { - return elem.nodeName && elem.nodeName.toLowerCase() === nodeName; - }; - }, - - "CLASS": function( className ) { - var pattern = classCache[ className + " " ]; - - return pattern || - ( pattern = new RegExp( "(^|" + whitespace + - ")" + className + "(" + whitespace + "|$)" ) ) && classCache( - className, function( elem ) { - return pattern.test( - typeof elem.className === "string" && elem.className || - typeof elem.getAttribute !== "undefined" && - elem.getAttribute( "class" ) || - "" - ); - } ); - }, - - "ATTR": function( name, operator, check ) { - return function( elem ) { - var result = Sizzle.attr( elem, name ); - - if ( result == null ) { - return operator === "!="; - } - if ( !operator ) { - return true; - } - - result += ""; - - /* eslint-disable max-len */ - - return operator === "=" ? result === check : - operator === "!=" ? result !== check : - operator === "^=" ? check && result.indexOf( check ) === 0 : - operator === "*=" ? check && result.indexOf( check ) > -1 : - operator === "$=" ? check && result.slice( -check.length ) === check : - operator === "~=" ? ( " " + result.replace( rwhitespace, " " ) + " " ).indexOf( check ) > -1 : - operator === "|=" ? result === check || result.slice( 0, check.length + 1 ) === check + "-" : - false; - /* eslint-enable max-len */ - - }; - }, - - "CHILD": function( type, what, _argument, first, last ) { - var simple = type.slice( 0, 3 ) !== "nth", - forward = type.slice( -4 ) !== "last", - ofType = what === "of-type"; - - return first === 1 && last === 0 ? - - // Shortcut for :nth-*(n) - function( elem ) { - return !!elem.parentNode; - } : - - function( elem, _context, xml ) { - var cache, uniqueCache, outerCache, node, nodeIndex, start, - dir = simple !== forward ? "nextSibling" : "previousSibling", - parent = elem.parentNode, - name = ofType && elem.nodeName.toLowerCase(), - useCache = !xml && !ofType, - diff = false; - - if ( parent ) { - - // :(first|last|only)-(child|of-type) - if ( simple ) { - while ( dir ) { - node = elem; - while ( ( node = node[ dir ] ) ) { - if ( ofType ? - node.nodeName.toLowerCase() === name : - node.nodeType === 1 ) { - - return false; - } - } - - // Reverse direction for :only-* (if we haven't yet done so) - start = dir = type === "only" && !start && "nextSibling"; - } - return true; - } - - start = [ forward ? parent.firstChild : parent.lastChild ]; - - // non-xml :nth-child(...) stores cache data on `parent` - if ( forward && useCache ) { - - // Seek `elem` from a previously-cached index - - // ...in a gzip-friendly way - node = parent; - outerCache = node[ expando ] || ( node[ expando ] = {} ); - - // Support: IE <9 only - // Defend against cloned attroperties (jQuery gh-1709) - uniqueCache = outerCache[ node.uniqueID ] || - ( outerCache[ node.uniqueID ] = {} ); - - cache = uniqueCache[ type ] || []; - nodeIndex = cache[ 0 ] === dirruns && cache[ 1 ]; - diff = nodeIndex && cache[ 2 ]; - node = nodeIndex && parent.childNodes[ nodeIndex ]; - - while ( ( node = ++nodeIndex && node && node[ dir ] || - - // Fallback to seeking `elem` from the start - ( diff = nodeIndex = 0 ) || start.pop() ) ) { - - // When found, cache indexes on `parent` and break - if ( node.nodeType === 1 && ++diff && node === elem ) { - uniqueCache[ type ] = [ dirruns, nodeIndex, diff ]; - break; - } - } - - } else { - - // Use previously-cached element index if available - if ( useCache ) { - - // ...in a gzip-friendly way - node = elem; - outerCache = node[ expando ] || ( node[ expando ] = {} ); - - // Support: IE <9 only - // Defend against cloned attroperties (jQuery gh-1709) - uniqueCache = outerCache[ node.uniqueID ] || - ( outerCache[ node.uniqueID ] = {} ); - - cache = uniqueCache[ type ] || []; - nodeIndex = cache[ 0 ] === dirruns && cache[ 1 ]; - diff = nodeIndex; - } - - // xml :nth-child(...) - // or :nth-last-child(...) or :nth(-last)?-of-type(...) - if ( diff === false ) { - - // Use the same loop as above to seek `elem` from the start - while ( ( node = ++nodeIndex && node && node[ dir ] || - ( diff = nodeIndex = 0 ) || start.pop() ) ) { - - if ( ( ofType ? - node.nodeName.toLowerCase() === name : - node.nodeType === 1 ) && - ++diff ) { - - // Cache the index of each encountered element - if ( useCache ) { - outerCache = node[ expando ] || - ( node[ expando ] = {} ); - - // Support: IE <9 only - // Defend against cloned attroperties (jQuery gh-1709) - uniqueCache = outerCache[ node.uniqueID ] || - ( outerCache[ node.uniqueID ] = {} ); - - uniqueCache[ type ] = [ dirruns, diff ]; - } - - if ( node === elem ) { - break; - } - } - } - } - } - - // Incorporate the offset, then check against cycle size - diff -= last; - return diff === first || ( diff % first === 0 && diff / first >= 0 ); - } - }; - }, - - "PSEUDO": function( pseudo, argument ) { - - // pseudo-class names are case-insensitive - // http://www.w3.org/TR/selectors/#pseudo-classes - // Prioritize by case sensitivity in case custom pseudos are added with uppercase letters - // Remember that setFilters inherits from pseudos - var args, - fn = Expr.pseudos[ pseudo ] || Expr.setFilters[ pseudo.toLowerCase() ] || - Sizzle.error( "unsupported pseudo: " + pseudo ); - - // The user may use createPseudo to indicate that - // arguments are needed to create the filter function - // just as Sizzle does - if ( fn[ expando ] ) { - return fn( argument ); - } - - // But maintain support for old signatures - if ( fn.length > 1 ) { - args = [ pseudo, pseudo, "", argument ]; - return Expr.setFilters.hasOwnProperty( pseudo.toLowerCase() ) ? - markFunction( function( seed, matches ) { - var idx, - matched = fn( seed, argument ), - i = matched.length; - while ( i-- ) { - idx = indexOf( seed, matched[ i ] ); - seed[ idx ] = !( matches[ idx ] = matched[ i ] ); - } - } ) : - function( elem ) { - return fn( elem, 0, args ); - }; - } - - return fn; - } - }, - - pseudos: { - - // Potentially complex pseudos - "not": markFunction( function( selector ) { - - // Trim the selector passed to compile - // to avoid treating leading and trailing - // spaces as combinators - var input = [], - results = [], - matcher = compile( selector.replace( rtrim, "$1" ) ); - - return matcher[ expando ] ? - markFunction( function( seed, matches, _context, xml ) { - var elem, - unmatched = matcher( seed, null, xml, [] ), - i = seed.length; - - // Match elements unmatched by `matcher` - while ( i-- ) { - if ( ( elem = unmatched[ i ] ) ) { - seed[ i ] = !( matches[ i ] = elem ); - } - } - } ) : - function( elem, _context, xml ) { - input[ 0 ] = elem; - matcher( input, null, xml, results ); - - // Don't keep the element (issue #299) - input[ 0 ] = null; - return !results.pop(); - }; - } ), - - "has": markFunction( function( selector ) { - return function( elem ) { - return Sizzle( selector, elem ).length > 0; - }; - } ), - - "contains": markFunction( function( text ) { - text = text.replace( runescape, funescape ); - return function( elem ) { - return ( elem.textContent || getText( elem ) ).indexOf( text ) > -1; - }; - } ), - - // "Whether an element is represented by a :lang() selector - // is based solely on the element's language value - // being equal to the identifier C, - // or beginning with the identifier C immediately followed by "-". - // The matching of C against the element's language value is performed case-insensitively. - // The identifier C does not have to be a valid language name." - // http://www.w3.org/TR/selectors/#lang-pseudo - "lang": markFunction( function( lang ) { - - // lang value must be a valid identifier - if ( !ridentifier.test( lang || "" ) ) { - Sizzle.error( "unsupported lang: " + lang ); - } - lang = lang.replace( runescape, funescape ).toLowerCase(); - return function( elem ) { - var elemLang; - do { - if ( ( elemLang = documentIsHTML ? - elem.lang : - elem.getAttribute( "xml:lang" ) || elem.getAttribute( "lang" ) ) ) { - - elemLang = elemLang.toLowerCase(); - return elemLang === lang || elemLang.indexOf( lang + "-" ) === 0; - } - } while ( ( elem = elem.parentNode ) && elem.nodeType === 1 ); - return false; - }; - } ), - - // Miscellaneous - "target": function( elem ) { - var hash = window.location && window.location.hash; - return hash && hash.slice( 1 ) === elem.id; - }, - - "root": function( elem ) { - return elem === docElem; - }, - - "focus": function( elem ) { - return elem === document.activeElement && - ( !document.hasFocus || document.hasFocus() ) && - !!( elem.type || elem.href || ~elem.tabIndex ); - }, - - // Boolean properties - "enabled": createDisabledPseudo( false ), - "disabled": createDisabledPseudo( true ), - - "checked": function( elem ) { - - // In CSS3, :checked should return both checked and selected elements - // http://www.w3.org/TR/2011/REC-css3-selectors-20110929/#checked - var nodeName = elem.nodeName.toLowerCase(); - return ( nodeName === "input" && !!elem.checked ) || - ( nodeName === "option" && !!elem.selected ); - }, - - "selected": function( elem ) { - - // Accessing this property makes selected-by-default - // options in Safari work properly - if ( elem.parentNode ) { - // eslint-disable-next-line no-unused-expressions - elem.parentNode.selectedIndex; - } - - return elem.selected === true; - }, - - // Contents - "empty": function( elem ) { - - // http://www.w3.org/TR/selectors/#empty-pseudo - // :empty is negated by element (1) or content nodes (text: 3; cdata: 4; entity ref: 5), - // but not by others (comment: 8; processing instruction: 7; etc.) - // nodeType < 6 works because attributes (2) do not appear as children - for ( elem = elem.firstChild; elem; elem = elem.nextSibling ) { - if ( elem.nodeType < 6 ) { - return false; - } - } - return true; - }, - - "parent": function( elem ) { - return !Expr.pseudos[ "empty" ]( elem ); - }, - - // Element/input types - "header": function( elem ) { - return rheader.test( elem.nodeName ); - }, - - "input": function( elem ) { - return rinputs.test( elem.nodeName ); - }, - - "button": function( elem ) { - var name = elem.nodeName.toLowerCase(); - return name === "input" && elem.type === "button" || name === "button"; - }, - - "text": function( elem ) { - var attr; - return elem.nodeName.toLowerCase() === "input" && - elem.type === "text" && - - // Support: IE<8 - // New HTML5 attribute values (e.g., "search") appear with elem.type === "text" - ( ( attr = elem.getAttribute( "type" ) ) == null || - attr.toLowerCase() === "text" ); - }, - - // Position-in-collection - "first": createPositionalPseudo( function() { - return [ 0 ]; - } ), - - "last": createPositionalPseudo( function( _matchIndexes, length ) { - return [ length - 1 ]; - } ), - - "eq": createPositionalPseudo( function( _matchIndexes, length, argument ) { - return [ argument < 0 ? argument + length : argument ]; - } ), - - "even": createPositionalPseudo( function( matchIndexes, length ) { - var i = 0; - for ( ; i < length; i += 2 ) { - matchIndexes.push( i ); - } - return matchIndexes; - } ), - - "odd": createPositionalPseudo( function( matchIndexes, length ) { - var i = 1; - for ( ; i < length; i += 2 ) { - matchIndexes.push( i ); - } - return matchIndexes; - } ), - - "lt": createPositionalPseudo( function( matchIndexes, length, argument ) { - var i = argument < 0 ? - argument + length : - argument > length ? - length : - argument; - for ( ; --i >= 0; ) { - matchIndexes.push( i ); - } - return matchIndexes; - } ), - - "gt": createPositionalPseudo( function( matchIndexes, length, argument ) { - var i = argument < 0 ? argument + length : argument; - for ( ; ++i < length; ) { - matchIndexes.push( i ); - } - return matchIndexes; - } ) - } -}; - -Expr.pseudos[ "nth" ] = Expr.pseudos[ "eq" ]; - -// Add button/input type pseudos -for ( i in { radio: true, checkbox: true, file: true, password: true, image: true } ) { - Expr.pseudos[ i ] = createInputPseudo( i ); -} -for ( i in { submit: true, reset: true } ) { - Expr.pseudos[ i ] = createButtonPseudo( i ); -} - -// Easy API for creating new setFilters -function setFilters() {} -setFilters.prototype = Expr.filters = Expr.pseudos; -Expr.setFilters = new setFilters(); - -tokenize = Sizzle.tokenize = function( selector, parseOnly ) { - var matched, match, tokens, type, - soFar, groups, preFilters, - cached = tokenCache[ selector + " " ]; - - if ( cached ) { - return parseOnly ? 0 : cached.slice( 0 ); - } - - soFar = selector; - groups = []; - preFilters = Expr.preFilter; - - while ( soFar ) { - - // Comma and first run - if ( !matched || ( match = rcomma.exec( soFar ) ) ) { - if ( match ) { - - // Don't consume trailing commas as valid - soFar = soFar.slice( match[ 0 ].length ) || soFar; - } - groups.push( ( tokens = [] ) ); - } - - matched = false; - - // Combinators - if ( ( match = rcombinators.exec( soFar ) ) ) { - matched = match.shift(); - tokens.push( { - value: matched, - - // Cast descendant combinators to space - type: match[ 0 ].replace( rtrim, " " ) - } ); - soFar = soFar.slice( matched.length ); - } - - // Filters - for ( type in Expr.filter ) { - if ( ( match = matchExpr[ type ].exec( soFar ) ) && ( !preFilters[ type ] || - ( match = preFilters[ type ]( match ) ) ) ) { - matched = match.shift(); - tokens.push( { - value: matched, - type: type, - matches: match - } ); - soFar = soFar.slice( matched.length ); - } - } - - if ( !matched ) { - break; - } - } - - // Return the length of the invalid excess - // if we're just parsing - // Otherwise, throw an error or return tokens - return parseOnly ? - soFar.length : - soFar ? - Sizzle.error( selector ) : - - // Cache the tokens - tokenCache( selector, groups ).slice( 0 ); -}; - -function toSelector( tokens ) { - var i = 0, - len = tokens.length, - selector = ""; - for ( ; i < len; i++ ) { - selector += tokens[ i ].value; - } - return selector; -} - -function addCombinator( matcher, combinator, base ) { - var dir = combinator.dir, - skip = combinator.next, - key = skip || dir, - checkNonElements = base && key === "parentNode", - doneName = done++; - - return combinator.first ? - - // Check against closest ancestor/preceding element - function( elem, context, xml ) { - while ( ( elem = elem[ dir ] ) ) { - if ( elem.nodeType === 1 || checkNonElements ) { - return matcher( elem, context, xml ); - } - } - return false; - } : - - // Check against all ancestor/preceding elements - function( elem, context, xml ) { - var oldCache, uniqueCache, outerCache, - newCache = [ dirruns, doneName ]; - - // We can't set arbitrary data on XML nodes, so they don't benefit from combinator caching - if ( xml ) { - while ( ( elem = elem[ dir ] ) ) { - if ( elem.nodeType === 1 || checkNonElements ) { - if ( matcher( elem, context, xml ) ) { - return true; - } - } - } - } else { - while ( ( elem = elem[ dir ] ) ) { - if ( elem.nodeType === 1 || checkNonElements ) { - outerCache = elem[ expando ] || ( elem[ expando ] = {} ); - - // Support: IE <9 only - // Defend against cloned attroperties (jQuery gh-1709) - uniqueCache = outerCache[ elem.uniqueID ] || - ( outerCache[ elem.uniqueID ] = {} ); - - if ( skip && skip === elem.nodeName.toLowerCase() ) { - elem = elem[ dir ] || elem; - } else if ( ( oldCache = uniqueCache[ key ] ) && - oldCache[ 0 ] === dirruns && oldCache[ 1 ] === doneName ) { - - // Assign to newCache so results back-propagate to previous elements - return ( newCache[ 2 ] = oldCache[ 2 ] ); - } else { - - // Reuse newcache so results back-propagate to previous elements - uniqueCache[ key ] = newCache; - - // A match means we're done; a fail means we have to keep checking - if ( ( newCache[ 2 ] = matcher( elem, context, xml ) ) ) { - return true; - } - } - } - } - } - return false; - }; -} - -function elementMatcher( matchers ) { - return matchers.length > 1 ? - function( elem, context, xml ) { - var i = matchers.length; - while ( i-- ) { - if ( !matchers[ i ]( elem, context, xml ) ) { - return false; - } - } - return true; - } : - matchers[ 0 ]; -} - -function multipleContexts( selector, contexts, results ) { - var i = 0, - len = contexts.length; - for ( ; i < len; i++ ) { - Sizzle( selector, contexts[ i ], results ); - } - return results; -} - -function condense( unmatched, map, filter, context, xml ) { - var elem, - newUnmatched = [], - i = 0, - len = unmatched.length, - mapped = map != null; - - for ( ; i < len; i++ ) { - if ( ( elem = unmatched[ i ] ) ) { - if ( !filter || filter( elem, context, xml ) ) { - newUnmatched.push( elem ); - if ( mapped ) { - map.push( i ); - } - } - } - } - - return newUnmatched; -} - -function setMatcher( preFilter, selector, matcher, postFilter, postFinder, postSelector ) { - if ( postFilter && !postFilter[ expando ] ) { - postFilter = setMatcher( postFilter ); - } - if ( postFinder && !postFinder[ expando ] ) { - postFinder = setMatcher( postFinder, postSelector ); - } - return markFunction( function( seed, results, context, xml ) { - var temp, i, elem, - preMap = [], - postMap = [], - preexisting = results.length, - - // Get initial elements from seed or context - elems = seed || multipleContexts( - selector || "*", - context.nodeType ? [ context ] : context, - [] - ), - - // Prefilter to get matcher input, preserving a map for seed-results synchronization - matcherIn = preFilter && ( seed || !selector ) ? - condense( elems, preMap, preFilter, context, xml ) : - elems, - - matcherOut = matcher ? - - // If we have a postFinder, or filtered seed, or non-seed postFilter or preexisting results, - postFinder || ( seed ? preFilter : preexisting || postFilter ) ? - - // ...intermediate processing is necessary - [] : - - // ...otherwise use results directly - results : - matcherIn; - - // Find primary matches - if ( matcher ) { - matcher( matcherIn, matcherOut, context, xml ); - } - - // Apply postFilter - if ( postFilter ) { - temp = condense( matcherOut, postMap ); - postFilter( temp, [], context, xml ); - - // Un-match failing elements by moving them back to matcherIn - i = temp.length; - while ( i-- ) { - if ( ( elem = temp[ i ] ) ) { - matcherOut[ postMap[ i ] ] = !( matcherIn[ postMap[ i ] ] = elem ); - } - } - } - - if ( seed ) { - if ( postFinder || preFilter ) { - if ( postFinder ) { - - // Get the final matcherOut by condensing this intermediate into postFinder contexts - temp = []; - i = matcherOut.length; - while ( i-- ) { - if ( ( elem = matcherOut[ i ] ) ) { - - // Restore matcherIn since elem is not yet a final match - temp.push( ( matcherIn[ i ] = elem ) ); - } - } - postFinder( null, ( matcherOut = [] ), temp, xml ); - } - - // Move matched elements from seed to results to keep them synchronized - i = matcherOut.length; - while ( i-- ) { - if ( ( elem = matcherOut[ i ] ) && - ( temp = postFinder ? indexOf( seed, elem ) : preMap[ i ] ) > -1 ) { - - seed[ temp ] = !( results[ temp ] = elem ); - } - } - } - - // Add elements to results, through postFinder if defined - } else { - matcherOut = condense( - matcherOut === results ? - matcherOut.splice( preexisting, matcherOut.length ) : - matcherOut - ); - if ( postFinder ) { - postFinder( null, results, matcherOut, xml ); - } else { - push.apply( results, matcherOut ); - } - } - } ); -} - -function matcherFromTokens( tokens ) { - var checkContext, matcher, j, - len = tokens.length, - leadingRelative = Expr.relative[ tokens[ 0 ].type ], - implicitRelative = leadingRelative || Expr.relative[ " " ], - i = leadingRelative ? 1 : 0, - - // The foundational matcher ensures that elements are reachable from top-level context(s) - matchContext = addCombinator( function( elem ) { - return elem === checkContext; - }, implicitRelative, true ), - matchAnyContext = addCombinator( function( elem ) { - return indexOf( checkContext, elem ) > -1; - }, implicitRelative, true ), - matchers = [ function( elem, context, xml ) { - var ret = ( !leadingRelative && ( xml || context !== outermostContext ) ) || ( - ( checkContext = context ).nodeType ? - matchContext( elem, context, xml ) : - matchAnyContext( elem, context, xml ) ); - - // Avoid hanging onto element (issue #299) - checkContext = null; - return ret; - } ]; - - for ( ; i < len; i++ ) { - if ( ( matcher = Expr.relative[ tokens[ i ].type ] ) ) { - matchers = [ addCombinator( elementMatcher( matchers ), matcher ) ]; - } else { - matcher = Expr.filter[ tokens[ i ].type ].apply( null, tokens[ i ].matches ); - - // Return special upon seeing a positional matcher - if ( matcher[ expando ] ) { - - // Find the next relative operator (if any) for proper handling - j = ++i; - for ( ; j < len; j++ ) { - if ( Expr.relative[ tokens[ j ].type ] ) { - break; - } - } - return setMatcher( - i > 1 && elementMatcher( matchers ), - i > 1 && toSelector( - - // If the preceding token was a descendant combinator, insert an implicit any-element `*` - tokens - .slice( 0, i - 1 ) - .concat( { value: tokens[ i - 2 ].type === " " ? "*" : "" } ) - ).replace( rtrim, "$1" ), - matcher, - i < j && matcherFromTokens( tokens.slice( i, j ) ), - j < len && matcherFromTokens( ( tokens = tokens.slice( j ) ) ), - j < len && toSelector( tokens ) - ); - } - matchers.push( matcher ); - } - } - - return elementMatcher( matchers ); -} - -function matcherFromGroupMatchers( elementMatchers, setMatchers ) { - var bySet = setMatchers.length > 0, - byElement = elementMatchers.length > 0, - superMatcher = function( seed, context, xml, results, outermost ) { - var elem, j, matcher, - matchedCount = 0, - i = "0", - unmatched = seed && [], - setMatched = [], - contextBackup = outermostContext, - - // We must always have either seed elements or outermost context - elems = seed || byElement && Expr.find[ "TAG" ]( "*", outermost ), - - // Use integer dirruns iff this is the outermost matcher - dirrunsUnique = ( dirruns += contextBackup == null ? 1 : Math.random() || 0.1 ), - len = elems.length; - - if ( outermost ) { - - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - outermostContext = context == document || context || outermost; - } - - // Add elements passing elementMatchers directly to results - // Support: IE<9, Safari - // Tolerate NodeList properties (IE: "length"; Safari: ) matching elements by id - for ( ; i !== len && ( elem = elems[ i ] ) != null; i++ ) { - if ( byElement && elem ) { - j = 0; - - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( !context && elem.ownerDocument != document ) { - setDocument( elem ); - xml = !documentIsHTML; - } - while ( ( matcher = elementMatchers[ j++ ] ) ) { - if ( matcher( elem, context || document, xml ) ) { - results.push( elem ); - break; - } - } - if ( outermost ) { - dirruns = dirrunsUnique; - } - } - - // Track unmatched elements for set filters - if ( bySet ) { - - // They will have gone through all possible matchers - if ( ( elem = !matcher && elem ) ) { - matchedCount--; - } - - // Lengthen the array for every element, matched or not - if ( seed ) { - unmatched.push( elem ); - } - } - } - - // `i` is now the count of elements visited above, and adding it to `matchedCount` - // makes the latter nonnegative. - matchedCount += i; - - // Apply set filters to unmatched elements - // NOTE: This can be skipped if there are no unmatched elements (i.e., `matchedCount` - // equals `i`), unless we didn't visit _any_ elements in the above loop because we have - // no element matchers and no seed. - // Incrementing an initially-string "0" `i` allows `i` to remain a string only in that - // case, which will result in a "00" `matchedCount` that differs from `i` but is also - // numerically zero. - if ( bySet && i !== matchedCount ) { - j = 0; - while ( ( matcher = setMatchers[ j++ ] ) ) { - matcher( unmatched, setMatched, context, xml ); - } - - if ( seed ) { - - // Reintegrate element matches to eliminate the need for sorting - if ( matchedCount > 0 ) { - while ( i-- ) { - if ( !( unmatched[ i ] || setMatched[ i ] ) ) { - setMatched[ i ] = pop.call( results ); - } - } - } - - // Discard index placeholder values to get only actual matches - setMatched = condense( setMatched ); - } - - // Add matches to results - push.apply( results, setMatched ); - - // Seedless set matches succeeding multiple successful matchers stipulate sorting - if ( outermost && !seed && setMatched.length > 0 && - ( matchedCount + setMatchers.length ) > 1 ) { - - Sizzle.uniqueSort( results ); - } - } - - // Override manipulation of globals by nested matchers - if ( outermost ) { - dirruns = dirrunsUnique; - outermostContext = contextBackup; - } - - return unmatched; - }; - - return bySet ? - markFunction( superMatcher ) : - superMatcher; -} - -compile = Sizzle.compile = function( selector, match /* Internal Use Only */ ) { - var i, - setMatchers = [], - elementMatchers = [], - cached = compilerCache[ selector + " " ]; - - if ( !cached ) { - - // Generate a function of recursive functions that can be used to check each element - if ( !match ) { - match = tokenize( selector ); - } - i = match.length; - while ( i-- ) { - cached = matcherFromTokens( match[ i ] ); - if ( cached[ expando ] ) { - setMatchers.push( cached ); - } else { - elementMatchers.push( cached ); - } - } - - // Cache the compiled function - cached = compilerCache( - selector, - matcherFromGroupMatchers( elementMatchers, setMatchers ) - ); - - // Save selector and tokenization - cached.selector = selector; - } - return cached; -}; - -/** - * A low-level selection function that works with Sizzle's compiled - * selector functions - * @param {String|Function} selector A selector or a pre-compiled - * selector function built with Sizzle.compile - * @param {Element} context - * @param {Array} [results] - * @param {Array} [seed] A set of elements to match against - */ -select = Sizzle.select = function( selector, context, results, seed ) { - var i, tokens, token, type, find, - compiled = typeof selector === "function" && selector, - match = !seed && tokenize( ( selector = compiled.selector || selector ) ); - - results = results || []; - - // Try to minimize operations if there is only one selector in the list and no seed - // (the latter of which guarantees us context) - if ( match.length === 1 ) { - - // Reduce context if the leading compound selector is an ID - tokens = match[ 0 ] = match[ 0 ].slice( 0 ); - if ( tokens.length > 2 && ( token = tokens[ 0 ] ).type === "ID" && - context.nodeType === 9 && documentIsHTML && Expr.relative[ tokens[ 1 ].type ] ) { - - context = ( Expr.find[ "ID" ]( token.matches[ 0 ] - .replace( runescape, funescape ), context ) || [] )[ 0 ]; - if ( !context ) { - return results; - - // Precompiled matchers will still verify ancestry, so step up a level - } else if ( compiled ) { - context = context.parentNode; - } - - selector = selector.slice( tokens.shift().value.length ); - } - - // Fetch a seed set for right-to-left matching - i = matchExpr[ "needsContext" ].test( selector ) ? 0 : tokens.length; - while ( i-- ) { - token = tokens[ i ]; - - // Abort if we hit a combinator - if ( Expr.relative[ ( type = token.type ) ] ) { - break; - } - if ( ( find = Expr.find[ type ] ) ) { - - // Search, expanding context for leading sibling combinators - if ( ( seed = find( - token.matches[ 0 ].replace( runescape, funescape ), - rsibling.test( tokens[ 0 ].type ) && testContext( context.parentNode ) || - context - ) ) ) { - - // If seed is empty or no tokens remain, we can return early - tokens.splice( i, 1 ); - selector = seed.length && toSelector( tokens ); - if ( !selector ) { - push.apply( results, seed ); - return results; - } - - break; - } - } - } - } - - // Compile and execute a filtering function if one is not provided - // Provide `match` to avoid retokenization if we modified the selector above - ( compiled || compile( selector, match ) )( - seed, - context, - !documentIsHTML, - results, - !context || rsibling.test( selector ) && testContext( context.parentNode ) || context - ); - return results; -}; - -// One-time assignments - -// Sort stability -support.sortStable = expando.split( "" ).sort( sortOrder ).join( "" ) === expando; - -// Support: Chrome 14-35+ -// Always assume duplicates if they aren't passed to the comparison function -support.detectDuplicates = !!hasDuplicate; - -// Initialize against the default document -setDocument(); - -// Support: Webkit<537.32 - Safari 6.0.3/Chrome 25 (fixed in Chrome 27) -// Detached nodes confoundingly follow *each other* -support.sortDetached = assert( function( el ) { - - // Should return 1, but returns 4 (following) - return el.compareDocumentPosition( document.createElement( "fieldset" ) ) & 1; -} ); - -// Support: IE<8 -// Prevent attribute/property "interpolation" -// https://msdn.microsoft.com/en-us/library/ms536429%28VS.85%29.aspx -if ( !assert( function( el ) { - el.innerHTML = ""; - return el.firstChild.getAttribute( "href" ) === "#"; -} ) ) { - addHandle( "type|href|height|width", function( elem, name, isXML ) { - if ( !isXML ) { - return elem.getAttribute( name, name.toLowerCase() === "type" ? 1 : 2 ); - } - } ); -} - -// Support: IE<9 -// Use defaultValue in place of getAttribute("value") -if ( !support.attributes || !assert( function( el ) { - el.innerHTML = ""; - el.firstChild.setAttribute( "value", "" ); - return el.firstChild.getAttribute( "value" ) === ""; -} ) ) { - addHandle( "value", function( elem, _name, isXML ) { - if ( !isXML && elem.nodeName.toLowerCase() === "input" ) { - return elem.defaultValue; - } - } ); -} - -// Support: IE<9 -// Use getAttributeNode to fetch booleans when getAttribute lies -if ( !assert( function( el ) { - return el.getAttribute( "disabled" ) == null; -} ) ) { - addHandle( booleans, function( elem, name, isXML ) { - var val; - if ( !isXML ) { - return elem[ name ] === true ? name.toLowerCase() : - ( val = elem.getAttributeNode( name ) ) && val.specified ? - val.value : - null; - } - } ); -} - -return Sizzle; - -} )( window ); - - - -jQuery.find = Sizzle; -jQuery.expr = Sizzle.selectors; - -// Deprecated -jQuery.expr[ ":" ] = jQuery.expr.pseudos; -jQuery.uniqueSort = jQuery.unique = Sizzle.uniqueSort; -jQuery.text = Sizzle.getText; -jQuery.isXMLDoc = Sizzle.isXML; -jQuery.contains = Sizzle.contains; -jQuery.escapeSelector = Sizzle.escape; - - - - -var dir = function( elem, dir, until ) { - var matched = [], - truncate = until !== undefined; - - while ( ( elem = elem[ dir ] ) && elem.nodeType !== 9 ) { - if ( elem.nodeType === 1 ) { - if ( truncate && jQuery( elem ).is( until ) ) { - break; - } - matched.push( elem ); - } - } - return matched; -}; - - -var siblings = function( n, elem ) { - var matched = []; - - for ( ; n; n = n.nextSibling ) { - if ( n.nodeType === 1 && n !== elem ) { - matched.push( n ); - } - } - - return matched; -}; - - -var rneedsContext = jQuery.expr.match.needsContext; - - - -function nodeName( elem, name ) { - - return elem.nodeName && elem.nodeName.toLowerCase() === name.toLowerCase(); - -}; -var rsingleTag = ( /^<([a-z][^\/\0>:\x20\t\r\n\f]*)[\x20\t\r\n\f]*\/?>(?:<\/\1>|)$/i ); - - - -// Implement the identical functionality for filter and not -function winnow( elements, qualifier, not ) { - if ( isFunction( qualifier ) ) { - return jQuery.grep( elements, function( elem, i ) { - return !!qualifier.call( elem, i, elem ) !== not; - } ); - } - - // Single element - if ( qualifier.nodeType ) { - return jQuery.grep( elements, function( elem ) { - return ( elem === qualifier ) !== not; - } ); - } - - // Arraylike of elements (jQuery, arguments, Array) - if ( typeof qualifier !== "string" ) { - return jQuery.grep( elements, function( elem ) { - return ( indexOf.call( qualifier, elem ) > -1 ) !== not; - } ); - } - - // Filtered directly for both simple and complex selectors - return jQuery.filter( qualifier, elements, not ); -} - -jQuery.filter = function( expr, elems, not ) { - var elem = elems[ 0 ]; - - if ( not ) { - expr = ":not(" + expr + ")"; - } - - if ( elems.length === 1 && elem.nodeType === 1 ) { - return jQuery.find.matchesSelector( elem, expr ) ? [ elem ] : []; - } - - return jQuery.find.matches( expr, jQuery.grep( elems, function( elem ) { - return elem.nodeType === 1; - } ) ); -}; - -jQuery.fn.extend( { - find: function( selector ) { - var i, ret, - len = this.length, - self = this; - - if ( typeof selector !== "string" ) { - return this.pushStack( jQuery( selector ).filter( function() { - for ( i = 0; i < len; i++ ) { - if ( jQuery.contains( self[ i ], this ) ) { - return true; - } - } - } ) ); - } - - ret = this.pushStack( [] ); - - for ( i = 0; i < len; i++ ) { - jQuery.find( selector, self[ i ], ret ); - } - - return len > 1 ? jQuery.uniqueSort( ret ) : ret; - }, - filter: function( selector ) { - return this.pushStack( winnow( this, selector || [], false ) ); - }, - not: function( selector ) { - return this.pushStack( winnow( this, selector || [], true ) ); - }, - is: function( selector ) { - return !!winnow( - this, - - // If this is a positional/relative selector, check membership in the returned set - // so $("p:first").is("p:last") won't return true for a doc with two "p". - typeof selector === "string" && rneedsContext.test( selector ) ? - jQuery( selector ) : - selector || [], - false - ).length; - } -} ); - - -// Initialize a jQuery object - - -// A central reference to the root jQuery(document) -var rootjQuery, - - // A simple way to check for HTML strings - // Prioritize #id over to avoid XSS via location.hash (#9521) - // Strict HTML recognition (#11290: must start with <) - // Shortcut simple #id case for speed - rquickExpr = /^(?:\s*(<[\w\W]+>)[^>]*|#([\w-]+))$/, - - init = jQuery.fn.init = function( selector, context, root ) { - var match, elem; - - // HANDLE: $(""), $(null), $(undefined), $(false) - if ( !selector ) { - return this; - } - - // Method init() accepts an alternate rootjQuery - // so migrate can support jQuery.sub (gh-2101) - root = root || rootjQuery; - - // Handle HTML strings - if ( typeof selector === "string" ) { - if ( selector[ 0 ] === "<" && - selector[ selector.length - 1 ] === ">" && - selector.length >= 3 ) { - - // Assume that strings that start and end with <> are HTML and skip the regex check - match = [ null, selector, null ]; - - } else { - match = rquickExpr.exec( selector ); - } - - // Match html or make sure no context is specified for #id - if ( match && ( match[ 1 ] || !context ) ) { - - // HANDLE: $(html) -> $(array) - if ( match[ 1 ] ) { - context = context instanceof jQuery ? context[ 0 ] : context; - - // Option to run scripts is true for back-compat - // Intentionally let the error be thrown if parseHTML is not present - jQuery.merge( this, jQuery.parseHTML( - match[ 1 ], - context && context.nodeType ? context.ownerDocument || context : document, - true - ) ); - - // HANDLE: $(html, props) - if ( rsingleTag.test( match[ 1 ] ) && jQuery.isPlainObject( context ) ) { - for ( match in context ) { - - // Properties of context are called as methods if possible - if ( isFunction( this[ match ] ) ) { - this[ match ]( context[ match ] ); - - // ...and otherwise set as attributes - } else { - this.attr( match, context[ match ] ); - } - } - } - - return this; - - // HANDLE: $(#id) - } else { - elem = document.getElementById( match[ 2 ] ); - - if ( elem ) { - - // Inject the element directly into the jQuery object - this[ 0 ] = elem; - this.length = 1; - } - return this; - } - - // HANDLE: $(expr, $(...)) - } else if ( !context || context.jquery ) { - return ( context || root ).find( selector ); - - // HANDLE: $(expr, context) - // (which is just equivalent to: $(context).find(expr) - } else { - return this.constructor( context ).find( selector ); - } - - // HANDLE: $(DOMElement) - } else if ( selector.nodeType ) { - this[ 0 ] = selector; - this.length = 1; - return this; - - // HANDLE: $(function) - // Shortcut for document ready - } else if ( isFunction( selector ) ) { - return root.ready !== undefined ? - root.ready( selector ) : - - // Execute immediately if ready is not present - selector( jQuery ); - } - - return jQuery.makeArray( selector, this ); - }; - -// Give the init function the jQuery prototype for later instantiation -init.prototype = jQuery.fn; - -// Initialize central reference -rootjQuery = jQuery( document ); - - -var rparentsprev = /^(?:parents|prev(?:Until|All))/, - - // Methods guaranteed to produce a unique set when starting from a unique set - guaranteedUnique = { - children: true, - contents: true, - next: true, - prev: true - }; - -jQuery.fn.extend( { - has: function( target ) { - var targets = jQuery( target, this ), - l = targets.length; - - return this.filter( function() { - var i = 0; - for ( ; i < l; i++ ) { - if ( jQuery.contains( this, targets[ i ] ) ) { - return true; - } - } - } ); - }, - - closest: function( selectors, context ) { - var cur, - i = 0, - l = this.length, - matched = [], - targets = typeof selectors !== "string" && jQuery( selectors ); - - // Positional selectors never match, since there's no _selection_ context - if ( !rneedsContext.test( selectors ) ) { - for ( ; i < l; i++ ) { - for ( cur = this[ i ]; cur && cur !== context; cur = cur.parentNode ) { - - // Always skip document fragments - if ( cur.nodeType < 11 && ( targets ? - targets.index( cur ) > -1 : - - // Don't pass non-elements to Sizzle - cur.nodeType === 1 && - jQuery.find.matchesSelector( cur, selectors ) ) ) { - - matched.push( cur ); - break; - } - } - } - } - - return this.pushStack( matched.length > 1 ? jQuery.uniqueSort( matched ) : matched ); - }, - - // Determine the position of an element within the set - index: function( elem ) { - - // No argument, return index in parent - if ( !elem ) { - return ( this[ 0 ] && this[ 0 ].parentNode ) ? this.first().prevAll().length : -1; - } - - // Index in selector - if ( typeof elem === "string" ) { - return indexOf.call( jQuery( elem ), this[ 0 ] ); - } - - // Locate the position of the desired element - return indexOf.call( this, - - // If it receives a jQuery object, the first element is used - elem.jquery ? elem[ 0 ] : elem - ); - }, - - add: function( selector, context ) { - return this.pushStack( - jQuery.uniqueSort( - jQuery.merge( this.get(), jQuery( selector, context ) ) - ) - ); - }, - - addBack: function( selector ) { - return this.add( selector == null ? - this.prevObject : this.prevObject.filter( selector ) - ); - } -} ); - -function sibling( cur, dir ) { - while ( ( cur = cur[ dir ] ) && cur.nodeType !== 1 ) {} - return cur; -} - -jQuery.each( { - parent: function( elem ) { - var parent = elem.parentNode; - return parent && parent.nodeType !== 11 ? parent : null; - }, - parents: function( elem ) { - return dir( elem, "parentNode" ); - }, - parentsUntil: function( elem, _i, until ) { - return dir( elem, "parentNode", until ); - }, - next: function( elem ) { - return sibling( elem, "nextSibling" ); - }, - prev: function( elem ) { - return sibling( elem, "previousSibling" ); - }, - nextAll: function( elem ) { - return dir( elem, "nextSibling" ); - }, - prevAll: function( elem ) { - return dir( elem, "previousSibling" ); - }, - nextUntil: function( elem, _i, until ) { - return dir( elem, "nextSibling", until ); - }, - prevUntil: function( elem, _i, until ) { - return dir( elem, "previousSibling", until ); - }, - siblings: function( elem ) { - return siblings( ( elem.parentNode || {} ).firstChild, elem ); - }, - children: function( elem ) { - return siblings( elem.firstChild ); - }, - contents: function( elem ) { - if ( elem.contentDocument != null && - - // Support: IE 11+ - // elements with no `data` attribute has an object - // `contentDocument` with a `null` prototype. - getProto( elem.contentDocument ) ) { - - return elem.contentDocument; - } - - // Support: IE 9 - 11 only, iOS 7 only, Android Browser <=4.3 only - // Treat the template element as a regular one in browsers that - // don't support it. - if ( nodeName( elem, "template" ) ) { - elem = elem.content || elem; - } - - return jQuery.merge( [], elem.childNodes ); - } -}, function( name, fn ) { - jQuery.fn[ name ] = function( until, selector ) { - var matched = jQuery.map( this, fn, until ); - - if ( name.slice( -5 ) !== "Until" ) { - selector = until; - } - - if ( selector && typeof selector === "string" ) { - matched = jQuery.filter( selector, matched ); - } - - if ( this.length > 1 ) { - - // Remove duplicates - if ( !guaranteedUnique[ name ] ) { - jQuery.uniqueSort( matched ); - } - - // Reverse order for parents* and prev-derivatives - if ( rparentsprev.test( name ) ) { - matched.reverse(); - } - } - - return this.pushStack( matched ); - }; -} ); -var rnothtmlwhite = ( /[^\x20\t\r\n\f]+/g ); - - - -// Convert String-formatted options into Object-formatted ones -function createOptions( options ) { - var object = {}; - jQuery.each( options.match( rnothtmlwhite ) || [], function( _, flag ) { - object[ flag ] = true; - } ); - return object; -} - -/* - * Create a callback list using the following parameters: - * - * options: an optional list of space-separated options that will change how - * the callback list behaves or a more traditional option object - * - * By default a callback list will act like an event callback list and can be - * "fired" multiple times. - * - * Possible options: - * - * once: will ensure the callback list can only be fired once (like a Deferred) - * - * memory: will keep track of previous values and will call any callback added - * after the list has been fired right away with the latest "memorized" - * values (like a Deferred) - * - * unique: will ensure a callback can only be added once (no duplicate in the list) - * - * stopOnFalse: interrupt callings when a callback returns false - * - */ -jQuery.Callbacks = function( options ) { - - // Convert options from String-formatted to Object-formatted if needed - // (we check in cache first) - options = typeof options === "string" ? - createOptions( options ) : - jQuery.extend( {}, options ); - - var // Flag to know if list is currently firing - firing, - - // Last fire value for non-forgettable lists - memory, - - // Flag to know if list was already fired - fired, - - // Flag to prevent firing - locked, - - // Actual callback list - list = [], - - // Queue of execution data for repeatable lists - queue = [], - - // Index of currently firing callback (modified by add/remove as needed) - firingIndex = -1, - - // Fire callbacks - fire = function() { - - // Enforce single-firing - locked = locked || options.once; - - // Execute callbacks for all pending executions, - // respecting firingIndex overrides and runtime changes - fired = firing = true; - for ( ; queue.length; firingIndex = -1 ) { - memory = queue.shift(); - while ( ++firingIndex < list.length ) { - - // Run callback and check for early termination - if ( list[ firingIndex ].apply( memory[ 0 ], memory[ 1 ] ) === false && - options.stopOnFalse ) { - - // Jump to end and forget the data so .add doesn't re-fire - firingIndex = list.length; - memory = false; - } - } - } - - // Forget the data if we're done with it - if ( !options.memory ) { - memory = false; - } - - firing = false; - - // Clean up if we're done firing for good - if ( locked ) { - - // Keep an empty list if we have data for future add calls - if ( memory ) { - list = []; - - // Otherwise, this object is spent - } else { - list = ""; - } - } - }, - - // Actual Callbacks object - self = { - - // Add a callback or a collection of callbacks to the list - add: function() { - if ( list ) { - - // If we have memory from a past run, we should fire after adding - if ( memory && !firing ) { - firingIndex = list.length - 1; - queue.push( memory ); - } - - ( function add( args ) { - jQuery.each( args, function( _, arg ) { - if ( isFunction( arg ) ) { - if ( !options.unique || !self.has( arg ) ) { - list.push( arg ); - } - } else if ( arg && arg.length && toType( arg ) !== "string" ) { - - // Inspect recursively - add( arg ); - } - } ); - } )( arguments ); - - if ( memory && !firing ) { - fire(); - } - } - return this; - }, - - // Remove a callback from the list - remove: function() { - jQuery.each( arguments, function( _, arg ) { - var index; - while ( ( index = jQuery.inArray( arg, list, index ) ) > -1 ) { - list.splice( index, 1 ); - - // Handle firing indexes - if ( index <= firingIndex ) { - firingIndex--; - } - } - } ); - return this; - }, - - // Check if a given callback is in the list. - // If no argument is given, return whether or not list has callbacks attached. - has: function( fn ) { - return fn ? - jQuery.inArray( fn, list ) > -1 : - list.length > 0; - }, - - // Remove all callbacks from the list - empty: function() { - if ( list ) { - list = []; - } - return this; - }, - - // Disable .fire and .add - // Abort any current/pending executions - // Clear all callbacks and values - disable: function() { - locked = queue = []; - list = memory = ""; - return this; - }, - disabled: function() { - return !list; - }, - - // Disable .fire - // Also disable .add unless we have memory (since it would have no effect) - // Abort any pending executions - lock: function() { - locked = queue = []; - if ( !memory && !firing ) { - list = memory = ""; - } - return this; - }, - locked: function() { - return !!locked; - }, - - // Call all callbacks with the given context and arguments - fireWith: function( context, args ) { - if ( !locked ) { - args = args || []; - args = [ context, args.slice ? args.slice() : args ]; - queue.push( args ); - if ( !firing ) { - fire(); - } - } - return this; - }, - - // Call all the callbacks with the given arguments - fire: function() { - self.fireWith( this, arguments ); - return this; - }, - - // To know if the callbacks have already been called at least once - fired: function() { - return !!fired; - } - }; - - return self; -}; - - -function Identity( v ) { - return v; -} -function Thrower( ex ) { - throw ex; -} - -function adoptValue( value, resolve, reject, noValue ) { - var method; - - try { - - // Check for promise aspect first to privilege synchronous behavior - if ( value && isFunction( ( method = value.promise ) ) ) { - method.call( value ).done( resolve ).fail( reject ); - - // Other thenables - } else if ( value && isFunction( ( method = value.then ) ) ) { - method.call( value, resolve, reject ); - - // Other non-thenables - } else { - - // Control `resolve` arguments by letting Array#slice cast boolean `noValue` to integer: - // * false: [ value ].slice( 0 ) => resolve( value ) - // * true: [ value ].slice( 1 ) => resolve() - resolve.apply( undefined, [ value ].slice( noValue ) ); - } - - // For Promises/A+, convert exceptions into rejections - // Since jQuery.when doesn't unwrap thenables, we can skip the extra checks appearing in - // Deferred#then to conditionally suppress rejection. - } catch ( value ) { - - // Support: Android 4.0 only - // Strict mode functions invoked without .call/.apply get global-object context - reject.apply( undefined, [ value ] ); - } -} - -jQuery.extend( { - - Deferred: function( func ) { - var tuples = [ - - // action, add listener, callbacks, - // ... .then handlers, argument index, [final state] - [ "notify", "progress", jQuery.Callbacks( "memory" ), - jQuery.Callbacks( "memory" ), 2 ], - [ "resolve", "done", jQuery.Callbacks( "once memory" ), - jQuery.Callbacks( "once memory" ), 0, "resolved" ], - [ "reject", "fail", jQuery.Callbacks( "once memory" ), - jQuery.Callbacks( "once memory" ), 1, "rejected" ] - ], - state = "pending", - promise = { - state: function() { - return state; - }, - always: function() { - deferred.done( arguments ).fail( arguments ); - return this; - }, - "catch": function( fn ) { - return promise.then( null, fn ); - }, - - // Keep pipe for back-compat - pipe: function( /* fnDone, fnFail, fnProgress */ ) { - var fns = arguments; - - return jQuery.Deferred( function( newDefer ) { - jQuery.each( tuples, function( _i, tuple ) { - - // Map tuples (progress, done, fail) to arguments (done, fail, progress) - var fn = isFunction( fns[ tuple[ 4 ] ] ) && fns[ tuple[ 4 ] ]; - - // deferred.progress(function() { bind to newDefer or newDefer.notify }) - // deferred.done(function() { bind to newDefer or newDefer.resolve }) - // deferred.fail(function() { bind to newDefer or newDefer.reject }) - deferred[ tuple[ 1 ] ]( function() { - var returned = fn && fn.apply( this, arguments ); - if ( returned && isFunction( returned.promise ) ) { - returned.promise() - .progress( newDefer.notify ) - .done( newDefer.resolve ) - .fail( newDefer.reject ); - } else { - newDefer[ tuple[ 0 ] + "With" ]( - this, - fn ? [ returned ] : arguments - ); - } - } ); - } ); - fns = null; - } ).promise(); - }, - then: function( onFulfilled, onRejected, onProgress ) { - var maxDepth = 0; - function resolve( depth, deferred, handler, special ) { - return function() { - var that = this, - args = arguments, - mightThrow = function() { - var returned, then; - - // Support: Promises/A+ section 2.3.3.3.3 - // https://promisesaplus.com/#point-59 - // Ignore double-resolution attempts - if ( depth < maxDepth ) { - return; - } - - returned = handler.apply( that, args ); - - // Support: Promises/A+ section 2.3.1 - // https://promisesaplus.com/#point-48 - if ( returned === deferred.promise() ) { - throw new TypeError( "Thenable self-resolution" ); - } - - // Support: Promises/A+ sections 2.3.3.1, 3.5 - // https://promisesaplus.com/#point-54 - // https://promisesaplus.com/#point-75 - // Retrieve `then` only once - then = returned && - - // Support: Promises/A+ section 2.3.4 - // https://promisesaplus.com/#point-64 - // Only check objects and functions for thenability - ( typeof returned === "object" || - typeof returned === "function" ) && - returned.then; - - // Handle a returned thenable - if ( isFunction( then ) ) { - - // Special processors (notify) just wait for resolution - if ( special ) { - then.call( - returned, - resolve( maxDepth, deferred, Identity, special ), - resolve( maxDepth, deferred, Thrower, special ) - ); - - // Normal processors (resolve) also hook into progress - } else { - - // ...and disregard older resolution values - maxDepth++; - - then.call( - returned, - resolve( maxDepth, deferred, Identity, special ), - resolve( maxDepth, deferred, Thrower, special ), - resolve( maxDepth, deferred, Identity, - deferred.notifyWith ) - ); - } - - // Handle all other returned values - } else { - - // Only substitute handlers pass on context - // and multiple values (non-spec behavior) - if ( handler !== Identity ) { - that = undefined; - args = [ returned ]; - } - - // Process the value(s) - // Default process is resolve - ( special || deferred.resolveWith )( that, args ); - } - }, - - // Only normal processors (resolve) catch and reject exceptions - process = special ? - mightThrow : - function() { - try { - mightThrow(); - } catch ( e ) { - - if ( jQuery.Deferred.exceptionHook ) { - jQuery.Deferred.exceptionHook( e, - process.stackTrace ); - } - - // Support: Promises/A+ section 2.3.3.3.4.1 - // https://promisesaplus.com/#point-61 - // Ignore post-resolution exceptions - if ( depth + 1 >= maxDepth ) { - - // Only substitute handlers pass on context - // and multiple values (non-spec behavior) - if ( handler !== Thrower ) { - that = undefined; - args = [ e ]; - } - - deferred.rejectWith( that, args ); - } - } - }; - - // Support: Promises/A+ section 2.3.3.3.1 - // https://promisesaplus.com/#point-57 - // Re-resolve promises immediately to dodge false rejection from - // subsequent errors - if ( depth ) { - process(); - } else { - - // Call an optional hook to record the stack, in case of exception - // since it's otherwise lost when execution goes async - if ( jQuery.Deferred.getStackHook ) { - process.stackTrace = jQuery.Deferred.getStackHook(); - } - window.setTimeout( process ); - } - }; - } - - return jQuery.Deferred( function( newDefer ) { - - // progress_handlers.add( ... ) - tuples[ 0 ][ 3 ].add( - resolve( - 0, - newDefer, - isFunction( onProgress ) ? - onProgress : - Identity, - newDefer.notifyWith - ) - ); - - // fulfilled_handlers.add( ... ) - tuples[ 1 ][ 3 ].add( - resolve( - 0, - newDefer, - isFunction( onFulfilled ) ? - onFulfilled : - Identity - ) - ); - - // rejected_handlers.add( ... ) - tuples[ 2 ][ 3 ].add( - resolve( - 0, - newDefer, - isFunction( onRejected ) ? - onRejected : - Thrower - ) - ); - } ).promise(); - }, - - // Get a promise for this deferred - // If obj is provided, the promise aspect is added to the object - promise: function( obj ) { - return obj != null ? jQuery.extend( obj, promise ) : promise; - } - }, - deferred = {}; - - // Add list-specific methods - jQuery.each( tuples, function( i, tuple ) { - var list = tuple[ 2 ], - stateString = tuple[ 5 ]; - - // promise.progress = list.add - // promise.done = list.add - // promise.fail = list.add - promise[ tuple[ 1 ] ] = list.add; - - // Handle state - if ( stateString ) { - list.add( - function() { - - // state = "resolved" (i.e., fulfilled) - // state = "rejected" - state = stateString; - }, - - // rejected_callbacks.disable - // fulfilled_callbacks.disable - tuples[ 3 - i ][ 2 ].disable, - - // rejected_handlers.disable - // fulfilled_handlers.disable - tuples[ 3 - i ][ 3 ].disable, - - // progress_callbacks.lock - tuples[ 0 ][ 2 ].lock, - - // progress_handlers.lock - tuples[ 0 ][ 3 ].lock - ); - } - - // progress_handlers.fire - // fulfilled_handlers.fire - // rejected_handlers.fire - list.add( tuple[ 3 ].fire ); - - // deferred.notify = function() { deferred.notifyWith(...) } - // deferred.resolve = function() { deferred.resolveWith(...) } - // deferred.reject = function() { deferred.rejectWith(...) } - deferred[ tuple[ 0 ] ] = function() { - deferred[ tuple[ 0 ] + "With" ]( this === deferred ? undefined : this, arguments ); - return this; - }; - - // deferred.notifyWith = list.fireWith - // deferred.resolveWith = list.fireWith - // deferred.rejectWith = list.fireWith - deferred[ tuple[ 0 ] + "With" ] = list.fireWith; - } ); - - // Make the deferred a promise - promise.promise( deferred ); - - // Call given func if any - if ( func ) { - func.call( deferred, deferred ); - } - - // All done! - return deferred; - }, - - // Deferred helper - when: function( singleValue ) { - var - - // count of uncompleted subordinates - remaining = arguments.length, - - // count of unprocessed arguments - i = remaining, - - // subordinate fulfillment data - resolveContexts = Array( i ), - resolveValues = slice.call( arguments ), - - // the master Deferred - master = jQuery.Deferred(), - - // subordinate callback factory - updateFunc = function( i ) { - return function( value ) { - resolveContexts[ i ] = this; - resolveValues[ i ] = arguments.length > 1 ? slice.call( arguments ) : value; - if ( !( --remaining ) ) { - master.resolveWith( resolveContexts, resolveValues ); - } - }; - }; - - // Single- and empty arguments are adopted like Promise.resolve - if ( remaining <= 1 ) { - adoptValue( singleValue, master.done( updateFunc( i ) ).resolve, master.reject, - !remaining ); - - // Use .then() to unwrap secondary thenables (cf. gh-3000) - if ( master.state() === "pending" || - isFunction( resolveValues[ i ] && resolveValues[ i ].then ) ) { - - return master.then(); - } - } - - // Multiple arguments are aggregated like Promise.all array elements - while ( i-- ) { - adoptValue( resolveValues[ i ], updateFunc( i ), master.reject ); - } - - return master.promise(); - } -} ); - - -// These usually indicate a programmer mistake during development, -// warn about them ASAP rather than swallowing them by default. -var rerrorNames = /^(Eval|Internal|Range|Reference|Syntax|Type|URI)Error$/; - -jQuery.Deferred.exceptionHook = function( error, stack ) { - - // Support: IE 8 - 9 only - // Console exists when dev tools are open, which can happen at any time - if ( window.console && window.console.warn && error && rerrorNames.test( error.name ) ) { - window.console.warn( "jQuery.Deferred exception: " + error.message, error.stack, stack ); - } -}; - - - - -jQuery.readyException = function( error ) { - window.setTimeout( function() { - throw error; - } ); -}; - - - - -// The deferred used on DOM ready -var readyList = jQuery.Deferred(); - -jQuery.fn.ready = function( fn ) { - - readyList - .then( fn ) - - // Wrap jQuery.readyException in a function so that the lookup - // happens at the time of error handling instead of callback - // registration. - .catch( function( error ) { - jQuery.readyException( error ); - } ); - - return this; -}; - -jQuery.extend( { - - // Is the DOM ready to be used? Set to true once it occurs. - isReady: false, - - // A counter to track how many items to wait for before - // the ready event fires. See #6781 - readyWait: 1, - - // Handle when the DOM is ready - ready: function( wait ) { - - // Abort if there are pending holds or we're already ready - if ( wait === true ? --jQuery.readyWait : jQuery.isReady ) { - return; - } - - // Remember that the DOM is ready - jQuery.isReady = true; - - // If a normal DOM Ready event fired, decrement, and wait if need be - if ( wait !== true && --jQuery.readyWait > 0 ) { - return; - } - - // If there are functions bound, to execute - readyList.resolveWith( document, [ jQuery ] ); - } -} ); - -jQuery.ready.then = readyList.then; - -// The ready event handler and self cleanup method -function completed() { - document.removeEventListener( "DOMContentLoaded", completed ); - window.removeEventListener( "load", completed ); - jQuery.ready(); -} - -// Catch cases where $(document).ready() is called -// after the browser event has already occurred. -// Support: IE <=9 - 10 only -// Older IE sometimes signals "interactive" too soon -if ( document.readyState === "complete" || - ( document.readyState !== "loading" && !document.documentElement.doScroll ) ) { - - // Handle it asynchronously to allow scripts the opportunity to delay ready - window.setTimeout( jQuery.ready ); - -} else { - - // Use the handy event callback - document.addEventListener( "DOMContentLoaded", completed ); - - // A fallback to window.onload, that will always work - window.addEventListener( "load", completed ); -} - - - - -// Multifunctional method to get and set values of a collection -// The value/s can optionally be executed if it's a function -var access = function( elems, fn, key, value, chainable, emptyGet, raw ) { - var i = 0, - len = elems.length, - bulk = key == null; - - // Sets many values - if ( toType( key ) === "object" ) { - chainable = true; - for ( i in key ) { - access( elems, fn, i, key[ i ], true, emptyGet, raw ); - } - - // Sets one value - } else if ( value !== undefined ) { - chainable = true; - - if ( !isFunction( value ) ) { - raw = true; - } - - if ( bulk ) { - - // Bulk operations run against the entire set - if ( raw ) { - fn.call( elems, value ); - fn = null; - - // ...except when executing function values - } else { - bulk = fn; - fn = function( elem, _key, value ) { - return bulk.call( jQuery( elem ), value ); - }; - } - } - - if ( fn ) { - for ( ; i < len; i++ ) { - fn( - elems[ i ], key, raw ? - value : - value.call( elems[ i ], i, fn( elems[ i ], key ) ) - ); - } - } - } - - if ( chainable ) { - return elems; - } - - // Gets - if ( bulk ) { - return fn.call( elems ); - } - - return len ? fn( elems[ 0 ], key ) : emptyGet; -}; - - -// Matches dashed string for camelizing -var rmsPrefix = /^-ms-/, - rdashAlpha = /-([a-z])/g; - -// Used by camelCase as callback to replace() -function fcamelCase( _all, letter ) { - return letter.toUpperCase(); -} - -// Convert dashed to camelCase; used by the css and data modules -// Support: IE <=9 - 11, Edge 12 - 15 -// Microsoft forgot to hump their vendor prefix (#9572) -function camelCase( string ) { - return string.replace( rmsPrefix, "ms-" ).replace( rdashAlpha, fcamelCase ); -} -var acceptData = function( owner ) { - - // Accepts only: - // - Node - // - Node.ELEMENT_NODE - // - Node.DOCUMENT_NODE - // - Object - // - Any - return owner.nodeType === 1 || owner.nodeType === 9 || !( +owner.nodeType ); -}; - - - - -function Data() { - this.expando = jQuery.expando + Data.uid++; -} - -Data.uid = 1; - -Data.prototype = { - - cache: function( owner ) { - - // Check if the owner object already has a cache - var value = owner[ this.expando ]; - - // If not, create one - if ( !value ) { - value = {}; - - // We can accept data for non-element nodes in modern browsers, - // but we should not, see #8335. - // Always return an empty object. - if ( acceptData( owner ) ) { - - // If it is a node unlikely to be stringify-ed or looped over - // use plain assignment - if ( owner.nodeType ) { - owner[ this.expando ] = value; - - // Otherwise secure it in a non-enumerable property - // configurable must be true to allow the property to be - // deleted when data is removed - } else { - Object.defineProperty( owner, this.expando, { - value: value, - configurable: true - } ); - } - } - } - - return value; - }, - set: function( owner, data, value ) { - var prop, - cache = this.cache( owner ); - - // Handle: [ owner, key, value ] args - // Always use camelCase key (gh-2257) - if ( typeof data === "string" ) { - cache[ camelCase( data ) ] = value; - - // Handle: [ owner, { properties } ] args - } else { - - // Copy the properties one-by-one to the cache object - for ( prop in data ) { - cache[ camelCase( prop ) ] = data[ prop ]; - } - } - return cache; - }, - get: function( owner, key ) { - return key === undefined ? - this.cache( owner ) : - - // Always use camelCase key (gh-2257) - owner[ this.expando ] && owner[ this.expando ][ camelCase( key ) ]; - }, - access: function( owner, key, value ) { - - // In cases where either: - // - // 1. No key was specified - // 2. A string key was specified, but no value provided - // - // Take the "read" path and allow the get method to determine - // which value to return, respectively either: - // - // 1. The entire cache object - // 2. The data stored at the key - // - if ( key === undefined || - ( ( key && typeof key === "string" ) && value === undefined ) ) { - - return this.get( owner, key ); - } - - // When the key is not a string, or both a key and value - // are specified, set or extend (existing objects) with either: - // - // 1. An object of properties - // 2. A key and value - // - this.set( owner, key, value ); - - // Since the "set" path can have two possible entry points - // return the expected data based on which path was taken[*] - return value !== undefined ? value : key; - }, - remove: function( owner, key ) { - var i, - cache = owner[ this.expando ]; - - if ( cache === undefined ) { - return; - } - - if ( key !== undefined ) { - - // Support array or space separated string of keys - if ( Array.isArray( key ) ) { - - // If key is an array of keys... - // We always set camelCase keys, so remove that. - key = key.map( camelCase ); - } else { - key = camelCase( key ); - - // If a key with the spaces exists, use it. - // Otherwise, create an array by matching non-whitespace - key = key in cache ? - [ key ] : - ( key.match( rnothtmlwhite ) || [] ); - } - - i = key.length; - - while ( i-- ) { - delete cache[ key[ i ] ]; - } - } - - // Remove the expando if there's no more data - if ( key === undefined || jQuery.isEmptyObject( cache ) ) { - - // Support: Chrome <=35 - 45 - // Webkit & Blink performance suffers when deleting properties - // from DOM nodes, so set to undefined instead - // https://bugs.chromium.org/p/chromium/issues/detail?id=378607 (bug restricted) - if ( owner.nodeType ) { - owner[ this.expando ] = undefined; - } else { - delete owner[ this.expando ]; - } - } - }, - hasData: function( owner ) { - var cache = owner[ this.expando ]; - return cache !== undefined && !jQuery.isEmptyObject( cache ); - } -}; -var dataPriv = new Data(); - -var dataUser = new Data(); - - - -// Implementation Summary -// -// 1. Enforce API surface and semantic compatibility with 1.9.x branch -// 2. Improve the module's maintainability by reducing the storage -// paths to a single mechanism. -// 3. Use the same single mechanism to support "private" and "user" data. -// 4. _Never_ expose "private" data to user code (TODO: Drop _data, _removeData) -// 5. Avoid exposing implementation details on user objects (eg. expando properties) -// 6. Provide a clear path for implementation upgrade to WeakMap in 2014 - -var rbrace = /^(?:\{[\w\W]*\}|\[[\w\W]*\])$/, - rmultiDash = /[A-Z]/g; - -function getData( data ) { - if ( data === "true" ) { - return true; - } - - if ( data === "false" ) { - return false; - } - - if ( data === "null" ) { - return null; - } - - // Only convert to a number if it doesn't change the string - if ( data === +data + "" ) { - return +data; - } - - if ( rbrace.test( data ) ) { - return JSON.parse( data ); - } - - return data; -} - -function dataAttr( elem, key, data ) { - var name; - - // If nothing was found internally, try to fetch any - // data from the HTML5 data-* attribute - if ( data === undefined && elem.nodeType === 1 ) { - name = "data-" + key.replace( rmultiDash, "-$&" ).toLowerCase(); - data = elem.getAttribute( name ); - - if ( typeof data === "string" ) { - try { - data = getData( data ); - } catch ( e ) {} - - // Make sure we set the data so it isn't changed later - dataUser.set( elem, key, data ); - } else { - data = undefined; - } - } - return data; -} - -jQuery.extend( { - hasData: function( elem ) { - return dataUser.hasData( elem ) || dataPriv.hasData( elem ); - }, - - data: function( elem, name, data ) { - return dataUser.access( elem, name, data ); - }, - - removeData: function( elem, name ) { - dataUser.remove( elem, name ); - }, - - // TODO: Now that all calls to _data and _removeData have been replaced - // with direct calls to dataPriv methods, these can be deprecated. - _data: function( elem, name, data ) { - return dataPriv.access( elem, name, data ); - }, - - _removeData: function( elem, name ) { - dataPriv.remove( elem, name ); - } -} ); - -jQuery.fn.extend( { - data: function( key, value ) { - var i, name, data, - elem = this[ 0 ], - attrs = elem && elem.attributes; - - // Gets all values - if ( key === undefined ) { - if ( this.length ) { - data = dataUser.get( elem ); - - if ( elem.nodeType === 1 && !dataPriv.get( elem, "hasDataAttrs" ) ) { - i = attrs.length; - while ( i-- ) { - - // Support: IE 11 only - // The attrs elements can be null (#14894) - if ( attrs[ i ] ) { - name = attrs[ i ].name; - if ( name.indexOf( "data-" ) === 0 ) { - name = camelCase( name.slice( 5 ) ); - dataAttr( elem, name, data[ name ] ); - } - } - } - dataPriv.set( elem, "hasDataAttrs", true ); - } - } - - return data; - } - - // Sets multiple values - if ( typeof key === "object" ) { - return this.each( function() { - dataUser.set( this, key ); - } ); - } - - return access( this, function( value ) { - var data; - - // The calling jQuery object (element matches) is not empty - // (and therefore has an element appears at this[ 0 ]) and the - // `value` parameter was not undefined. An empty jQuery object - // will result in `undefined` for elem = this[ 0 ] which will - // throw an exception if an attempt to read a data cache is made. - if ( elem && value === undefined ) { - - // Attempt to get data from the cache - // The key will always be camelCased in Data - data = dataUser.get( elem, key ); - if ( data !== undefined ) { - return data; - } - - // Attempt to "discover" the data in - // HTML5 custom data-* attrs - data = dataAttr( elem, key ); - if ( data !== undefined ) { - return data; - } - - // We tried really hard, but the data doesn't exist. - return; - } - - // Set the data... - this.each( function() { - - // We always store the camelCased key - dataUser.set( this, key, value ); - } ); - }, null, value, arguments.length > 1, null, true ); - }, - - removeData: function( key ) { - return this.each( function() { - dataUser.remove( this, key ); - } ); - } -} ); - - -jQuery.extend( { - queue: function( elem, type, data ) { - var queue; - - if ( elem ) { - type = ( type || "fx" ) + "queue"; - queue = dataPriv.get( elem, type ); - - // Speed up dequeue by getting out quickly if this is just a lookup - if ( data ) { - if ( !queue || Array.isArray( data ) ) { - queue = dataPriv.access( elem, type, jQuery.makeArray( data ) ); - } else { - queue.push( data ); - } - } - return queue || []; - } - }, - - dequeue: function( elem, type ) { - type = type || "fx"; - - var queue = jQuery.queue( elem, type ), - startLength = queue.length, - fn = queue.shift(), - hooks = jQuery._queueHooks( elem, type ), - next = function() { - jQuery.dequeue( elem, type ); - }; - - // If the fx queue is dequeued, always remove the progress sentinel - if ( fn === "inprogress" ) { - fn = queue.shift(); - startLength--; - } - - if ( fn ) { - - // Add a progress sentinel to prevent the fx queue from being - // automatically dequeued - if ( type === "fx" ) { - queue.unshift( "inprogress" ); - } - - // Clear up the last queue stop function - delete hooks.stop; - fn.call( elem, next, hooks ); - } - - if ( !startLength && hooks ) { - hooks.empty.fire(); - } - }, - - // Not public - generate a queueHooks object, or return the current one - _queueHooks: function( elem, type ) { - var key = type + "queueHooks"; - return dataPriv.get( elem, key ) || dataPriv.access( elem, key, { - empty: jQuery.Callbacks( "once memory" ).add( function() { - dataPriv.remove( elem, [ type + "queue", key ] ); - } ) - } ); - } -} ); - -jQuery.fn.extend( { - queue: function( type, data ) { - var setter = 2; - - if ( typeof type !== "string" ) { - data = type; - type = "fx"; - setter--; - } - - if ( arguments.length < setter ) { - return jQuery.queue( this[ 0 ], type ); - } - - return data === undefined ? - this : - this.each( function() { - var queue = jQuery.queue( this, type, data ); - - // Ensure a hooks for this queue - jQuery._queueHooks( this, type ); - - if ( type === "fx" && queue[ 0 ] !== "inprogress" ) { - jQuery.dequeue( this, type ); - } - } ); - }, - dequeue: function( type ) { - return this.each( function() { - jQuery.dequeue( this, type ); - } ); - }, - clearQueue: function( type ) { - return this.queue( type || "fx", [] ); - }, - - // Get a promise resolved when queues of a certain type - // are emptied (fx is the type by default) - promise: function( type, obj ) { - var tmp, - count = 1, - defer = jQuery.Deferred(), - elements = this, - i = this.length, - resolve = function() { - if ( !( --count ) ) { - defer.resolveWith( elements, [ elements ] ); - } - }; - - if ( typeof type !== "string" ) { - obj = type; - type = undefined; - } - type = type || "fx"; - - while ( i-- ) { - tmp = dataPriv.get( elements[ i ], type + "queueHooks" ); - if ( tmp && tmp.empty ) { - count++; - tmp.empty.add( resolve ); - } - } - resolve(); - return defer.promise( obj ); - } -} ); -var pnum = ( /[+-]?(?:\d*\.|)\d+(?:[eE][+-]?\d+|)/ ).source; - -var rcssNum = new RegExp( "^(?:([+-])=|)(" + pnum + ")([a-z%]*)$", "i" ); - - -var cssExpand = [ "Top", "Right", "Bottom", "Left" ]; - -var documentElement = document.documentElement; - - - - var isAttached = function( elem ) { - return jQuery.contains( elem.ownerDocument, elem ); - }, - composed = { composed: true }; - - // Support: IE 9 - 11+, Edge 12 - 18+, iOS 10.0 - 10.2 only - // Check attachment across shadow DOM boundaries when possible (gh-3504) - // Support: iOS 10.0-10.2 only - // Early iOS 10 versions support `attachShadow` but not `getRootNode`, - // leading to errors. We need to check for `getRootNode`. - if ( documentElement.getRootNode ) { - isAttached = function( elem ) { - return jQuery.contains( elem.ownerDocument, elem ) || - elem.getRootNode( composed ) === elem.ownerDocument; - }; - } -var isHiddenWithinTree = function( elem, el ) { - - // isHiddenWithinTree might be called from jQuery#filter function; - // in that case, element will be second argument - elem = el || elem; - - // Inline style trumps all - return elem.style.display === "none" || - elem.style.display === "" && - - // Otherwise, check computed style - // Support: Firefox <=43 - 45 - // Disconnected elements can have computed display: none, so first confirm that elem is - // in the document. - isAttached( elem ) && - - jQuery.css( elem, "display" ) === "none"; - }; - - - -function adjustCSS( elem, prop, valueParts, tween ) { - var adjusted, scale, - maxIterations = 20, - currentValue = tween ? - function() { - return tween.cur(); - } : - function() { - return jQuery.css( elem, prop, "" ); - }, - initial = currentValue(), - unit = valueParts && valueParts[ 3 ] || ( jQuery.cssNumber[ prop ] ? "" : "px" ), - - // Starting value computation is required for potential unit mismatches - initialInUnit = elem.nodeType && - ( jQuery.cssNumber[ prop ] || unit !== "px" && +initial ) && - rcssNum.exec( jQuery.css( elem, prop ) ); - - if ( initialInUnit && initialInUnit[ 3 ] !== unit ) { - - // Support: Firefox <=54 - // Halve the iteration target value to prevent interference from CSS upper bounds (gh-2144) - initial = initial / 2; - - // Trust units reported by jQuery.css - unit = unit || initialInUnit[ 3 ]; - - // Iteratively approximate from a nonzero starting point - initialInUnit = +initial || 1; - - while ( maxIterations-- ) { - - // Evaluate and update our best guess (doubling guesses that zero out). - // Finish if the scale equals or crosses 1 (making the old*new product non-positive). - jQuery.style( elem, prop, initialInUnit + unit ); - if ( ( 1 - scale ) * ( 1 - ( scale = currentValue() / initial || 0.5 ) ) <= 0 ) { - maxIterations = 0; - } - initialInUnit = initialInUnit / scale; - - } - - initialInUnit = initialInUnit * 2; - jQuery.style( elem, prop, initialInUnit + unit ); - - // Make sure we update the tween properties later on - valueParts = valueParts || []; - } - - if ( valueParts ) { - initialInUnit = +initialInUnit || +initial || 0; - - // Apply relative offset (+=/-=) if specified - adjusted = valueParts[ 1 ] ? - initialInUnit + ( valueParts[ 1 ] + 1 ) * valueParts[ 2 ] : - +valueParts[ 2 ]; - if ( tween ) { - tween.unit = unit; - tween.start = initialInUnit; - tween.end = adjusted; - } - } - return adjusted; -} - - -var defaultDisplayMap = {}; - -function getDefaultDisplay( elem ) { - var temp, - doc = elem.ownerDocument, - nodeName = elem.nodeName, - display = defaultDisplayMap[ nodeName ]; - - if ( display ) { - return display; - } - - temp = doc.body.appendChild( doc.createElement( nodeName ) ); - display = jQuery.css( temp, "display" ); - - temp.parentNode.removeChild( temp ); - - if ( display === "none" ) { - display = "block"; - } - defaultDisplayMap[ nodeName ] = display; - - return display; -} - -function showHide( elements, show ) { - var display, elem, - values = [], - index = 0, - length = elements.length; - - // Determine new display value for elements that need to change - for ( ; index < length; index++ ) { - elem = elements[ index ]; - if ( !elem.style ) { - continue; - } - - display = elem.style.display; - if ( show ) { - - // Since we force visibility upon cascade-hidden elements, an immediate (and slow) - // check is required in this first loop unless we have a nonempty display value (either - // inline or about-to-be-restored) - if ( display === "none" ) { - values[ index ] = dataPriv.get( elem, "display" ) || null; - if ( !values[ index ] ) { - elem.style.display = ""; - } - } - if ( elem.style.display === "" && isHiddenWithinTree( elem ) ) { - values[ index ] = getDefaultDisplay( elem ); - } - } else { - if ( display !== "none" ) { - values[ index ] = "none"; - - // Remember what we're overwriting - dataPriv.set( elem, "display", display ); - } - } - } - - // Set the display of the elements in a second loop to avoid constant reflow - for ( index = 0; index < length; index++ ) { - if ( values[ index ] != null ) { - elements[ index ].style.display = values[ index ]; - } - } - - return elements; -} - -jQuery.fn.extend( { - show: function() { - return showHide( this, true ); - }, - hide: function() { - return showHide( this ); - }, - toggle: function( state ) { - if ( typeof state === "boolean" ) { - return state ? this.show() : this.hide(); - } - - return this.each( function() { - if ( isHiddenWithinTree( this ) ) { - jQuery( this ).show(); - } else { - jQuery( this ).hide(); - } - } ); - } -} ); -var rcheckableType = ( /^(?:checkbox|radio)$/i ); - -var rtagName = ( /<([a-z][^\/\0>\x20\t\r\n\f]*)/i ); - -var rscriptType = ( /^$|^module$|\/(?:java|ecma)script/i ); - - - -( function() { - var fragment = document.createDocumentFragment(), - div = fragment.appendChild( document.createElement( "div" ) ), - input = document.createElement( "input" ); - - // Support: Android 4.0 - 4.3 only - // Check state lost if the name is set (#11217) - // Support: Windows Web Apps (WWA) - // `name` and `type` must use .setAttribute for WWA (#14901) - input.setAttribute( "type", "radio" ); - input.setAttribute( "checked", "checked" ); - input.setAttribute( "name", "t" ); - - div.appendChild( input ); - - // Support: Android <=4.1 only - // Older WebKit doesn't clone checked state correctly in fragments - support.checkClone = div.cloneNode( true ).cloneNode( true ).lastChild.checked; - - // Support: IE <=11 only - // Make sure textarea (and checkbox) defaultValue is properly cloned - div.innerHTML = ""; - support.noCloneChecked = !!div.cloneNode( true ).lastChild.defaultValue; - - // Support: IE <=9 only - // IE <=9 replaces "; - support.option = !!div.lastChild; -} )(); - - -// We have to close these tags to support XHTML (#13200) -var wrapMap = { - - // XHTML parsers do not magically insert elements in the - // same way that tag soup parsers do. So we cannot shorten - // this by omitting or other required elements. - thead: [ 1, "", "
    " ], - col: [ 2, "", "
    " ], - tr: [ 2, "", "
    " ], - td: [ 3, "", "
    " ], - - _default: [ 0, "", "" ] -}; - -wrapMap.tbody = wrapMap.tfoot = wrapMap.colgroup = wrapMap.caption = wrapMap.thead; -wrapMap.th = wrapMap.td; - -// Support: IE <=9 only -if ( !support.option ) { - wrapMap.optgroup = wrapMap.option = [ 1, "" ]; -} - - -function getAll( context, tag ) { - - // Support: IE <=9 - 11 only - // Use typeof to avoid zero-argument method invocation on host objects (#15151) - var ret; - - if ( typeof context.getElementsByTagName !== "undefined" ) { - ret = context.getElementsByTagName( tag || "*" ); - - } else if ( typeof context.querySelectorAll !== "undefined" ) { - ret = context.querySelectorAll( tag || "*" ); - - } else { - ret = []; - } - - if ( tag === undefined || tag && nodeName( context, tag ) ) { - return jQuery.merge( [ context ], ret ); - } - - return ret; -} - - -// Mark scripts as having already been evaluated -function setGlobalEval( elems, refElements ) { - var i = 0, - l = elems.length; - - for ( ; i < l; i++ ) { - dataPriv.set( - elems[ i ], - "globalEval", - !refElements || dataPriv.get( refElements[ i ], "globalEval" ) - ); - } -} - - -var rhtml = /<|&#?\w+;/; - -function buildFragment( elems, context, scripts, selection, ignored ) { - var elem, tmp, tag, wrap, attached, j, - fragment = context.createDocumentFragment(), - nodes = [], - i = 0, - l = elems.length; - - for ( ; i < l; i++ ) { - elem = elems[ i ]; - - if ( elem || elem === 0 ) { - - // Add nodes directly - if ( toType( elem ) === "object" ) { - - // Support: Android <=4.0 only, PhantomJS 1 only - // push.apply(_, arraylike) throws on ancient WebKit - jQuery.merge( nodes, elem.nodeType ? [ elem ] : elem ); - - // Convert non-html into a text node - } else if ( !rhtml.test( elem ) ) { - nodes.push( context.createTextNode( elem ) ); - - // Convert html into DOM nodes - } else { - tmp = tmp || fragment.appendChild( context.createElement( "div" ) ); - - // Deserialize a standard representation - tag = ( rtagName.exec( elem ) || [ "", "" ] )[ 1 ].toLowerCase(); - wrap = wrapMap[ tag ] || wrapMap._default; - tmp.innerHTML = wrap[ 1 ] + jQuery.htmlPrefilter( elem ) + wrap[ 2 ]; - - // Descend through wrappers to the right content - j = wrap[ 0 ]; - while ( j-- ) { - tmp = tmp.lastChild; - } - - // Support: Android <=4.0 only, PhantomJS 1 only - // push.apply(_, arraylike) throws on ancient WebKit - jQuery.merge( nodes, tmp.childNodes ); - - // Remember the top-level container - tmp = fragment.firstChild; - - // Ensure the created nodes are orphaned (#12392) - tmp.textContent = ""; - } - } - } - - // Remove wrapper from fragment - fragment.textContent = ""; - - i = 0; - while ( ( elem = nodes[ i++ ] ) ) { - - // Skip elements already in the context collection (trac-4087) - if ( selection && jQuery.inArray( elem, selection ) > -1 ) { - if ( ignored ) { - ignored.push( elem ); - } - continue; - } - - attached = isAttached( elem ); - - // Append to fragment - tmp = getAll( fragment.appendChild( elem ), "script" ); - - // Preserve script evaluation history - if ( attached ) { - setGlobalEval( tmp ); - } - - // Capture executables - if ( scripts ) { - j = 0; - while ( ( elem = tmp[ j++ ] ) ) { - if ( rscriptType.test( elem.type || "" ) ) { - scripts.push( elem ); - } - } - } - } - - return fragment; -} - - -var - rkeyEvent = /^key/, - rmouseEvent = /^(?:mouse|pointer|contextmenu|drag|drop)|click/, - rtypenamespace = /^([^.]*)(?:\.(.+)|)/; - -function returnTrue() { - return true; -} - -function returnFalse() { - return false; -} - -// Support: IE <=9 - 11+ -// focus() and blur() are asynchronous, except when they are no-op. -// So expect focus to be synchronous when the element is already active, -// and blur to be synchronous when the element is not already active. -// (focus and blur are always synchronous in other supported browsers, -// this just defines when we can count on it). -function expectSync( elem, type ) { - return ( elem === safeActiveElement() ) === ( type === "focus" ); -} - -// Support: IE <=9 only -// Accessing document.activeElement can throw unexpectedly -// https://bugs.jquery.com/ticket/13393 -function safeActiveElement() { - try { - return document.activeElement; - } catch ( err ) { } -} - -function on( elem, types, selector, data, fn, one ) { - var origFn, type; - - // Types can be a map of types/handlers - if ( typeof types === "object" ) { - - // ( types-Object, selector, data ) - if ( typeof selector !== "string" ) { - - // ( types-Object, data ) - data = data || selector; - selector = undefined; - } - for ( type in types ) { - on( elem, type, selector, data, types[ type ], one ); - } - return elem; - } - - if ( data == null && fn == null ) { - - // ( types, fn ) - fn = selector; - data = selector = undefined; - } else if ( fn == null ) { - if ( typeof selector === "string" ) { - - // ( types, selector, fn ) - fn = data; - data = undefined; - } else { - - // ( types, data, fn ) - fn = data; - data = selector; - selector = undefined; - } - } - if ( fn === false ) { - fn = returnFalse; - } else if ( !fn ) { - return elem; - } - - if ( one === 1 ) { - origFn = fn; - fn = function( event ) { - - // Can use an empty set, since event contains the info - jQuery().off( event ); - return origFn.apply( this, arguments ); - }; - - // Use same guid so caller can remove using origFn - fn.guid = origFn.guid || ( origFn.guid = jQuery.guid++ ); - } - return elem.each( function() { - jQuery.event.add( this, types, fn, data, selector ); - } ); -} - -/* - * Helper functions for managing events -- not part of the public interface. - * Props to Dean Edwards' addEvent library for many of the ideas. - */ -jQuery.event = { - - global: {}, - - add: function( elem, types, handler, data, selector ) { - - var handleObjIn, eventHandle, tmp, - events, t, handleObj, - special, handlers, type, namespaces, origType, - elemData = dataPriv.get( elem ); - - // Only attach events to objects that accept data - if ( !acceptData( elem ) ) { - return; - } - - // Caller can pass in an object of custom data in lieu of the handler - if ( handler.handler ) { - handleObjIn = handler; - handler = handleObjIn.handler; - selector = handleObjIn.selector; - } - - // Ensure that invalid selectors throw exceptions at attach time - // Evaluate against documentElement in case elem is a non-element node (e.g., document) - if ( selector ) { - jQuery.find.matchesSelector( documentElement, selector ); - } - - // Make sure that the handler has a unique ID, used to find/remove it later - if ( !handler.guid ) { - handler.guid = jQuery.guid++; - } - - // Init the element's event structure and main handler, if this is the first - if ( !( events = elemData.events ) ) { - events = elemData.events = Object.create( null ); - } - if ( !( eventHandle = elemData.handle ) ) { - eventHandle = elemData.handle = function( e ) { - - // Discard the second event of a jQuery.event.trigger() and - // when an event is called after a page has unloaded - return typeof jQuery !== "undefined" && jQuery.event.triggered !== e.type ? - jQuery.event.dispatch.apply( elem, arguments ) : undefined; - }; - } - - // Handle multiple events separated by a space - types = ( types || "" ).match( rnothtmlwhite ) || [ "" ]; - t = types.length; - while ( t-- ) { - tmp = rtypenamespace.exec( types[ t ] ) || []; - type = origType = tmp[ 1 ]; - namespaces = ( tmp[ 2 ] || "" ).split( "." ).sort(); - - // There *must* be a type, no attaching namespace-only handlers - if ( !type ) { - continue; - } - - // If event changes its type, use the special event handlers for the changed type - special = jQuery.event.special[ type ] || {}; - - // If selector defined, determine special event api type, otherwise given type - type = ( selector ? special.delegateType : special.bindType ) || type; - - // Update special based on newly reset type - special = jQuery.event.special[ type ] || {}; - - // handleObj is passed to all event handlers - handleObj = jQuery.extend( { - type: type, - origType: origType, - data: data, - handler: handler, - guid: handler.guid, - selector: selector, - needsContext: selector && jQuery.expr.match.needsContext.test( selector ), - namespace: namespaces.join( "." ) - }, handleObjIn ); - - // Init the event handler queue if we're the first - if ( !( handlers = events[ type ] ) ) { - handlers = events[ type ] = []; - handlers.delegateCount = 0; - - // Only use addEventListener if the special events handler returns false - if ( !special.setup || - special.setup.call( elem, data, namespaces, eventHandle ) === false ) { - - if ( elem.addEventListener ) { - elem.addEventListener( type, eventHandle ); - } - } - } - - if ( special.add ) { - special.add.call( elem, handleObj ); - - if ( !handleObj.handler.guid ) { - handleObj.handler.guid = handler.guid; - } - } - - // Add to the element's handler list, delegates in front - if ( selector ) { - handlers.splice( handlers.delegateCount++, 0, handleObj ); - } else { - handlers.push( handleObj ); - } - - // Keep track of which events have ever been used, for event optimization - jQuery.event.global[ type ] = true; - } - - }, - - // Detach an event or set of events from an element - remove: function( elem, types, handler, selector, mappedTypes ) { - - var j, origCount, tmp, - events, t, handleObj, - special, handlers, type, namespaces, origType, - elemData = dataPriv.hasData( elem ) && dataPriv.get( elem ); - - if ( !elemData || !( events = elemData.events ) ) { - return; - } - - // Once for each type.namespace in types; type may be omitted - types = ( types || "" ).match( rnothtmlwhite ) || [ "" ]; - t = types.length; - while ( t-- ) { - tmp = rtypenamespace.exec( types[ t ] ) || []; - type = origType = tmp[ 1 ]; - namespaces = ( tmp[ 2 ] || "" ).split( "." ).sort(); - - // Unbind all events (on this namespace, if provided) for the element - if ( !type ) { - for ( type in events ) { - jQuery.event.remove( elem, type + types[ t ], handler, selector, true ); - } - continue; - } - - special = jQuery.event.special[ type ] || {}; - type = ( selector ? special.delegateType : special.bindType ) || type; - handlers = events[ type ] || []; - tmp = tmp[ 2 ] && - new RegExp( "(^|\\.)" + namespaces.join( "\\.(?:.*\\.|)" ) + "(\\.|$)" ); - - // Remove matching events - origCount = j = handlers.length; - while ( j-- ) { - handleObj = handlers[ j ]; - - if ( ( mappedTypes || origType === handleObj.origType ) && - ( !handler || handler.guid === handleObj.guid ) && - ( !tmp || tmp.test( handleObj.namespace ) ) && - ( !selector || selector === handleObj.selector || - selector === "**" && handleObj.selector ) ) { - handlers.splice( j, 1 ); - - if ( handleObj.selector ) { - handlers.delegateCount--; - } - if ( special.remove ) { - special.remove.call( elem, handleObj ); - } - } - } - - // Remove generic event handler if we removed something and no more handlers exist - // (avoids potential for endless recursion during removal of special event handlers) - if ( origCount && !handlers.length ) { - if ( !special.teardown || - special.teardown.call( elem, namespaces, elemData.handle ) === false ) { - - jQuery.removeEvent( elem, type, elemData.handle ); - } - - delete events[ type ]; - } - } - - // Remove data and the expando if it's no longer used - if ( jQuery.isEmptyObject( events ) ) { - dataPriv.remove( elem, "handle events" ); - } - }, - - dispatch: function( nativeEvent ) { - - var i, j, ret, matched, handleObj, handlerQueue, - args = new Array( arguments.length ), - - // Make a writable jQuery.Event from the native event object - event = jQuery.event.fix( nativeEvent ), - - handlers = ( - dataPriv.get( this, "events" ) || Object.create( null ) - )[ event.type ] || [], - special = jQuery.event.special[ event.type ] || {}; - - // Use the fix-ed jQuery.Event rather than the (read-only) native event - args[ 0 ] = event; - - for ( i = 1; i < arguments.length; i++ ) { - args[ i ] = arguments[ i ]; - } - - event.delegateTarget = this; - - // Call the preDispatch hook for the mapped type, and let it bail if desired - if ( special.preDispatch && special.preDispatch.call( this, event ) === false ) { - return; - } - - // Determine handlers - handlerQueue = jQuery.event.handlers.call( this, event, handlers ); - - // Run delegates first; they may want to stop propagation beneath us - i = 0; - while ( ( matched = handlerQueue[ i++ ] ) && !event.isPropagationStopped() ) { - event.currentTarget = matched.elem; - - j = 0; - while ( ( handleObj = matched.handlers[ j++ ] ) && - !event.isImmediatePropagationStopped() ) { - - // If the event is namespaced, then each handler is only invoked if it is - // specially universal or its namespaces are a superset of the event's. - if ( !event.rnamespace || handleObj.namespace === false || - event.rnamespace.test( handleObj.namespace ) ) { - - event.handleObj = handleObj; - event.data = handleObj.data; - - ret = ( ( jQuery.event.special[ handleObj.origType ] || {} ).handle || - handleObj.handler ).apply( matched.elem, args ); - - if ( ret !== undefined ) { - if ( ( event.result = ret ) === false ) { - event.preventDefault(); - event.stopPropagation(); - } - } - } - } - } - - // Call the postDispatch hook for the mapped type - if ( special.postDispatch ) { - special.postDispatch.call( this, event ); - } - - return event.result; - }, - - handlers: function( event, handlers ) { - var i, handleObj, sel, matchedHandlers, matchedSelectors, - handlerQueue = [], - delegateCount = handlers.delegateCount, - cur = event.target; - - // Find delegate handlers - if ( delegateCount && - - // Support: IE <=9 - // Black-hole SVG instance trees (trac-13180) - cur.nodeType && - - // Support: Firefox <=42 - // Suppress spec-violating clicks indicating a non-primary pointer button (trac-3861) - // https://www.w3.org/TR/DOM-Level-3-Events/#event-type-click - // Support: IE 11 only - // ...but not arrow key "clicks" of radio inputs, which can have `button` -1 (gh-2343) - !( event.type === "click" && event.button >= 1 ) ) { - - for ( ; cur !== this; cur = cur.parentNode || this ) { - - // Don't check non-elements (#13208) - // Don't process clicks on disabled elements (#6911, #8165, #11382, #11764) - if ( cur.nodeType === 1 && !( event.type === "click" && cur.disabled === true ) ) { - matchedHandlers = []; - matchedSelectors = {}; - for ( i = 0; i < delegateCount; i++ ) { - handleObj = handlers[ i ]; - - // Don't conflict with Object.prototype properties (#13203) - sel = handleObj.selector + " "; - - if ( matchedSelectors[ sel ] === undefined ) { - matchedSelectors[ sel ] = handleObj.needsContext ? - jQuery( sel, this ).index( cur ) > -1 : - jQuery.find( sel, this, null, [ cur ] ).length; - } - if ( matchedSelectors[ sel ] ) { - matchedHandlers.push( handleObj ); - } - } - if ( matchedHandlers.length ) { - handlerQueue.push( { elem: cur, handlers: matchedHandlers } ); - } - } - } - } - - // Add the remaining (directly-bound) handlers - cur = this; - if ( delegateCount < handlers.length ) { - handlerQueue.push( { elem: cur, handlers: handlers.slice( delegateCount ) } ); - } - - return handlerQueue; - }, - - addProp: function( name, hook ) { - Object.defineProperty( jQuery.Event.prototype, name, { - enumerable: true, - configurable: true, - - get: isFunction( hook ) ? - function() { - if ( this.originalEvent ) { - return hook( this.originalEvent ); - } - } : - function() { - if ( this.originalEvent ) { - return this.originalEvent[ name ]; - } - }, - - set: function( value ) { - Object.defineProperty( this, name, { - enumerable: true, - configurable: true, - writable: true, - value: value - } ); - } - } ); - }, - - fix: function( originalEvent ) { - return originalEvent[ jQuery.expando ] ? - originalEvent : - new jQuery.Event( originalEvent ); - }, - - special: { - load: { - - // Prevent triggered image.load events from bubbling to window.load - noBubble: true - }, - click: { - - // Utilize native event to ensure correct state for checkable inputs - setup: function( data ) { - - // For mutual compressibility with _default, replace `this` access with a local var. - // `|| data` is dead code meant only to preserve the variable through minification. - var el = this || data; - - // Claim the first handler - if ( rcheckableType.test( el.type ) && - el.click && nodeName( el, "input" ) ) { - - // dataPriv.set( el, "click", ... ) - leverageNative( el, "click", returnTrue ); - } - - // Return false to allow normal processing in the caller - return false; - }, - trigger: function( data ) { - - // For mutual compressibility with _default, replace `this` access with a local var. - // `|| data` is dead code meant only to preserve the variable through minification. - var el = this || data; - - // Force setup before triggering a click - if ( rcheckableType.test( el.type ) && - el.click && nodeName( el, "input" ) ) { - - leverageNative( el, "click" ); - } - - // Return non-false to allow normal event-path propagation - return true; - }, - - // For cross-browser consistency, suppress native .click() on links - // Also prevent it if we're currently inside a leveraged native-event stack - _default: function( event ) { - var target = event.target; - return rcheckableType.test( target.type ) && - target.click && nodeName( target, "input" ) && - dataPriv.get( target, "click" ) || - nodeName( target, "a" ); - } - }, - - beforeunload: { - postDispatch: function( event ) { - - // Support: Firefox 20+ - // Firefox doesn't alert if the returnValue field is not set. - if ( event.result !== undefined && event.originalEvent ) { - event.originalEvent.returnValue = event.result; - } - } - } - } -}; - -// Ensure the presence of an event listener that handles manually-triggered -// synthetic events by interrupting progress until reinvoked in response to -// *native* events that it fires directly, ensuring that state changes have -// already occurred before other listeners are invoked. -function leverageNative( el, type, expectSync ) { - - // Missing expectSync indicates a trigger call, which must force setup through jQuery.event.add - if ( !expectSync ) { - if ( dataPriv.get( el, type ) === undefined ) { - jQuery.event.add( el, type, returnTrue ); - } - return; - } - - // Register the controller as a special universal handler for all event namespaces - dataPriv.set( el, type, false ); - jQuery.event.add( el, type, { - namespace: false, - handler: function( event ) { - var notAsync, result, - saved = dataPriv.get( this, type ); - - if ( ( event.isTrigger & 1 ) && this[ type ] ) { - - // Interrupt processing of the outer synthetic .trigger()ed event - // Saved data should be false in such cases, but might be a leftover capture object - // from an async native handler (gh-4350) - if ( !saved.length ) { - - // Store arguments for use when handling the inner native event - // There will always be at least one argument (an event object), so this array - // will not be confused with a leftover capture object. - saved = slice.call( arguments ); - dataPriv.set( this, type, saved ); - - // Trigger the native event and capture its result - // Support: IE <=9 - 11+ - // focus() and blur() are asynchronous - notAsync = expectSync( this, type ); - this[ type ](); - result = dataPriv.get( this, type ); - if ( saved !== result || notAsync ) { - dataPriv.set( this, type, false ); - } else { - result = {}; - } - if ( saved !== result ) { - - // Cancel the outer synthetic event - event.stopImmediatePropagation(); - event.preventDefault(); - return result.value; - } - - // If this is an inner synthetic event for an event with a bubbling surrogate - // (focus or blur), assume that the surrogate already propagated from triggering the - // native event and prevent that from happening again here. - // This technically gets the ordering wrong w.r.t. to `.trigger()` (in which the - // bubbling surrogate propagates *after* the non-bubbling base), but that seems - // less bad than duplication. - } else if ( ( jQuery.event.special[ type ] || {} ).delegateType ) { - event.stopPropagation(); - } - - // If this is a native event triggered above, everything is now in order - // Fire an inner synthetic event with the original arguments - } else if ( saved.length ) { - - // ...and capture the result - dataPriv.set( this, type, { - value: jQuery.event.trigger( - - // Support: IE <=9 - 11+ - // Extend with the prototype to reset the above stopImmediatePropagation() - jQuery.extend( saved[ 0 ], jQuery.Event.prototype ), - saved.slice( 1 ), - this - ) - } ); - - // Abort handling of the native event - event.stopImmediatePropagation(); - } - } - } ); -} - -jQuery.removeEvent = function( elem, type, handle ) { - - // This "if" is needed for plain objects - if ( elem.removeEventListener ) { - elem.removeEventListener( type, handle ); - } -}; - -jQuery.Event = function( src, props ) { - - // Allow instantiation without the 'new' keyword - if ( !( this instanceof jQuery.Event ) ) { - return new jQuery.Event( src, props ); - } - - // Event object - if ( src && src.type ) { - this.originalEvent = src; - this.type = src.type; - - // Events bubbling up the document may have been marked as prevented - // by a handler lower down the tree; reflect the correct value. - this.isDefaultPrevented = src.defaultPrevented || - src.defaultPrevented === undefined && - - // Support: Android <=2.3 only - src.returnValue === false ? - returnTrue : - returnFalse; - - // Create target properties - // Support: Safari <=6 - 7 only - // Target should not be a text node (#504, #13143) - this.target = ( src.target && src.target.nodeType === 3 ) ? - src.target.parentNode : - src.target; - - this.currentTarget = src.currentTarget; - this.relatedTarget = src.relatedTarget; - - // Event type - } else { - this.type = src; - } - - // Put explicitly provided properties onto the event object - if ( props ) { - jQuery.extend( this, props ); - } - - // Create a timestamp if incoming event doesn't have one - this.timeStamp = src && src.timeStamp || Date.now(); - - // Mark it as fixed - this[ jQuery.expando ] = true; -}; - -// jQuery.Event is based on DOM3 Events as specified by the ECMAScript Language Binding -// https://www.w3.org/TR/2003/WD-DOM-Level-3-Events-20030331/ecma-script-binding.html -jQuery.Event.prototype = { - constructor: jQuery.Event, - isDefaultPrevented: returnFalse, - isPropagationStopped: returnFalse, - isImmediatePropagationStopped: returnFalse, - isSimulated: false, - - preventDefault: function() { - var e = this.originalEvent; - - this.isDefaultPrevented = returnTrue; - - if ( e && !this.isSimulated ) { - e.preventDefault(); - } - }, - stopPropagation: function() { - var e = this.originalEvent; - - this.isPropagationStopped = returnTrue; - - if ( e && !this.isSimulated ) { - e.stopPropagation(); - } - }, - stopImmediatePropagation: function() { - var e = this.originalEvent; - - this.isImmediatePropagationStopped = returnTrue; - - if ( e && !this.isSimulated ) { - e.stopImmediatePropagation(); - } - - this.stopPropagation(); - } -}; - -// Includes all common event props including KeyEvent and MouseEvent specific props -jQuery.each( { - altKey: true, - bubbles: true, - cancelable: true, - changedTouches: true, - ctrlKey: true, - detail: true, - eventPhase: true, - metaKey: true, - pageX: true, - pageY: true, - shiftKey: true, - view: true, - "char": true, - code: true, - charCode: true, - key: true, - keyCode: true, - button: true, - buttons: true, - clientX: true, - clientY: true, - offsetX: true, - offsetY: true, - pointerId: true, - pointerType: true, - screenX: true, - screenY: true, - targetTouches: true, - toElement: true, - touches: true, - - which: function( event ) { - var button = event.button; - - // Add which for key events - if ( event.which == null && rkeyEvent.test( event.type ) ) { - return event.charCode != null ? event.charCode : event.keyCode; - } - - // Add which for click: 1 === left; 2 === middle; 3 === right - if ( !event.which && button !== undefined && rmouseEvent.test( event.type ) ) { - if ( button & 1 ) { - return 1; - } - - if ( button & 2 ) { - return 3; - } - - if ( button & 4 ) { - return 2; - } - - return 0; - } - - return event.which; - } -}, jQuery.event.addProp ); - -jQuery.each( { focus: "focusin", blur: "focusout" }, function( type, delegateType ) { - jQuery.event.special[ type ] = { - - // Utilize native event if possible so blur/focus sequence is correct - setup: function() { - - // Claim the first handler - // dataPriv.set( this, "focus", ... ) - // dataPriv.set( this, "blur", ... ) - leverageNative( this, type, expectSync ); - - // Return false to allow normal processing in the caller - return false; - }, - trigger: function() { - - // Force setup before trigger - leverageNative( this, type ); - - // Return non-false to allow normal event-path propagation - return true; - }, - - delegateType: delegateType - }; -} ); - -// Create mouseenter/leave events using mouseover/out and event-time checks -// so that event delegation works in jQuery. -// Do the same for pointerenter/pointerleave and pointerover/pointerout -// -// Support: Safari 7 only -// Safari sends mouseenter too often; see: -// https://bugs.chromium.org/p/chromium/issues/detail?id=470258 -// for the description of the bug (it existed in older Chrome versions as well). -jQuery.each( { - mouseenter: "mouseover", - mouseleave: "mouseout", - pointerenter: "pointerover", - pointerleave: "pointerout" -}, function( orig, fix ) { - jQuery.event.special[ orig ] = { - delegateType: fix, - bindType: fix, - - handle: function( event ) { - var ret, - target = this, - related = event.relatedTarget, - handleObj = event.handleObj; - - // For mouseenter/leave call the handler if related is outside the target. - // NB: No relatedTarget if the mouse left/entered the browser window - if ( !related || ( related !== target && !jQuery.contains( target, related ) ) ) { - event.type = handleObj.origType; - ret = handleObj.handler.apply( this, arguments ); - event.type = fix; - } - return ret; - } - }; -} ); - -jQuery.fn.extend( { - - on: function( types, selector, data, fn ) { - return on( this, types, selector, data, fn ); - }, - one: function( types, selector, data, fn ) { - return on( this, types, selector, data, fn, 1 ); - }, - off: function( types, selector, fn ) { - var handleObj, type; - if ( types && types.preventDefault && types.handleObj ) { - - // ( event ) dispatched jQuery.Event - handleObj = types.handleObj; - jQuery( types.delegateTarget ).off( - handleObj.namespace ? - handleObj.origType + "." + handleObj.namespace : - handleObj.origType, - handleObj.selector, - handleObj.handler - ); - return this; - } - if ( typeof types === "object" ) { - - // ( types-object [, selector] ) - for ( type in types ) { - this.off( type, selector, types[ type ] ); - } - return this; - } - if ( selector === false || typeof selector === "function" ) { - - // ( types [, fn] ) - fn = selector; - selector = undefined; - } - if ( fn === false ) { - fn = returnFalse; - } - return this.each( function() { - jQuery.event.remove( this, types, fn, selector ); - } ); - } -} ); - - -var - - // Support: IE <=10 - 11, Edge 12 - 13 only - // In IE/Edge using regex groups here causes severe slowdowns. - // See https://connect.microsoft.com/IE/feedback/details/1736512/ - rnoInnerhtml = /\s*$/g; - -// Prefer a tbody over its parent table for containing new rows -function manipulationTarget( elem, content ) { - if ( nodeName( elem, "table" ) && - nodeName( content.nodeType !== 11 ? content : content.firstChild, "tr" ) ) { - - return jQuery( elem ).children( "tbody" )[ 0 ] || elem; - } - - return elem; -} - -// Replace/restore the type attribute of script elements for safe DOM manipulation -function disableScript( elem ) { - elem.type = ( elem.getAttribute( "type" ) !== null ) + "/" + elem.type; - return elem; -} -function restoreScript( elem ) { - if ( ( elem.type || "" ).slice( 0, 5 ) === "true/" ) { - elem.type = elem.type.slice( 5 ); - } else { - elem.removeAttribute( "type" ); - } - - return elem; -} - -function cloneCopyEvent( src, dest ) { - var i, l, type, pdataOld, udataOld, udataCur, events; - - if ( dest.nodeType !== 1 ) { - return; - } - - // 1. Copy private data: events, handlers, etc. - if ( dataPriv.hasData( src ) ) { - pdataOld = dataPriv.get( src ); - events = pdataOld.events; - - if ( events ) { - dataPriv.remove( dest, "handle events" ); - - for ( type in events ) { - for ( i = 0, l = events[ type ].length; i < l; i++ ) { - jQuery.event.add( dest, type, events[ type ][ i ] ); - } - } - } - } - - // 2. Copy user data - if ( dataUser.hasData( src ) ) { - udataOld = dataUser.access( src ); - udataCur = jQuery.extend( {}, udataOld ); - - dataUser.set( dest, udataCur ); - } -} - -// Fix IE bugs, see support tests -function fixInput( src, dest ) { - var nodeName = dest.nodeName.toLowerCase(); - - // Fails to persist the checked state of a cloned checkbox or radio button. - if ( nodeName === "input" && rcheckableType.test( src.type ) ) { - dest.checked = src.checked; - - // Fails to return the selected option to the default selected state when cloning options - } else if ( nodeName === "input" || nodeName === "textarea" ) { - dest.defaultValue = src.defaultValue; - } -} - -function domManip( collection, args, callback, ignored ) { - - // Flatten any nested arrays - args = flat( args ); - - var fragment, first, scripts, hasScripts, node, doc, - i = 0, - l = collection.length, - iNoClone = l - 1, - value = args[ 0 ], - valueIsFunction = isFunction( value ); - - // We can't cloneNode fragments that contain checked, in WebKit - if ( valueIsFunction || - ( l > 1 && typeof value === "string" && - !support.checkClone && rchecked.test( value ) ) ) { - return collection.each( function( index ) { - var self = collection.eq( index ); - if ( valueIsFunction ) { - args[ 0 ] = value.call( this, index, self.html() ); - } - domManip( self, args, callback, ignored ); - } ); - } - - if ( l ) { - fragment = buildFragment( args, collection[ 0 ].ownerDocument, false, collection, ignored ); - first = fragment.firstChild; - - if ( fragment.childNodes.length === 1 ) { - fragment = first; - } - - // Require either new content or an interest in ignored elements to invoke the callback - if ( first || ignored ) { - scripts = jQuery.map( getAll( fragment, "script" ), disableScript ); - hasScripts = scripts.length; - - // Use the original fragment for the last item - // instead of the first because it can end up - // being emptied incorrectly in certain situations (#8070). - for ( ; i < l; i++ ) { - node = fragment; - - if ( i !== iNoClone ) { - node = jQuery.clone( node, true, true ); - - // Keep references to cloned scripts for later restoration - if ( hasScripts ) { - - // Support: Android <=4.0 only, PhantomJS 1 only - // push.apply(_, arraylike) throws on ancient WebKit - jQuery.merge( scripts, getAll( node, "script" ) ); - } - } - - callback.call( collection[ i ], node, i ); - } - - if ( hasScripts ) { - doc = scripts[ scripts.length - 1 ].ownerDocument; - - // Reenable scripts - jQuery.map( scripts, restoreScript ); - - // Evaluate executable scripts on first document insertion - for ( i = 0; i < hasScripts; i++ ) { - node = scripts[ i ]; - if ( rscriptType.test( node.type || "" ) && - !dataPriv.access( node, "globalEval" ) && - jQuery.contains( doc, node ) ) { - - if ( node.src && ( node.type || "" ).toLowerCase() !== "module" ) { - - // Optional AJAX dependency, but won't run scripts if not present - if ( jQuery._evalUrl && !node.noModule ) { - jQuery._evalUrl( node.src, { - nonce: node.nonce || node.getAttribute( "nonce" ) - }, doc ); - } - } else { - DOMEval( node.textContent.replace( rcleanScript, "" ), node, doc ); - } - } - } - } - } - } - - return collection; -} - -function remove( elem, selector, keepData ) { - var node, - nodes = selector ? jQuery.filter( selector, elem ) : elem, - i = 0; - - for ( ; ( node = nodes[ i ] ) != null; i++ ) { - if ( !keepData && node.nodeType === 1 ) { - jQuery.cleanData( getAll( node ) ); - } - - if ( node.parentNode ) { - if ( keepData && isAttached( node ) ) { - setGlobalEval( getAll( node, "script" ) ); - } - node.parentNode.removeChild( node ); - } - } - - return elem; -} - -jQuery.extend( { - htmlPrefilter: function( html ) { - return html; - }, - - clone: function( elem, dataAndEvents, deepDataAndEvents ) { - var i, l, srcElements, destElements, - clone = elem.cloneNode( true ), - inPage = isAttached( elem ); - - // Fix IE cloning issues - if ( !support.noCloneChecked && ( elem.nodeType === 1 || elem.nodeType === 11 ) && - !jQuery.isXMLDoc( elem ) ) { - - // We eschew Sizzle here for performance reasons: https://jsperf.com/getall-vs-sizzle/2 - destElements = getAll( clone ); - srcElements = getAll( elem ); - - for ( i = 0, l = srcElements.length; i < l; i++ ) { - fixInput( srcElements[ i ], destElements[ i ] ); - } - } - - // Copy the events from the original to the clone - if ( dataAndEvents ) { - if ( deepDataAndEvents ) { - srcElements = srcElements || getAll( elem ); - destElements = destElements || getAll( clone ); - - for ( i = 0, l = srcElements.length; i < l; i++ ) { - cloneCopyEvent( srcElements[ i ], destElements[ i ] ); - } - } else { - cloneCopyEvent( elem, clone ); - } - } - - // Preserve script evaluation history - destElements = getAll( clone, "script" ); - if ( destElements.length > 0 ) { - setGlobalEval( destElements, !inPage && getAll( elem, "script" ) ); - } - - // Return the cloned set - return clone; - }, - - cleanData: function( elems ) { - var data, elem, type, - special = jQuery.event.special, - i = 0; - - for ( ; ( elem = elems[ i ] ) !== undefined; i++ ) { - if ( acceptData( elem ) ) { - if ( ( data = elem[ dataPriv.expando ] ) ) { - if ( data.events ) { - for ( type in data.events ) { - if ( special[ type ] ) { - jQuery.event.remove( elem, type ); - - // This is a shortcut to avoid jQuery.event.remove's overhead - } else { - jQuery.removeEvent( elem, type, data.handle ); - } - } - } - - // Support: Chrome <=35 - 45+ - // Assign undefined instead of using delete, see Data#remove - elem[ dataPriv.expando ] = undefined; - } - if ( elem[ dataUser.expando ] ) { - - // Support: Chrome <=35 - 45+ - // Assign undefined instead of using delete, see Data#remove - elem[ dataUser.expando ] = undefined; - } - } - } - } -} ); - -jQuery.fn.extend( { - detach: function( selector ) { - return remove( this, selector, true ); - }, - - remove: function( selector ) { - return remove( this, selector ); - }, - - text: function( value ) { - return access( this, function( value ) { - return value === undefined ? - jQuery.text( this ) : - this.empty().each( function() { - if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { - this.textContent = value; - } - } ); - }, null, value, arguments.length ); - }, - - append: function() { - return domManip( this, arguments, function( elem ) { - if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { - var target = manipulationTarget( this, elem ); - target.appendChild( elem ); - } - } ); - }, - - prepend: function() { - return domManip( this, arguments, function( elem ) { - if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { - var target = manipulationTarget( this, elem ); - target.insertBefore( elem, target.firstChild ); - } - } ); - }, - - before: function() { - return domManip( this, arguments, function( elem ) { - if ( this.parentNode ) { - this.parentNode.insertBefore( elem, this ); - } - } ); - }, - - after: function() { - return domManip( this, arguments, function( elem ) { - if ( this.parentNode ) { - this.parentNode.insertBefore( elem, this.nextSibling ); - } - } ); - }, - - empty: function() { - var elem, - i = 0; - - for ( ; ( elem = this[ i ] ) != null; i++ ) { - if ( elem.nodeType === 1 ) { - - // Prevent memory leaks - jQuery.cleanData( getAll( elem, false ) ); - - // Remove any remaining nodes - elem.textContent = ""; - } - } - - return this; - }, - - clone: function( dataAndEvents, deepDataAndEvents ) { - dataAndEvents = dataAndEvents == null ? false : dataAndEvents; - deepDataAndEvents = deepDataAndEvents == null ? dataAndEvents : deepDataAndEvents; - - return this.map( function() { - return jQuery.clone( this, dataAndEvents, deepDataAndEvents ); - } ); - }, - - html: function( value ) { - return access( this, function( value ) { - var elem = this[ 0 ] || {}, - i = 0, - l = this.length; - - if ( value === undefined && elem.nodeType === 1 ) { - return elem.innerHTML; - } - - // See if we can take a shortcut and just use innerHTML - if ( typeof value === "string" && !rnoInnerhtml.test( value ) && - !wrapMap[ ( rtagName.exec( value ) || [ "", "" ] )[ 1 ].toLowerCase() ] ) { - - value = jQuery.htmlPrefilter( value ); - - try { - for ( ; i < l; i++ ) { - elem = this[ i ] || {}; - - // Remove element nodes and prevent memory leaks - if ( elem.nodeType === 1 ) { - jQuery.cleanData( getAll( elem, false ) ); - elem.innerHTML = value; - } - } - - elem = 0; - - // If using innerHTML throws an exception, use the fallback method - } catch ( e ) {} - } - - if ( elem ) { - this.empty().append( value ); - } - }, null, value, arguments.length ); - }, - - replaceWith: function() { - var ignored = []; - - // Make the changes, replacing each non-ignored context element with the new content - return domManip( this, arguments, function( elem ) { - var parent = this.parentNode; - - if ( jQuery.inArray( this, ignored ) < 0 ) { - jQuery.cleanData( getAll( this ) ); - if ( parent ) { - parent.replaceChild( elem, this ); - } - } - - // Force callback invocation - }, ignored ); - } -} ); - -jQuery.each( { - appendTo: "append", - prependTo: "prepend", - insertBefore: "before", - insertAfter: "after", - replaceAll: "replaceWith" -}, function( name, original ) { - jQuery.fn[ name ] = function( selector ) { - var elems, - ret = [], - insert = jQuery( selector ), - last = insert.length - 1, - i = 0; - - for ( ; i <= last; i++ ) { - elems = i === last ? this : this.clone( true ); - jQuery( insert[ i ] )[ original ]( elems ); - - // Support: Android <=4.0 only, PhantomJS 1 only - // .get() because push.apply(_, arraylike) throws on ancient WebKit - push.apply( ret, elems.get() ); - } - - return this.pushStack( ret ); - }; -} ); -var rnumnonpx = new RegExp( "^(" + pnum + ")(?!px)[a-z%]+$", "i" ); - -var getStyles = function( elem ) { - - // Support: IE <=11 only, Firefox <=30 (#15098, #14150) - // IE throws on elements created in popups - // FF meanwhile throws on frame elements through "defaultView.getComputedStyle" - var view = elem.ownerDocument.defaultView; - - if ( !view || !view.opener ) { - view = window; - } - - return view.getComputedStyle( elem ); - }; - -var swap = function( elem, options, callback ) { - var ret, name, - old = {}; - - // Remember the old values, and insert the new ones - for ( name in options ) { - old[ name ] = elem.style[ name ]; - elem.style[ name ] = options[ name ]; - } - - ret = callback.call( elem ); - - // Revert the old values - for ( name in options ) { - elem.style[ name ] = old[ name ]; - } - - return ret; -}; - - -var rboxStyle = new RegExp( cssExpand.join( "|" ), "i" ); - - - -( function() { - - // Executing both pixelPosition & boxSizingReliable tests require only one layout - // so they're executed at the same time to save the second computation. - function computeStyleTests() { - - // This is a singleton, we need to execute it only once - if ( !div ) { - return; - } - - container.style.cssText = "position:absolute;left:-11111px;width:60px;" + - "margin-top:1px;padding:0;border:0"; - div.style.cssText = - "position:relative;display:block;box-sizing:border-box;overflow:scroll;" + - "margin:auto;border:1px;padding:1px;" + - "width:60%;top:1%"; - documentElement.appendChild( container ).appendChild( div ); - - var divStyle = window.getComputedStyle( div ); - pixelPositionVal = divStyle.top !== "1%"; - - // Support: Android 4.0 - 4.3 only, Firefox <=3 - 44 - reliableMarginLeftVal = roundPixelMeasures( divStyle.marginLeft ) === 12; - - // Support: Android 4.0 - 4.3 only, Safari <=9.1 - 10.1, iOS <=7.0 - 9.3 - // Some styles come back with percentage values, even though they shouldn't - div.style.right = "60%"; - pixelBoxStylesVal = roundPixelMeasures( divStyle.right ) === 36; - - // Support: IE 9 - 11 only - // Detect misreporting of content dimensions for box-sizing:border-box elements - boxSizingReliableVal = roundPixelMeasures( divStyle.width ) === 36; - - // Support: IE 9 only - // Detect overflow:scroll screwiness (gh-3699) - // Support: Chrome <=64 - // Don't get tricked when zoom affects offsetWidth (gh-4029) - div.style.position = "absolute"; - scrollboxSizeVal = roundPixelMeasures( div.offsetWidth / 3 ) === 12; - - documentElement.removeChild( container ); - - // Nullify the div so it wouldn't be stored in the memory and - // it will also be a sign that checks already performed - div = null; - } - - function roundPixelMeasures( measure ) { - return Math.round( parseFloat( measure ) ); - } - - var pixelPositionVal, boxSizingReliableVal, scrollboxSizeVal, pixelBoxStylesVal, - reliableTrDimensionsVal, reliableMarginLeftVal, - container = document.createElement( "div" ), - div = document.createElement( "div" ); - - // Finish early in limited (non-browser) environments - if ( !div.style ) { - return; - } - - // Support: IE <=9 - 11 only - // Style of cloned element affects source element cloned (#8908) - div.style.backgroundClip = "content-box"; - div.cloneNode( true ).style.backgroundClip = ""; - support.clearCloneStyle = div.style.backgroundClip === "content-box"; - - jQuery.extend( support, { - boxSizingReliable: function() { - computeStyleTests(); - return boxSizingReliableVal; - }, - pixelBoxStyles: function() { - computeStyleTests(); - return pixelBoxStylesVal; - }, - pixelPosition: function() { - computeStyleTests(); - return pixelPositionVal; - }, - reliableMarginLeft: function() { - computeStyleTests(); - return reliableMarginLeftVal; - }, - scrollboxSize: function() { - computeStyleTests(); - return scrollboxSizeVal; - }, - - // Support: IE 9 - 11+, Edge 15 - 18+ - // IE/Edge misreport `getComputedStyle` of table rows with width/height - // set in CSS while `offset*` properties report correct values. - // Behavior in IE 9 is more subtle than in newer versions & it passes - // some versions of this test; make sure not to make it pass there! - reliableTrDimensions: function() { - var table, tr, trChild, trStyle; - if ( reliableTrDimensionsVal == null ) { - table = document.createElement( "table" ); - tr = document.createElement( "tr" ); - trChild = document.createElement( "div" ); - - table.style.cssText = "position:absolute;left:-11111px"; - tr.style.height = "1px"; - trChild.style.height = "9px"; - - documentElement - .appendChild( table ) - .appendChild( tr ) - .appendChild( trChild ); - - trStyle = window.getComputedStyle( tr ); - reliableTrDimensionsVal = parseInt( trStyle.height ) > 3; - - documentElement.removeChild( table ); - } - return reliableTrDimensionsVal; - } - } ); -} )(); - - -function curCSS( elem, name, computed ) { - var width, minWidth, maxWidth, ret, - - // Support: Firefox 51+ - // Retrieving style before computed somehow - // fixes an issue with getting wrong values - // on detached elements - style = elem.style; - - computed = computed || getStyles( elem ); - - // getPropertyValue is needed for: - // .css('filter') (IE 9 only, #12537) - // .css('--customProperty) (#3144) - if ( computed ) { - ret = computed.getPropertyValue( name ) || computed[ name ]; - - if ( ret === "" && !isAttached( elem ) ) { - ret = jQuery.style( elem, name ); - } - - // A tribute to the "awesome hack by Dean Edwards" - // Android Browser returns percentage for some values, - // but width seems to be reliably pixels. - // This is against the CSSOM draft spec: - // https://drafts.csswg.org/cssom/#resolved-values - if ( !support.pixelBoxStyles() && rnumnonpx.test( ret ) && rboxStyle.test( name ) ) { - - // Remember the original values - width = style.width; - minWidth = style.minWidth; - maxWidth = style.maxWidth; - - // Put in the new values to get a computed value out - style.minWidth = style.maxWidth = style.width = ret; - ret = computed.width; - - // Revert the changed values - style.width = width; - style.minWidth = minWidth; - style.maxWidth = maxWidth; - } - } - - return ret !== undefined ? - - // Support: IE <=9 - 11 only - // IE returns zIndex value as an integer. - ret + "" : - ret; -} - - -function addGetHookIf( conditionFn, hookFn ) { - - // Define the hook, we'll check on the first run if it's really needed. - return { - get: function() { - if ( conditionFn() ) { - - // Hook not needed (or it's not possible to use it due - // to missing dependency), remove it. - delete this.get; - return; - } - - // Hook needed; redefine it so that the support test is not executed again. - return ( this.get = hookFn ).apply( this, arguments ); - } - }; -} - - -var cssPrefixes = [ "Webkit", "Moz", "ms" ], - emptyStyle = document.createElement( "div" ).style, - vendorProps = {}; - -// Return a vendor-prefixed property or undefined -function vendorPropName( name ) { - - // Check for vendor prefixed names - var capName = name[ 0 ].toUpperCase() + name.slice( 1 ), - i = cssPrefixes.length; - - while ( i-- ) { - name = cssPrefixes[ i ] + capName; - if ( name in emptyStyle ) { - return name; - } - } -} - -// Return a potentially-mapped jQuery.cssProps or vendor prefixed property -function finalPropName( name ) { - var final = jQuery.cssProps[ name ] || vendorProps[ name ]; - - if ( final ) { - return final; - } - if ( name in emptyStyle ) { - return name; - } - return vendorProps[ name ] = vendorPropName( name ) || name; -} - - -var - - // Swappable if display is none or starts with table - // except "table", "table-cell", or "table-caption" - // See here for display values: https://developer.mozilla.org/en-US/docs/CSS/display - rdisplayswap = /^(none|table(?!-c[ea]).+)/, - rcustomProp = /^--/, - cssShow = { position: "absolute", visibility: "hidden", display: "block" }, - cssNormalTransform = { - letterSpacing: "0", - fontWeight: "400" - }; - -function setPositiveNumber( _elem, value, subtract ) { - - // Any relative (+/-) values have already been - // normalized at this point - var matches = rcssNum.exec( value ); - return matches ? - - // Guard against undefined "subtract", e.g., when used as in cssHooks - Math.max( 0, matches[ 2 ] - ( subtract || 0 ) ) + ( matches[ 3 ] || "px" ) : - value; -} - -function boxModelAdjustment( elem, dimension, box, isBorderBox, styles, computedVal ) { - var i = dimension === "width" ? 1 : 0, - extra = 0, - delta = 0; - - // Adjustment may not be necessary - if ( box === ( isBorderBox ? "border" : "content" ) ) { - return 0; - } - - for ( ; i < 4; i += 2 ) { - - // Both box models exclude margin - if ( box === "margin" ) { - delta += jQuery.css( elem, box + cssExpand[ i ], true, styles ); - } - - // If we get here with a content-box, we're seeking "padding" or "border" or "margin" - if ( !isBorderBox ) { - - // Add padding - delta += jQuery.css( elem, "padding" + cssExpand[ i ], true, styles ); - - // For "border" or "margin", add border - if ( box !== "padding" ) { - delta += jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); - - // But still keep track of it otherwise - } else { - extra += jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); - } - - // If we get here with a border-box (content + padding + border), we're seeking "content" or - // "padding" or "margin" - } else { - - // For "content", subtract padding - if ( box === "content" ) { - delta -= jQuery.css( elem, "padding" + cssExpand[ i ], true, styles ); - } - - // For "content" or "padding", subtract border - if ( box !== "margin" ) { - delta -= jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); - } - } - } - - // Account for positive content-box scroll gutter when requested by providing computedVal - if ( !isBorderBox && computedVal >= 0 ) { - - // offsetWidth/offsetHeight is a rounded sum of content, padding, scroll gutter, and border - // Assuming integer scroll gutter, subtract the rest and round down - delta += Math.max( 0, Math.ceil( - elem[ "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ) ] - - computedVal - - delta - - extra - - 0.5 - - // If offsetWidth/offsetHeight is unknown, then we can't determine content-box scroll gutter - // Use an explicit zero to avoid NaN (gh-3964) - ) ) || 0; - } - - return delta; -} - -function getWidthOrHeight( elem, dimension, extra ) { - - // Start with computed style - var styles = getStyles( elem ), - - // To avoid forcing a reflow, only fetch boxSizing if we need it (gh-4322). - // Fake content-box until we know it's needed to know the true value. - boxSizingNeeded = !support.boxSizingReliable() || extra, - isBorderBox = boxSizingNeeded && - jQuery.css( elem, "boxSizing", false, styles ) === "border-box", - valueIsBorderBox = isBorderBox, - - val = curCSS( elem, dimension, styles ), - offsetProp = "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ); - - // Support: Firefox <=54 - // Return a confounding non-pixel value or feign ignorance, as appropriate. - if ( rnumnonpx.test( val ) ) { - if ( !extra ) { - return val; - } - val = "auto"; - } - - - // Support: IE 9 - 11 only - // Use offsetWidth/offsetHeight for when box sizing is unreliable. - // In those cases, the computed value can be trusted to be border-box. - if ( ( !support.boxSizingReliable() && isBorderBox || - - // Support: IE 10 - 11+, Edge 15 - 18+ - // IE/Edge misreport `getComputedStyle` of table rows with width/height - // set in CSS while `offset*` properties report correct values. - // Interestingly, in some cases IE 9 doesn't suffer from this issue. - !support.reliableTrDimensions() && nodeName( elem, "tr" ) || - - // Fall back to offsetWidth/offsetHeight when value is "auto" - // This happens for inline elements with no explicit setting (gh-3571) - val === "auto" || - - // Support: Android <=4.1 - 4.3 only - // Also use offsetWidth/offsetHeight for misreported inline dimensions (gh-3602) - !parseFloat( val ) && jQuery.css( elem, "display", false, styles ) === "inline" ) && - - // Make sure the element is visible & connected - elem.getClientRects().length ) { - - isBorderBox = jQuery.css( elem, "boxSizing", false, styles ) === "border-box"; - - // Where available, offsetWidth/offsetHeight approximate border box dimensions. - // Where not available (e.g., SVG), assume unreliable box-sizing and interpret the - // retrieved value as a content box dimension. - valueIsBorderBox = offsetProp in elem; - if ( valueIsBorderBox ) { - val = elem[ offsetProp ]; - } - } - - // Normalize "" and auto - val = parseFloat( val ) || 0; - - // Adjust for the element's box model - return ( val + - boxModelAdjustment( - elem, - dimension, - extra || ( isBorderBox ? "border" : "content" ), - valueIsBorderBox, - styles, - - // Provide the current computed size to request scroll gutter calculation (gh-3589) - val - ) - ) + "px"; -} - -jQuery.extend( { - - // Add in style property hooks for overriding the default - // behavior of getting and setting a style property - cssHooks: { - opacity: { - get: function( elem, computed ) { - if ( computed ) { - - // We should always get a number back from opacity - var ret = curCSS( elem, "opacity" ); - return ret === "" ? "1" : ret; - } - } - } - }, - - // Don't automatically add "px" to these possibly-unitless properties - cssNumber: { - "animationIterationCount": true, - "columnCount": true, - "fillOpacity": true, - "flexGrow": true, - "flexShrink": true, - "fontWeight": true, - "gridArea": true, - "gridColumn": true, - "gridColumnEnd": true, - "gridColumnStart": true, - "gridRow": true, - "gridRowEnd": true, - "gridRowStart": true, - "lineHeight": true, - "opacity": true, - "order": true, - "orphans": true, - "widows": true, - "zIndex": true, - "zoom": true - }, - - // Add in properties whose names you wish to fix before - // setting or getting the value - cssProps: {}, - - // Get and set the style property on a DOM Node - style: function( elem, name, value, extra ) { - - // Don't set styles on text and comment nodes - if ( !elem || elem.nodeType === 3 || elem.nodeType === 8 || !elem.style ) { - return; - } - - // Make sure that we're working with the right name - var ret, type, hooks, - origName = camelCase( name ), - isCustomProp = rcustomProp.test( name ), - style = elem.style; - - // Make sure that we're working with the right name. We don't - // want to query the value if it is a CSS custom property - // since they are user-defined. - if ( !isCustomProp ) { - name = finalPropName( origName ); - } - - // Gets hook for the prefixed version, then unprefixed version - hooks = jQuery.cssHooks[ name ] || jQuery.cssHooks[ origName ]; - - // Check if we're setting a value - if ( value !== undefined ) { - type = typeof value; - - // Convert "+=" or "-=" to relative numbers (#7345) - if ( type === "string" && ( ret = rcssNum.exec( value ) ) && ret[ 1 ] ) { - value = adjustCSS( elem, name, ret ); - - // Fixes bug #9237 - type = "number"; - } - - // Make sure that null and NaN values aren't set (#7116) - if ( value == null || value !== value ) { - return; - } - - // If a number was passed in, add the unit (except for certain CSS properties) - // The isCustomProp check can be removed in jQuery 4.0 when we only auto-append - // "px" to a few hardcoded values. - if ( type === "number" && !isCustomProp ) { - value += ret && ret[ 3 ] || ( jQuery.cssNumber[ origName ] ? "" : "px" ); - } - - // background-* props affect original clone's values - if ( !support.clearCloneStyle && value === "" && name.indexOf( "background" ) === 0 ) { - style[ name ] = "inherit"; - } - - // If a hook was provided, use that value, otherwise just set the specified value - if ( !hooks || !( "set" in hooks ) || - ( value = hooks.set( elem, value, extra ) ) !== undefined ) { - - if ( isCustomProp ) { - style.setProperty( name, value ); - } else { - style[ name ] = value; - } - } - - } else { - - // If a hook was provided get the non-computed value from there - if ( hooks && "get" in hooks && - ( ret = hooks.get( elem, false, extra ) ) !== undefined ) { - - return ret; - } - - // Otherwise just get the value from the style object - return style[ name ]; - } - }, - - css: function( elem, name, extra, styles ) { - var val, num, hooks, - origName = camelCase( name ), - isCustomProp = rcustomProp.test( name ); - - // Make sure that we're working with the right name. We don't - // want to modify the value if it is a CSS custom property - // since they are user-defined. - if ( !isCustomProp ) { - name = finalPropName( origName ); - } - - // Try prefixed name followed by the unprefixed name - hooks = jQuery.cssHooks[ name ] || jQuery.cssHooks[ origName ]; - - // If a hook was provided get the computed value from there - if ( hooks && "get" in hooks ) { - val = hooks.get( elem, true, extra ); - } - - // Otherwise, if a way to get the computed value exists, use that - if ( val === undefined ) { - val = curCSS( elem, name, styles ); - } - - // Convert "normal" to computed value - if ( val === "normal" && name in cssNormalTransform ) { - val = cssNormalTransform[ name ]; - } - - // Make numeric if forced or a qualifier was provided and val looks numeric - if ( extra === "" || extra ) { - num = parseFloat( val ); - return extra === true || isFinite( num ) ? num || 0 : val; - } - - return val; - } -} ); - -jQuery.each( [ "height", "width" ], function( _i, dimension ) { - jQuery.cssHooks[ dimension ] = { - get: function( elem, computed, extra ) { - if ( computed ) { - - // Certain elements can have dimension info if we invisibly show them - // but it must have a current display style that would benefit - return rdisplayswap.test( jQuery.css( elem, "display" ) ) && - - // Support: Safari 8+ - // Table columns in Safari have non-zero offsetWidth & zero - // getBoundingClientRect().width unless display is changed. - // Support: IE <=11 only - // Running getBoundingClientRect on a disconnected node - // in IE throws an error. - ( !elem.getClientRects().length || !elem.getBoundingClientRect().width ) ? - swap( elem, cssShow, function() { - return getWidthOrHeight( elem, dimension, extra ); - } ) : - getWidthOrHeight( elem, dimension, extra ); - } - }, - - set: function( elem, value, extra ) { - var matches, - styles = getStyles( elem ), - - // Only read styles.position if the test has a chance to fail - // to avoid forcing a reflow. - scrollboxSizeBuggy = !support.scrollboxSize() && - styles.position === "absolute", - - // To avoid forcing a reflow, only fetch boxSizing if we need it (gh-3991) - boxSizingNeeded = scrollboxSizeBuggy || extra, - isBorderBox = boxSizingNeeded && - jQuery.css( elem, "boxSizing", false, styles ) === "border-box", - subtract = extra ? - boxModelAdjustment( - elem, - dimension, - extra, - isBorderBox, - styles - ) : - 0; - - // Account for unreliable border-box dimensions by comparing offset* to computed and - // faking a content-box to get border and padding (gh-3699) - if ( isBorderBox && scrollboxSizeBuggy ) { - subtract -= Math.ceil( - elem[ "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ) ] - - parseFloat( styles[ dimension ] ) - - boxModelAdjustment( elem, dimension, "border", false, styles ) - - 0.5 - ); - } - - // Convert to pixels if value adjustment is needed - if ( subtract && ( matches = rcssNum.exec( value ) ) && - ( matches[ 3 ] || "px" ) !== "px" ) { - - elem.style[ dimension ] = value; - value = jQuery.css( elem, dimension ); - } - - return setPositiveNumber( elem, value, subtract ); - } - }; -} ); - -jQuery.cssHooks.marginLeft = addGetHookIf( support.reliableMarginLeft, - function( elem, computed ) { - if ( computed ) { - return ( parseFloat( curCSS( elem, "marginLeft" ) ) || - elem.getBoundingClientRect().left - - swap( elem, { marginLeft: 0 }, function() { - return elem.getBoundingClientRect().left; - } ) - ) + "px"; - } - } -); - -// These hooks are used by animate to expand properties -jQuery.each( { - margin: "", - padding: "", - border: "Width" -}, function( prefix, suffix ) { - jQuery.cssHooks[ prefix + suffix ] = { - expand: function( value ) { - var i = 0, - expanded = {}, - - // Assumes a single number if not a string - parts = typeof value === "string" ? value.split( " " ) : [ value ]; - - for ( ; i < 4; i++ ) { - expanded[ prefix + cssExpand[ i ] + suffix ] = - parts[ i ] || parts[ i - 2 ] || parts[ 0 ]; - } - - return expanded; - } - }; - - if ( prefix !== "margin" ) { - jQuery.cssHooks[ prefix + suffix ].set = setPositiveNumber; - } -} ); - -jQuery.fn.extend( { - css: function( name, value ) { - return access( this, function( elem, name, value ) { - var styles, len, - map = {}, - i = 0; - - if ( Array.isArray( name ) ) { - styles = getStyles( elem ); - len = name.length; - - for ( ; i < len; i++ ) { - map[ name[ i ] ] = jQuery.css( elem, name[ i ], false, styles ); - } - - return map; - } - - return value !== undefined ? - jQuery.style( elem, name, value ) : - jQuery.css( elem, name ); - }, name, value, arguments.length > 1 ); - } -} ); - - -function Tween( elem, options, prop, end, easing ) { - return new Tween.prototype.init( elem, options, prop, end, easing ); -} -jQuery.Tween = Tween; - -Tween.prototype = { - constructor: Tween, - init: function( elem, options, prop, end, easing, unit ) { - this.elem = elem; - this.prop = prop; - this.easing = easing || jQuery.easing._default; - this.options = options; - this.start = this.now = this.cur(); - this.end = end; - this.unit = unit || ( jQuery.cssNumber[ prop ] ? "" : "px" ); - }, - cur: function() { - var hooks = Tween.propHooks[ this.prop ]; - - return hooks && hooks.get ? - hooks.get( this ) : - Tween.propHooks._default.get( this ); - }, - run: function( percent ) { - var eased, - hooks = Tween.propHooks[ this.prop ]; - - if ( this.options.duration ) { - this.pos = eased = jQuery.easing[ this.easing ]( - percent, this.options.duration * percent, 0, 1, this.options.duration - ); - } else { - this.pos = eased = percent; - } - this.now = ( this.end - this.start ) * eased + this.start; - - if ( this.options.step ) { - this.options.step.call( this.elem, this.now, this ); - } - - if ( hooks && hooks.set ) { - hooks.set( this ); - } else { - Tween.propHooks._default.set( this ); - } - return this; - } -}; - -Tween.prototype.init.prototype = Tween.prototype; - -Tween.propHooks = { - _default: { - get: function( tween ) { - var result; - - // Use a property on the element directly when it is not a DOM element, - // or when there is no matching style property that exists. - if ( tween.elem.nodeType !== 1 || - tween.elem[ tween.prop ] != null && tween.elem.style[ tween.prop ] == null ) { - return tween.elem[ tween.prop ]; - } - - // Passing an empty string as a 3rd parameter to .css will automatically - // attempt a parseFloat and fallback to a string if the parse fails. - // Simple values such as "10px" are parsed to Float; - // complex values such as "rotate(1rad)" are returned as-is. - result = jQuery.css( tween.elem, tween.prop, "" ); - - // Empty strings, null, undefined and "auto" are converted to 0. - return !result || result === "auto" ? 0 : result; - }, - set: function( tween ) { - - // Use step hook for back compat. - // Use cssHook if its there. - // Use .style if available and use plain properties where available. - if ( jQuery.fx.step[ tween.prop ] ) { - jQuery.fx.step[ tween.prop ]( tween ); - } else if ( tween.elem.nodeType === 1 && ( - jQuery.cssHooks[ tween.prop ] || - tween.elem.style[ finalPropName( tween.prop ) ] != null ) ) { - jQuery.style( tween.elem, tween.prop, tween.now + tween.unit ); - } else { - tween.elem[ tween.prop ] = tween.now; - } - } - } -}; - -// Support: IE <=9 only -// Panic based approach to setting things on disconnected nodes -Tween.propHooks.scrollTop = Tween.propHooks.scrollLeft = { - set: function( tween ) { - if ( tween.elem.nodeType && tween.elem.parentNode ) { - tween.elem[ tween.prop ] = tween.now; - } - } -}; - -jQuery.easing = { - linear: function( p ) { - return p; - }, - swing: function( p ) { - return 0.5 - Math.cos( p * Math.PI ) / 2; - }, - _default: "swing" -}; - -jQuery.fx = Tween.prototype.init; - -// Back compat <1.8 extension point -jQuery.fx.step = {}; - - - - -var - fxNow, inProgress, - rfxtypes = /^(?:toggle|show|hide)$/, - rrun = /queueHooks$/; - -function schedule() { - if ( inProgress ) { - if ( document.hidden === false && window.requestAnimationFrame ) { - window.requestAnimationFrame( schedule ); - } else { - window.setTimeout( schedule, jQuery.fx.interval ); - } - - jQuery.fx.tick(); - } -} - -// Animations created synchronously will run synchronously -function createFxNow() { - window.setTimeout( function() { - fxNow = undefined; - } ); - return ( fxNow = Date.now() ); -} - -// Generate parameters to create a standard animation -function genFx( type, includeWidth ) { - var which, - i = 0, - attrs = { height: type }; - - // If we include width, step value is 1 to do all cssExpand values, - // otherwise step value is 2 to skip over Left and Right - includeWidth = includeWidth ? 1 : 0; - for ( ; i < 4; i += 2 - includeWidth ) { - which = cssExpand[ i ]; - attrs[ "margin" + which ] = attrs[ "padding" + which ] = type; - } - - if ( includeWidth ) { - attrs.opacity = attrs.width = type; - } - - return attrs; -} - -function createTween( value, prop, animation ) { - var tween, - collection = ( Animation.tweeners[ prop ] || [] ).concat( Animation.tweeners[ "*" ] ), - index = 0, - length = collection.length; - for ( ; index < length; index++ ) { - if ( ( tween = collection[ index ].call( animation, prop, value ) ) ) { - - // We're done with this property - return tween; - } - } -} - -function defaultPrefilter( elem, props, opts ) { - var prop, value, toggle, hooks, oldfire, propTween, restoreDisplay, display, - isBox = "width" in props || "height" in props, - anim = this, - orig = {}, - style = elem.style, - hidden = elem.nodeType && isHiddenWithinTree( elem ), - dataShow = dataPriv.get( elem, "fxshow" ); - - // Queue-skipping animations hijack the fx hooks - if ( !opts.queue ) { - hooks = jQuery._queueHooks( elem, "fx" ); - if ( hooks.unqueued == null ) { - hooks.unqueued = 0; - oldfire = hooks.empty.fire; - hooks.empty.fire = function() { - if ( !hooks.unqueued ) { - oldfire(); - } - }; - } - hooks.unqueued++; - - anim.always( function() { - - // Ensure the complete handler is called before this completes - anim.always( function() { - hooks.unqueued--; - if ( !jQuery.queue( elem, "fx" ).length ) { - hooks.empty.fire(); - } - } ); - } ); - } - - // Detect show/hide animations - for ( prop in props ) { - value = props[ prop ]; - if ( rfxtypes.test( value ) ) { - delete props[ prop ]; - toggle = toggle || value === "toggle"; - if ( value === ( hidden ? "hide" : "show" ) ) { - - // Pretend to be hidden if this is a "show" and - // there is still data from a stopped show/hide - if ( value === "show" && dataShow && dataShow[ prop ] !== undefined ) { - hidden = true; - - // Ignore all other no-op show/hide data - } else { - continue; - } - } - orig[ prop ] = dataShow && dataShow[ prop ] || jQuery.style( elem, prop ); - } - } - - // Bail out if this is a no-op like .hide().hide() - propTween = !jQuery.isEmptyObject( props ); - if ( !propTween && jQuery.isEmptyObject( orig ) ) { - return; - } - - // Restrict "overflow" and "display" styles during box animations - if ( isBox && elem.nodeType === 1 ) { - - // Support: IE <=9 - 11, Edge 12 - 15 - // Record all 3 overflow attributes because IE does not infer the shorthand - // from identically-valued overflowX and overflowY and Edge just mirrors - // the overflowX value there. - opts.overflow = [ style.overflow, style.overflowX, style.overflowY ]; - - // Identify a display type, preferring old show/hide data over the CSS cascade - restoreDisplay = dataShow && dataShow.display; - if ( restoreDisplay == null ) { - restoreDisplay = dataPriv.get( elem, "display" ); - } - display = jQuery.css( elem, "display" ); - if ( display === "none" ) { - if ( restoreDisplay ) { - display = restoreDisplay; - } else { - - // Get nonempty value(s) by temporarily forcing visibility - showHide( [ elem ], true ); - restoreDisplay = elem.style.display || restoreDisplay; - display = jQuery.css( elem, "display" ); - showHide( [ elem ] ); - } - } - - // Animate inline elements as inline-block - if ( display === "inline" || display === "inline-block" && restoreDisplay != null ) { - if ( jQuery.css( elem, "float" ) === "none" ) { - - // Restore the original display value at the end of pure show/hide animations - if ( !propTween ) { - anim.done( function() { - style.display = restoreDisplay; - } ); - if ( restoreDisplay == null ) { - display = style.display; - restoreDisplay = display === "none" ? "" : display; - } - } - style.display = "inline-block"; - } - } - } - - if ( opts.overflow ) { - style.overflow = "hidden"; - anim.always( function() { - style.overflow = opts.overflow[ 0 ]; - style.overflowX = opts.overflow[ 1 ]; - style.overflowY = opts.overflow[ 2 ]; - } ); - } - - // Implement show/hide animations - propTween = false; - for ( prop in orig ) { - - // General show/hide setup for this element animation - if ( !propTween ) { - if ( dataShow ) { - if ( "hidden" in dataShow ) { - hidden = dataShow.hidden; - } - } else { - dataShow = dataPriv.access( elem, "fxshow", { display: restoreDisplay } ); - } - - // Store hidden/visible for toggle so `.stop().toggle()` "reverses" - if ( toggle ) { - dataShow.hidden = !hidden; - } - - // Show elements before animating them - if ( hidden ) { - showHide( [ elem ], true ); - } - - /* eslint-disable no-loop-func */ - - anim.done( function() { - - /* eslint-enable no-loop-func */ - - // The final step of a "hide" animation is actually hiding the element - if ( !hidden ) { - showHide( [ elem ] ); - } - dataPriv.remove( elem, "fxshow" ); - for ( prop in orig ) { - jQuery.style( elem, prop, orig[ prop ] ); - } - } ); - } - - // Per-property setup - propTween = createTween( hidden ? dataShow[ prop ] : 0, prop, anim ); - if ( !( prop in dataShow ) ) { - dataShow[ prop ] = propTween.start; - if ( hidden ) { - propTween.end = propTween.start; - propTween.start = 0; - } - } - } -} - -function propFilter( props, specialEasing ) { - var index, name, easing, value, hooks; - - // camelCase, specialEasing and expand cssHook pass - for ( index in props ) { - name = camelCase( index ); - easing = specialEasing[ name ]; - value = props[ index ]; - if ( Array.isArray( value ) ) { - easing = value[ 1 ]; - value = props[ index ] = value[ 0 ]; - } - - if ( index !== name ) { - props[ name ] = value; - delete props[ index ]; - } - - hooks = jQuery.cssHooks[ name ]; - if ( hooks && "expand" in hooks ) { - value = hooks.expand( value ); - delete props[ name ]; - - // Not quite $.extend, this won't overwrite existing keys. - // Reusing 'index' because we have the correct "name" - for ( index in value ) { - if ( !( index in props ) ) { - props[ index ] = value[ index ]; - specialEasing[ index ] = easing; - } - } - } else { - specialEasing[ name ] = easing; - } - } -} - -function Animation( elem, properties, options ) { - var result, - stopped, - index = 0, - length = Animation.prefilters.length, - deferred = jQuery.Deferred().always( function() { - - // Don't match elem in the :animated selector - delete tick.elem; - } ), - tick = function() { - if ( stopped ) { - return false; - } - var currentTime = fxNow || createFxNow(), - remaining = Math.max( 0, animation.startTime + animation.duration - currentTime ), - - // Support: Android 2.3 only - // Archaic crash bug won't allow us to use `1 - ( 0.5 || 0 )` (#12497) - temp = remaining / animation.duration || 0, - percent = 1 - temp, - index = 0, - length = animation.tweens.length; - - for ( ; index < length; index++ ) { - animation.tweens[ index ].run( percent ); - } - - deferred.notifyWith( elem, [ animation, percent, remaining ] ); - - // If there's more to do, yield - if ( percent < 1 && length ) { - return remaining; - } - - // If this was an empty animation, synthesize a final progress notification - if ( !length ) { - deferred.notifyWith( elem, [ animation, 1, 0 ] ); - } - - // Resolve the animation and report its conclusion - deferred.resolveWith( elem, [ animation ] ); - return false; - }, - animation = deferred.promise( { - elem: elem, - props: jQuery.extend( {}, properties ), - opts: jQuery.extend( true, { - specialEasing: {}, - easing: jQuery.easing._default - }, options ), - originalProperties: properties, - originalOptions: options, - startTime: fxNow || createFxNow(), - duration: options.duration, - tweens: [], - createTween: function( prop, end ) { - var tween = jQuery.Tween( elem, animation.opts, prop, end, - animation.opts.specialEasing[ prop ] || animation.opts.easing ); - animation.tweens.push( tween ); - return tween; - }, - stop: function( gotoEnd ) { - var index = 0, - - // If we are going to the end, we want to run all the tweens - // otherwise we skip this part - length = gotoEnd ? animation.tweens.length : 0; - if ( stopped ) { - return this; - } - stopped = true; - for ( ; index < length; index++ ) { - animation.tweens[ index ].run( 1 ); - } - - // Resolve when we played the last frame; otherwise, reject - if ( gotoEnd ) { - deferred.notifyWith( elem, [ animation, 1, 0 ] ); - deferred.resolveWith( elem, [ animation, gotoEnd ] ); - } else { - deferred.rejectWith( elem, [ animation, gotoEnd ] ); - } - return this; - } - } ), - props = animation.props; - - propFilter( props, animation.opts.specialEasing ); - - for ( ; index < length; index++ ) { - result = Animation.prefilters[ index ].call( animation, elem, props, animation.opts ); - if ( result ) { - if ( isFunction( result.stop ) ) { - jQuery._queueHooks( animation.elem, animation.opts.queue ).stop = - result.stop.bind( result ); - } - return result; - } - } - - jQuery.map( props, createTween, animation ); - - if ( isFunction( animation.opts.start ) ) { - animation.opts.start.call( elem, animation ); - } - - // Attach callbacks from options - animation - .progress( animation.opts.progress ) - .done( animation.opts.done, animation.opts.complete ) - .fail( animation.opts.fail ) - .always( animation.opts.always ); - - jQuery.fx.timer( - jQuery.extend( tick, { - elem: elem, - anim: animation, - queue: animation.opts.queue - } ) - ); - - return animation; -} - -jQuery.Animation = jQuery.extend( Animation, { - - tweeners: { - "*": [ function( prop, value ) { - var tween = this.createTween( prop, value ); - adjustCSS( tween.elem, prop, rcssNum.exec( value ), tween ); - return tween; - } ] - }, - - tweener: function( props, callback ) { - if ( isFunction( props ) ) { - callback = props; - props = [ "*" ]; - } else { - props = props.match( rnothtmlwhite ); - } - - var prop, - index = 0, - length = props.length; - - for ( ; index < length; index++ ) { - prop = props[ index ]; - Animation.tweeners[ prop ] = Animation.tweeners[ prop ] || []; - Animation.tweeners[ prop ].unshift( callback ); - } - }, - - prefilters: [ defaultPrefilter ], - - prefilter: function( callback, prepend ) { - if ( prepend ) { - Animation.prefilters.unshift( callback ); - } else { - Animation.prefilters.push( callback ); - } - } -} ); - -jQuery.speed = function( speed, easing, fn ) { - var opt = speed && typeof speed === "object" ? jQuery.extend( {}, speed ) : { - complete: fn || !fn && easing || - isFunction( speed ) && speed, - duration: speed, - easing: fn && easing || easing && !isFunction( easing ) && easing - }; - - // Go to the end state if fx are off - if ( jQuery.fx.off ) { - opt.duration = 0; - - } else { - if ( typeof opt.duration !== "number" ) { - if ( opt.duration in jQuery.fx.speeds ) { - opt.duration = jQuery.fx.speeds[ opt.duration ]; - - } else { - opt.duration = jQuery.fx.speeds._default; - } - } - } - - // Normalize opt.queue - true/undefined/null -> "fx" - if ( opt.queue == null || opt.queue === true ) { - opt.queue = "fx"; - } - - // Queueing - opt.old = opt.complete; - - opt.complete = function() { - if ( isFunction( opt.old ) ) { - opt.old.call( this ); - } - - if ( opt.queue ) { - jQuery.dequeue( this, opt.queue ); - } - }; - - return opt; -}; - -jQuery.fn.extend( { - fadeTo: function( speed, to, easing, callback ) { - - // Show any hidden elements after setting opacity to 0 - return this.filter( isHiddenWithinTree ).css( "opacity", 0 ).show() - - // Animate to the value specified - .end().animate( { opacity: to }, speed, easing, callback ); - }, - animate: function( prop, speed, easing, callback ) { - var empty = jQuery.isEmptyObject( prop ), - optall = jQuery.speed( speed, easing, callback ), - doAnimation = function() { - - // Operate on a copy of prop so per-property easing won't be lost - var anim = Animation( this, jQuery.extend( {}, prop ), optall ); - - // Empty animations, or finishing resolves immediately - if ( empty || dataPriv.get( this, "finish" ) ) { - anim.stop( true ); - } - }; - doAnimation.finish = doAnimation; - - return empty || optall.queue === false ? - this.each( doAnimation ) : - this.queue( optall.queue, doAnimation ); - }, - stop: function( type, clearQueue, gotoEnd ) { - var stopQueue = function( hooks ) { - var stop = hooks.stop; - delete hooks.stop; - stop( gotoEnd ); - }; - - if ( typeof type !== "string" ) { - gotoEnd = clearQueue; - clearQueue = type; - type = undefined; - } - if ( clearQueue ) { - this.queue( type || "fx", [] ); - } - - return this.each( function() { - var dequeue = true, - index = type != null && type + "queueHooks", - timers = jQuery.timers, - data = dataPriv.get( this ); - - if ( index ) { - if ( data[ index ] && data[ index ].stop ) { - stopQueue( data[ index ] ); - } - } else { - for ( index in data ) { - if ( data[ index ] && data[ index ].stop && rrun.test( index ) ) { - stopQueue( data[ index ] ); - } - } - } - - for ( index = timers.length; index--; ) { - if ( timers[ index ].elem === this && - ( type == null || timers[ index ].queue === type ) ) { - - timers[ index ].anim.stop( gotoEnd ); - dequeue = false; - timers.splice( index, 1 ); - } - } - - // Start the next in the queue if the last step wasn't forced. - // Timers currently will call their complete callbacks, which - // will dequeue but only if they were gotoEnd. - if ( dequeue || !gotoEnd ) { - jQuery.dequeue( this, type ); - } - } ); - }, - finish: function( type ) { - if ( type !== false ) { - type = type || "fx"; - } - return this.each( function() { - var index, - data = dataPriv.get( this ), - queue = data[ type + "queue" ], - hooks = data[ type + "queueHooks" ], - timers = jQuery.timers, - length = queue ? queue.length : 0; - - // Enable finishing flag on private data - data.finish = true; - - // Empty the queue first - jQuery.queue( this, type, [] ); - - if ( hooks && hooks.stop ) { - hooks.stop.call( this, true ); - } - - // Look for any active animations, and finish them - for ( index = timers.length; index--; ) { - if ( timers[ index ].elem === this && timers[ index ].queue === type ) { - timers[ index ].anim.stop( true ); - timers.splice( index, 1 ); - } - } - - // Look for any animations in the old queue and finish them - for ( index = 0; index < length; index++ ) { - if ( queue[ index ] && queue[ index ].finish ) { - queue[ index ].finish.call( this ); - } - } - - // Turn off finishing flag - delete data.finish; - } ); - } -} ); - -jQuery.each( [ "toggle", "show", "hide" ], function( _i, name ) { - var cssFn = jQuery.fn[ name ]; - jQuery.fn[ name ] = function( speed, easing, callback ) { - return speed == null || typeof speed === "boolean" ? - cssFn.apply( this, arguments ) : - this.animate( genFx( name, true ), speed, easing, callback ); - }; -} ); - -// Generate shortcuts for custom animations -jQuery.each( { - slideDown: genFx( "show" ), - slideUp: genFx( "hide" ), - slideToggle: genFx( "toggle" ), - fadeIn: { opacity: "show" }, - fadeOut: { opacity: "hide" }, - fadeToggle: { opacity: "toggle" } -}, function( name, props ) { - jQuery.fn[ name ] = function( speed, easing, callback ) { - return this.animate( props, speed, easing, callback ); - }; -} ); - -jQuery.timers = []; -jQuery.fx.tick = function() { - var timer, - i = 0, - timers = jQuery.timers; - - fxNow = Date.now(); - - for ( ; i < timers.length; i++ ) { - timer = timers[ i ]; - - // Run the timer and safely remove it when done (allowing for external removal) - if ( !timer() && timers[ i ] === timer ) { - timers.splice( i--, 1 ); - } - } - - if ( !timers.length ) { - jQuery.fx.stop(); - } - fxNow = undefined; -}; - -jQuery.fx.timer = function( timer ) { - jQuery.timers.push( timer ); - jQuery.fx.start(); -}; - -jQuery.fx.interval = 13; -jQuery.fx.start = function() { - if ( inProgress ) { - return; - } - - inProgress = true; - schedule(); -}; - -jQuery.fx.stop = function() { - inProgress = null; -}; - -jQuery.fx.speeds = { - slow: 600, - fast: 200, - - // Default speed - _default: 400 -}; - - -// Based off of the plugin by Clint Helfers, with permission. -// https://web.archive.org/web/20100324014747/http://blindsignals.com/index.php/2009/07/jquery-delay/ -jQuery.fn.delay = function( time, type ) { - time = jQuery.fx ? jQuery.fx.speeds[ time ] || time : time; - type = type || "fx"; - - return this.queue( type, function( next, hooks ) { - var timeout = window.setTimeout( next, time ); - hooks.stop = function() { - window.clearTimeout( timeout ); - }; - } ); -}; - - -( function() { - var input = document.createElement( "input" ), - select = document.createElement( "select" ), - opt = select.appendChild( document.createElement( "option" ) ); - - input.type = "checkbox"; - - // Support: Android <=4.3 only - // Default value for a checkbox should be "on" - support.checkOn = input.value !== ""; - - // Support: IE <=11 only - // Must access selectedIndex to make default options select - support.optSelected = opt.selected; - - // Support: IE <=11 only - // An input loses its value after becoming a radio - input = document.createElement( "input" ); - input.value = "t"; - input.type = "radio"; - support.radioValue = input.value === "t"; -} )(); - - -var boolHook, - attrHandle = jQuery.expr.attrHandle; - -jQuery.fn.extend( { - attr: function( name, value ) { - return access( this, jQuery.attr, name, value, arguments.length > 1 ); - }, - - removeAttr: function( name ) { - return this.each( function() { - jQuery.removeAttr( this, name ); - } ); - } -} ); - -jQuery.extend( { - attr: function( elem, name, value ) { - var ret, hooks, - nType = elem.nodeType; - - // Don't get/set attributes on text, comment and attribute nodes - if ( nType === 3 || nType === 8 || nType === 2 ) { - return; - } - - // Fallback to prop when attributes are not supported - if ( typeof elem.getAttribute === "undefined" ) { - return jQuery.prop( elem, name, value ); - } - - // Attribute hooks are determined by the lowercase version - // Grab necessary hook if one is defined - if ( nType !== 1 || !jQuery.isXMLDoc( elem ) ) { - hooks = jQuery.attrHooks[ name.toLowerCase() ] || - ( jQuery.expr.match.bool.test( name ) ? boolHook : undefined ); - } - - if ( value !== undefined ) { - if ( value === null ) { - jQuery.removeAttr( elem, name ); - return; - } - - if ( hooks && "set" in hooks && - ( ret = hooks.set( elem, value, name ) ) !== undefined ) { - return ret; - } - - elem.setAttribute( name, value + "" ); - return value; - } - - if ( hooks && "get" in hooks && ( ret = hooks.get( elem, name ) ) !== null ) { - return ret; - } - - ret = jQuery.find.attr( elem, name ); - - // Non-existent attributes return null, we normalize to undefined - return ret == null ? undefined : ret; - }, - - attrHooks: { - type: { - set: function( elem, value ) { - if ( !support.radioValue && value === "radio" && - nodeName( elem, "input" ) ) { - var val = elem.value; - elem.setAttribute( "type", value ); - if ( val ) { - elem.value = val; - } - return value; - } - } - } - }, - - removeAttr: function( elem, value ) { - var name, - i = 0, - - // Attribute names can contain non-HTML whitespace characters - // https://html.spec.whatwg.org/multipage/syntax.html#attributes-2 - attrNames = value && value.match( rnothtmlwhite ); - - if ( attrNames && elem.nodeType === 1 ) { - while ( ( name = attrNames[ i++ ] ) ) { - elem.removeAttribute( name ); - } - } - } -} ); - -// Hooks for boolean attributes -boolHook = { - set: function( elem, value, name ) { - if ( value === false ) { - - // Remove boolean attributes when set to false - jQuery.removeAttr( elem, name ); - } else { - elem.setAttribute( name, name ); - } - return name; - } -}; - -jQuery.each( jQuery.expr.match.bool.source.match( /\w+/g ), function( _i, name ) { - var getter = attrHandle[ name ] || jQuery.find.attr; - - attrHandle[ name ] = function( elem, name, isXML ) { - var ret, handle, - lowercaseName = name.toLowerCase(); - - if ( !isXML ) { - - // Avoid an infinite loop by temporarily removing this function from the getter - handle = attrHandle[ lowercaseName ]; - attrHandle[ lowercaseName ] = ret; - ret = getter( elem, name, isXML ) != null ? - lowercaseName : - null; - attrHandle[ lowercaseName ] = handle; - } - return ret; - }; -} ); - - - - -var rfocusable = /^(?:input|select|textarea|button)$/i, - rclickable = /^(?:a|area)$/i; - -jQuery.fn.extend( { - prop: function( name, value ) { - return access( this, jQuery.prop, name, value, arguments.length > 1 ); - }, - - removeProp: function( name ) { - return this.each( function() { - delete this[ jQuery.propFix[ name ] || name ]; - } ); - } -} ); - -jQuery.extend( { - prop: function( elem, name, value ) { - var ret, hooks, - nType = elem.nodeType; - - // Don't get/set properties on text, comment and attribute nodes - if ( nType === 3 || nType === 8 || nType === 2 ) { - return; - } - - if ( nType !== 1 || !jQuery.isXMLDoc( elem ) ) { - - // Fix name and attach hooks - name = jQuery.propFix[ name ] || name; - hooks = jQuery.propHooks[ name ]; - } - - if ( value !== undefined ) { - if ( hooks && "set" in hooks && - ( ret = hooks.set( elem, value, name ) ) !== undefined ) { - return ret; - } - - return ( elem[ name ] = value ); - } - - if ( hooks && "get" in hooks && ( ret = hooks.get( elem, name ) ) !== null ) { - return ret; - } - - return elem[ name ]; - }, - - propHooks: { - tabIndex: { - get: function( elem ) { - - // Support: IE <=9 - 11 only - // elem.tabIndex doesn't always return the - // correct value when it hasn't been explicitly set - // https://web.archive.org/web/20141116233347/http://fluidproject.org/blog/2008/01/09/getting-setting-and-removing-tabindex-values-with-javascript/ - // Use proper attribute retrieval(#12072) - var tabindex = jQuery.find.attr( elem, "tabindex" ); - - if ( tabindex ) { - return parseInt( tabindex, 10 ); - } - - if ( - rfocusable.test( elem.nodeName ) || - rclickable.test( elem.nodeName ) && - elem.href - ) { - return 0; - } - - return -1; - } - } - }, - - propFix: { - "for": "htmlFor", - "class": "className" - } -} ); - -// Support: IE <=11 only -// Accessing the selectedIndex property -// forces the browser to respect setting selected -// on the option -// The getter ensures a default option is selected -// when in an optgroup -// eslint rule "no-unused-expressions" is disabled for this code -// since it considers such accessions noop -if ( !support.optSelected ) { - jQuery.propHooks.selected = { - get: function( elem ) { - - /* eslint no-unused-expressions: "off" */ - - var parent = elem.parentNode; - if ( parent && parent.parentNode ) { - parent.parentNode.selectedIndex; - } - return null; - }, - set: function( elem ) { - - /* eslint no-unused-expressions: "off" */ - - var parent = elem.parentNode; - if ( parent ) { - parent.selectedIndex; - - if ( parent.parentNode ) { - parent.parentNode.selectedIndex; - } - } - } - }; -} - -jQuery.each( [ - "tabIndex", - "readOnly", - "maxLength", - "cellSpacing", - "cellPadding", - "rowSpan", - "colSpan", - "useMap", - "frameBorder", - "contentEditable" -], function() { - jQuery.propFix[ this.toLowerCase() ] = this; -} ); - - - - - // Strip and collapse whitespace according to HTML spec - // https://infra.spec.whatwg.org/#strip-and-collapse-ascii-whitespace - function stripAndCollapse( value ) { - var tokens = value.match( rnothtmlwhite ) || []; - return tokens.join( " " ); - } - - -function getClass( elem ) { - return elem.getAttribute && elem.getAttribute( "class" ) || ""; -} - -function classesToArray( value ) { - if ( Array.isArray( value ) ) { - return value; - } - if ( typeof value === "string" ) { - return value.match( rnothtmlwhite ) || []; - } - return []; -} - -jQuery.fn.extend( { - addClass: function( value ) { - var classes, elem, cur, curValue, clazz, j, finalValue, - i = 0; - - if ( isFunction( value ) ) { - return this.each( function( j ) { - jQuery( this ).addClass( value.call( this, j, getClass( this ) ) ); - } ); - } - - classes = classesToArray( value ); - - if ( classes.length ) { - while ( ( elem = this[ i++ ] ) ) { - curValue = getClass( elem ); - cur = elem.nodeType === 1 && ( " " + stripAndCollapse( curValue ) + " " ); - - if ( cur ) { - j = 0; - while ( ( clazz = classes[ j++ ] ) ) { - if ( cur.indexOf( " " + clazz + " " ) < 0 ) { - cur += clazz + " "; - } - } - - // Only assign if different to avoid unneeded rendering. - finalValue = stripAndCollapse( cur ); - if ( curValue !== finalValue ) { - elem.setAttribute( "class", finalValue ); - } - } - } - } - - return this; - }, - - removeClass: function( value ) { - var classes, elem, cur, curValue, clazz, j, finalValue, - i = 0; - - if ( isFunction( value ) ) { - return this.each( function( j ) { - jQuery( this ).removeClass( value.call( this, j, getClass( this ) ) ); - } ); - } - - if ( !arguments.length ) { - return this.attr( "class", "" ); - } - - classes = classesToArray( value ); - - if ( classes.length ) { - while ( ( elem = this[ i++ ] ) ) { - curValue = getClass( elem ); - - // This expression is here for better compressibility (see addClass) - cur = elem.nodeType === 1 && ( " " + stripAndCollapse( curValue ) + " " ); - - if ( cur ) { - j = 0; - while ( ( clazz = classes[ j++ ] ) ) { - - // Remove *all* instances - while ( cur.indexOf( " " + clazz + " " ) > -1 ) { - cur = cur.replace( " " + clazz + " ", " " ); - } - } - - // Only assign if different to avoid unneeded rendering. - finalValue = stripAndCollapse( cur ); - if ( curValue !== finalValue ) { - elem.setAttribute( "class", finalValue ); - } - } - } - } - - return this; - }, - - toggleClass: function( value, stateVal ) { - var type = typeof value, - isValidValue = type === "string" || Array.isArray( value ); - - if ( typeof stateVal === "boolean" && isValidValue ) { - return stateVal ? this.addClass( value ) : this.removeClass( value ); - } - - if ( isFunction( value ) ) { - return this.each( function( i ) { - jQuery( this ).toggleClass( - value.call( this, i, getClass( this ), stateVal ), - stateVal - ); - } ); - } - - return this.each( function() { - var className, i, self, classNames; - - if ( isValidValue ) { - - // Toggle individual class names - i = 0; - self = jQuery( this ); - classNames = classesToArray( value ); - - while ( ( className = classNames[ i++ ] ) ) { - - // Check each className given, space separated list - if ( self.hasClass( className ) ) { - self.removeClass( className ); - } else { - self.addClass( className ); - } - } - - // Toggle whole class name - } else if ( value === undefined || type === "boolean" ) { - className = getClass( this ); - if ( className ) { - - // Store className if set - dataPriv.set( this, "__className__", className ); - } - - // If the element has a class name or if we're passed `false`, - // then remove the whole classname (if there was one, the above saved it). - // Otherwise bring back whatever was previously saved (if anything), - // falling back to the empty string if nothing was stored. - if ( this.setAttribute ) { - this.setAttribute( "class", - className || value === false ? - "" : - dataPriv.get( this, "__className__" ) || "" - ); - } - } - } ); - }, - - hasClass: function( selector ) { - var className, elem, - i = 0; - - className = " " + selector + " "; - while ( ( elem = this[ i++ ] ) ) { - if ( elem.nodeType === 1 && - ( " " + stripAndCollapse( getClass( elem ) ) + " " ).indexOf( className ) > -1 ) { - return true; - } - } - - return false; - } -} ); - - - - -var rreturn = /\r/g; - -jQuery.fn.extend( { - val: function( value ) { - var hooks, ret, valueIsFunction, - elem = this[ 0 ]; - - if ( !arguments.length ) { - if ( elem ) { - hooks = jQuery.valHooks[ elem.type ] || - jQuery.valHooks[ elem.nodeName.toLowerCase() ]; - - if ( hooks && - "get" in hooks && - ( ret = hooks.get( elem, "value" ) ) !== undefined - ) { - return ret; - } - - ret = elem.value; - - // Handle most common string cases - if ( typeof ret === "string" ) { - return ret.replace( rreturn, "" ); - } - - // Handle cases where value is null/undef or number - return ret == null ? "" : ret; - } - - return; - } - - valueIsFunction = isFunction( value ); - - return this.each( function( i ) { - var val; - - if ( this.nodeType !== 1 ) { - return; - } - - if ( valueIsFunction ) { - val = value.call( this, i, jQuery( this ).val() ); - } else { - val = value; - } - - // Treat null/undefined as ""; convert numbers to string - if ( val == null ) { - val = ""; - - } else if ( typeof val === "number" ) { - val += ""; - - } else if ( Array.isArray( val ) ) { - val = jQuery.map( val, function( value ) { - return value == null ? "" : value + ""; - } ); - } - - hooks = jQuery.valHooks[ this.type ] || jQuery.valHooks[ this.nodeName.toLowerCase() ]; - - // If set returns undefined, fall back to normal setting - if ( !hooks || !( "set" in hooks ) || hooks.set( this, val, "value" ) === undefined ) { - this.value = val; - } - } ); - } -} ); - -jQuery.extend( { - valHooks: { - option: { - get: function( elem ) { - - var val = jQuery.find.attr( elem, "value" ); - return val != null ? - val : - - // Support: IE <=10 - 11 only - // option.text throws exceptions (#14686, #14858) - // Strip and collapse whitespace - // https://html.spec.whatwg.org/#strip-and-collapse-whitespace - stripAndCollapse( jQuery.text( elem ) ); - } - }, - select: { - get: function( elem ) { - var value, option, i, - options = elem.options, - index = elem.selectedIndex, - one = elem.type === "select-one", - values = one ? null : [], - max = one ? index + 1 : options.length; - - if ( index < 0 ) { - i = max; - - } else { - i = one ? index : 0; - } - - // Loop through all the selected options - for ( ; i < max; i++ ) { - option = options[ i ]; - - // Support: IE <=9 only - // IE8-9 doesn't update selected after form reset (#2551) - if ( ( option.selected || i === index ) && - - // Don't return options that are disabled or in a disabled optgroup - !option.disabled && - ( !option.parentNode.disabled || - !nodeName( option.parentNode, "optgroup" ) ) ) { - - // Get the specific value for the option - value = jQuery( option ).val(); - - // We don't need an array for one selects - if ( one ) { - return value; - } - - // Multi-Selects return an array - values.push( value ); - } - } - - return values; - }, - - set: function( elem, value ) { - var optionSet, option, - options = elem.options, - values = jQuery.makeArray( value ), - i = options.length; - - while ( i-- ) { - option = options[ i ]; - - /* eslint-disable no-cond-assign */ - - if ( option.selected = - jQuery.inArray( jQuery.valHooks.option.get( option ), values ) > -1 - ) { - optionSet = true; - } - - /* eslint-enable no-cond-assign */ - } - - // Force browsers to behave consistently when non-matching value is set - if ( !optionSet ) { - elem.selectedIndex = -1; - } - return values; - } - } - } -} ); - -// Radios and checkboxes getter/setter -jQuery.each( [ "radio", "checkbox" ], function() { - jQuery.valHooks[ this ] = { - set: function( elem, value ) { - if ( Array.isArray( value ) ) { - return ( elem.checked = jQuery.inArray( jQuery( elem ).val(), value ) > -1 ); - } - } - }; - if ( !support.checkOn ) { - jQuery.valHooks[ this ].get = function( elem ) { - return elem.getAttribute( "value" ) === null ? "on" : elem.value; - }; - } -} ); - - - - -// Return jQuery for attributes-only inclusion - - -support.focusin = "onfocusin" in window; - - -var rfocusMorph = /^(?:focusinfocus|focusoutblur)$/, - stopPropagationCallback = function( e ) { - e.stopPropagation(); - }; - -jQuery.extend( jQuery.event, { - - trigger: function( event, data, elem, onlyHandlers ) { - - var i, cur, tmp, bubbleType, ontype, handle, special, lastElement, - eventPath = [ elem || document ], - type = hasOwn.call( event, "type" ) ? event.type : event, - namespaces = hasOwn.call( event, "namespace" ) ? event.namespace.split( "." ) : []; - - cur = lastElement = tmp = elem = elem || document; - - // Don't do events on text and comment nodes - if ( elem.nodeType === 3 || elem.nodeType === 8 ) { - return; - } - - // focus/blur morphs to focusin/out; ensure we're not firing them right now - if ( rfocusMorph.test( type + jQuery.event.triggered ) ) { - return; - } - - if ( type.indexOf( "." ) > -1 ) { - - // Namespaced trigger; create a regexp to match event type in handle() - namespaces = type.split( "." ); - type = namespaces.shift(); - namespaces.sort(); - } - ontype = type.indexOf( ":" ) < 0 && "on" + type; - - // Caller can pass in a jQuery.Event object, Object, or just an event type string - event = event[ jQuery.expando ] ? - event : - new jQuery.Event( type, typeof event === "object" && event ); - - // Trigger bitmask: & 1 for native handlers; & 2 for jQuery (always true) - event.isTrigger = onlyHandlers ? 2 : 3; - event.namespace = namespaces.join( "." ); - event.rnamespace = event.namespace ? - new RegExp( "(^|\\.)" + namespaces.join( "\\.(?:.*\\.|)" ) + "(\\.|$)" ) : - null; - - // Clean up the event in case it is being reused - event.result = undefined; - if ( !event.target ) { - event.target = elem; - } - - // Clone any incoming data and prepend the event, creating the handler arg list - data = data == null ? - [ event ] : - jQuery.makeArray( data, [ event ] ); - - // Allow special events to draw outside the lines - special = jQuery.event.special[ type ] || {}; - if ( !onlyHandlers && special.trigger && special.trigger.apply( elem, data ) === false ) { - return; - } - - // Determine event propagation path in advance, per W3C events spec (#9951) - // Bubble up to document, then to window; watch for a global ownerDocument var (#9724) - if ( !onlyHandlers && !special.noBubble && !isWindow( elem ) ) { - - bubbleType = special.delegateType || type; - if ( !rfocusMorph.test( bubbleType + type ) ) { - cur = cur.parentNode; - } - for ( ; cur; cur = cur.parentNode ) { - eventPath.push( cur ); - tmp = cur; - } - - // Only add window if we got to document (e.g., not plain obj or detached DOM) - if ( tmp === ( elem.ownerDocument || document ) ) { - eventPath.push( tmp.defaultView || tmp.parentWindow || window ); - } - } - - // Fire handlers on the event path - i = 0; - while ( ( cur = eventPath[ i++ ] ) && !event.isPropagationStopped() ) { - lastElement = cur; - event.type = i > 1 ? - bubbleType : - special.bindType || type; - - // jQuery handler - handle = ( - dataPriv.get( cur, "events" ) || Object.create( null ) - )[ event.type ] && - dataPriv.get( cur, "handle" ); - if ( handle ) { - handle.apply( cur, data ); - } - - // Native handler - handle = ontype && cur[ ontype ]; - if ( handle && handle.apply && acceptData( cur ) ) { - event.result = handle.apply( cur, data ); - if ( event.result === false ) { - event.preventDefault(); - } - } - } - event.type = type; - - // If nobody prevented the default action, do it now - if ( !onlyHandlers && !event.isDefaultPrevented() ) { - - if ( ( !special._default || - special._default.apply( eventPath.pop(), data ) === false ) && - acceptData( elem ) ) { - - // Call a native DOM method on the target with the same name as the event. - // Don't do default actions on window, that's where global variables be (#6170) - if ( ontype && isFunction( elem[ type ] ) && !isWindow( elem ) ) { - - // Don't re-trigger an onFOO event when we call its FOO() method - tmp = elem[ ontype ]; - - if ( tmp ) { - elem[ ontype ] = null; - } - - // Prevent re-triggering of the same event, since we already bubbled it above - jQuery.event.triggered = type; - - if ( event.isPropagationStopped() ) { - lastElement.addEventListener( type, stopPropagationCallback ); - } - - elem[ type ](); - - if ( event.isPropagationStopped() ) { - lastElement.removeEventListener( type, stopPropagationCallback ); - } - - jQuery.event.triggered = undefined; - - if ( tmp ) { - elem[ ontype ] = tmp; - } - } - } - } - - return event.result; - }, - - // Piggyback on a donor event to simulate a different one - // Used only for `focus(in | out)` events - simulate: function( type, elem, event ) { - var e = jQuery.extend( - new jQuery.Event(), - event, - { - type: type, - isSimulated: true - } - ); - - jQuery.event.trigger( e, null, elem ); - } - -} ); - -jQuery.fn.extend( { - - trigger: function( type, data ) { - return this.each( function() { - jQuery.event.trigger( type, data, this ); - } ); - }, - triggerHandler: function( type, data ) { - var elem = this[ 0 ]; - if ( elem ) { - return jQuery.event.trigger( type, data, elem, true ); - } - } -} ); - - -// Support: Firefox <=44 -// Firefox doesn't have focus(in | out) events -// Related ticket - https://bugzilla.mozilla.org/show_bug.cgi?id=687787 -// -// Support: Chrome <=48 - 49, Safari <=9.0 - 9.1 -// focus(in | out) events fire after focus & blur events, -// which is spec violation - http://www.w3.org/TR/DOM-Level-3-Events/#events-focusevent-event-order -// Related ticket - https://bugs.chromium.org/p/chromium/issues/detail?id=449857 -if ( !support.focusin ) { - jQuery.each( { focus: "focusin", blur: "focusout" }, function( orig, fix ) { - - // Attach a single capturing handler on the document while someone wants focusin/focusout - var handler = function( event ) { - jQuery.event.simulate( fix, event.target, jQuery.event.fix( event ) ); - }; - - jQuery.event.special[ fix ] = { - setup: function() { - - // Handle: regular nodes (via `this.ownerDocument`), window - // (via `this.document`) & document (via `this`). - var doc = this.ownerDocument || this.document || this, - attaches = dataPriv.access( doc, fix ); - - if ( !attaches ) { - doc.addEventListener( orig, handler, true ); - } - dataPriv.access( doc, fix, ( attaches || 0 ) + 1 ); - }, - teardown: function() { - var doc = this.ownerDocument || this.document || this, - attaches = dataPriv.access( doc, fix ) - 1; - - if ( !attaches ) { - doc.removeEventListener( orig, handler, true ); - dataPriv.remove( doc, fix ); - - } else { - dataPriv.access( doc, fix, attaches ); - } - } - }; - } ); -} -var location = window.location; - -var nonce = { guid: Date.now() }; - -var rquery = ( /\?/ ); - - - -// Cross-browser xml parsing -jQuery.parseXML = function( data ) { - var xml; - if ( !data || typeof data !== "string" ) { - return null; - } - - // Support: IE 9 - 11 only - // IE throws on parseFromString with invalid input. - try { - xml = ( new window.DOMParser() ).parseFromString( data, "text/xml" ); - } catch ( e ) { - xml = undefined; - } - - if ( !xml || xml.getElementsByTagName( "parsererror" ).length ) { - jQuery.error( "Invalid XML: " + data ); - } - return xml; -}; - - -var - rbracket = /\[\]$/, - rCRLF = /\r?\n/g, - rsubmitterTypes = /^(?:submit|button|image|reset|file)$/i, - rsubmittable = /^(?:input|select|textarea|keygen)/i; - -function buildParams( prefix, obj, traditional, add ) { - var name; - - if ( Array.isArray( obj ) ) { - - // Serialize array item. - jQuery.each( obj, function( i, v ) { - if ( traditional || rbracket.test( prefix ) ) { - - // Treat each array item as a scalar. - add( prefix, v ); - - } else { - - // Item is non-scalar (array or object), encode its numeric index. - buildParams( - prefix + "[" + ( typeof v === "object" && v != null ? i : "" ) + "]", - v, - traditional, - add - ); - } - } ); - - } else if ( !traditional && toType( obj ) === "object" ) { - - // Serialize object item. - for ( name in obj ) { - buildParams( prefix + "[" + name + "]", obj[ name ], traditional, add ); - } - - } else { - - // Serialize scalar item. - add( prefix, obj ); - } -} - -// Serialize an array of form elements or a set of -// key/values into a query string -jQuery.param = function( a, traditional ) { - var prefix, - s = [], - add = function( key, valueOrFunction ) { - - // If value is a function, invoke it and use its return value - var value = isFunction( valueOrFunction ) ? - valueOrFunction() : - valueOrFunction; - - s[ s.length ] = encodeURIComponent( key ) + "=" + - encodeURIComponent( value == null ? "" : value ); - }; - - if ( a == null ) { - return ""; - } - - // If an array was passed in, assume that it is an array of form elements. - if ( Array.isArray( a ) || ( a.jquery && !jQuery.isPlainObject( a ) ) ) { - - // Serialize the form elements - jQuery.each( a, function() { - add( this.name, this.value ); - } ); - - } else { - - // If traditional, encode the "old" way (the way 1.3.2 or older - // did it), otherwise encode params recursively. - for ( prefix in a ) { - buildParams( prefix, a[ prefix ], traditional, add ); - } - } - - // Return the resulting serialization - return s.join( "&" ); -}; - -jQuery.fn.extend( { - serialize: function() { - return jQuery.param( this.serializeArray() ); - }, - serializeArray: function() { - return this.map( function() { - - // Can add propHook for "elements" to filter or add form elements - var elements = jQuery.prop( this, "elements" ); - return elements ? jQuery.makeArray( elements ) : this; - } ) - .filter( function() { - var type = this.type; - - // Use .is( ":disabled" ) so that fieldset[disabled] works - return this.name && !jQuery( this ).is( ":disabled" ) && - rsubmittable.test( this.nodeName ) && !rsubmitterTypes.test( type ) && - ( this.checked || !rcheckableType.test( type ) ); - } ) - .map( function( _i, elem ) { - var val = jQuery( this ).val(); - - if ( val == null ) { - return null; - } - - if ( Array.isArray( val ) ) { - return jQuery.map( val, function( val ) { - return { name: elem.name, value: val.replace( rCRLF, "\r\n" ) }; - } ); - } - - return { name: elem.name, value: val.replace( rCRLF, "\r\n" ) }; - } ).get(); - } -} ); - - -var - r20 = /%20/g, - rhash = /#.*$/, - rantiCache = /([?&])_=[^&]*/, - rheaders = /^(.*?):[ \t]*([^\r\n]*)$/mg, - - // #7653, #8125, #8152: local protocol detection - rlocalProtocol = /^(?:about|app|app-storage|.+-extension|file|res|widget):$/, - rnoContent = /^(?:GET|HEAD)$/, - rprotocol = /^\/\//, - - /* Prefilters - * 1) They are useful to introduce custom dataTypes (see ajax/jsonp.js for an example) - * 2) These are called: - * - BEFORE asking for a transport - * - AFTER param serialization (s.data is a string if s.processData is true) - * 3) key is the dataType - * 4) the catchall symbol "*" can be used - * 5) execution will start with transport dataType and THEN continue down to "*" if needed - */ - prefilters = {}, - - /* Transports bindings - * 1) key is the dataType - * 2) the catchall symbol "*" can be used - * 3) selection will start with transport dataType and THEN go to "*" if needed - */ - transports = {}, - - // Avoid comment-prolog char sequence (#10098); must appease lint and evade compression - allTypes = "*/".concat( "*" ), - - // Anchor tag for parsing the document origin - originAnchor = document.createElement( "a" ); - originAnchor.href = location.href; - -// Base "constructor" for jQuery.ajaxPrefilter and jQuery.ajaxTransport -function addToPrefiltersOrTransports( structure ) { - - // dataTypeExpression is optional and defaults to "*" - return function( dataTypeExpression, func ) { - - if ( typeof dataTypeExpression !== "string" ) { - func = dataTypeExpression; - dataTypeExpression = "*"; - } - - var dataType, - i = 0, - dataTypes = dataTypeExpression.toLowerCase().match( rnothtmlwhite ) || []; - - if ( isFunction( func ) ) { - - // For each dataType in the dataTypeExpression - while ( ( dataType = dataTypes[ i++ ] ) ) { - - // Prepend if requested - if ( dataType[ 0 ] === "+" ) { - dataType = dataType.slice( 1 ) || "*"; - ( structure[ dataType ] = structure[ dataType ] || [] ).unshift( func ); - - // Otherwise append - } else { - ( structure[ dataType ] = structure[ dataType ] || [] ).push( func ); - } - } - } - }; -} - -// Base inspection function for prefilters and transports -function inspectPrefiltersOrTransports( structure, options, originalOptions, jqXHR ) { - - var inspected = {}, - seekingTransport = ( structure === transports ); - - function inspect( dataType ) { - var selected; - inspected[ dataType ] = true; - jQuery.each( structure[ dataType ] || [], function( _, prefilterOrFactory ) { - var dataTypeOrTransport = prefilterOrFactory( options, originalOptions, jqXHR ); - if ( typeof dataTypeOrTransport === "string" && - !seekingTransport && !inspected[ dataTypeOrTransport ] ) { - - options.dataTypes.unshift( dataTypeOrTransport ); - inspect( dataTypeOrTransport ); - return false; - } else if ( seekingTransport ) { - return !( selected = dataTypeOrTransport ); - } - } ); - return selected; - } - - return inspect( options.dataTypes[ 0 ] ) || !inspected[ "*" ] && inspect( "*" ); -} - -// A special extend for ajax options -// that takes "flat" options (not to be deep extended) -// Fixes #9887 -function ajaxExtend( target, src ) { - var key, deep, - flatOptions = jQuery.ajaxSettings.flatOptions || {}; - - for ( key in src ) { - if ( src[ key ] !== undefined ) { - ( flatOptions[ key ] ? target : ( deep || ( deep = {} ) ) )[ key ] = src[ key ]; - } - } - if ( deep ) { - jQuery.extend( true, target, deep ); - } - - return target; -} - -/* Handles responses to an ajax request: - * - finds the right dataType (mediates between content-type and expected dataType) - * - returns the corresponding response - */ -function ajaxHandleResponses( s, jqXHR, responses ) { - - var ct, type, finalDataType, firstDataType, - contents = s.contents, - dataTypes = s.dataTypes; - - // Remove auto dataType and get content-type in the process - while ( dataTypes[ 0 ] === "*" ) { - dataTypes.shift(); - if ( ct === undefined ) { - ct = s.mimeType || jqXHR.getResponseHeader( "Content-Type" ); - } - } - - // Check if we're dealing with a known content-type - if ( ct ) { - for ( type in contents ) { - if ( contents[ type ] && contents[ type ].test( ct ) ) { - dataTypes.unshift( type ); - break; - } - } - } - - // Check to see if we have a response for the expected dataType - if ( dataTypes[ 0 ] in responses ) { - finalDataType = dataTypes[ 0 ]; - } else { - - // Try convertible dataTypes - for ( type in responses ) { - if ( !dataTypes[ 0 ] || s.converters[ type + " " + dataTypes[ 0 ] ] ) { - finalDataType = type; - break; - } - if ( !firstDataType ) { - firstDataType = type; - } - } - - // Or just use first one - finalDataType = finalDataType || firstDataType; - } - - // If we found a dataType - // We add the dataType to the list if needed - // and return the corresponding response - if ( finalDataType ) { - if ( finalDataType !== dataTypes[ 0 ] ) { - dataTypes.unshift( finalDataType ); - } - return responses[ finalDataType ]; - } -} - -/* Chain conversions given the request and the original response - * Also sets the responseXXX fields on the jqXHR instance - */ -function ajaxConvert( s, response, jqXHR, isSuccess ) { - var conv2, current, conv, tmp, prev, - converters = {}, - - // Work with a copy of dataTypes in case we need to modify it for conversion - dataTypes = s.dataTypes.slice(); - - // Create converters map with lowercased keys - if ( dataTypes[ 1 ] ) { - for ( conv in s.converters ) { - converters[ conv.toLowerCase() ] = s.converters[ conv ]; - } - } - - current = dataTypes.shift(); - - // Convert to each sequential dataType - while ( current ) { - - if ( s.responseFields[ current ] ) { - jqXHR[ s.responseFields[ current ] ] = response; - } - - // Apply the dataFilter if provided - if ( !prev && isSuccess && s.dataFilter ) { - response = s.dataFilter( response, s.dataType ); - } - - prev = current; - current = dataTypes.shift(); - - if ( current ) { - - // There's only work to do if current dataType is non-auto - if ( current === "*" ) { - - current = prev; - - // Convert response if prev dataType is non-auto and differs from current - } else if ( prev !== "*" && prev !== current ) { - - // Seek a direct converter - conv = converters[ prev + " " + current ] || converters[ "* " + current ]; - - // If none found, seek a pair - if ( !conv ) { - for ( conv2 in converters ) { - - // If conv2 outputs current - tmp = conv2.split( " " ); - if ( tmp[ 1 ] === current ) { - - // If prev can be converted to accepted input - conv = converters[ prev + " " + tmp[ 0 ] ] || - converters[ "* " + tmp[ 0 ] ]; - if ( conv ) { - - // Condense equivalence converters - if ( conv === true ) { - conv = converters[ conv2 ]; - - // Otherwise, insert the intermediate dataType - } else if ( converters[ conv2 ] !== true ) { - current = tmp[ 0 ]; - dataTypes.unshift( tmp[ 1 ] ); - } - break; - } - } - } - } - - // Apply converter (if not an equivalence) - if ( conv !== true ) { - - // Unless errors are allowed to bubble, catch and return them - if ( conv && s.throws ) { - response = conv( response ); - } else { - try { - response = conv( response ); - } catch ( e ) { - return { - state: "parsererror", - error: conv ? e : "No conversion from " + prev + " to " + current - }; - } - } - } - } - } - } - - return { state: "success", data: response }; -} - -jQuery.extend( { - - // Counter for holding the number of active queries - active: 0, - - // Last-Modified header cache for next request - lastModified: {}, - etag: {}, - - ajaxSettings: { - url: location.href, - type: "GET", - isLocal: rlocalProtocol.test( location.protocol ), - global: true, - processData: true, - async: true, - contentType: "application/x-www-form-urlencoded; charset=UTF-8", - - /* - timeout: 0, - data: null, - dataType: null, - username: null, - password: null, - cache: null, - throws: false, - traditional: false, - headers: {}, - */ - - accepts: { - "*": allTypes, - text: "text/plain", - html: "text/html", - xml: "application/xml, text/xml", - json: "application/json, text/javascript" - }, - - contents: { - xml: /\bxml\b/, - html: /\bhtml/, - json: /\bjson\b/ - }, - - responseFields: { - xml: "responseXML", - text: "responseText", - json: "responseJSON" - }, - - // Data converters - // Keys separate source (or catchall "*") and destination types with a single space - converters: { - - // Convert anything to text - "* text": String, - - // Text to html (true = no transformation) - "text html": true, - - // Evaluate text as a json expression - "text json": JSON.parse, - - // Parse text as xml - "text xml": jQuery.parseXML - }, - - // For options that shouldn't be deep extended: - // you can add your own custom options here if - // and when you create one that shouldn't be - // deep extended (see ajaxExtend) - flatOptions: { - url: true, - context: true - } - }, - - // Creates a full fledged settings object into target - // with both ajaxSettings and settings fields. - // If target is omitted, writes into ajaxSettings. - ajaxSetup: function( target, settings ) { - return settings ? - - // Building a settings object - ajaxExtend( ajaxExtend( target, jQuery.ajaxSettings ), settings ) : - - // Extending ajaxSettings - ajaxExtend( jQuery.ajaxSettings, target ); - }, - - ajaxPrefilter: addToPrefiltersOrTransports( prefilters ), - ajaxTransport: addToPrefiltersOrTransports( transports ), - - // Main method - ajax: function( url, options ) { - - // If url is an object, simulate pre-1.5 signature - if ( typeof url === "object" ) { - options = url; - url = undefined; - } - - // Force options to be an object - options = options || {}; - - var transport, - - // URL without anti-cache param - cacheURL, - - // Response headers - responseHeadersString, - responseHeaders, - - // timeout handle - timeoutTimer, - - // Url cleanup var - urlAnchor, - - // Request state (becomes false upon send and true upon completion) - completed, - - // To know if global events are to be dispatched - fireGlobals, - - // Loop variable - i, - - // uncached part of the url - uncached, - - // Create the final options object - s = jQuery.ajaxSetup( {}, options ), - - // Callbacks context - callbackContext = s.context || s, - - // Context for global events is callbackContext if it is a DOM node or jQuery collection - globalEventContext = s.context && - ( callbackContext.nodeType || callbackContext.jquery ) ? - jQuery( callbackContext ) : - jQuery.event, - - // Deferreds - deferred = jQuery.Deferred(), - completeDeferred = jQuery.Callbacks( "once memory" ), - - // Status-dependent callbacks - statusCode = s.statusCode || {}, - - // Headers (they are sent all at once) - requestHeaders = {}, - requestHeadersNames = {}, - - // Default abort message - strAbort = "canceled", - - // Fake xhr - jqXHR = { - readyState: 0, - - // Builds headers hashtable if needed - getResponseHeader: function( key ) { - var match; - if ( completed ) { - if ( !responseHeaders ) { - responseHeaders = {}; - while ( ( match = rheaders.exec( responseHeadersString ) ) ) { - responseHeaders[ match[ 1 ].toLowerCase() + " " ] = - ( responseHeaders[ match[ 1 ].toLowerCase() + " " ] || [] ) - .concat( match[ 2 ] ); - } - } - match = responseHeaders[ key.toLowerCase() + " " ]; - } - return match == null ? null : match.join( ", " ); - }, - - // Raw string - getAllResponseHeaders: function() { - return completed ? responseHeadersString : null; - }, - - // Caches the header - setRequestHeader: function( name, value ) { - if ( completed == null ) { - name = requestHeadersNames[ name.toLowerCase() ] = - requestHeadersNames[ name.toLowerCase() ] || name; - requestHeaders[ name ] = value; - } - return this; - }, - - // Overrides response content-type header - overrideMimeType: function( type ) { - if ( completed == null ) { - s.mimeType = type; - } - return this; - }, - - // Status-dependent callbacks - statusCode: function( map ) { - var code; - if ( map ) { - if ( completed ) { - - // Execute the appropriate callbacks - jqXHR.always( map[ jqXHR.status ] ); - } else { - - // Lazy-add the new callbacks in a way that preserves old ones - for ( code in map ) { - statusCode[ code ] = [ statusCode[ code ], map[ code ] ]; - } - } - } - return this; - }, - - // Cancel the request - abort: function( statusText ) { - var finalText = statusText || strAbort; - if ( transport ) { - transport.abort( finalText ); - } - done( 0, finalText ); - return this; - } - }; - - // Attach deferreds - deferred.promise( jqXHR ); - - // Add protocol if not provided (prefilters might expect it) - // Handle falsy url in the settings object (#10093: consistency with old signature) - // We also use the url parameter if available - s.url = ( ( url || s.url || location.href ) + "" ) - .replace( rprotocol, location.protocol + "//" ); - - // Alias method option to type as per ticket #12004 - s.type = options.method || options.type || s.method || s.type; - - // Extract dataTypes list - s.dataTypes = ( s.dataType || "*" ).toLowerCase().match( rnothtmlwhite ) || [ "" ]; - - // A cross-domain request is in order when the origin doesn't match the current origin. - if ( s.crossDomain == null ) { - urlAnchor = document.createElement( "a" ); - - // Support: IE <=8 - 11, Edge 12 - 15 - // IE throws exception on accessing the href property if url is malformed, - // e.g. http://example.com:80x/ - try { - urlAnchor.href = s.url; - - // Support: IE <=8 - 11 only - // Anchor's host property isn't correctly set when s.url is relative - urlAnchor.href = urlAnchor.href; - s.crossDomain = originAnchor.protocol + "//" + originAnchor.host !== - urlAnchor.protocol + "//" + urlAnchor.host; - } catch ( e ) { - - // If there is an error parsing the URL, assume it is crossDomain, - // it can be rejected by the transport if it is invalid - s.crossDomain = true; - } - } - - // Convert data if not already a string - if ( s.data && s.processData && typeof s.data !== "string" ) { - s.data = jQuery.param( s.data, s.traditional ); - } - - // Apply prefilters - inspectPrefiltersOrTransports( prefilters, s, options, jqXHR ); - - // If request was aborted inside a prefilter, stop there - if ( completed ) { - return jqXHR; - } - - // We can fire global events as of now if asked to - // Don't fire events if jQuery.event is undefined in an AMD-usage scenario (#15118) - fireGlobals = jQuery.event && s.global; - - // Watch for a new set of requests - if ( fireGlobals && jQuery.active++ === 0 ) { - jQuery.event.trigger( "ajaxStart" ); - } - - // Uppercase the type - s.type = s.type.toUpperCase(); - - // Determine if request has content - s.hasContent = !rnoContent.test( s.type ); - - // Save the URL in case we're toying with the If-Modified-Since - // and/or If-None-Match header later on - // Remove hash to simplify url manipulation - cacheURL = s.url.replace( rhash, "" ); - - // More options handling for requests with no content - if ( !s.hasContent ) { - - // Remember the hash so we can put it back - uncached = s.url.slice( cacheURL.length ); - - // If data is available and should be processed, append data to url - if ( s.data && ( s.processData || typeof s.data === "string" ) ) { - cacheURL += ( rquery.test( cacheURL ) ? "&" : "?" ) + s.data; - - // #9682: remove data so that it's not used in an eventual retry - delete s.data; - } - - // Add or update anti-cache param if needed - if ( s.cache === false ) { - cacheURL = cacheURL.replace( rantiCache, "$1" ); - uncached = ( rquery.test( cacheURL ) ? "&" : "?" ) + "_=" + ( nonce.guid++ ) + - uncached; - } - - // Put hash and anti-cache on the URL that will be requested (gh-1732) - s.url = cacheURL + uncached; - - // Change '%20' to '+' if this is encoded form body content (gh-2658) - } else if ( s.data && s.processData && - ( s.contentType || "" ).indexOf( "application/x-www-form-urlencoded" ) === 0 ) { - s.data = s.data.replace( r20, "+" ); - } - - // Set the If-Modified-Since and/or If-None-Match header, if in ifModified mode. - if ( s.ifModified ) { - if ( jQuery.lastModified[ cacheURL ] ) { - jqXHR.setRequestHeader( "If-Modified-Since", jQuery.lastModified[ cacheURL ] ); - } - if ( jQuery.etag[ cacheURL ] ) { - jqXHR.setRequestHeader( "If-None-Match", jQuery.etag[ cacheURL ] ); - } - } - - // Set the correct header, if data is being sent - if ( s.data && s.hasContent && s.contentType !== false || options.contentType ) { - jqXHR.setRequestHeader( "Content-Type", s.contentType ); - } - - // Set the Accepts header for the server, depending on the dataType - jqXHR.setRequestHeader( - "Accept", - s.dataTypes[ 0 ] && s.accepts[ s.dataTypes[ 0 ] ] ? - s.accepts[ s.dataTypes[ 0 ] ] + - ( s.dataTypes[ 0 ] !== "*" ? ", " + allTypes + "; q=0.01" : "" ) : - s.accepts[ "*" ] - ); - - // Check for headers option - for ( i in s.headers ) { - jqXHR.setRequestHeader( i, s.headers[ i ] ); - } - - // Allow custom headers/mimetypes and early abort - if ( s.beforeSend && - ( s.beforeSend.call( callbackContext, jqXHR, s ) === false || completed ) ) { - - // Abort if not done already and return - return jqXHR.abort(); - } - - // Aborting is no longer a cancellation - strAbort = "abort"; - - // Install callbacks on deferreds - completeDeferred.add( s.complete ); - jqXHR.done( s.success ); - jqXHR.fail( s.error ); - - // Get transport - transport = inspectPrefiltersOrTransports( transports, s, options, jqXHR ); - - // If no transport, we auto-abort - if ( !transport ) { - done( -1, "No Transport" ); - } else { - jqXHR.readyState = 1; - - // Send global event - if ( fireGlobals ) { - globalEventContext.trigger( "ajaxSend", [ jqXHR, s ] ); - } - - // If request was aborted inside ajaxSend, stop there - if ( completed ) { - return jqXHR; - } - - // Timeout - if ( s.async && s.timeout > 0 ) { - timeoutTimer = window.setTimeout( function() { - jqXHR.abort( "timeout" ); - }, s.timeout ); - } - - try { - completed = false; - transport.send( requestHeaders, done ); - } catch ( e ) { - - // Rethrow post-completion exceptions - if ( completed ) { - throw e; - } - - // Propagate others as results - done( -1, e ); - } - } - - // Callback for when everything is done - function done( status, nativeStatusText, responses, headers ) { - var isSuccess, success, error, response, modified, - statusText = nativeStatusText; - - // Ignore repeat invocations - if ( completed ) { - return; - } - - completed = true; - - // Clear timeout if it exists - if ( timeoutTimer ) { - window.clearTimeout( timeoutTimer ); - } - - // Dereference transport for early garbage collection - // (no matter how long the jqXHR object will be used) - transport = undefined; - - // Cache response headers - responseHeadersString = headers || ""; - - // Set readyState - jqXHR.readyState = status > 0 ? 4 : 0; - - // Determine if successful - isSuccess = status >= 200 && status < 300 || status === 304; - - // Get response data - if ( responses ) { - response = ajaxHandleResponses( s, jqXHR, responses ); - } - - // Use a noop converter for missing script - if ( !isSuccess && jQuery.inArray( "script", s.dataTypes ) > -1 ) { - s.converters[ "text script" ] = function() {}; - } - - // Convert no matter what (that way responseXXX fields are always set) - response = ajaxConvert( s, response, jqXHR, isSuccess ); - - // If successful, handle type chaining - if ( isSuccess ) { - - // Set the If-Modified-Since and/or If-None-Match header, if in ifModified mode. - if ( s.ifModified ) { - modified = jqXHR.getResponseHeader( "Last-Modified" ); - if ( modified ) { - jQuery.lastModified[ cacheURL ] = modified; - } - modified = jqXHR.getResponseHeader( "etag" ); - if ( modified ) { - jQuery.etag[ cacheURL ] = modified; - } - } - - // if no content - if ( status === 204 || s.type === "HEAD" ) { - statusText = "nocontent"; - - // if not modified - } else if ( status === 304 ) { - statusText = "notmodified"; - - // If we have data, let's convert it - } else { - statusText = response.state; - success = response.data; - error = response.error; - isSuccess = !error; - } - } else { - - // Extract error from statusText and normalize for non-aborts - error = statusText; - if ( status || !statusText ) { - statusText = "error"; - if ( status < 0 ) { - status = 0; - } - } - } - - // Set data for the fake xhr object - jqXHR.status = status; - jqXHR.statusText = ( nativeStatusText || statusText ) + ""; - - // Success/Error - if ( isSuccess ) { - deferred.resolveWith( callbackContext, [ success, statusText, jqXHR ] ); - } else { - deferred.rejectWith( callbackContext, [ jqXHR, statusText, error ] ); - } - - // Status-dependent callbacks - jqXHR.statusCode( statusCode ); - statusCode = undefined; - - if ( fireGlobals ) { - globalEventContext.trigger( isSuccess ? "ajaxSuccess" : "ajaxError", - [ jqXHR, s, isSuccess ? success : error ] ); - } - - // Complete - completeDeferred.fireWith( callbackContext, [ jqXHR, statusText ] ); - - if ( fireGlobals ) { - globalEventContext.trigger( "ajaxComplete", [ jqXHR, s ] ); - - // Handle the global AJAX counter - if ( !( --jQuery.active ) ) { - jQuery.event.trigger( "ajaxStop" ); - } - } - } - - return jqXHR; - }, - - getJSON: function( url, data, callback ) { - return jQuery.get( url, data, callback, "json" ); - }, - - getScript: function( url, callback ) { - return jQuery.get( url, undefined, callback, "script" ); - } -} ); - -jQuery.each( [ "get", "post" ], function( _i, method ) { - jQuery[ method ] = function( url, data, callback, type ) { - - // Shift arguments if data argument was omitted - if ( isFunction( data ) ) { - type = type || callback; - callback = data; - data = undefined; - } - - // The url can be an options object (which then must have .url) - return jQuery.ajax( jQuery.extend( { - url: url, - type: method, - dataType: type, - data: data, - success: callback - }, jQuery.isPlainObject( url ) && url ) ); - }; -} ); - -jQuery.ajaxPrefilter( function( s ) { - var i; - for ( i in s.headers ) { - if ( i.toLowerCase() === "content-type" ) { - s.contentType = s.headers[ i ] || ""; - } - } -} ); - - -jQuery._evalUrl = function( url, options, doc ) { - return jQuery.ajax( { - url: url, - - // Make this explicit, since user can override this through ajaxSetup (#11264) - type: "GET", - dataType: "script", - cache: true, - async: false, - global: false, - - // Only evaluate the response if it is successful (gh-4126) - // dataFilter is not invoked for failure responses, so using it instead - // of the default converter is kludgy but it works. - converters: { - "text script": function() {} - }, - dataFilter: function( response ) { - jQuery.globalEval( response, options, doc ); - } - } ); -}; - - -jQuery.fn.extend( { - wrapAll: function( html ) { - var wrap; - - if ( this[ 0 ] ) { - if ( isFunction( html ) ) { - html = html.call( this[ 0 ] ); - } - - // The elements to wrap the target around - wrap = jQuery( html, this[ 0 ].ownerDocument ).eq( 0 ).clone( true ); - - if ( this[ 0 ].parentNode ) { - wrap.insertBefore( this[ 0 ] ); - } - - wrap.map( function() { - var elem = this; - - while ( elem.firstElementChild ) { - elem = elem.firstElementChild; - } - - return elem; - } ).append( this ); - } - - return this; - }, - - wrapInner: function( html ) { - if ( isFunction( html ) ) { - return this.each( function( i ) { - jQuery( this ).wrapInner( html.call( this, i ) ); - } ); - } - - return this.each( function() { - var self = jQuery( this ), - contents = self.contents(); - - if ( contents.length ) { - contents.wrapAll( html ); - - } else { - self.append( html ); - } - } ); - }, - - wrap: function( html ) { - var htmlIsFunction = isFunction( html ); - - return this.each( function( i ) { - jQuery( this ).wrapAll( htmlIsFunction ? html.call( this, i ) : html ); - } ); - }, - - unwrap: function( selector ) { - this.parent( selector ).not( "body" ).each( function() { - jQuery( this ).replaceWith( this.childNodes ); - } ); - return this; - } -} ); - - -jQuery.expr.pseudos.hidden = function( elem ) { - return !jQuery.expr.pseudos.visible( elem ); -}; -jQuery.expr.pseudos.visible = function( elem ) { - return !!( elem.offsetWidth || elem.offsetHeight || elem.getClientRects().length ); -}; - - - - -jQuery.ajaxSettings.xhr = function() { - try { - return new window.XMLHttpRequest(); - } catch ( e ) {} -}; - -var xhrSuccessStatus = { - - // File protocol always yields status code 0, assume 200 - 0: 200, - - // Support: IE <=9 only - // #1450: sometimes IE returns 1223 when it should be 204 - 1223: 204 - }, - xhrSupported = jQuery.ajaxSettings.xhr(); - -support.cors = !!xhrSupported && ( "withCredentials" in xhrSupported ); -support.ajax = xhrSupported = !!xhrSupported; - -jQuery.ajaxTransport( function( options ) { - var callback, errorCallback; - - // Cross domain only allowed if supported through XMLHttpRequest - if ( support.cors || xhrSupported && !options.crossDomain ) { - return { - send: function( headers, complete ) { - var i, - xhr = options.xhr(); - - xhr.open( - options.type, - options.url, - options.async, - options.username, - options.password - ); - - // Apply custom fields if provided - if ( options.xhrFields ) { - for ( i in options.xhrFields ) { - xhr[ i ] = options.xhrFields[ i ]; - } - } - - // Override mime type if needed - if ( options.mimeType && xhr.overrideMimeType ) { - xhr.overrideMimeType( options.mimeType ); - } - - // X-Requested-With header - // For cross-domain requests, seeing as conditions for a preflight are - // akin to a jigsaw puzzle, we simply never set it to be sure. - // (it can always be set on a per-request basis or even using ajaxSetup) - // For same-domain requests, won't change header if already provided. - if ( !options.crossDomain && !headers[ "X-Requested-With" ] ) { - headers[ "X-Requested-With" ] = "XMLHttpRequest"; - } - - // Set headers - for ( i in headers ) { - xhr.setRequestHeader( i, headers[ i ] ); - } - - // Callback - callback = function( type ) { - return function() { - if ( callback ) { - callback = errorCallback = xhr.onload = - xhr.onerror = xhr.onabort = xhr.ontimeout = - xhr.onreadystatechange = null; - - if ( type === "abort" ) { - xhr.abort(); - } else if ( type === "error" ) { - - // Support: IE <=9 only - // On a manual native abort, IE9 throws - // errors on any property access that is not readyState - if ( typeof xhr.status !== "number" ) { - complete( 0, "error" ); - } else { - complete( - - // File: protocol always yields status 0; see #8605, #14207 - xhr.status, - xhr.statusText - ); - } - } else { - complete( - xhrSuccessStatus[ xhr.status ] || xhr.status, - xhr.statusText, - - // Support: IE <=9 only - // IE9 has no XHR2 but throws on binary (trac-11426) - // For XHR2 non-text, let the caller handle it (gh-2498) - ( xhr.responseType || "text" ) !== "text" || - typeof xhr.responseText !== "string" ? - { binary: xhr.response } : - { text: xhr.responseText }, - xhr.getAllResponseHeaders() - ); - } - } - }; - }; - - // Listen to events - xhr.onload = callback(); - errorCallback = xhr.onerror = xhr.ontimeout = callback( "error" ); - - // Support: IE 9 only - // Use onreadystatechange to replace onabort - // to handle uncaught aborts - if ( xhr.onabort !== undefined ) { - xhr.onabort = errorCallback; - } else { - xhr.onreadystatechange = function() { - - // Check readyState before timeout as it changes - if ( xhr.readyState === 4 ) { - - // Allow onerror to be called first, - // but that will not handle a native abort - // Also, save errorCallback to a variable - // as xhr.onerror cannot be accessed - window.setTimeout( function() { - if ( callback ) { - errorCallback(); - } - } ); - } - }; - } - - // Create the abort callback - callback = callback( "abort" ); - - try { - - // Do send the request (this may raise an exception) - xhr.send( options.hasContent && options.data || null ); - } catch ( e ) { - - // #14683: Only rethrow if this hasn't been notified as an error yet - if ( callback ) { - throw e; - } - } - }, - - abort: function() { - if ( callback ) { - callback(); - } - } - }; - } -} ); - - - - -// Prevent auto-execution of scripts when no explicit dataType was provided (See gh-2432) -jQuery.ajaxPrefilter( function( s ) { - if ( s.crossDomain ) { - s.contents.script = false; - } -} ); - -// Install script dataType -jQuery.ajaxSetup( { - accepts: { - script: "text/javascript, application/javascript, " + - "application/ecmascript, application/x-ecmascript" - }, - contents: { - script: /\b(?:java|ecma)script\b/ - }, - converters: { - "text script": function( text ) { - jQuery.globalEval( text ); - return text; - } - } -} ); - -// Handle cache's special case and crossDomain -jQuery.ajaxPrefilter( "script", function( s ) { - if ( s.cache === undefined ) { - s.cache = false; - } - if ( s.crossDomain ) { - s.type = "GET"; - } -} ); - -// Bind script tag hack transport -jQuery.ajaxTransport( "script", function( s ) { - - // This transport only deals with cross domain or forced-by-attrs requests - if ( s.crossDomain || s.scriptAttrs ) { - var script, callback; - return { - send: function( _, complete ) { - script = jQuery( "' ); - - const leadingWs = text.match( /^\n?(\s*)/ )[1].length, - leadingTabs = text.match( /^\n?(\t*)/ )[1].length; - - if( leadingTabs > 0 ) { - text = text.replace( new RegExp('\\n?\\t{' + leadingTabs + '}(.*)','g'), function(m, p1) { return '\n' + p1 ; } ); - } - else if( leadingWs > 1 ) { - text = text.replace( new RegExp('\\n? {' + leadingWs + '}(.*)', 'g'), function(m, p1) { return '\n' + p1 ; } ); - } - - return text; - - } - - /** - * Given a markdown slide section element, this will - * return all arguments that aren't related to markdown - * parsing. Used to forward any other user-defined arguments - * to the output markdown slide. - */ - function getForwardedAttributes( section ) { - - const attributes = section.attributes; - const result = []; - - for( let i = 0, len = attributes.length; i < len; i++ ) { - const name = attributes[i].name, - value = attributes[i].value; - - // disregard attributes that are used for markdown loading/parsing - if( /data\-(markdown|separator|vertical|notes)/gi.test( name ) ) continue; - - if( value ) { - result.push( name + '="' + value + '"' ); - } - else { - result.push( name ); - } - } - - return result.join( ' ' ); - - } - - /** - * Inspects the given options and fills out default - * values for what's not defined. - */ - function getSlidifyOptions( options ) { - const markdownConfig = deck?.getConfig?.().markdown; - - options = options || {}; - options.separator = options.separator || markdownConfig?.separator || DEFAULT_SLIDE_SEPARATOR; - options.verticalSeparator = options.verticalSeparator || markdownConfig?.verticalSeparator || DEFAULT_VERTICAL_SEPARATOR; - options.notesSeparator = options.notesSeparator || markdownConfig?.notesSeparator || DEFAULT_NOTES_SEPARATOR; - options.attributes = options.attributes || ''; - - return options; - - } - - /** - * Helper function for constructing a markdown slide. - */ - function createMarkdownSlide( content, options ) { - - options = getSlidifyOptions( options ); - - const notesMatch = content.split( new RegExp( options.notesSeparator, 'mgi' ) ); - - if( notesMatch.length === 2 ) { - content = notesMatch[0] + ''; - } - - // prevent script end tags in the content from interfering - // with parsing - content = content.replace( /<\/script>/g, SCRIPT_END_PLACEHOLDER ); - - return ''; - - } - - /** - * Parses a data string into multiple slides based - * on the passed in separator arguments. - */ - function slidify( markdown, options ) { - - options = getSlidifyOptions( options ); - - const separatorRegex = new RegExp( options.separator + ( options.verticalSeparator ? '|' + options.verticalSeparator : '' ), 'mg' ), - horizontalSeparatorRegex = new RegExp( options.separator ); - - let matches, - lastIndex = 0, - isHorizontal, - wasHorizontal = true, - content, - sectionStack = []; - - // iterate until all blocks between separators are stacked up - while( matches = separatorRegex.exec( markdown ) ) { - const notes = null; - - // determine direction (horizontal by default) - isHorizontal = horizontalSeparatorRegex.test( matches[0] ); - - if( !isHorizontal && wasHorizontal ) { - // create vertical stack - sectionStack.push( [] ); - } - - // pluck slide content from markdown input - content = markdown.substring( lastIndex, matches.index ); - - if( isHorizontal && wasHorizontal ) { - // add to horizontal stack - sectionStack.push( content ); - } - else { - // add to vertical stack - sectionStack[sectionStack.length-1].push( content ); - } - - lastIndex = separatorRegex.lastIndex; - wasHorizontal = isHorizontal; - } - - // add the remaining slide - ( wasHorizontal ? sectionStack : sectionStack[sectionStack.length-1] ).push( markdown.substring( lastIndex ) ); - - let markdownSections = ''; - - // flatten the hierarchical stack, and insert
    tags - for( let i = 0, len = sectionStack.length; i < len; i++ ) { - // vertical - if( sectionStack[i] instanceof Array ) { - markdownSections += '
    '; - - sectionStack[i].forEach( function( child ) { - markdownSections += '
    ' + createMarkdownSlide( child, options ) + '
    '; - } ); - - markdownSections += '
    '; - } - else { - markdownSections += '
    ' + createMarkdownSlide( sectionStack[i], options ) + '
    '; - } - } - - return markdownSections; - - } - - /** - * Parses any current data-markdown slides, splits - * multi-slide markdown into separate sections and - * handles loading of external markdown. - */ - function processSlides( scope ) { - - return new Promise( function( resolve ) { - - const externalPromises = []; - - [].slice.call( scope.querySelectorAll( 'section[data-markdown]:not([data-markdown-parsed])') ).forEach( function( section, i ) { - - if( section.getAttribute( 'data-markdown' ).length ) { - - externalPromises.push( loadExternalMarkdown( section ).then( - - // Finished loading external file - function( xhr, url ) { - section.outerHTML = slidify( xhr.responseText, { - separator: section.getAttribute( 'data-separator' ), - verticalSeparator: section.getAttribute( 'data-separator-vertical' ), - notesSeparator: section.getAttribute( 'data-separator-notes' ), - attributes: getForwardedAttributes( section ) - }); - }, - - // Failed to load markdown - function( xhr, url ) { - section.outerHTML = '
    ' + - 'ERROR: The attempt to fetch ' + url + ' failed with HTTP status ' + xhr.status + '.' + - 'Check your browser\'s JavaScript console for more details.' + - '

    Remember that you need to serve the presentation HTML from a HTTP server.

    ' + - '
    '; - } - - ) ); - - } - else { - - section.outerHTML = slidify( getMarkdownFromSlide( section ), { - separator: section.getAttribute( 'data-separator' ), - verticalSeparator: section.getAttribute( 'data-separator-vertical' ), - notesSeparator: section.getAttribute( 'data-separator-notes' ), - attributes: getForwardedAttributes( section ) - }); - - } - - }); - - Promise.all( externalPromises ).then( resolve ); - - } ); - - } - - function loadExternalMarkdown( section ) { - - return new Promise( function( resolve, reject ) { - - const xhr = new XMLHttpRequest(), - url = section.getAttribute( 'data-markdown' ); - - const datacharset = section.getAttribute( 'data-charset' ); - - // see https://developer.mozilla.org/en-US/docs/Web/API/element.getAttribute#Notes - if( datacharset !== null && datacharset !== '' ) { - xhr.overrideMimeType( 'text/html; charset=' + datacharset ); - } - - xhr.onreadystatechange = function( section, xhr ) { - if( xhr.readyState === 4 ) { - // file protocol yields status code 0 (useful for local debug, mobile applications etc.) - if ( ( xhr.status >= 200 && xhr.status < 300 ) || xhr.status === 0 ) { - - resolve( xhr, url ); - - } - else { - - reject( xhr, url ); - - } - } - }.bind( this, section, xhr ); - - xhr.open( 'GET', url, true ); - - try { - xhr.send(); - } - catch ( e ) { - console.warn( 'Failed to get the Markdown file ' + url + '. Make sure that the presentation and the file are served by a HTTP server and the file can be found there. ' + e ); - resolve( xhr, url ); - } - - } ); - - } - - /** - * Check if a node value has the attributes pattern. - * If yes, extract it and add that value as one or several attributes - * to the target element. - * - * You need Cache Killer on Chrome to see the effect on any FOM transformation - * directly on refresh (F5) - * http://stackoverflow.com/questions/5690269/disabling-chrome-cache-for-website-development/7000899#answer-11786277 - */ - function addAttributeInElement( node, elementTarget, separator ) { - - const markdownClassesInElementsRegex = new RegExp( separator, 'mg' ); - const markdownClassRegex = new RegExp( "([^\"= ]+?)=\"([^\"]+?)\"|(data-[^\"= ]+?)(?=[\" ])", 'mg' ); - let nodeValue = node.nodeValue; - let matches, - matchesClass; - if( matches = markdownClassesInElementsRegex.exec( nodeValue ) ) { - - const classes = matches[1]; - nodeValue = nodeValue.substring( 0, matches.index ) + nodeValue.substring( markdownClassesInElementsRegex.lastIndex ); - node.nodeValue = nodeValue; - while( matchesClass = markdownClassRegex.exec( classes ) ) { - if( matchesClass[2] ) { - elementTarget.setAttribute( matchesClass[1], matchesClass[2] ); - } else { - elementTarget.setAttribute( matchesClass[3], "" ); - } - } - return true; - } - return false; - } - - /** - * Add attributes to the parent element of a text node, - * or the element of an attribute node. - */ - function addAttributes( section, element, previousElement, separatorElementAttributes, separatorSectionAttributes ) { - - if ( element !== null && element.childNodes !== undefined && element.childNodes.length > 0 ) { - let previousParentElement = element; - for( let i = 0; i < element.childNodes.length; i++ ) { - const childElement = element.childNodes[i]; - if ( i > 0 ) { - let j = i - 1; - while ( j >= 0 ) { - const aPreviousChildElement = element.childNodes[j]; - if ( typeof aPreviousChildElement.setAttribute === 'function' && aPreviousChildElement.tagName !== "BR" ) { - previousParentElement = aPreviousChildElement; - break; - } - j = j - 1; - } - } - let parentSection = section; - if( childElement.nodeName === "section" ) { - parentSection = childElement ; - previousParentElement = childElement ; - } - if ( typeof childElement.setAttribute === 'function' || childElement.nodeType === Node.COMMENT_NODE ) { - addAttributes( parentSection, childElement, previousParentElement, separatorElementAttributes, separatorSectionAttributes ); - } - } - } - - if ( element.nodeType === Node.COMMENT_NODE ) { - if ( addAttributeInElement( element, previousElement, separatorElementAttributes ) === false ) { - addAttributeInElement( element, section, separatorSectionAttributes ); - } - } - } - - /** - * Converts any current data-markdown slides in the - * DOM to HTML. - */ - function convertSlides() { - - const sections = deck.getRevealElement().querySelectorAll( '[data-markdown]:not([data-markdown-parsed])'); - - [].slice.call( sections ).forEach( function( section ) { - - section.setAttribute( 'data-markdown-parsed', true ) - - const notes = section.querySelector( 'aside.notes' ); - const markdown = getMarkdownFromSlide( section ); - - section.innerHTML = marked( markdown ); - addAttributes( section, section, null, section.getAttribute( 'data-element-attributes' ) || - section.parentNode.getAttribute( 'data-element-attributes' ) || - DEFAULT_ELEMENT_ATTRIBUTES_SEPARATOR, - section.getAttribute( 'data-attributes' ) || - section.parentNode.getAttribute( 'data-attributes' ) || - DEFAULT_SLIDE_ATTRIBUTES_SEPARATOR); - - // If there were notes, we need to re-add them after - // having overwritten the section's HTML - if( notes ) { - section.appendChild( notes ); - } - - } ); - - return Promise.resolve(); - - } - - function escapeForHTML( input ) { - - return input.replace( /([&<>'"])/g, char => HTML_ESCAPE_MAP[char] ); - - } - - return { - id: 'markdown', - - /** - * Starts processing and converting Markdown within the - * current reveal.js deck. - */ - init: function( reveal ) { - - deck = reveal; - - let { renderer, animateLists, ...markedOptions } = deck.getConfig().markdown || {}; - - if( !renderer ) { - renderer = new marked.Renderer(); - - renderer.code = ( code, language ) => { - - // Off by default - let lineNumberOffset = ''; - let lineNumbers = ''; - - // Users can opt in to show line numbers and highlight - // specific lines. - // ```javascript [] show line numbers - // ```javascript [1,4-8] highlights lines 1 and 4-8 - // optional line number offset: - // ```javascript [25: 1,4-8] start line numbering at 25, - // highlights lines 1 (numbered as 25) and 4-8 (numbered as 28-32) - if( CODE_LINE_NUMBER_REGEX.test( language ) ) { - let lineNumberOffsetMatch = language.match( CODE_LINE_NUMBER_REGEX )[2]; - if (lineNumberOffsetMatch){ - lineNumberOffset = `data-ln-start-from="${lineNumberOffsetMatch.trim()}"`; - } - - lineNumbers = language.match( CODE_LINE_NUMBER_REGEX )[3].trim(); - lineNumbers = `data-line-numbers="${lineNumbers}"`; - language = language.replace( CODE_LINE_NUMBER_REGEX, '' ).trim(); - } - - // Escape before this gets injected into the DOM to - // avoid having the HTML parser alter our code before - // highlight.js is able to read it - code = escapeForHTML( code ); - - // return `
    ${code}
    `; - - return `
    ${code}
    `; - }; - } - - if( animateLists === true ) { - renderer.listitem = text => `
  • ${text}
    • `; - } - - marked.setOptions( { - renderer, - ...markedOptions - } ); - - return processSlides( deck.getRevealElement() ).then( convertSlides ); - - }, - - // TODO: Do these belong in the API? - processSlides: processSlides, - convertSlides: convertSlides, - slidify: slidify, - marked: marked - } - -}; - -export default Plugin; +/*! + * The reveal.js markdown plugin. Handles parsing of + * markdown inside of presentations as well as loading + * of external markdown documents. + */ + +import { marked } from 'marked'; + +const DEFAULT_SLIDE_SEPARATOR = '\r?\n---\r?\n', + DEFAULT_VERTICAL_SEPARATOR = null, + DEFAULT_NOTES_SEPARATOR = '^\s*notes?:', + DEFAULT_ELEMENT_ATTRIBUTES_SEPARATOR = '\\\.element\\\s*?(.+?)$', + DEFAULT_SLIDE_ATTRIBUTES_SEPARATOR = '\\\.slide:\\\s*?(\\\S.+?)$'; + +const SCRIPT_END_PLACEHOLDER = '__SCRIPT_END__'; + +// match an optional line number offset and highlight line numbers +// [] or [: ] +const CODE_LINE_NUMBER_REGEX = /\[\s*((\d*):)?\s*([\s\d,|-]*)\]/; + +const HTML_ESCAPE_MAP = { + '&': '&', + '<': '<', + '>': '>', + '"': '"', + "'": ''' +}; + +const Plugin = () => { + + // The reveal.js instance this plugin is attached to + let deck; + + /** + * Retrieves the markdown contents of a slide section + * element. Normalizes leading tabs/whitespace. + */ + function getMarkdownFromSlide( section ) { + + // look for a ' ); + + const leadingWs = text.match( /^\n?(\s*)/ )[1].length, + leadingTabs = text.match( /^\n?(\t*)/ )[1].length; + + if( leadingTabs > 0 ) { + text = text.replace( new RegExp('\\n?\\t{' + leadingTabs + '}(.*)','g'), function(m, p1) { return '\n' + p1 ; } ); + } + else if( leadingWs > 1 ) { + text = text.replace( new RegExp('\\n? {' + leadingWs + '}(.*)', 'g'), function(m, p1) { return '\n' + p1 ; } ); + } + + return text; + + } + + /** + * Given a markdown slide section element, this will + * return all arguments that aren't related to markdown + * parsing. Used to forward any other user-defined arguments + * to the output markdown slide. + */ + function getForwardedAttributes( section ) { + + const attributes = section.attributes; + const result = []; + + for( let i = 0, len = attributes.length; i < len; i++ ) { + const name = attributes[i].name, + value = attributes[i].value; + + // disregard attributes that are used for markdown loading/parsing + if( /data\-(markdown|separator|vertical|notes)/gi.test( name ) ) continue; + + if( value ) { + result.push( name + '="' + value + '"' ); + } + else { + result.push( name ); + } + } + + return result.join( ' ' ); + + } + + /** + * Inspects the given options and fills out default + * values for what's not defined. + */ + function getSlidifyOptions( options ) { + const markdownConfig = deck?.getConfig?.().markdown; + + options = options || {}; + options.separator = options.separator || markdownConfig?.separator || DEFAULT_SLIDE_SEPARATOR; + options.verticalSeparator = options.verticalSeparator || markdownConfig?.verticalSeparator || DEFAULT_VERTICAL_SEPARATOR; + options.notesSeparator = options.notesSeparator || markdownConfig?.notesSeparator || DEFAULT_NOTES_SEPARATOR; + options.attributes = options.attributes || ''; + + return options; + + } + + /** + * Helper function for constructing a markdown slide. + */ + function createMarkdownSlide( content, options ) { + + options = getSlidifyOptions( options ); + + const notesMatch = content.split( new RegExp( options.notesSeparator, 'mgi' ) ); + + if( notesMatch.length === 2 ) { + content = notesMatch[0] + ''; + } + + // prevent script end tags in the content from interfering + // with parsing + content = content.replace( /<\/script>/g, SCRIPT_END_PLACEHOLDER ); + + return ''; + + } + + /** + * Parses a data string into multiple slides based + * on the passed in separator arguments. + */ + function slidify( markdown, options ) { + + options = getSlidifyOptions( options ); + + const separatorRegex = new RegExp( options.separator + ( options.verticalSeparator ? '|' + options.verticalSeparator : '' ), 'mg' ), + horizontalSeparatorRegex = new RegExp( options.separator ); + + let matches, + lastIndex = 0, + isHorizontal, + wasHorizontal = true, + content, + sectionStack = []; + + // iterate until all blocks between separators are stacked up + while( matches = separatorRegex.exec( markdown ) ) { + const notes = null; + + // determine direction (horizontal by default) + isHorizontal = horizontalSeparatorRegex.test( matches[0] ); + + if( !isHorizontal && wasHorizontal ) { + // create vertical stack + sectionStack.push( [] ); + } + + // pluck slide content from markdown input + content = markdown.substring( lastIndex, matches.index ); + + if( isHorizontal && wasHorizontal ) { + // add to horizontal stack + sectionStack.push( content ); + } + else { + // add to vertical stack + sectionStack[sectionStack.length-1].push( content ); + } + + lastIndex = separatorRegex.lastIndex; + wasHorizontal = isHorizontal; + } + + // add the remaining slide + ( wasHorizontal ? sectionStack : sectionStack[sectionStack.length-1] ).push( markdown.substring( lastIndex ) ); + + let markdownSections = ''; + + // flatten the hierarchical stack, and insert
    tags + for( let i = 0, len = sectionStack.length; i < len; i++ ) { + // vertical + if( sectionStack[i] instanceof Array ) { + markdownSections += '
    '; + + sectionStack[i].forEach( function( child ) { + markdownSections += '
    ' + createMarkdownSlide( child, options ) + '
    '; + } ); + + markdownSections += '
    '; + } + else { + markdownSections += '
    ' + createMarkdownSlide( sectionStack[i], options ) + '
    '; + } + } + + return markdownSections; + + } + + /** + * Parses any current data-markdown slides, splits + * multi-slide markdown into separate sections and + * handles loading of external markdown. + */ + function processSlides( scope ) { + + return new Promise( function( resolve ) { + + const externalPromises = []; + + [].slice.call( scope.querySelectorAll( 'section[data-markdown]:not([data-markdown-parsed])') ).forEach( function( section, i ) { + + if( section.getAttribute( 'data-markdown' ).length ) { + + externalPromises.push( loadExternalMarkdown( section ).then( + + // Finished loading external file + function( xhr, url ) { + section.outerHTML = slidify( xhr.responseText, { + separator: section.getAttribute( 'data-separator' ), + verticalSeparator: section.getAttribute( 'data-separator-vertical' ), + notesSeparator: section.getAttribute( 'data-separator-notes' ), + attributes: getForwardedAttributes( section ) + }); + }, + + // Failed to load markdown + function( xhr, url ) { + section.outerHTML = '
    ' + + 'ERROR: The attempt to fetch ' + url + ' failed with HTTP status ' + xhr.status + '.' + + 'Check your browser\'s JavaScript console for more details.' + + '

    Remember that you need to serve the presentation HTML from a HTTP server.

    ' + + '
    '; + } + + ) ); + + } + else { + + section.outerHTML = slidify( getMarkdownFromSlide( section ), { + separator: section.getAttribute( 'data-separator' ), + verticalSeparator: section.getAttribute( 'data-separator-vertical' ), + notesSeparator: section.getAttribute( 'data-separator-notes' ), + attributes: getForwardedAttributes( section ) + }); + + } + + }); + + Promise.all( externalPromises ).then( resolve ); + + } ); + + } + + function loadExternalMarkdown( section ) { + + return new Promise( function( resolve, reject ) { + + const xhr = new XMLHttpRequest(), + url = section.getAttribute( 'data-markdown' ); + + const datacharset = section.getAttribute( 'data-charset' ); + + // see https://developer.mozilla.org/en-US/docs/Web/API/element.getAttribute#Notes + if( datacharset !== null && datacharset !== '' ) { + xhr.overrideMimeType( 'text/html; charset=' + datacharset ); + } + + xhr.onreadystatechange = function( section, xhr ) { + if( xhr.readyState === 4 ) { + // file protocol yields status code 0 (useful for local debug, mobile applications etc.) + if ( ( xhr.status >= 200 && xhr.status < 300 ) || xhr.status === 0 ) { + + resolve( xhr, url ); + + } + else { + + reject( xhr, url ); + + } + } + }.bind( this, section, xhr ); + + xhr.open( 'GET', url, true ); + + try { + xhr.send(); + } + catch ( e ) { + console.warn( 'Failed to get the Markdown file ' + url + '. Make sure that the presentation and the file are served by a HTTP server and the file can be found there. ' + e ); + resolve( xhr, url ); + } + + } ); + + } + + /** + * Check if a node value has the attributes pattern. + * If yes, extract it and add that value as one or several attributes + * to the target element. + * + * You need Cache Killer on Chrome to see the effect on any FOM transformation + * directly on refresh (F5) + * http://stackoverflow.com/questions/5690269/disabling-chrome-cache-for-website-development/7000899#answer-11786277 + */ + function addAttributeInElement( node, elementTarget, separator ) { + + const markdownClassesInElementsRegex = new RegExp( separator, 'mg' ); + const markdownClassRegex = new RegExp( "([^\"= ]+?)=\"([^\"]+?)\"|(data-[^\"= ]+?)(?=[\" ])", 'mg' ); + let nodeValue = node.nodeValue; + let matches, + matchesClass; + if( matches = markdownClassesInElementsRegex.exec( nodeValue ) ) { + + const classes = matches[1]; + nodeValue = nodeValue.substring( 0, matches.index ) + nodeValue.substring( markdownClassesInElementsRegex.lastIndex ); + node.nodeValue = nodeValue; + while( matchesClass = markdownClassRegex.exec( classes ) ) { + if( matchesClass[2] ) { + elementTarget.setAttribute( matchesClass[1], matchesClass[2] ); + } else { + elementTarget.setAttribute( matchesClass[3], "" ); + } + } + return true; + } + return false; + } + + /** + * Add attributes to the parent element of a text node, + * or the element of an attribute node. + */ + function addAttributes( section, element, previousElement, separatorElementAttributes, separatorSectionAttributes ) { + + if ( element !== null && element.childNodes !== undefined && element.childNodes.length > 0 ) { + let previousParentElement = element; + for( let i = 0; i < element.childNodes.length; i++ ) { + const childElement = element.childNodes[i]; + if ( i > 0 ) { + let j = i - 1; + while ( j >= 0 ) { + const aPreviousChildElement = element.childNodes[j]; + if ( typeof aPreviousChildElement.setAttribute === 'function' && aPreviousChildElement.tagName !== "BR" ) { + previousParentElement = aPreviousChildElement; + break; + } + j = j - 1; + } + } + let parentSection = section; + if( childElement.nodeName === "section" ) { + parentSection = childElement ; + previousParentElement = childElement ; + } + if ( typeof childElement.setAttribute === 'function' || childElement.nodeType === Node.COMMENT_NODE ) { + addAttributes( parentSection, childElement, previousParentElement, separatorElementAttributes, separatorSectionAttributes ); + } + } + } + + if ( element.nodeType === Node.COMMENT_NODE ) { + if ( addAttributeInElement( element, previousElement, separatorElementAttributes ) === false ) { + addAttributeInElement( element, section, separatorSectionAttributes ); + } + } + } + + /** + * Converts any current data-markdown slides in the + * DOM to HTML. + */ + function convertSlides() { + + const sections = deck.getRevealElement().querySelectorAll( '[data-markdown]:not([data-markdown-parsed])'); + + [].slice.call( sections ).forEach( function( section ) { + + section.setAttribute( 'data-markdown-parsed', true ) + + const notes = section.querySelector( 'aside.notes' ); + const markdown = getMarkdownFromSlide( section ); + + section.innerHTML = marked( markdown ); + addAttributes( section, section, null, section.getAttribute( 'data-element-attributes' ) || + section.parentNode.getAttribute( 'data-element-attributes' ) || + DEFAULT_ELEMENT_ATTRIBUTES_SEPARATOR, + section.getAttribute( 'data-attributes' ) || + section.parentNode.getAttribute( 'data-attributes' ) || + DEFAULT_SLIDE_ATTRIBUTES_SEPARATOR); + + // If there were notes, we need to re-add them after + // having overwritten the section's HTML + if( notes ) { + section.appendChild( notes ); + } + + } ); + + return Promise.resolve(); + + } + + function escapeForHTML( input ) { + + return input.replace( /([&<>'"])/g, char => HTML_ESCAPE_MAP[char] ); + + } + + return { + id: 'markdown', + + /** + * Starts processing and converting Markdown within the + * current reveal.js deck. + */ + init: function( reveal ) { + + deck = reveal; + + let { renderer, animateLists, ...markedOptions } = deck.getConfig().markdown || {}; + + if( !renderer ) { + renderer = new marked.Renderer(); + + renderer.code = ( code, language ) => { + + // Off by default + let lineNumberOffset = ''; + let lineNumbers = ''; + + // Users can opt in to show line numbers and highlight + // specific lines. + // ```javascript [] show line numbers + // ```javascript [1,4-8] highlights lines 1 and 4-8 + // optional line number offset: + // ```javascript [25: 1,4-8] start line numbering at 25, + // highlights lines 1 (numbered as 25) and 4-8 (numbered as 28-32) + if( CODE_LINE_NUMBER_REGEX.test( language ) ) { + let lineNumberOffsetMatch = language.match( CODE_LINE_NUMBER_REGEX )[2]; + if (lineNumberOffsetMatch){ + lineNumberOffset = `data-ln-start-from="${lineNumberOffsetMatch.trim()}"`; + } + + lineNumbers = language.match( CODE_LINE_NUMBER_REGEX )[3].trim(); + lineNumbers = `data-line-numbers="${lineNumbers}"`; + language = language.replace( CODE_LINE_NUMBER_REGEX, '' ).trim(); + } + + // Escape before this gets injected into the DOM to + // avoid having the HTML parser alter our code before + // highlight.js is able to read it + code = escapeForHTML( code ); + + // return `
    ${code}
    `; + + return `
    ${code}
    `; + }; + } + + if( animateLists === true ) { + renderer.listitem = text => `
  • ${text}
    • `; + } + + marked.setOptions( { + renderer, + ...markedOptions + } ); + + return processSlides( deck.getRevealElement() ).then( convertSlides ); + + }, + + // TODO: Do these belong in the API? + processSlides: processSlides, + convertSlides: convertSlides, + slidify: slidify, + marked: marked + } + +}; + +export default Plugin; diff --git a/docs/site_libs/revealjs/plugin/math/katex.js b/docs/site_libs/revealjs/plugin/math/katex.js index a8b47c4..f7f47e8 100644 --- a/docs/site_libs/revealjs/plugin/math/katex.js +++ b/docs/site_libs/revealjs/plugin/math/katex.js @@ -1,96 +1,96 @@ -/** - * A plugin which enables rendering of math equations inside - * of reveal.js slides. Essentially a thin wrapper for KaTeX. - * - * @author Hakim El Hattab - * @author Gerhard Burger - */ -export const KaTeX = () => { - let deck; - - let defaultOptions = { - version: 'latest', - delimiters: [ - {left: '$$', right: '$$', display: true}, // Note: $$ has to come before $ - {left: '$', right: '$', display: false}, - {left: '\\(', right: '\\)', display: false}, - {left: '\\[', right: '\\]', display: true} - ], - ignoredTags: ['script', 'noscript', 'style', 'textarea', 'pre'] - } - - const loadCss = src => { - let link = document.createElement('link'); - link.rel = 'stylesheet'; - link.href = src; - document.head.appendChild(link); - }; - - /** - * Loads a JavaScript file and returns a Promise for when it is loaded - * Credits: https://aaronsmith.online/easily-load-an-external-script-using-javascript/ - */ - const loadScript = src => { - return new Promise((resolve, reject) => { - const script = document.createElement('script') - script.type = 'text/javascript' - script.onload = resolve - script.onerror = reject - script.src = src - document.head.append(script) - }) - }; - - async function loadScripts(urls) { - for(const url of urls) { - await loadScript(url); - } - } - - return { - id: 'katex', - - init: function (reveal) { - - deck = reveal; - - let revealOptions = deck.getConfig().katex || {}; - - let options = {...defaultOptions, ...revealOptions}; - const {local, version, extensions, ...katexOptions} = options; - - let baseUrl = options.local || 'https://cdn.jsdelivr.net/npm/katex'; - let versionString = options.local ? '' : '@' + options.version; - - let cssUrl = baseUrl + versionString + '/dist/katex.min.css'; - let katexUrl = baseUrl + versionString + '/dist/katex.min.js'; - let mhchemUrl = baseUrl + versionString + '/dist/contrib/mhchem.min.js' - let karUrl = baseUrl + versionString + '/dist/contrib/auto-render.min.js'; - - let katexScripts = [katexUrl]; - if(options.extensions && options.extensions.includes("mhchem")) { - katexScripts.push(mhchemUrl); - } - katexScripts.push(karUrl); - - const renderMath = () => { - renderMathInElement(reveal.getSlidesElement(), katexOptions); - deck.layout(); - } - - loadCss(cssUrl); - - // For some reason dynamically loading with defer attribute doesn't result in the expected behavior, the below code does - loadScripts(katexScripts).then(() => { - if( deck.isReady() ) { - renderMath(); - } - else { - deck.on( 'ready', renderMath.bind( this ) ); - } - }); - - } - } - -}; +/** + * A plugin which enables rendering of math equations inside + * of reveal.js slides. Essentially a thin wrapper for KaTeX. + * + * @author Hakim El Hattab + * @author Gerhard Burger + */ +export const KaTeX = () => { + let deck; + + let defaultOptions = { + version: 'latest', + delimiters: [ + {left: '$$', right: '$$', display: true}, // Note: $$ has to come before $ + {left: '$', right: '$', display: false}, + {left: '\\(', right: '\\)', display: false}, + {left: '\\[', right: '\\]', display: true} + ], + ignoredTags: ['script', 'noscript', 'style', 'textarea', 'pre'] + } + + const loadCss = src => { + let link = document.createElement('link'); + link.rel = 'stylesheet'; + link.href = src; + document.head.appendChild(link); + }; + + /** + * Loads a JavaScript file and returns a Promise for when it is loaded + * Credits: https://aaronsmith.online/easily-load-an-external-script-using-javascript/ + */ + const loadScript = src => { + return new Promise((resolve, reject) => { + const script = document.createElement('script') + script.type = 'text/javascript' + script.onload = resolve + script.onerror = reject + script.src = src + document.head.append(script) + }) + }; + + async function loadScripts(urls) { + for(const url of urls) { + await loadScript(url); + } + } + + return { + id: 'katex', + + init: function (reveal) { + + deck = reveal; + + let revealOptions = deck.getConfig().katex || {}; + + let options = {...defaultOptions, ...revealOptions}; + const {local, version, extensions, ...katexOptions} = options; + + let baseUrl = options.local || 'https://cdn.jsdelivr.net/npm/katex'; + let versionString = options.local ? '' : '@' + options.version; + + let cssUrl = baseUrl + versionString + '/dist/katex.min.css'; + let katexUrl = baseUrl + versionString + '/dist/katex.min.js'; + let mhchemUrl = baseUrl + versionString + '/dist/contrib/mhchem.min.js' + let karUrl = baseUrl + versionString + '/dist/contrib/auto-render.min.js'; + + let katexScripts = [katexUrl]; + if(options.extensions && options.extensions.includes("mhchem")) { + katexScripts.push(mhchemUrl); + } + katexScripts.push(karUrl); + + const renderMath = () => { + renderMathInElement(reveal.getSlidesElement(), katexOptions); + deck.layout(); + } + + loadCss(cssUrl); + + // For some reason dynamically loading with defer attribute doesn't result in the expected behavior, the below code does + loadScripts(katexScripts).then(() => { + if( deck.isReady() ) { + renderMath(); + } + else { + deck.on( 'ready', renderMath.bind( this ) ); + } + }); + + } + } + +}; diff --git a/docs/site_libs/revealjs/plugin/math/math.esm.js b/docs/site_libs/revealjs/plugin/math/math.esm.js index 55c07a0..a48c091 100644 --- a/docs/site_libs/revealjs/plugin/math/math.esm.js +++ b/docs/site_libs/revealjs/plugin/math/math.esm.js @@ -1,6 +1,6 @@ -const t=()=>{let t,e={messageStyle:"none",tex2jax:{inlineMath:[["$","$"],["\\(","\\)"]],skipTags:["script","noscript","style","textarea","pre"]},skipStartupTypeset:!0};return{id:"mathjax2",init:function(a){t=a;let n=t.getConfig().mathjax2||t.getConfig().math||{},i={...e,...n},s=(i.mathjax||"https://cdn.jsdelivr.net/npm/mathjax@2/MathJax.js")+"?config="+(i.config||"TeX-AMS_HTML-full");i.tex2jax={...e.tex2jax,...n.tex2jax},i.mathjax=i.config=null,function(t,e){let a=document.querySelector("head"),n=document.createElement("script");n.type="text/javascript",n.src=t;let i=()=>{"function"==typeof e&&(e.call(),e=null)};n.onload=i,n.onreadystatechange=()=>{"loaded"===this.readyState&&i()},a.appendChild(n)}(s,(function(){MathJax.Hub.Config(i),MathJax.Hub.Queue(["Typeset",MathJax.Hub,t.getRevealElement()]),MathJax.Hub.Queue(t.layout),t.on("slidechanged",(function(t){MathJax.Hub.Queue(["Typeset",MathJax.Hub,t.currentSlide])}))}))}}},e=t; -/*! - * This plugin is a wrapper for the MathJax2, - * MathJax3 and KaTeX typesetter plugins. - */ -var a=Plugin=Object.assign(e(),{KaTeX:()=>{let t,e={version:"latest",delimiters:[{left:"$$",right:"$$",display:!0},{left:"$",right:"$",display:!1},{left:"\\(",right:"\\)",display:!1},{left:"\\[",right:"\\]",display:!0}],ignoredTags:["script","noscript","style","textarea","pre"]};const a=t=>new Promise(((e,a)=>{const n=document.createElement("script");n.type="text/javascript",n.onload=e,n.onerror=a,n.src=t,document.head.append(n)}));return{id:"katex",init:function(n){t=n;let i=t.getConfig().katex||{},s={...e,...i};const{local:l,version:o,extensions:r,...c}=s;let d=s.local||"https://cdn.jsdelivr.net/npm/katex",p=s.local?"":"@"+s.version,u=d+p+"/dist/katex.min.css",h=d+p+"/dist/contrib/mhchem.min.js",x=d+p+"/dist/contrib/auto-render.min.js",m=[d+p+"/dist/katex.min.js"];s.extensions&&s.extensions.includes("mhchem")&&m.push(h),m.push(x);const f=()=>{renderMathInElement(n.getSlidesElement(),c),t.layout()};(t=>{let e=document.createElement("link");e.rel="stylesheet",e.href=t,document.head.appendChild(e)})(u),async function(t){for(const e of t)await a(e)}(m).then((()=>{t.isReady()?f():t.on("ready",f.bind(this))}))}}},MathJax2:t,MathJax3:()=>{let t,e={tex:{inlineMath:[["$","$"],["\\(","\\)"]]},options:{skipHtmlTags:["script","noscript","style","textarea","pre"]},startup:{ready:()=>{MathJax.startup.defaultReady(),MathJax.startup.promise.then((()=>{t.layout()}))}}};return{id:"mathjax3",init:function(a){t=a;let n=t.getConfig().mathjax3||{},i={...e,...n};i.tex={...e.tex,...n.tex},i.options={...e.options,...n.options},i.startup={...e.startup,...n.startup};let s=i.mathjax||"https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js";i.mathjax=null,window.MathJax=i,function(t,e){let a=document.createElement("script");a.type="text/javascript",a.id="MathJax-script",a.src=t,a.async=!0,a.onload=()=>{"function"==typeof e&&(e.call(),e=null)},document.head.appendChild(a)}(s,(function(){t.addEventListener("slidechanged",(function(t){MathJax.typeset()}))}))}}}});export{a as default}; +const t=()=>{let t,e={messageStyle:"none",tex2jax:{inlineMath:[["$","$"],["\\(","\\)"]],skipTags:["script","noscript","style","textarea","pre"]},skipStartupTypeset:!0};return{id:"mathjax2",init:function(a){t=a;let n=t.getConfig().mathjax2||t.getConfig().math||{},i={...e,...n},s=(i.mathjax||"https://cdn.jsdelivr.net/npm/mathjax@2/MathJax.js")+"?config="+(i.config||"TeX-AMS_HTML-full");i.tex2jax={...e.tex2jax,...n.tex2jax},i.mathjax=i.config=null,function(t,e){let a=document.querySelector("head"),n=document.createElement("script");n.type="text/javascript",n.src=t;let i=()=>{"function"==typeof e&&(e.call(),e=null)};n.onload=i,n.onreadystatechange=()=>{"loaded"===this.readyState&&i()},a.appendChild(n)}(s,(function(){MathJax.Hub.Config(i),MathJax.Hub.Queue(["Typeset",MathJax.Hub,t.getRevealElement()]),MathJax.Hub.Queue(t.layout),t.on("slidechanged",(function(t){MathJax.Hub.Queue(["Typeset",MathJax.Hub,t.currentSlide])}))}))}}},e=t; +/*! + * This plugin is a wrapper for the MathJax2, + * MathJax3 and KaTeX typesetter plugins. + */ +var a=Plugin=Object.assign(e(),{KaTeX:()=>{let t,e={version:"latest",delimiters:[{left:"$$",right:"$$",display:!0},{left:"$",right:"$",display:!1},{left:"\\(",right:"\\)",display:!1},{left:"\\[",right:"\\]",display:!0}],ignoredTags:["script","noscript","style","textarea","pre"]};const a=t=>new Promise(((e,a)=>{const n=document.createElement("script");n.type="text/javascript",n.onload=e,n.onerror=a,n.src=t,document.head.append(n)}));return{id:"katex",init:function(n){t=n;let i=t.getConfig().katex||{},s={...e,...i};const{local:l,version:o,extensions:r,...c}=s;let d=s.local||"https://cdn.jsdelivr.net/npm/katex",p=s.local?"":"@"+s.version,u=d+p+"/dist/katex.min.css",h=d+p+"/dist/contrib/mhchem.min.js",x=d+p+"/dist/contrib/auto-render.min.js",m=[d+p+"/dist/katex.min.js"];s.extensions&&s.extensions.includes("mhchem")&&m.push(h),m.push(x);const f=()=>{renderMathInElement(n.getSlidesElement(),c),t.layout()};(t=>{let e=document.createElement("link");e.rel="stylesheet",e.href=t,document.head.appendChild(e)})(u),async function(t){for(const e of t)await a(e)}(m).then((()=>{t.isReady()?f():t.on("ready",f.bind(this))}))}}},MathJax2:t,MathJax3:()=>{let t,e={tex:{inlineMath:[["$","$"],["\\(","\\)"]]},options:{skipHtmlTags:["script","noscript","style","textarea","pre"]},startup:{ready:()=>{MathJax.startup.defaultReady(),MathJax.startup.promise.then((()=>{t.layout()}))}}};return{id:"mathjax3",init:function(a){t=a;let n=t.getConfig().mathjax3||{},i={...e,...n};i.tex={...e.tex,...n.tex},i.options={...e.options,...n.options},i.startup={...e.startup,...n.startup};let s=i.mathjax||"https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js";i.mathjax=null,window.MathJax=i,function(t,e){let a=document.createElement("script");a.type="text/javascript",a.id="MathJax-script",a.src=t,a.async=!0,a.onload=()=>{"function"==typeof e&&(e.call(),e=null)},document.head.appendChild(a)}(s,(function(){t.addEventListener("slidechanged",(function(t){MathJax.typeset()}))}))}}}});export{a as default}; diff --git a/docs/site_libs/revealjs/plugin/math/math.js b/docs/site_libs/revealjs/plugin/math/math.js index ec644bd..d413998 100644 --- a/docs/site_libs/revealjs/plugin/math/math.js +++ b/docs/site_libs/revealjs/plugin/math/math.js @@ -1 +1 @@ -!function(t,e){"object"==typeof exports&&"undefined"!=typeof module?module.exports=e():"function"==typeof define&&define.amd?define(e):(t="undefined"!=typeof globalThis?globalThis:t||self).RevealMath=e()}(this,(function(){"use strict";const t=()=>{let t,e={messageStyle:"none",tex2jax:{inlineMath:[["$","$"],["\\(","\\)"]],skipTags:["script","noscript","style","textarea","pre"]},skipStartupTypeset:!0};return{id:"mathjax2",init:function(n){t=n;let a=t.getConfig().mathjax2||t.getConfig().math||{},i={...e,...a},s=(i.mathjax||"https://cdn.jsdelivr.net/npm/mathjax@2/MathJax.js")+"?config="+(i.config||"TeX-AMS_HTML-full");i.tex2jax={...e.tex2jax,...a.tex2jax},i.mathjax=i.config=null,function(t,e){let n=document.querySelector("head"),a=document.createElement("script");a.type="text/javascript",a.src=t;let i=()=>{"function"==typeof e&&(e.call(),e=null)};a.onload=i,a.onreadystatechange=()=>{"loaded"===this.readyState&&i()},n.appendChild(a)}(s,(function(){MathJax.Hub.Config(i),MathJax.Hub.Queue(["Typeset",MathJax.Hub,t.getRevealElement()]),MathJax.Hub.Queue(t.layout),t.on("slidechanged",(function(t){MathJax.Hub.Queue(["Typeset",MathJax.Hub,t.currentSlide])}))}))}}},e=t;return Plugin=Object.assign(e(),{KaTeX:()=>{let t,e={version:"latest",delimiters:[{left:"$$",right:"$$",display:!0},{left:"$",right:"$",display:!1},{left:"\\(",right:"\\)",display:!1},{left:"\\[",right:"\\]",display:!0}],ignoredTags:["script","noscript","style","textarea","pre"]};const n=t=>new Promise(((e,n)=>{const a=document.createElement("script");a.type="text/javascript",a.onload=e,a.onerror=n,a.src=t,document.head.append(a)}));return{id:"katex",init:function(a){t=a;let i=t.getConfig().katex||{},s={...e,...i};const{local:o,version:l,extensions:r,...c}=s;let d=s.local||"https://cdn.jsdelivr.net/npm/katex",u=s.local?"":"@"+s.version,p=d+u+"/dist/katex.min.css",h=d+u+"/dist/contrib/mhchem.min.js",x=d+u+"/dist/contrib/auto-render.min.js",m=[d+u+"/dist/katex.min.js"];s.extensions&&s.extensions.includes("mhchem")&&m.push(h),m.push(x);const f=()=>{renderMathInElement(a.getSlidesElement(),c),t.layout()};(t=>{let e=document.createElement("link");e.rel="stylesheet",e.href=t,document.head.appendChild(e)})(p),async function(t){for(const e of t)await n(e)}(m).then((()=>{t.isReady()?f():t.on("ready",f.bind(this))}))}}},MathJax2:t,MathJax3:()=>{let t,e={tex:{inlineMath:[["$","$"],["\\(","\\)"]]},options:{skipHtmlTags:["script","noscript","style","textarea","pre"]},startup:{ready:()=>{MathJax.startup.defaultReady(),MathJax.startup.promise.then((()=>{t.layout()}))}}};return{id:"mathjax3",init:function(n){t=n;let a=t.getConfig().mathjax3||{},i={...e,...a};i.tex={...e.tex,...a.tex},i.options={...e.options,...a.options},i.startup={...e.startup,...a.startup};let s=i.mathjax||"https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js";i.mathjax=null,window.MathJax=i,function(t,e){let n=document.createElement("script");n.type="text/javascript",n.id="MathJax-script",n.src=t,n.async=!0,n.onload=()=>{"function"==typeof e&&(e.call(),e=null)},document.head.appendChild(n)}(s,(function(){t.addEventListener("slidechanged",(function(t){MathJax.typeset()}))}))}}}})})); +!function(t,e){"object"==typeof exports&&"undefined"!=typeof module?module.exports=e():"function"==typeof define&&define.amd?define(e):(t="undefined"!=typeof globalThis?globalThis:t||self).RevealMath=e()}(this,(function(){"use strict";const t=()=>{let t,e={messageStyle:"none",tex2jax:{inlineMath:[["$","$"],["\\(","\\)"]],skipTags:["script","noscript","style","textarea","pre"]},skipStartupTypeset:!0};return{id:"mathjax2",init:function(n){t=n;let a=t.getConfig().mathjax2||t.getConfig().math||{},i={...e,...a},s=(i.mathjax||"https://cdn.jsdelivr.net/npm/mathjax@2/MathJax.js")+"?config="+(i.config||"TeX-AMS_HTML-full");i.tex2jax={...e.tex2jax,...a.tex2jax},i.mathjax=i.config=null,function(t,e){let n=document.querySelector("head"),a=document.createElement("script");a.type="text/javascript",a.src=t;let i=()=>{"function"==typeof e&&(e.call(),e=null)};a.onload=i,a.onreadystatechange=()=>{"loaded"===this.readyState&&i()},n.appendChild(a)}(s,(function(){MathJax.Hub.Config(i),MathJax.Hub.Queue(["Typeset",MathJax.Hub,t.getRevealElement()]),MathJax.Hub.Queue(t.layout),t.on("slidechanged",(function(t){MathJax.Hub.Queue(["Typeset",MathJax.Hub,t.currentSlide])}))}))}}},e=t;return Plugin=Object.assign(e(),{KaTeX:()=>{let t,e={version:"latest",delimiters:[{left:"$$",right:"$$",display:!0},{left:"$",right:"$",display:!1},{left:"\\(",right:"\\)",display:!1},{left:"\\[",right:"\\]",display:!0}],ignoredTags:["script","noscript","style","textarea","pre"]};const n=t=>new Promise(((e,n)=>{const a=document.createElement("script");a.type="text/javascript",a.onload=e,a.onerror=n,a.src=t,document.head.append(a)}));return{id:"katex",init:function(a){t=a;let i=t.getConfig().katex||{},s={...e,...i};const{local:o,version:l,extensions:r,...c}=s;let d=s.local||"https://cdn.jsdelivr.net/npm/katex",u=s.local?"":"@"+s.version,p=d+u+"/dist/katex.min.css",h=d+u+"/dist/contrib/mhchem.min.js",x=d+u+"/dist/contrib/auto-render.min.js",m=[d+u+"/dist/katex.min.js"];s.extensions&&s.extensions.includes("mhchem")&&m.push(h),m.push(x);const f=()=>{renderMathInElement(a.getSlidesElement(),c),t.layout()};(t=>{let e=document.createElement("link");e.rel="stylesheet",e.href=t,document.head.appendChild(e)})(p),async function(t){for(const e of t)await n(e)}(m).then((()=>{t.isReady()?f():t.on("ready",f.bind(this))}))}}},MathJax2:t,MathJax3:()=>{let t,e={tex:{inlineMath:[["$","$"],["\\(","\\)"]]},options:{skipHtmlTags:["script","noscript","style","textarea","pre"]},startup:{ready:()=>{MathJax.startup.defaultReady(),MathJax.startup.promise.then((()=>{t.layout()}))}}};return{id:"mathjax3",init:function(n){t=n;let a=t.getConfig().mathjax3||{},i={...e,...a};i.tex={...e.tex,...a.tex},i.options={...e.options,...a.options},i.startup={...e.startup,...a.startup};let s=i.mathjax||"https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js";i.mathjax=null,window.MathJax=i,function(t,e){let n=document.createElement("script");n.type="text/javascript",n.id="MathJax-script",n.src=t,n.async=!0,n.onload=()=>{"function"==typeof e&&(e.call(),e=null)},document.head.appendChild(n)}(s,(function(){t.addEventListener("slidechanged",(function(t){MathJax.typeset()}))}))}}}})})); diff --git a/docs/site_libs/revealjs/plugin/math/mathjax2.js b/docs/site_libs/revealjs/plugin/math/mathjax2.js index daebe7e..3a698e0 100644 --- a/docs/site_libs/revealjs/plugin/math/mathjax2.js +++ b/docs/site_libs/revealjs/plugin/math/mathjax2.js @@ -1,89 +1,89 @@ -/** - * A plugin which enables rendering of math equations inside - * of reveal.js slides. Essentially a thin wrapper for MathJax. - * - * @author Hakim El Hattab - */ -export const MathJax2 = () => { - - // The reveal.js instance this plugin is attached to - let deck; - - let defaultOptions = { - messageStyle: 'none', - tex2jax: { - inlineMath: [ [ '$', '$' ], [ '\\(', '\\)' ] ], - skipTags: [ 'script', 'noscript', 'style', 'textarea', 'pre' ] - }, - skipStartupTypeset: true - }; - - function loadScript( url, callback ) { - - let head = document.querySelector( 'head' ); - let script = document.createElement( 'script' ); - script.type = 'text/javascript'; - script.src = url; - - // Wrapper for callback to make sure it only fires once - let finish = () => { - if( typeof callback === 'function' ) { - callback.call(); - callback = null; - } - } - - script.onload = finish; - - // IE - script.onreadystatechange = () => { - if ( this.readyState === 'loaded' ) { - finish(); - } - } - - // Normal browsers - head.appendChild( script ); - - } - - return { - id: 'mathjax2', - - init: function( reveal ) { - - deck = reveal; - - let revealOptions = deck.getConfig().mathjax2 || deck.getConfig().math || {}; - - let options = { ...defaultOptions, ...revealOptions }; - let mathjax = options.mathjax || 'https://cdn.jsdelivr.net/npm/mathjax@2/MathJax.js'; - let config = options.config || 'TeX-AMS_HTML-full'; - let url = mathjax + '?config=' + config; - - options.tex2jax = { ...defaultOptions.tex2jax, ...revealOptions.tex2jax }; - - options.mathjax = options.config = null; - - loadScript( url, function() { - - MathJax.Hub.Config( options ); - - // Typeset followed by an immediate reveal.js layout since - // the typesetting process could affect slide height - MathJax.Hub.Queue( [ 'Typeset', MathJax.Hub, deck.getRevealElement() ] ); - MathJax.Hub.Queue( deck.layout ); - - // Reprocess equations in slides when they turn visible - deck.on( 'slidechanged', function( event ) { - - MathJax.Hub.Queue( [ 'Typeset', MathJax.Hub, event.currentSlide ] ); - - } ); - - } ); - - } - } - -}; +/** + * A plugin which enables rendering of math equations inside + * of reveal.js slides. Essentially a thin wrapper for MathJax. + * + * @author Hakim El Hattab + */ +export const MathJax2 = () => { + + // The reveal.js instance this plugin is attached to + let deck; + + let defaultOptions = { + messageStyle: 'none', + tex2jax: { + inlineMath: [ [ '$', '$' ], [ '\\(', '\\)' ] ], + skipTags: [ 'script', 'noscript', 'style', 'textarea', 'pre' ] + }, + skipStartupTypeset: true + }; + + function loadScript( url, callback ) { + + let head = document.querySelector( 'head' ); + let script = document.createElement( 'script' ); + script.type = 'text/javascript'; + script.src = url; + + // Wrapper for callback to make sure it only fires once + let finish = () => { + if( typeof callback === 'function' ) { + callback.call(); + callback = null; + } + } + + script.onload = finish; + + // IE + script.onreadystatechange = () => { + if ( this.readyState === 'loaded' ) { + finish(); + } + } + + // Normal browsers + head.appendChild( script ); + + } + + return { + id: 'mathjax2', + + init: function( reveal ) { + + deck = reveal; + + let revealOptions = deck.getConfig().mathjax2 || deck.getConfig().math || {}; + + let options = { ...defaultOptions, ...revealOptions }; + let mathjax = options.mathjax || 'https://cdn.jsdelivr.net/npm/mathjax@2/MathJax.js'; + let config = options.config || 'TeX-AMS_HTML-full'; + let url = mathjax + '?config=' + config; + + options.tex2jax = { ...defaultOptions.tex2jax, ...revealOptions.tex2jax }; + + options.mathjax = options.config = null; + + loadScript( url, function() { + + MathJax.Hub.Config( options ); + + // Typeset followed by an immediate reveal.js layout since + // the typesetting process could affect slide height + MathJax.Hub.Queue( [ 'Typeset', MathJax.Hub, deck.getRevealElement() ] ); + MathJax.Hub.Queue( deck.layout ); + + // Reprocess equations in slides when they turn visible + deck.on( 'slidechanged', function( event ) { + + MathJax.Hub.Queue( [ 'Typeset', MathJax.Hub, event.currentSlide ] ); + + } ); + + } ); + + } + } + +}; diff --git a/docs/site_libs/revealjs/plugin/math/mathjax3.js b/docs/site_libs/revealjs/plugin/math/mathjax3.js index 767129c..8f755bc 100644 --- a/docs/site_libs/revealjs/plugin/math/mathjax3.js +++ b/docs/site_libs/revealjs/plugin/math/mathjax3.js @@ -1,77 +1,77 @@ -/** - * A plugin which enables rendering of math equations inside - * of reveal.js slides. Essentially a thin wrapper for MathJax 3 - * - * @author Hakim El Hattab - * @author Gerhard Burger - */ -export const MathJax3 = () => { - - // The reveal.js instance this plugin is attached to - let deck; - - let defaultOptions = { - tex: { - inlineMath: [ [ '$', '$' ], [ '\\(', '\\)' ] ] - }, - options: { - skipHtmlTags: [ 'script', 'noscript', 'style', 'textarea', 'pre' ] - }, - startup: { - ready: () => { - MathJax.startup.defaultReady(); - MathJax.startup.promise.then(() => { - deck.layout(); - }); - } - } - }; - - function loadScript( url, callback ) { - - let script = document.createElement( 'script' ); - script.type = "text/javascript" - script.id = "MathJax-script" - script.src = url; - script.async = true - - // Wrapper for callback to make sure it only fires once - script.onload = () => { - if (typeof callback === 'function') { - callback.call(); - callback = null; - } - }; - - document.head.appendChild( script ); - - } - - return { - id: 'mathjax3', - init: function(reveal) { - - deck = reveal; - - let revealOptions = deck.getConfig().mathjax3 || {}; - let options = {...defaultOptions, ...revealOptions}; - options.tex = {...defaultOptions.tex, ...revealOptions.tex} - options.options = {...defaultOptions.options, ...revealOptions.options} - options.startup = {...defaultOptions.startup, ...revealOptions.startup} - - let url = options.mathjax || 'https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js'; - options.mathjax = null; - - window.MathJax = options; - - loadScript( url, function() { - // Reprocess equations in slides when they turn visible - deck.addEventListener( 'slidechanged', function( event ) { - MathJax.typeset(); - } ); - } ); - - } - } - -}; +/** + * A plugin which enables rendering of math equations inside + * of reveal.js slides. Essentially a thin wrapper for MathJax 3 + * + * @author Hakim El Hattab + * @author Gerhard Burger + */ +export const MathJax3 = () => { + + // The reveal.js instance this plugin is attached to + let deck; + + let defaultOptions = { + tex: { + inlineMath: [ [ '$', '$' ], [ '\\(', '\\)' ] ] + }, + options: { + skipHtmlTags: [ 'script', 'noscript', 'style', 'textarea', 'pre' ] + }, + startup: { + ready: () => { + MathJax.startup.defaultReady(); + MathJax.startup.promise.then(() => { + deck.layout(); + }); + } + } + }; + + function loadScript( url, callback ) { + + let script = document.createElement( 'script' ); + script.type = "text/javascript" + script.id = "MathJax-script" + script.src = url; + script.async = true + + // Wrapper for callback to make sure it only fires once + script.onload = () => { + if (typeof callback === 'function') { + callback.call(); + callback = null; + } + }; + + document.head.appendChild( script ); + + } + + return { + id: 'mathjax3', + init: function(reveal) { + + deck = reveal; + + let revealOptions = deck.getConfig().mathjax3 || {}; + let options = {...defaultOptions, ...revealOptions}; + options.tex = {...defaultOptions.tex, ...revealOptions.tex} + options.options = {...defaultOptions.options, ...revealOptions.options} + options.startup = {...defaultOptions.startup, ...revealOptions.startup} + + let url = options.mathjax || 'https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js'; + options.mathjax = null; + + window.MathJax = options; + + loadScript( url, function() { + // Reprocess equations in slides when they turn visible + deck.addEventListener( 'slidechanged', function( event ) { + MathJax.typeset(); + } ); + } ); + + } + } + +}; diff --git a/docs/site_libs/revealjs/plugin/math/plugin.js b/docs/site_libs/revealjs/plugin/math/plugin.js index a92ccfb..5237aa1 100644 --- a/docs/site_libs/revealjs/plugin/math/plugin.js +++ b/docs/site_libs/revealjs/plugin/math/plugin.js @@ -1,15 +1,15 @@ -import {KaTeX} from 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    Loading speaker view...
    \n\n\t\t
    \n\t\t
    Upcoming
    \n\t\t
    \n\t\t\t
    \n\t\t\t\t

    Time Click to Reset

    \n\t\t\t\t
    \n\t\t\t\t\t0:00 AM\n\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t00:00:00\n\t\t\t\t
    \n\t\t\t\t
    \n\n\t\t\t\t

    Pacing – Time to finish current slide

    \n\t\t\t\t
    \n\t\t\t\t\t00:00:00\n\t\t\t\t
    \n\t\t\t
    \n\n\t\t\t
    \n\t\t\t\t

    Notes

    \n\t\t\t\t
    \n\t\t\t
    \n\t\t
    \n\t\t
    \n\t\t\t\n\t\t\t\n\t\t
    \n\n\t\t - + + + + + + reveal.js - Speaker View + + + + + + +
    Loading speaker view...
    + +
    +
    Upcoming
    +
    +
    +

    Time Click to Reset

    +
    + 0:00 AM +
    +
    + 00:00:00 +
    +
    + + + +
    + + +
    +
    + + +
    + + + \ No newline at end of file diff --git a/docs/site_libs/revealjs/plugin/pdf-export/pdfexport.js b/docs/site_libs/revealjs/plugin/pdf-export/pdfexport.js index 0cf0bd7..5b2a2ea 100644 --- a/docs/site_libs/revealjs/plugin/pdf-export/pdfexport.js +++ b/docs/site_libs/revealjs/plugin/pdf-export/pdfexport.js @@ -1,115 +1,115 @@ -var PdfExport = ( function( _Reveal ){ - - var Reveal = _Reveal; - var setStylesheet = null; - var installAltKeyBindings = null; - - function getRevealJsPath(){ - var regex = /\b[^/]+\/reveal.css$/i; - var script = Array.from( document.querySelectorAll( 'link' ) ).find( function( e ){ - return e.attributes.href && e.attributes.href.value.search( regex ) >= 0; - }); - if( !script ){ - console.error( 'reveal.css could not be found in included elements. Did you rename this file?' ); - return ''; - } - return script.attributes.href.value.replace( regex, '' ); - } - - function setStylesheet3( pdfExport ){ - var link = document.querySelector( '#print' ); - if( !link ){ - link = document.createElement( 'link' ); - link.rel = 'stylesheet'; - link.id = 'print'; - document.querySelector( 'head' ).appendChild( link ); - } - var style = 'paper'; - if( pdfExport ){ - style = 'pdf'; - } - link.href = getRevealJsPath() + 'css/print/' + style + '.css'; - } - - function setStylesheet4( pdfExport ){ - } - - function installAltKeyBindings3(){ - } - - function installAltKeyBindings4(){ - if( isPrintingPDF() ){ - var config = Reveal.getConfig(); - var shortcut = config.pdfExportShortcut || 'E'; - window.addEventListener( 'keydown', function( e ){ - if( e.target.nodeName.toUpperCase() == 'BODY' - && ( e.key.toUpperCase() == shortcut.toUpperCase() || e.keyCode == shortcut.toUpperCase().charCodeAt( 0 ) ) ){ - e.preventDefault(); - togglePdfExport(); - return false; - } - }, true ); - } - } - - function isPrintingPDF(){ - return /print-pdf/gi.test(window.location.search) || /view=print/gi.test(window.location.search); - } - - function togglePdfExport(){ - var url_doc = new URL( document.URL ); - var query_doc = new URLSearchParams( url_doc.searchParams ); - if( isPrintingPDF() ){ - if (query_doc.has('print-pdf')) { - query_doc.delete('print-pdf'); - } else if (query_doc.has('view')) { - query_doc.delete('view'); - } - }else{ - query_doc.set( 'view', 'print' ); - } - url_doc.search = ( query_doc.toString() ? '?' + query_doc.toString() : '' ); - window.location.href = url_doc.toString(); - } - - function installKeyBindings(){ - var config = Reveal.getConfig(); - var shortcut = config.pdfExportShortcut || 'E'; - Reveal.addKeyBinding({ - keyCode: shortcut.toUpperCase().charCodeAt( 0 ), - key: shortcut.toUpperCase(), - description: 'PDF export mode' - }, togglePdfExport ); - installAltKeyBindings(); - } - - function install(){ - installKeyBindings(); - setStylesheet( isPrintingPDF() ); - } - - var Plugin = { - } - - if( Reveal && Reveal.VERSION && Reveal.VERSION.length && Reveal.VERSION[ 0 ] == '3' ){ - // reveal 3.x - setStylesheet = setStylesheet3; - installAltKeyBindings = installAltKeyBindings3; - install(); - }else{ - // must be reveal 4.x - setStylesheet = setStylesheet4; - installAltKeyBindings = installAltKeyBindings4; - Plugin.id = 'pdf-export'; - Plugin.init = function( _Reveal ){ - Reveal = _Reveal; - install(); - }; - Plugin.togglePdfExport = function () { - togglePdfExport(); - }; - } - - return Plugin; - -})( Reveal ); +var PdfExport = ( function( _Reveal ){ + + var Reveal = _Reveal; + var setStylesheet = null; + var installAltKeyBindings = null; + + function getRevealJsPath(){ + var regex = /\b[^/]+\/reveal.css$/i; + var script = Array.from( document.querySelectorAll( 'link' ) ).find( function( e ){ + return e.attributes.href && e.attributes.href.value.search( regex ) >= 0; + }); + if( !script ){ + console.error( 'reveal.css could not be found in included elements. Did you rename this file?' ); + return ''; + } + return script.attributes.href.value.replace( regex, '' ); + } + + function setStylesheet3( pdfExport ){ + var link = document.querySelector( '#print' ); + if( !link ){ + link = document.createElement( 'link' ); + link.rel = 'stylesheet'; + link.id = 'print'; + document.querySelector( 'head' ).appendChild( link ); + } + var style = 'paper'; + if( pdfExport ){ + style = 'pdf'; + } + link.href = getRevealJsPath() + 'css/print/' + style + '.css'; + } + + function setStylesheet4( pdfExport ){ + } + + function installAltKeyBindings3(){ + } + + function installAltKeyBindings4(){ + if( isPrintingPDF() ){ + var config = Reveal.getConfig(); + var shortcut = config.pdfExportShortcut || 'E'; + window.addEventListener( 'keydown', function( e ){ + if( e.target.nodeName.toUpperCase() == 'BODY' + && ( e.key.toUpperCase() == shortcut.toUpperCase() || e.keyCode == shortcut.toUpperCase().charCodeAt( 0 ) ) ){ + e.preventDefault(); + togglePdfExport(); + return false; + } + }, true ); + } + } + + function isPrintingPDF(){ + return /print-pdf/gi.test(window.location.search) || /view=print/gi.test(window.location.search); + } + + function togglePdfExport(){ + var url_doc = new URL( document.URL ); + var query_doc = new URLSearchParams( url_doc.searchParams ); + if( isPrintingPDF() ){ + if (query_doc.has('print-pdf')) { + query_doc.delete('print-pdf'); + } else if (query_doc.has('view')) { + query_doc.delete('view'); + } + }else{ + query_doc.set( 'view', 'print' ); + } + url_doc.search = ( query_doc.toString() ? '?' + query_doc.toString() : '' ); + window.location.href = url_doc.toString(); + } + + function installKeyBindings(){ + var config = Reveal.getConfig(); + var shortcut = config.pdfExportShortcut || 'E'; + Reveal.addKeyBinding({ + keyCode: shortcut.toUpperCase().charCodeAt( 0 ), + key: shortcut.toUpperCase(), + description: 'PDF export mode' + }, togglePdfExport ); + installAltKeyBindings(); + } + + function install(){ + installKeyBindings(); + setStylesheet( isPrintingPDF() ); + } + + var Plugin = { + } + + if( Reveal && Reveal.VERSION && Reveal.VERSION.length && Reveal.VERSION[ 0 ] == '3' ){ + // reveal 3.x + setStylesheet = setStylesheet3; + installAltKeyBindings = installAltKeyBindings3; + install(); + }else{ + // must be reveal 4.x + setStylesheet = setStylesheet4; + installAltKeyBindings = installAltKeyBindings4; + Plugin.id = 'pdf-export'; + Plugin.init = function( _Reveal ){ + Reveal = _Reveal; + install(); + }; + Plugin.togglePdfExport = function () { + togglePdfExport(); + }; + } + + return Plugin; + +})( Reveal ); diff --git a/docs/site_libs/revealjs/plugin/pdf-export/plugin.yml b/docs/site_libs/revealjs/plugin/pdf-export/plugin.yml index f6db9d0..aa4b61d 100644 --- a/docs/site_libs/revealjs/plugin/pdf-export/plugin.yml +++ b/docs/site_libs/revealjs/plugin/pdf-export/plugin.yml @@ -1,2 +1,2 @@ -name: PdfExport -script: pdfexport.js +name: PdfExport +script: pdfexport.js diff --git a/docs/site_libs/revealjs/plugin/quarto-line-highlight/line-highlight.css b/docs/site_libs/revealjs/plugin/quarto-line-highlight/line-highlight.css index e8410fe..676e51a 100644 --- a/docs/site_libs/revealjs/plugin/quarto-line-highlight/line-highlight.css +++ b/docs/site_libs/revealjs/plugin/quarto-line-highlight/line-highlight.css @@ -1,31 +1,31 @@ -.reveal - div.sourceCode - pre - code.has-line-highlights - > span:not(.highlight-line) { - opacity: 0.4; -} - -.reveal pre.numberSource { - padding-left: 0; -} - -.reveal pre.numberSource code > span { - left: -2.1em; -} - -pre.numberSource code > span > a:first-child::before { - left: -0.7em; -} - -.reveal pre > code:not(:first-child).fragment { - position: absolute; - top: 0; - left: 0; - width: 100%; - box-sizing: border-box; -} - -.reveal div.sourceCode pre code { - min-height: 100%; -} +.reveal + div.sourceCode + pre + code.has-line-highlights + > span:not(.highlight-line) { + opacity: 0.4; +} + +.reveal pre.numberSource { + padding-left: 0; +} + +.reveal pre.numberSource code > span { + left: -2.1em; +} + +pre.numberSource code > span > a:first-child::before { + left: -0.7em; +} + +.reveal pre > code:not(:first-child).fragment { + position: absolute; + top: 0; + left: 0; + width: 100%; + box-sizing: border-box; +} + +.reveal div.sourceCode pre code { + min-height: 100%; +} diff --git a/docs/site_libs/revealjs/plugin/quarto-line-highlight/line-highlight.js b/docs/site_libs/revealjs/plugin/quarto-line-highlight/line-highlight.js index 16a3893..cd77107 100644 --- a/docs/site_libs/revealjs/plugin/quarto-line-highlight/line-highlight.js +++ b/docs/site_libs/revealjs/plugin/quarto-line-highlight/line-highlight.js @@ -1,351 +1,351 @@ -window.QuartoLineHighlight = function () { - function isPrintView() { - return /print-pdf/gi.test(window.location.search) || /view=print/gi.test(window.location.search); - } - - const delimiters = { - step: "|", - line: ",", - lineRange: "-", - }; - - const regex = new RegExp( - "^[\\d" + Object.values(delimiters).join("") + "]+$" - ); - - function handleLinesSelector(deck, attr) { - // if we are in printview with pdfSeparateFragments: false - // then we'll also want to supress - if (regex.test(attr)) { - if (isPrintView() && deck.getConfig().pdfSeparateFragments !== true) { - return false; - } else { - return true; - } - } else { - return false; - } - } - - const kCodeLineNumbersAttr = "data-code-line-numbers"; - const kFragmentIndex = "data-fragment-index"; - - function initQuartoLineHighlight(deck) { - const divSourceCode = deck - .getRevealElement() - .querySelectorAll("div.sourceCode"); - // Process each div created by Pandoc highlighting - numbered line are already included. - divSourceCode.forEach((el) => { - if (el.hasAttribute(kCodeLineNumbersAttr)) { - const codeLineAttr = el.getAttribute(kCodeLineNumbersAttr); - el.removeAttribute(kCodeLineNumbersAttr); - if (handleLinesSelector(deck, codeLineAttr)) { - // Only process if attr is a string to select lines to highlights - // e.g "1|3,6|8-11" - const codeBlock = el.querySelectorAll("pre code"); - codeBlock.forEach((code) => { - // move attributes on code block - code.setAttribute(kCodeLineNumbersAttr, codeLineAttr); - - const scrollState = { currentBlock: code }; - - // Check if there are steps and duplicate code block accordingly - const highlightSteps = splitLineNumbers(codeLineAttr); - if (highlightSteps.length > 1) { - // If the original code block has a fragment-index, - // each clone should follow in an incremental sequence - let fragmentIndex = parseInt( - code.getAttribute(kFragmentIndex), - 10 - ); - fragmentIndex = - typeof fragmentIndex !== "number" || isNaN(fragmentIndex) - ? null - : fragmentIndex; - - let stepN = 1; - highlightSteps.slice(1).forEach( - // Generate fragments for all steps except the original block - (step) => { - var fragmentBlock = code.cloneNode(true); - fragmentBlock.setAttribute( - "data-code-line-numbers", - joinLineNumbers([step]) - ); - fragmentBlock.classList.add("fragment"); - - // Pandoc sets id on spans we need to keep unique - fragmentBlock - .querySelectorAll(":scope > span") - .forEach((span) => { - if (span.hasAttribute("id")) { - span.setAttribute( - "id", - span.getAttribute("id").concat("-" + stepN) - ); - } - }); - stepN = ++stepN; - - // Add duplicated element after existing one - code.parentNode.appendChild(fragmentBlock); - - // Each new element is highlighted based on the new attributes value - highlightCodeBlock(fragmentBlock); - - if (typeof fragmentIndex === "number") { - fragmentBlock.setAttribute(kFragmentIndex, fragmentIndex); - fragmentIndex += 1; - } else { - fragmentBlock.removeAttribute(kFragmentIndex); - } - - // Scroll highlights into view as we step through them - fragmentBlock.addEventListener( - "visible", - scrollHighlightedLineIntoView.bind( - this, - fragmentBlock, - scrollState - ) - ); - fragmentBlock.addEventListener( - "hidden", - scrollHighlightedLineIntoView.bind( - this, - fragmentBlock.previousSibling, - scrollState - ) - ); - } - ); - code.removeAttribute(kFragmentIndex); - code.setAttribute( - kCodeLineNumbersAttr, - joinLineNumbers([highlightSteps[0]]) - ); - } - - // Scroll the first highlight into view when the slide becomes visible. - const slide = - typeof code.closest === "function" - ? code.closest("section:not(.stack)") - : null; - if (slide) { - const scrollFirstHighlightIntoView = function () { - scrollHighlightedLineIntoView(code, scrollState, true); - slide.removeEventListener( - "visible", - scrollFirstHighlightIntoView - ); - }; - slide.addEventListener("visible", scrollFirstHighlightIntoView); - } - - highlightCodeBlock(code); - }); - } - } - }); - } - - function highlightCodeBlock(codeBlock) { - const highlightSteps = splitLineNumbers( - codeBlock.getAttribute(kCodeLineNumbersAttr) - ); - - if (highlightSteps.length) { - // If we have at least one step, we generate fragments - highlightSteps[0].forEach((highlight) => { - // Add expected class on 
     for reveal CSS
-        codeBlock.parentNode.classList.add("code-wrapper");
-
-        // Select lines to highlight
-        spanToHighlight = [];
-        if (typeof highlight.last === "number") {
-          spanToHighlight = [].slice.call(
-            codeBlock.querySelectorAll(
-              ":scope > span:nth-of-type(n+" +
-                highlight.first +
-                "):nth-of-type(-n+" +
-                highlight.last +
-                ")"
-            )
-          );
-        } else if (typeof highlight.first === "number") {
-          spanToHighlight = [].slice.call(
-            codeBlock.querySelectorAll(
-              ":scope > span:nth-of-type(" + highlight.first + ")"
-            )
-          );
-        }
-        if (spanToHighlight.length) {
-          // Add a class on  and  to select line to highlight
-          spanToHighlight.forEach((span) =>
-            span.classList.add("highlight-line")
-          );
-          codeBlock.classList.add("has-line-highlights");
-        }
-      });
-    }
-  }
-
-  /**
-   * Animates scrolling to the first highlighted line
-   * in the given code block.
-   */
-  function scrollHighlightedLineIntoView(block, scrollState, skipAnimation) {
-    window.cancelAnimationFrame(scrollState.animationFrameID);
-
-    // Match the scroll position of the currently visible
-    // code block
-    if (scrollState.currentBlock) {
-      block.scrollTop = scrollState.currentBlock.scrollTop;
-    }
-
-    // Remember the current code block so that we can match
-    // its scroll position when showing/hiding fragments
-    scrollState.currentBlock = block;
-
-    const highlightBounds = getHighlightedLineBounds(block);
-    let viewportHeight = block.offsetHeight;
-
-    // Subtract padding from the viewport height
-    const blockStyles = window.getComputedStyle(block);
-    viewportHeight -=
-      parseInt(blockStyles.paddingTop) + parseInt(blockStyles.paddingBottom);
-
-    // Scroll position which centers all highlights
-    const startTop = block.scrollTop;
-    let targetTop =
-      highlightBounds.top +
-      (Math.min(highlightBounds.bottom - highlightBounds.top, viewportHeight) -
-        viewportHeight) /
-        2;
-
-    // Make sure the scroll target is within bounds
-    targetTop = Math.max(
-      Math.min(targetTop, block.scrollHeight - viewportHeight),
-      0
-    );
-
-    if (skipAnimation === true || startTop === targetTop) {
-      block.scrollTop = targetTop;
-    } else {
-      // Don't attempt to scroll if there is no overflow
-      if (block.scrollHeight <= viewportHeight) return;
-
-      let time = 0;
-
-      const animate = function () {
-        time = Math.min(time + 0.02, 1);
-
-        // Update our eased scroll position
-        block.scrollTop =
-          startTop + (targetTop - startTop) * easeInOutQuart(time);
-
-        // Keep animating unless we've reached the end
-        if (time < 1) {
-          scrollState.animationFrameID = requestAnimationFrame(animate);
-        }
-      };
-
-      animate();
-    }
-  }
-
-  function getHighlightedLineBounds(block) {
-    const highlightedLines = block.querySelectorAll(".highlight-line");
-    if (highlightedLines.length === 0) {
-      return { top: 0, bottom: 0 };
-    } else {
-      const firstHighlight = highlightedLines[0];
-      const lastHighlight = highlightedLines[highlightedLines.length - 1];
-
-      return {
-        top: firstHighlight.offsetTop,
-        bottom: lastHighlight.offsetTop + lastHighlight.offsetHeight,
-      };
-    }
-  }
-
-  /**
-   * The easing function used when scrolling.
-   */
-  function easeInOutQuart(t) {
-    // easeInOutQuart
-    return t < 0.5 ? 8 * t * t * t * t : 1 - 8 * --t * t * t * t;
-  }
-
-  function splitLineNumbers(lineNumbersAttr) {
-    // remove space
-    lineNumbersAttr = lineNumbersAttr.replace("/s/g", "");
-    // seperate steps (for fragment)
-    lineNumbersAttr = lineNumbersAttr.split(delimiters.step);
-
-    // for each step, calculate first and last line, if any
-    return lineNumbersAttr.map((highlights) => {
-      // detect lines
-      const lines = highlights.split(delimiters.line);
-      return lines.map((range) => {
-        if (/^[\d-]+$/.test(range)) {
-          range = range.split(delimiters.lineRange);
-          const firstLine = parseInt(range[0], 10);
-          const lastLine = range[1] ? parseInt(range[1], 10) : undefined;
-          return {
-            first: firstLine,
-            last: lastLine,
-          };
-        } else {
-          return {};
-        }
-      });
-    });
-  }
-
-  function joinLineNumbers(splittedLineNumbers) {
-    return splittedLineNumbers
-      .map(function (highlights) {
-        return highlights
-          .map(function (highlight) {
-            // Line range
-            if (typeof highlight.last === "number") {
-              return highlight.first + delimiters.lineRange + highlight.last;
-            }
-            // Single line
-            else if (typeof highlight.first === "number") {
-              return highlight.first;
-            }
-            // All lines
-            else {
-              return "";
-            }
-          })
-          .join(delimiters.line);
-      })
-      .join(delimiters.step);
-  }
-
-  return {
-    id: "quarto-line-highlight",
-    init: function (deck) {
-      initQuartoLineHighlight(deck);
-
-      // If we're printing to PDF, scroll the code highlights of
-      // all blocks in the deck into view at once
-      deck.on("pdf-ready", function () {
-        [].slice
-          .call(
-            deck
-              .getRevealElement()
-              .querySelectorAll(
-                "pre code[data-code-line-numbers].current-fragment"
-              )
-          )
-          .forEach(function (block) {
-            scrollHighlightedLineIntoView(block, {}, true);
-          });
-      });
-    },
-  };
-};
+window.QuartoLineHighlight = function () {
+  function isPrintView() {
+    return /print-pdf/gi.test(window.location.search) || /view=print/gi.test(window.location.search);
+  }
+
+  const delimiters = {
+    step: "|",
+    line: ",",
+    lineRange: "-",
+  };
+
+  const regex = new RegExp(
+    "^[\\d" + Object.values(delimiters).join("") + "]+$"
+  );
+
+  function handleLinesSelector(deck, attr) {
+    // if we are in printview with pdfSeparateFragments: false
+    // then we'll also want to supress
+    if (regex.test(attr)) {
+      if (isPrintView() && deck.getConfig().pdfSeparateFragments !== true) {
+        return false;
+      } else {
+        return true;
+      }
+    } else {
+      return false;
+    }
+  }
+
+  const kCodeLineNumbersAttr = "data-code-line-numbers";
+  const kFragmentIndex = "data-fragment-index";
+
+  function initQuartoLineHighlight(deck) {
+    const divSourceCode = deck
+      .getRevealElement()
+      .querySelectorAll("div.sourceCode");
+    // Process each div created by Pandoc highlighting - numbered line are already included.
+    divSourceCode.forEach((el) => {
+      if (el.hasAttribute(kCodeLineNumbersAttr)) {
+        const codeLineAttr = el.getAttribute(kCodeLineNumbersAttr);
+        el.removeAttribute(kCodeLineNumbersAttr);
+        if (handleLinesSelector(deck, codeLineAttr)) {
+          // Only process if attr is a string to select lines to highlights
+          // e.g "1|3,6|8-11"
+          const codeBlock = el.querySelectorAll("pre code");
+          codeBlock.forEach((code) => {
+            // move attributes on code block
+            code.setAttribute(kCodeLineNumbersAttr, codeLineAttr);
+
+            const scrollState = { currentBlock: code };
+
+            // Check if there are steps and duplicate code block accordingly
+            const highlightSteps = splitLineNumbers(codeLineAttr);
+            if (highlightSteps.length > 1) {
+              // If the original code block has a fragment-index,
+              // each clone should follow in an incremental sequence
+              let fragmentIndex = parseInt(
+                code.getAttribute(kFragmentIndex),
+                10
+              );
+              fragmentIndex =
+                typeof fragmentIndex !== "number" || isNaN(fragmentIndex)
+                  ? null
+                  : fragmentIndex;
+
+              let stepN = 1;
+              highlightSteps.slice(1).forEach(
+                // Generate fragments for all steps except the original block
+                (step) => {
+                  var fragmentBlock = code.cloneNode(true);
+                  fragmentBlock.setAttribute(
+                    "data-code-line-numbers",
+                    joinLineNumbers([step])
+                  );
+                  fragmentBlock.classList.add("fragment");
+
+                  // Pandoc sets id on spans we need to keep unique
+                  fragmentBlock
+                    .querySelectorAll(":scope > span")
+                    .forEach((span) => {
+                      if (span.hasAttribute("id")) {
+                        span.setAttribute(
+                          "id",
+                          span.getAttribute("id").concat("-" + stepN)
+                        );
+                      }
+                    });
+                  stepN = ++stepN;
+
+                  // Add duplicated  element after existing one
+                  code.parentNode.appendChild(fragmentBlock);
+
+                  // Each new  element is highlighted based on the new attributes value
+                  highlightCodeBlock(fragmentBlock);
+
+                  if (typeof fragmentIndex === "number") {
+                    fragmentBlock.setAttribute(kFragmentIndex, fragmentIndex);
+                    fragmentIndex += 1;
+                  } else {
+                    fragmentBlock.removeAttribute(kFragmentIndex);
+                  }
+
+                  // Scroll highlights into view as we step through them
+                  fragmentBlock.addEventListener(
+                    "visible",
+                    scrollHighlightedLineIntoView.bind(
+                      this,
+                      fragmentBlock,
+                      scrollState
+                    )
+                  );
+                  fragmentBlock.addEventListener(
+                    "hidden",
+                    scrollHighlightedLineIntoView.bind(
+                      this,
+                      fragmentBlock.previousSibling,
+                      scrollState
+                    )
+                  );
+                }
+              );
+              code.removeAttribute(kFragmentIndex);
+              code.setAttribute(
+                kCodeLineNumbersAttr,
+                joinLineNumbers([highlightSteps[0]])
+              );
+            }
+
+            // Scroll the first highlight into view when the slide becomes visible.
+            const slide =
+              typeof code.closest === "function"
+                ? code.closest("section:not(.stack)")
+                : null;
+            if (slide) {
+              const scrollFirstHighlightIntoView = function () {
+                scrollHighlightedLineIntoView(code, scrollState, true);
+                slide.removeEventListener(
+                  "visible",
+                  scrollFirstHighlightIntoView
+                );
+              };
+              slide.addEventListener("visible", scrollFirstHighlightIntoView);
+            }
+
+            highlightCodeBlock(code);
+          });
+        }
+      }
+    });
+  }
+
+  function highlightCodeBlock(codeBlock) {
+    const highlightSteps = splitLineNumbers(
+      codeBlock.getAttribute(kCodeLineNumbersAttr)
+    );
+
+    if (highlightSteps.length) {
+      // If we have at least one step, we generate fragments
+      highlightSteps[0].forEach((highlight) => {
+        // Add expected class on 
     for reveal CSS
+        codeBlock.parentNode.classList.add("code-wrapper");
+
+        // Select lines to highlight
+        spanToHighlight = [];
+        if (typeof highlight.last === "number") {
+          spanToHighlight = [].slice.call(
+            codeBlock.querySelectorAll(
+              ":scope > span:nth-of-type(n+" +
+                highlight.first +
+                "):nth-of-type(-n+" +
+                highlight.last +
+                ")"
+            )
+          );
+        } else if (typeof highlight.first === "number") {
+          spanToHighlight = [].slice.call(
+            codeBlock.querySelectorAll(
+              ":scope > span:nth-of-type(" + highlight.first + ")"
+            )
+          );
+        }
+        if (spanToHighlight.length) {
+          // Add a class on  and  to select line to highlight
+          spanToHighlight.forEach((span) =>
+            span.classList.add("highlight-line")
+          );
+          codeBlock.classList.add("has-line-highlights");
+        }
+      });
+    }
+  }
+
+  /**
+   * Animates scrolling to the first highlighted line
+   * in the given code block.
+   */
+  function scrollHighlightedLineIntoView(block, scrollState, skipAnimation) {
+    window.cancelAnimationFrame(scrollState.animationFrameID);
+
+    // Match the scroll position of the currently visible
+    // code block
+    if (scrollState.currentBlock) {
+      block.scrollTop = scrollState.currentBlock.scrollTop;
+    }
+
+    // Remember the current code block so that we can match
+    // its scroll position when showing/hiding fragments
+    scrollState.currentBlock = block;
+
+    const highlightBounds = getHighlightedLineBounds(block);
+    let viewportHeight = block.offsetHeight;
+
+    // Subtract padding from the viewport height
+    const blockStyles = window.getComputedStyle(block);
+    viewportHeight -=
+      parseInt(blockStyles.paddingTop) + parseInt(blockStyles.paddingBottom);
+
+    // Scroll position which centers all highlights
+    const startTop = block.scrollTop;
+    let targetTop =
+      highlightBounds.top +
+      (Math.min(highlightBounds.bottom - highlightBounds.top, viewportHeight) -
+        viewportHeight) /
+        2;
+
+    // Make sure the scroll target is within bounds
+    targetTop = Math.max(
+      Math.min(targetTop, block.scrollHeight - viewportHeight),
+      0
+    );
+
+    if (skipAnimation === true || startTop === targetTop) {
+      block.scrollTop = targetTop;
+    } else {
+      // Don't attempt to scroll if there is no overflow
+      if (block.scrollHeight <= viewportHeight) return;
+
+      let time = 0;
+
+      const animate = function () {
+        time = Math.min(time + 0.02, 1);
+
+        // Update our eased scroll position
+        block.scrollTop =
+          startTop + (targetTop - startTop) * easeInOutQuart(time);
+
+        // Keep animating unless we've reached the end
+        if (time < 1) {
+          scrollState.animationFrameID = requestAnimationFrame(animate);
+        }
+      };
+
+      animate();
+    }
+  }
+
+  function getHighlightedLineBounds(block) {
+    const highlightedLines = block.querySelectorAll(".highlight-line");
+    if (highlightedLines.length === 0) {
+      return { top: 0, bottom: 0 };
+    } else {
+      const firstHighlight = highlightedLines[0];
+      const lastHighlight = highlightedLines[highlightedLines.length - 1];
+
+      return {
+        top: firstHighlight.offsetTop,
+        bottom: lastHighlight.offsetTop + lastHighlight.offsetHeight,
+      };
+    }
+  }
+
+  /**
+   * The easing function used when scrolling.
+   */
+  function easeInOutQuart(t) {
+    // easeInOutQuart
+    return t < 0.5 ? 8 * t * t * t * t : 1 - 8 * --t * t * t * t;
+  }
+
+  function splitLineNumbers(lineNumbersAttr) {
+    // remove space
+    lineNumbersAttr = lineNumbersAttr.replace("/s/g", "");
+    // seperate steps (for fragment)
+    lineNumbersAttr = lineNumbersAttr.split(delimiters.step);
+
+    // for each step, calculate first and last line, if any
+    return lineNumbersAttr.map((highlights) => {
+      // detect lines
+      const lines = highlights.split(delimiters.line);
+      return lines.map((range) => {
+        if (/^[\d-]+$/.test(range)) {
+          range = range.split(delimiters.lineRange);
+          const firstLine = parseInt(range[0], 10);
+          const lastLine = range[1] ? parseInt(range[1], 10) : undefined;
+          return {
+            first: firstLine,
+            last: lastLine,
+          };
+        } else {
+          return {};
+        }
+      });
+    });
+  }
+
+  function joinLineNumbers(splittedLineNumbers) {
+    return splittedLineNumbers
+      .map(function (highlights) {
+        return highlights
+          .map(function (highlight) {
+            // Line range
+            if (typeof highlight.last === "number") {
+              return highlight.first + delimiters.lineRange + highlight.last;
+            }
+            // Single line
+            else if (typeof highlight.first === "number") {
+              return highlight.first;
+            }
+            // All lines
+            else {
+              return "";
+            }
+          })
+          .join(delimiters.line);
+      })
+      .join(delimiters.step);
+  }
+
+  return {
+    id: "quarto-line-highlight",
+    init: function (deck) {
+      initQuartoLineHighlight(deck);
+
+      // If we're printing to PDF, scroll the code highlights of
+      // all blocks in the deck into view at once
+      deck.on("pdf-ready", function () {
+        [].slice
+          .call(
+            deck
+              .getRevealElement()
+              .querySelectorAll(
+                "pre code[data-code-line-numbers].current-fragment"
+              )
+          )
+          .forEach(function (block) {
+            scrollHighlightedLineIntoView(block, {}, true);
+          });
+      });
+    },
+  };
+};
diff --git a/docs/site_libs/revealjs/plugin/quarto-line-highlight/plugin.yml b/docs/site_libs/revealjs/plugin/quarto-line-highlight/plugin.yml
index ca20686..61f53a5 100644
--- a/docs/site_libs/revealjs/plugin/quarto-line-highlight/plugin.yml
+++ b/docs/site_libs/revealjs/plugin/quarto-line-highlight/plugin.yml
@@ -1,4 +1,4 @@
-# adapted from https://github.com/hakimel/reveal.js/tree/master/plugin/highlight
-name: QuartoLineHighlight
-script: line-highlight.js
-stylesheet: line-highlight.css
+# adapted from https://github.com/hakimel/reveal.js/tree/master/plugin/highlight
+name: QuartoLineHighlight
+script: line-highlight.js
+stylesheet: line-highlight.css
diff --git a/docs/site_libs/revealjs/plugin/quarto-support/footer.css b/docs/site_libs/revealjs/plugin/quarto-support/footer.css
index 390d5b3..07ace0a 100644
--- a/docs/site_libs/revealjs/plugin/quarto-support/footer.css
+++ b/docs/site_libs/revealjs/plugin/quarto-support/footer.css
@@ -1,110 +1,110 @@
-.reveal .slide-logo {
-  display: block;
-  position: fixed;
-  bottom: 0;
-  right: 12px;
-  max-height: 2.2rem;
-  height: 100%;
-  width: auto;
-  z-index: 2;
-}
-
-.reveal .footer {
-  display: block;
-  position: fixed;
-  bottom: 18px;
-  width: 100%;
-  margin: 0 auto;
-  text-align: center;
-  font-size: 18px;
-  z-index: 2;
-}
-
-.reveal .footer > * {
-  margin-top: 0;
-  margin-bottom: 0;
-}
-
-.reveal .slide .footer {
-  display: none;
-}
-
-.reveal .slide-number {
-  bottom: 10px;
-  right: 10px;
-  font-size: 16px;
-  background-color: transparent;
-}
-
-.reveal.has-logo .slide-number {
-  bottom: initial;
-  top: 8px;
-  right: 8px;
-}
-
-.reveal .slide-number .slide-number-delimiter {
-  margin: 0;
-}
-
-.reveal .slide-menu-button {
-  left: 8px;
-  bottom: 8px;
-}
-
-.reveal .slide-chalkboard-buttons {
-  position: fixed;
-  left: 12px;
-  bottom: 8px;
-  z-index: 30;
-  font-size: 24px;
-}
-
-.reveal .slide-chalkboard-buttons.slide-menu-offset {
-  left: 54px;
-}
-
-.reveal .slide-chalkboard-buttons > span {
-  margin-right: 14px;
-  cursor: pointer;
-}
-
-@media screen and (max-width: 800px) {
-  .reveal .slide-logo {
-    max-height: 1.1rem;
-    bottom: -2px;
-    right: 10px;
-  }
-  .reveal .footer {
-    font-size: 14px;
-    bottom: 12px;
-  }
-  .reveal .slide-number {
-    font-size: 12px;
-    bottom: 7px;
-  }
-  .reveal .slide-menu-button .fas::before {
-    height: 1.3rem;
-    width: 1.3rem;
-    vertical-align: -0.125em;
-    background-size: 1.3rem 1.3rem;
-  }
-
-  .reveal .slide-chalkboard-buttons .fas::before {
-    height: 0.95rem;
-    width: 0.95rem;
-    background-size: 0.95rem 0.95rem;
-    vertical-align: -0em;
-  }
-
-  .reveal .slide-chalkboard-buttons.slide-menu-offset {
-    left: 36px;
-  }
-  .reveal .slide-chalkboard-buttons > span {
-    margin-right: 9px;
-  }
-}
-
-html.print-pdf .reveal .slide-menu-button,
-html.print-pdf .reveal .slide-chalkboard-buttons {
-  display: none;
-}
+.reveal .slide-logo {
+  display: block;
+  position: fixed;
+  bottom: 0;
+  right: 12px;
+  max-height: 2.2rem;
+  height: 100%;
+  width: auto;
+  z-index: 2;
+}
+
+.reveal .footer {
+  display: block;
+  position: fixed;
+  bottom: 18px;
+  width: 100%;
+  margin: 0 auto;
+  text-align: center;
+  font-size: 18px;
+  z-index: 2;
+}
+
+.reveal .footer > * {
+  margin-top: 0;
+  margin-bottom: 0;
+}
+
+.reveal .slide .footer {
+  display: none;
+}
+
+.reveal .slide-number {
+  bottom: 10px;
+  right: 10px;
+  font-size: 16px;
+  background-color: transparent;
+}
+
+.reveal.has-logo .slide-number {
+  bottom: initial;
+  top: 8px;
+  right: 8px;
+}
+
+.reveal .slide-number .slide-number-delimiter {
+  margin: 0;
+}
+
+.reveal .slide-menu-button {
+  left: 8px;
+  bottom: 8px;
+}
+
+.reveal .slide-chalkboard-buttons {
+  position: fixed;
+  left: 12px;
+  bottom: 8px;
+  z-index: 30;
+  font-size: 24px;
+}
+
+.reveal .slide-chalkboard-buttons.slide-menu-offset {
+  left: 54px;
+}
+
+.reveal .slide-chalkboard-buttons > span {
+  margin-right: 14px;
+  cursor: pointer;
+}
+
+@media screen and (max-width: 800px) {
+  .reveal .slide-logo {
+    max-height: 1.1rem;
+    bottom: -2px;
+    right: 10px;
+  }
+  .reveal .footer {
+    font-size: 14px;
+    bottom: 12px;
+  }
+  .reveal .slide-number {
+    font-size: 12px;
+    bottom: 7px;
+  }
+  .reveal .slide-menu-button .fas::before {
+    height: 1.3rem;
+    width: 1.3rem;
+    vertical-align: -0.125em;
+    background-size: 1.3rem 1.3rem;
+  }
+
+  .reveal .slide-chalkboard-buttons .fas::before {
+    height: 0.95rem;
+    width: 0.95rem;
+    background-size: 0.95rem 0.95rem;
+    vertical-align: -0em;
+  }
+
+  .reveal .slide-chalkboard-buttons.slide-menu-offset {
+    left: 36px;
+  }
+  .reveal .slide-chalkboard-buttons > span {
+    margin-right: 9px;
+  }
+}
+
+html.print-pdf .reveal .slide-menu-button,
+html.print-pdf .reveal .slide-chalkboard-buttons {
+  display: none;
+}
diff --git a/docs/site_libs/revealjs/plugin/quarto-support/plugin.yml b/docs/site_libs/revealjs/plugin/quarto-support/plugin.yml
index 546956e..ce79701 100644
--- a/docs/site_libs/revealjs/plugin/quarto-support/plugin.yml
+++ b/docs/site_libs/revealjs/plugin/quarto-support/plugin.yml
@@ -1,5 +1,5 @@
-name: QuartoSupport
-script: support.js
-stylesheet: footer.css
-config:
-  smaller: false
+name: QuartoSupport
+script: support.js
+stylesheet: footer.css
+config:
+  smaller: false
diff --git a/docs/site_libs/revealjs/plugin/quarto-support/support.js b/docs/site_libs/revealjs/plugin/quarto-support/support.js
index 2019291..d2bffb2 100644
--- a/docs/site_libs/revealjs/plugin/quarto-support/support.js
+++ b/docs/site_libs/revealjs/plugin/quarto-support/support.js
@@ -1,419 +1,419 @@
-// catch all plugin for various quarto features
-window.QuartoSupport = function () {
-  function isPrintView() {
-    return /print-pdf/gi.test(window.location.search) || /view=print/gi.test(window.location.search);
-  }
-
-  // helper for theme toggling
-  function toggleBackgroundTheme(el, onDarkBackground, onLightBackground) {
-    if (onDarkBackground) {
-      el.classList.add('has-dark-background')
-    } else {
-      el.classList.remove('has-dark-background')
-    }
-    if (onLightBackground) {
-      el.classList.add('has-light-background')
-    } else {
-      el.classList.remove('has-light-background')
-    }
-  }
-
-  // implement controlsAudo
-  function controlsAuto(deck) {
-    const config = deck.getConfig();
-    if (config.controlsAuto === true) {
-      const iframe = window.location !== window.parent.location;
-      const localhost =
-        window.location.hostname === "localhost" ||
-        window.location.hostname === "127.0.0.1";
-      deck.configure({
-        controls:
-          (iframe && !localhost) ||
-          (deck.hasVerticalSlides() && config.navigationMode !== "linear"),
-      });
-    }
-  }
-
-  // helper to provide event handlers for all links in a container
-  function handleLinkClickEvents(deck, container) {
-    Array.from(container.querySelectorAll("a")).forEach((el) => {
-      const url = el.getAttribute("href");
-      if (/^(http|www)/gi.test(url)) {
-        el.addEventListener(
-          "click",
-          (ev) => {
-            const fullscreen = !!window.document.fullscreen;
-            const dataPreviewLink = el.getAttribute("data-preview-link");
-
-            // if there is a local specifcation then use that
-            if (dataPreviewLink) {
-              if (
-                dataPreviewLink === "true" ||
-                (dataPreviewLink === "auto" && fullscreen)
-              ) {
-                ev.preventDefault();
-                deck.showPreview(url);
-                return false;
-              }
-            } else {
-              const previewLinks = !!deck.getConfig().previewLinks;
-              const previewLinksAuto =
-                deck.getConfig().previewLinksAuto === true;
-              if (previewLinks == true || (previewLinksAuto && fullscreen)) {
-                ev.preventDefault();
-                deck.showPreview(url);
-                return false;
-              }
-            }
-
-            // if the deck is in an iframe we want to open it externally
-            // (don't do this when in vscode though as it has its own
-            // handler for opening links externally that will be play)
-            const iframe = window.location !== window.parent.location;
-            if (
-              iframe &&
-              !window.location.search.includes("quartoPreviewReqId=")
-            ) {
-              ev.preventDefault();
-              ev.stopImmediatePropagation();
-              window.open(url, "_blank");
-              return false;
-            }
-
-            // if the user has set data-preview-link to "auto" we need to handle the event
-            // (because reveal will interpret "auto" as true)
-            if (dataPreviewLink === "auto") {
-              ev.preventDefault();
-              ev.stopImmediatePropagation();
-              const target =
-                el.getAttribute("target") ||
-                (ev.ctrlKey || ev.metaKey ? "_blank" : "");
-              if (target) {
-                window.open(url, target);
-              } else {
-                window.location.href = url;
-              }
-              return false;
-            }
-          },
-          false
-        );
-      }
-    });
-  }
-
-  // implement previewLinksAuto
-  function previewLinksAuto(deck) {
-    handleLinkClickEvents(deck, deck.getRevealElement());
-  }
-
-  // apply styles
-  function applyGlobalStyles(deck) {
-    if (deck.getConfig()["smaller"] === true) {
-      const revealParent = deck.getRevealElement();
-      revealParent.classList.add("smaller");
-    }
-  }
-
-  // add logo image
-  function addLogoImage(deck) {
-    const revealParent = deck.getRevealElement();
-    const logoImg = document.querySelector(".slide-logo");
-    if (logoImg) {
-      revealParent.appendChild(logoImg);
-      revealParent.classList.add("has-logo");
-    }
-  }
-
-  // tweak slide-number element
-  function tweakSlideNumber(deck) {
-    deck.on("slidechanged", function (ev) {
-      // No slide number in scroll view
-      if (deck.isScrollView()) { return }
-      const revealParent = deck.getRevealElement();
-      const slideNumberEl = revealParent.querySelector(".slide-number");
-      const slideBackground = Reveal.getSlideBackground(ev.currentSlide);
-      const onDarkBackground = slideBackground.classList.contains('has-dark-background')
-      const onLightBackground = slideBackground.classList.contains('has-light-background')
-      toggleBackgroundTheme(slideNumberEl, onDarkBackground, onLightBackground);
-    })
-  }
-
-  // add footer text
-  function addFooter(deck) {
-    const revealParent = deck.getRevealElement();
-    const defaultFooterDiv = document.querySelector(".footer-default");
-    // Set per slide footer if any defined, 
-    // or show default unless data-footer="false" for no footer on this slide
-    const setSlideFooter = (ev, defaultFooterDiv) => {
-      const currentSlideFooter = ev.currentSlide.querySelector(".footer");
-      const onDarkBackground = deck.getSlideBackground(ev.currentSlide).classList.contains('has-dark-background')
-      const onLightBackground = deck.getSlideBackground(ev.currentSlide).classList.contains('has-light-background')
-      if (currentSlideFooter) {
-        defaultFooterDiv.style.display = "none";
-        const slideFooter = currentSlideFooter.cloneNode(true);
-        handleLinkClickEvents(deck, slideFooter);
-        deck.getRevealElement().appendChild(slideFooter);
-        toggleBackgroundTheme(slideFooter, onDarkBackground, onLightBackground)
-      } else if (ev.currentSlide.getAttribute("data-footer") === "false") {
-        defaultFooterDiv.style.display = "none";
-      } else {
-        defaultFooterDiv.style.display = "block";
-        toggleBackgroundTheme(defaultFooterDiv, onDarkBackground, onLightBackground)
-      }
-    }
-    if (defaultFooterDiv) {
-      // move default footnote to the div.reveal element
-      revealParent.appendChild(defaultFooterDiv);
-      handleLinkClickEvents(deck, defaultFooterDiv);
-
-      if (!isPrintView()) {
-        // Ready even is needed so that footer customization applies on first loaded slide
-        deck.on('ready', (ev) => {
-          // Set footer (custom, default or none)
-          setSlideFooter(ev, defaultFooterDiv)
-        });
-        // Any new navigated new slide will get the custom footnote check
-        deck.on("slidechanged", function (ev) {
-          // Remove presentation footer defined by previous slide
-          const prevSlideFooter = document.querySelector(
-            ".reveal > .footer:not(.footer-default)"
-          );
-          if (prevSlideFooter) {
-            prevSlideFooter.remove();
-          }
-          // Set new one (custom, default or none)
-          setSlideFooter(ev, defaultFooterDiv)
-        });
-      }
-    }
-  }
-
-  // add chalkboard buttons
-  function addChalkboardButtons(deck) {
-    const chalkboard = deck.getPlugin("RevealChalkboard");
-    if (chalkboard && !isPrintView()) {
-      const revealParent = deck.getRevealElement();
-      const chalkboardDiv = document.createElement("div");
-      chalkboardDiv.classList.add("slide-chalkboard-buttons");
-      if (document.querySelector(".slide-menu-button")) {
-        chalkboardDiv.classList.add("slide-menu-offset");
-      }
-      // add buttons
-      const buttons = [
-        {
-          icon: "easel2",
-          title: "Toggle Chalkboard (b)",
-          onclick: chalkboard.toggleChalkboard,
-        },
-        {
-          icon: "brush",
-          title: "Toggle Notes Canvas (c)",
-          onclick: chalkboard.toggleNotesCanvas,
-        },
-      ];
-      buttons.forEach(function (button) {
-        const span = document.createElement("span");
-        span.title = button.title;
-        const icon = document.createElement("i");
-        icon.classList.add("fas");
-        icon.classList.add("fa-" + button.icon);
-        span.appendChild(icon);
-        span.onclick = function (event) {
-          event.preventDefault();
-          button.onclick();
-        };
-        chalkboardDiv.appendChild(span);
-      });
-      revealParent.appendChild(chalkboardDiv);
-      const config = deck.getConfig();
-      if (!config.chalkboard.buttons) {
-        chalkboardDiv.classList.add("hidden");
-      }
-
-      // show and hide chalkboard buttons on slidechange
-      deck.on("slidechanged", function (ev) {
-        const config = deck.getConfig();
-        let buttons = !!config.chalkboard.buttons;
-        const slideButtons = ev.currentSlide.getAttribute(
-          "data-chalkboard-buttons"
-        );
-        if (slideButtons) {
-          if (slideButtons === "true" || slideButtons === "1") {
-            buttons = true;
-          } else if (slideButtons === "false" || slideButtons === "0") {
-            buttons = false;
-          }
-        }
-        if (buttons) {
-          chalkboardDiv.classList.remove("hidden");
-        } else {
-          chalkboardDiv.classList.add("hidden");
-        }
-      });
-    }
-  }
-
-  function handleTabbyClicks() {
-    const tabs = document.querySelectorAll(".panel-tabset-tabby > li > a");
-    for (let i = 0; i < tabs.length; i++) {
-      const tab = tabs[i];
-      tab.onclick = function (ev) {
-        ev.preventDefault();
-        ev.stopPropagation();
-        return false;
-      };
-    }
-  }
-
-  function fixupForPrint(deck) {
-    if (isPrintView()) {
-      const slides = deck.getSlides();
-      slides.forEach(function (slide) {
-        slide.removeAttribute("data-auto-animate");
-      });
-      window.document.querySelectorAll(".hljs").forEach(function (el) {
-        el.classList.remove("hljs");
-      });
-      window.document.querySelectorAll(".hljs-ln-code").forEach(function (el) {
-        el.classList.remove("hljs-ln-code");
-      });
-    }
-  }
-
-  // dispatch for htmlwidgets
-  // they use slideenter event to trigger resize
-  const fireSlideEnter = () => {
-    const event = window.document.createEvent("Event");
-    event.initEvent("slideenter", true, true);
-    window.document.dispatchEvent(event);
-  };
-
-  // dispatch for shiny
-  // they use BS shown and hidden events to trigger rendering
-  const distpatchShinyEvents = (previous, current) => {
-    if (window.jQuery) {
-      if (previous) {
-        window.jQuery(previous).trigger("hidden");
-      }
-      if (current) {
-        window.jQuery(current).trigger("shown");
-      }
-    }
-  };
-
-  function handleSlideChanges(deck) {
-
-    const fireSlideChanged = (previousSlide, currentSlide) => {
-      fireSlideEnter();
-      distpatchShinyEvents(previousSlide, currentSlide);
-    };
-
-    deck.on("slidechanged", function (event) {
-      fireSlideChanged(event.previousSlide, event.currentSlide);
-    });
-  }
-
-  function handleTabbyChanges() {
-    const fireTabChanged = (previousTab, currentTab) => {
-      fireSlideEnter()
-      distpatchShinyEvents(previousTab, currentTab);
-    };
-    document.addEventListener("tabby", function(event) {
-      fireTabChanged(event.detail.previousTab, event.detail.tab);
-    }, false);
-  }
-
-  function workaroundMermaidDistance(deck) {
-    if (window.document.querySelector("pre.mermaid-js")) {
-      const slideCount = deck.getTotalSlides();
-      deck.configure({
-        mobileViewDistance: slideCount,
-        viewDistance: slideCount,
-      });
-    }
-  }
-
-  function handleWhiteSpaceInColumns(deck) {
-    for (const outerDiv of window.document.querySelectorAll("div.columns")) {
-      // remove all whitespace text nodes
-      // whitespace nodes cause the columns to be misaligned
-      // since they have inline-block layout
-      // 
-      // Quarto emits no whitespace nodes, but third-party tooling
-      // has bugs that can cause whitespace nodes to be emitted.
-      // See https://github.com/quarto-dev/quarto-cli/issues/8382
-      for (const node of outerDiv.childNodes) {
-        if (node.nodeType === 3 && node.nodeValue.trim() === "") {
-          outerDiv.removeChild(node);
-        }
-      }
-    }
-  }
-
-  function cleanEmptyAutoGeneratedContent(deck) {
-    const div = document.querySelector('div.quarto-auto-generated-content')
-    if (div && div.textContent.trim() === '') {
-      div.remove()
-    }
-  }
-
-  // FIXME: Possibly remove this wrapper class when upstream trigger is fixed
-  // https://github.com/hakimel/reveal.js/issues/3688
-  // Currently, scrollActivationWidth needs to be unset for toggle to work
-  class ScrollViewToggler {
-    constructor(deck) {
-      this.deck = deck;
-      this.oldScrollActivationWidth = deck.getConfig()['scrollActivationWidth'];
-    }
-  
-    toggleScrollViewWrapper() {
-      if (this.deck.isScrollView() === true) {
-        this.deck.configure({ scrollActivationWidth: this.oldScrollActivationWidth });
-        this.deck.toggleScrollView(false);
-      } else if (this.deck.isScrollView() === false) {
-        this.deck.configure({ scrollActivationWidth: null });
-        this.deck.toggleScrollView(true);
-      }
-    }
-  }
-
-  let scrollViewToggler;
-
-  function installScollViewKeyBindings(deck) {
-		var config = deck.getConfig();
-		var shortcut = config.scrollViewShortcut || 'R';
-		Reveal.addKeyBinding({
-			keyCode: shortcut.toUpperCase().charCodeAt( 0 ),
-			key: shortcut.toUpperCase(),
-			description: 'Scroll View Mode'
-		}, () => { scrollViewToggler.toggleScrollViewWrapper() } );
-	}
-
-  return {
-    id: "quarto-support",
-    init: function (deck) {
-      scrollViewToggler = new ScrollViewToggler(deck);
-      controlsAuto(deck);
-      previewLinksAuto(deck);
-      fixupForPrint(deck);
-      applyGlobalStyles(deck);
-      addLogoImage(deck);
-      tweakSlideNumber(deck);
-      addFooter(deck);
-      addChalkboardButtons(deck);
-      handleTabbyClicks();
-      handleTabbyChanges();
-      handleSlideChanges(deck);
-      workaroundMermaidDistance(deck);
-      handleWhiteSpaceInColumns(deck);
-      installScollViewKeyBindings(deck);
-      // should stay last
-      cleanEmptyAutoGeneratedContent(deck);
-    },
-    // Export for adding in menu
-    toggleScrollView: function() {
-      scrollViewToggler.toggleScrollViewWrapper();
-    }
-  };
-};
+// catch all plugin for various quarto features
+window.QuartoSupport = function () {
+  function isPrintView() {
+    return /print-pdf/gi.test(window.location.search) || /view=print/gi.test(window.location.search);
+  }
+
+  // helper for theme toggling
+  function toggleBackgroundTheme(el, onDarkBackground, onLightBackground) {
+    if (onDarkBackground) {
+      el.classList.add('has-dark-background')
+    } else {
+      el.classList.remove('has-dark-background')
+    }
+    if (onLightBackground) {
+      el.classList.add('has-light-background')
+    } else {
+      el.classList.remove('has-light-background')
+    }
+  }
+
+  // implement controlsAudo
+  function controlsAuto(deck) {
+    const config = deck.getConfig();
+    if (config.controlsAuto === true) {
+      const iframe = window.location !== window.parent.location;
+      const localhost =
+        window.location.hostname === "localhost" ||
+        window.location.hostname === "127.0.0.1";
+      deck.configure({
+        controls:
+          (iframe && !localhost) ||
+          (deck.hasVerticalSlides() && config.navigationMode !== "linear"),
+      });
+    }
+  }
+
+  // helper to provide event handlers for all links in a container
+  function handleLinkClickEvents(deck, container) {
+    Array.from(container.querySelectorAll("a")).forEach((el) => {
+      const url = el.getAttribute("href");
+      if (/^(http|www)/gi.test(url)) {
+        el.addEventListener(
+          "click",
+          (ev) => {
+            const fullscreen = !!window.document.fullscreen;
+            const dataPreviewLink = el.getAttribute("data-preview-link");
+
+            // if there is a local specifcation then use that
+            if (dataPreviewLink) {
+              if (
+                dataPreviewLink === "true" ||
+                (dataPreviewLink === "auto" && fullscreen)
+              ) {
+                ev.preventDefault();
+                deck.showPreview(url);
+                return false;
+              }
+            } else {
+              const previewLinks = !!deck.getConfig().previewLinks;
+              const previewLinksAuto =
+                deck.getConfig().previewLinksAuto === true;
+              if (previewLinks == true || (previewLinksAuto && fullscreen)) {
+                ev.preventDefault();
+                deck.showPreview(url);
+                return false;
+              }
+            }
+
+            // if the deck is in an iframe we want to open it externally
+            // (don't do this when in vscode though as it has its own
+            // handler for opening links externally that will be play)
+            const iframe = window.location !== window.parent.location;
+            if (
+              iframe &&
+              !window.location.search.includes("quartoPreviewReqId=")
+            ) {
+              ev.preventDefault();
+              ev.stopImmediatePropagation();
+              window.open(url, "_blank");
+              return false;
+            }
+
+            // if the user has set data-preview-link to "auto" we need to handle the event
+            // (because reveal will interpret "auto" as true)
+            if (dataPreviewLink === "auto") {
+              ev.preventDefault();
+              ev.stopImmediatePropagation();
+              const target =
+                el.getAttribute("target") ||
+                (ev.ctrlKey || ev.metaKey ? "_blank" : "");
+              if (target) {
+                window.open(url, target);
+              } else {
+                window.location.href = url;
+              }
+              return false;
+            }
+          },
+          false
+        );
+      }
+    });
+  }
+
+  // implement previewLinksAuto
+  function previewLinksAuto(deck) {
+    handleLinkClickEvents(deck, deck.getRevealElement());
+  }
+
+  // apply styles
+  function applyGlobalStyles(deck) {
+    if (deck.getConfig()["smaller"] === true) {
+      const revealParent = deck.getRevealElement();
+      revealParent.classList.add("smaller");
+    }
+  }
+
+  // add logo image
+  function addLogoImage(deck) {
+    const revealParent = deck.getRevealElement();
+    const logoImg = document.querySelector(".slide-logo");
+    if (logoImg) {
+      revealParent.appendChild(logoImg);
+      revealParent.classList.add("has-logo");
+    }
+  }
+
+  // tweak slide-number element
+  function tweakSlideNumber(deck) {
+    deck.on("slidechanged", function (ev) {
+      // No slide number in scroll view
+      if (deck.isScrollView()) { return }
+      const revealParent = deck.getRevealElement();
+      const slideNumberEl = revealParent.querySelector(".slide-number");
+      const slideBackground = Reveal.getSlideBackground(ev.currentSlide);
+      const onDarkBackground = slideBackground.classList.contains('has-dark-background')
+      const onLightBackground = slideBackground.classList.contains('has-light-background')
+      toggleBackgroundTheme(slideNumberEl, onDarkBackground, onLightBackground);
+    })
+  }
+
+  // add footer text
+  function addFooter(deck) {
+    const revealParent = deck.getRevealElement();
+    const defaultFooterDiv = document.querySelector(".footer-default");
+    // Set per slide footer if any defined, 
+    // or show default unless data-footer="false" for no footer on this slide
+    const setSlideFooter = (ev, defaultFooterDiv) => {
+      const currentSlideFooter = ev.currentSlide.querySelector(".footer");
+      const onDarkBackground = deck.getSlideBackground(ev.currentSlide).classList.contains('has-dark-background')
+      const onLightBackground = deck.getSlideBackground(ev.currentSlide).classList.contains('has-light-background')
+      if (currentSlideFooter) {
+        defaultFooterDiv.style.display = "none";
+        const slideFooter = currentSlideFooter.cloneNode(true);
+        handleLinkClickEvents(deck, slideFooter);
+        deck.getRevealElement().appendChild(slideFooter);
+        toggleBackgroundTheme(slideFooter, onDarkBackground, onLightBackground)
+      } else if (ev.currentSlide.getAttribute("data-footer") === "false") {
+        defaultFooterDiv.style.display = "none";
+      } else {
+        defaultFooterDiv.style.display = "block";
+        toggleBackgroundTheme(defaultFooterDiv, onDarkBackground, onLightBackground)
+      }
+    }
+    if (defaultFooterDiv) {
+      // move default footnote to the div.reveal element
+      revealParent.appendChild(defaultFooterDiv);
+      handleLinkClickEvents(deck, defaultFooterDiv);
+
+      if (!isPrintView()) {
+        // Ready even is needed so that footer customization applies on first loaded slide
+        deck.on('ready', (ev) => {
+          // Set footer (custom, default or none)
+          setSlideFooter(ev, defaultFooterDiv)
+        });
+        // Any new navigated new slide will get the custom footnote check
+        deck.on("slidechanged", function (ev) {
+          // Remove presentation footer defined by previous slide
+          const prevSlideFooter = document.querySelector(
+            ".reveal > .footer:not(.footer-default)"
+          );
+          if (prevSlideFooter) {
+            prevSlideFooter.remove();
+          }
+          // Set new one (custom, default or none)
+          setSlideFooter(ev, defaultFooterDiv)
+        });
+      }
+    }
+  }
+
+  // add chalkboard buttons
+  function addChalkboardButtons(deck) {
+    const chalkboard = deck.getPlugin("RevealChalkboard");
+    if (chalkboard && !isPrintView()) {
+      const revealParent = deck.getRevealElement();
+      const chalkboardDiv = document.createElement("div");
+      chalkboardDiv.classList.add("slide-chalkboard-buttons");
+      if (document.querySelector(".slide-menu-button")) {
+        chalkboardDiv.classList.add("slide-menu-offset");
+      }
+      // add buttons
+      const buttons = [
+        {
+          icon: "easel2",
+          title: "Toggle Chalkboard (b)",
+          onclick: chalkboard.toggleChalkboard,
+        },
+        {
+          icon: "brush",
+          title: "Toggle Notes Canvas (c)",
+          onclick: chalkboard.toggleNotesCanvas,
+        },
+      ];
+      buttons.forEach(function (button) {
+        const span = document.createElement("span");
+        span.title = button.title;
+        const icon = document.createElement("i");
+        icon.classList.add("fas");
+        icon.classList.add("fa-" + button.icon);
+        span.appendChild(icon);
+        span.onclick = function (event) {
+          event.preventDefault();
+          button.onclick();
+        };
+        chalkboardDiv.appendChild(span);
+      });
+      revealParent.appendChild(chalkboardDiv);
+      const config = deck.getConfig();
+      if (!config.chalkboard.buttons) {
+        chalkboardDiv.classList.add("hidden");
+      }
+
+      // show and hide chalkboard buttons on slidechange
+      deck.on("slidechanged", function (ev) {
+        const config = deck.getConfig();
+        let buttons = !!config.chalkboard.buttons;
+        const slideButtons = ev.currentSlide.getAttribute(
+          "data-chalkboard-buttons"
+        );
+        if (slideButtons) {
+          if (slideButtons === "true" || slideButtons === "1") {
+            buttons = true;
+          } else if (slideButtons === "false" || slideButtons === "0") {
+            buttons = false;
+          }
+        }
+        if (buttons) {
+          chalkboardDiv.classList.remove("hidden");
+        } else {
+          chalkboardDiv.classList.add("hidden");
+        }
+      });
+    }
+  }
+
+  function handleTabbyClicks() {
+    const tabs = document.querySelectorAll(".panel-tabset-tabby > li > a");
+    for (let i = 0; i < tabs.length; i++) {
+      const tab = tabs[i];
+      tab.onclick = function (ev) {
+        ev.preventDefault();
+        ev.stopPropagation();
+        return false;
+      };
+    }
+  }
+
+  function fixupForPrint(deck) {
+    if (isPrintView()) {
+      const slides = deck.getSlides();
+      slides.forEach(function (slide) {
+        slide.removeAttribute("data-auto-animate");
+      });
+      window.document.querySelectorAll(".hljs").forEach(function (el) {
+        el.classList.remove("hljs");
+      });
+      window.document.querySelectorAll(".hljs-ln-code").forEach(function (el) {
+        el.classList.remove("hljs-ln-code");
+      });
+    }
+  }
+
+  // dispatch for htmlwidgets
+  // they use slideenter event to trigger resize
+  const fireSlideEnter = () => {
+    const event = window.document.createEvent("Event");
+    event.initEvent("slideenter", true, true);
+    window.document.dispatchEvent(event);
+  };
+
+  // dispatch for shiny
+  // they use BS shown and hidden events to trigger rendering
+  const distpatchShinyEvents = (previous, current) => {
+    if (window.jQuery) {
+      if (previous) {
+        window.jQuery(previous).trigger("hidden");
+      }
+      if (current) {
+        window.jQuery(current).trigger("shown");
+      }
+    }
+  };
+
+  function handleSlideChanges(deck) {
+
+    const fireSlideChanged = (previousSlide, currentSlide) => {
+      fireSlideEnter();
+      distpatchShinyEvents(previousSlide, currentSlide);
+    };
+
+    deck.on("slidechanged", function (event) {
+      fireSlideChanged(event.previousSlide, event.currentSlide);
+    });
+  }
+
+  function handleTabbyChanges() {
+    const fireTabChanged = (previousTab, currentTab) => {
+      fireSlideEnter()
+      distpatchShinyEvents(previousTab, currentTab);
+    };
+    document.addEventListener("tabby", function(event) {
+      fireTabChanged(event.detail.previousTab, event.detail.tab);
+    }, false);
+  }
+
+  function workaroundMermaidDistance(deck) {
+    if (window.document.querySelector("pre.mermaid-js")) {
+      const slideCount = deck.getTotalSlides();
+      deck.configure({
+        mobileViewDistance: slideCount,
+        viewDistance: slideCount,
+      });
+    }
+  }
+
+  function handleWhiteSpaceInColumns(deck) {
+    for (const outerDiv of window.document.querySelectorAll("div.columns")) {
+      // remove all whitespace text nodes
+      // whitespace nodes cause the columns to be misaligned
+      // since they have inline-block layout
+      // 
+      // Quarto emits no whitespace nodes, but third-party tooling
+      // has bugs that can cause whitespace nodes to be emitted.
+      // See https://github.com/quarto-dev/quarto-cli/issues/8382
+      for (const node of outerDiv.childNodes) {
+        if (node.nodeType === 3 && node.nodeValue.trim() === "") {
+          outerDiv.removeChild(node);
+        }
+      }
+    }
+  }
+
+  function cleanEmptyAutoGeneratedContent(deck) {
+    const div = document.querySelector('div.quarto-auto-generated-content')
+    if (div && div.textContent.trim() === '') {
+      div.remove()
+    }
+  }
+
+  // FIXME: Possibly remove this wrapper class when upstream trigger is fixed
+  // https://github.com/hakimel/reveal.js/issues/3688
+  // Currently, scrollActivationWidth needs to be unset for toggle to work
+  class ScrollViewToggler {
+    constructor(deck) {
+      this.deck = deck;
+      this.oldScrollActivationWidth = deck.getConfig()['scrollActivationWidth'];
+    }
+  
+    toggleScrollViewWrapper() {
+      if (this.deck.isScrollView() === true) {
+        this.deck.configure({ scrollActivationWidth: this.oldScrollActivationWidth });
+        this.deck.toggleScrollView(false);
+      } else if (this.deck.isScrollView() === false) {
+        this.deck.configure({ scrollActivationWidth: null });
+        this.deck.toggleScrollView(true);
+      }
+    }
+  }
+
+  let scrollViewToggler;
+
+  function installScollViewKeyBindings(deck) {
+		var config = deck.getConfig();
+		var shortcut = config.scrollViewShortcut || 'R';
+		Reveal.addKeyBinding({
+			keyCode: shortcut.toUpperCase().charCodeAt( 0 ),
+			key: shortcut.toUpperCase(),
+			description: 'Scroll View Mode'
+		}, () => { scrollViewToggler.toggleScrollViewWrapper() } );
+	}
+
+  return {
+    id: "quarto-support",
+    init: function (deck) {
+      scrollViewToggler = new ScrollViewToggler(deck);
+      controlsAuto(deck);
+      previewLinksAuto(deck);
+      fixupForPrint(deck);
+      applyGlobalStyles(deck);
+      addLogoImage(deck);
+      tweakSlideNumber(deck);
+      addFooter(deck);
+      addChalkboardButtons(deck);
+      handleTabbyClicks();
+      handleTabbyChanges();
+      handleSlideChanges(deck);
+      workaroundMermaidDistance(deck);
+      handleWhiteSpaceInColumns(deck);
+      installScollViewKeyBindings(deck);
+      // should stay last
+      cleanEmptyAutoGeneratedContent(deck);
+    },
+    // Export for adding in menu
+    toggleScrollView: function() {
+      scrollViewToggler.toggleScrollViewWrapper();
+    }
+  };
+};
diff --git a/docs/site_libs/revealjs/plugin/reveal-menu/menu.css b/docs/site_libs/revealjs/plugin/reveal-menu/menu.css
index 5a300fd..07b2a2e 100644
--- a/docs/site_libs/revealjs/plugin/reveal-menu/menu.css
+++ b/docs/site_libs/revealjs/plugin/reveal-menu/menu.css
@@ -1,346 +1,346 @@
-.slide-menu-wrapper {
-  font-family: 'Source Sans Pro', Helvetica, sans-serif;
-}
-
-.slide-menu-wrapper .slide-menu {
-  background-color: #333;
-  z-index: 200;
-  position: fixed;
-  top: 0;
-  width: 300px;
-  height: 100%;
-  /*overflow-y: scroll;*/
-  transition: transform 0.3s;
-  font-size: 16px;
-  font-weight: normal;
-}
-
-.slide-menu-wrapper .slide-menu.slide-menu--wide {
-  width: 500px;
-}
-
-.slide-menu-wrapper .slide-menu.slide-menu--third {
-  width: 33%;
-}
-
-.slide-menu-wrapper .slide-menu.slide-menu--half {
-  width: 50%;
-}
-
-.slide-menu-wrapper .slide-menu.slide-menu--full {
-  width: 95%;
-}
-
-/*
- * Slides menu
- */
-
-.slide-menu-wrapper .slide-menu-items {
-  margin: 0;
-  padding: 0;
-  width: 100%;
-  border-bottom: solid 1px #555;
-}
-
-.slide-menu-wrapper .slide-menu-item,
-.slide-menu-wrapper .slide-menu-item-vertical {
-  display: block;
-  text-align: left;
-  padding: 10px 18px;
-  color: #aaa;
-  cursor: pointer;
-}
-
-.slide-menu-wrapper .slide-menu-item-vertical {
-  padding-left: 30px;
-}
-
-.slide-menu-wrapper .slide-menu--wide .slide-menu-item-vertical,
-.slide-menu-wrapper .slide-menu--third .slide-menu-item-vertical,
-.slide-menu-wrapper .slide-menu--half .slide-menu-item-vertical,
-.slide-menu-wrapper .slide-menu--full .slide-menu-item-vertical,
-.slide-menu-wrapper .slide-menu--custom .slide-menu-item-vertical {
-  padding-left: 50px;
-}
-
-.slide-menu-wrapper .slide-menu-item {
-  border-top: solid 1px #555;
-}
-
-.slide-menu-wrapper .active-menu-panel li.selected {
-  background-color: #222;
-  color: white;
-}
-
-.slide-menu-wrapper .active-menu-panel li.active {
-  color: #eee;
-}
-
-.slide-menu-wrapper .slide-menu-item.no-title .slide-menu-item-title,
-.slide-menu-wrapper .slide-menu-item-vertical.no-title .slide-menu-item-title {
-  font-style: italic;
-}
-
-.slide-menu-wrapper .slide-menu-item-number {
-  color: #999;
-  padding-right: 6px;
-}
-
-.slide-menu-wrapper .slide-menu-item i.far,
-.slide-menu-wrapper .slide-menu-item i.fas,
-.slide-menu-wrapper .slide-menu-item-vertical i.far,
-.slide-menu-wrapper .slide-menu-item-vertical i.fas,
-.slide-menu-wrapper .slide-menu-item svg.svg-inline--fa,
-.slide-menu-wrapper .slide-menu-item-vertical svg.svg-inline--fa {
-  padding-right: 12px;
-  display: none;
-}
-
-.slide-menu-wrapper .slide-menu-item.past i.fas.past,
-.slide-menu-wrapper .slide-menu-item-vertical.past i.fas.past,
-.slide-menu-wrapper .slide-menu-item.active i.fas.active,
-.slide-menu-wrapper .slide-menu-item-vertical.active i.fas.active,
-.slide-menu-wrapper .slide-menu-item.future i.far.future,
-.slide-menu-wrapper .slide-menu-item-vertical.future i.far.future,
-.slide-menu-wrapper .slide-menu-item.past svg.svg-inline--fa.past,
-.slide-menu-wrapper .slide-menu-item-vertical.past svg.svg-inline--fa.past,
-.slide-menu-wrapper .slide-menu-item.active svg.svg-inline--fa.active,
-.slide-menu-wrapper .slide-menu-item-vertical.active svg.svg-inline--fa.active,
-.slide-menu-wrapper .slide-menu-item.future svg.svg-inline--fa.future,
-.slide-menu-wrapper .slide-menu-item-vertical.future svg.svg-inline--fa.future {
-  display: inline-block;
-}
-
-.slide-menu-wrapper .slide-menu-item.past i.fas.past,
-.slide-menu-wrapper .slide-menu-item-vertical.past i.fas.past,
-.slide-menu-wrapper .slide-menu-item.future i.far.future,
-.slide-menu-wrapper .slide-menu-item-vertical.future i.far.future,
-.slide-menu-wrapper .slide-menu-item.past svg.svg-inline--fa.past,
-.slide-menu-wrapper .slide-menu-item-vertical.past svg.svg-inline--fa.past,
-.slide-menu-wrapper .slide-menu-item.future svg.svg-inline--fa.future,
-.slide-menu-wrapper .slide-menu-item-vertical.future svg.svg-inline--fa.future {
-  opacity: 0.4;
-}
-
-.slide-menu-wrapper .slide-menu-item.active i.fas.active,
-.slide-menu-wrapper .slide-menu-item-vertical.active i.fas.active,
-.slide-menu-wrapper .slide-menu-item.active svg.svg-inline--fa.active,
-.slide-menu-wrapper .slide-menu-item-vertical.active svg.svg-inline--fa.active {
-  opacity: 0.8;
-}
-
-.slide-menu-wrapper .slide-menu--left {
-  left: 0;
-  -webkit-transform: translateX(-100%);
-  -ms-transform: translateX(-100%);
-  transform: translateX(-100%);
-}
-
-.slide-menu-wrapper .slide-menu--left.active {
-  -webkit-transform: translateX(0);
-  -ms-transform: translateX(0);
-  transform: translateX(0);
-}
-
-.slide-menu-wrapper .slide-menu--right {
-  right: 0;
-  -webkit-transform: translateX(100%);
-  -ms-transform: translateX(100%);
-  transform: translateX(100%);
-}
-
-.slide-menu-wrapper .slide-menu--right.active {
-  -webkit-transform: translateX(0);
-  -ms-transform: translateX(0);
-  transform: translateX(0);
-}
-
-.slide-menu-wrapper {
-  transition: transform 0.3s;
-}
-
-/*
- * Toolbar
- */
-.slide-menu-wrapper .slide-menu-toolbar {
-  height: 60px;
-  width: 100%;
-  font-size: 12px;
-  display: table;
-  table-layout: fixed; /* ensures equal width */
-  margin: 0;
-  padding: 0;
-  border-bottom: solid 2px #666;
-}
-
-.slide-menu-wrapper .slide-menu-toolbar > li {
-  display: table-cell;
-  line-height: 150%;
-  text-align: center;
-  vertical-align: middle;
-  cursor: pointer;
-  color: #aaa;
-  border-radius: 3px;
-}
-
-.slide-menu-wrapper .slide-menu-toolbar > li.toolbar-panel-button i,
-.slide-menu-wrapper
-  .slide-menu-toolbar
-  > li.toolbar-panel-button
-  svg.svg-inline--fa {
-  font-size: 1.7em;
-}
-
-.slide-menu-wrapper .slide-menu-toolbar > li.active-toolbar-button {
-  color: white;
-  text-shadow: 0 1px black;
-  text-decoration: underline;
-}
-
-.slide-menu-toolbar > li.toolbar-panel-button:hover {
-  color: white;
-}
-
-.slide-menu-toolbar
-  > li.toolbar-panel-button:hover
-  span.slide-menu-toolbar-label,
-.slide-menu-wrapper
-  .slide-menu-toolbar
-  > li.active-toolbar-button
-  span.slide-menu-toolbar-label {
-  visibility: visible;
-}
-
-/*
- * Panels
- */
-.slide-menu-wrapper .slide-menu-panel {
-  position: absolute;
-  width: 100%;
-  visibility: hidden;
-  height: calc(100% - 60px);
-  overflow-x: hidden;
-  overflow-y: auto;
-  color: #aaa;
-}
-
-.slide-menu-wrapper .slide-menu-panel.active-menu-panel {
-  visibility: visible;
-}
-
-.slide-menu-wrapper .slide-menu-panel h1,
-.slide-menu-wrapper .slide-menu-panel h2,
-.slide-menu-wrapper .slide-menu-panel h3,
-.slide-menu-wrapper .slide-menu-panel h4,
-.slide-menu-wrapper .slide-menu-panel h5,
-.slide-menu-wrapper .slide-menu-panel h6 {
-  margin: 20px 0 10px 0;
-  color: #fff;
-  line-height: 1.2;
-  letter-spacing: normal;
-  text-shadow: none;
-}
-
-.slide-menu-wrapper .slide-menu-panel h1 {
-  font-size: 1.6em;
-}
-.slide-menu-wrapper .slide-menu-panel h2 {
-  font-size: 1.4em;
-}
-.slide-menu-wrapper .slide-menu-panel h3 {
-  font-size: 1.3em;
-}
-.slide-menu-wrapper .slide-menu-panel h4 {
-  font-size: 1.1em;
-}
-.slide-menu-wrapper .slide-menu-panel h5 {
-  font-size: 1em;
-}
-.slide-menu-wrapper .slide-menu-panel h6 {
-  font-size: 0.9em;
-}
-
-.slide-menu-wrapper .slide-menu-panel p {
-  margin: 10px 0 5px 0;
-}
-
-.slide-menu-wrapper .slide-menu-panel a {
-  color: #ccc;
-  text-decoration: underline;
-}
-
-.slide-menu-wrapper .slide-menu-panel a:hover {
-  color: white;
-}
-
-.slide-menu-wrapper .slide-menu-item a {
-  text-decoration: none;
-}
-
-.slide-menu-wrapper .slide-menu-custom-panel {
-  width: calc(100% - 20px);
-  padding-left: 10px;
-  padding-right: 10px;
-}
-
-.slide-menu-wrapper .slide-menu-custom-panel .slide-menu-items {
-  width: calc(100% + 20px);
-  margin-left: -10px;
-  margin-right: 10px;
-}
-
-/*
- * Theme and Transitions buttons
- */
-
-.slide-menu-wrapper div[data-panel='Themes'] li,
-.slide-menu-wrapper div[data-panel='Transitions'] li {
-  display: block;
-  text-align: left;
-  cursor: pointer;
-  color: #848484;
-}
-
-/*
- * Menu controls
- */
-.reveal .slide-menu-button {
-  position: fixed;
-  left: 30px;
-  bottom: 30px;
-  z-index: 30;
-  font-size: 24px;
-}
-
-/*
- * Menu overlay
- */
-
-.slide-menu-wrapper .slide-menu-overlay {
-  position: fixed;
-  z-index: 199;
-  top: 0;
-  left: 0;
-  overflow: hidden;
-  width: 0;
-  height: 0;
-  background-color: #000;
-  opacity: 0;
-  transition: opacity 0.3s, width 0s 0.3s, height 0s 0.3s;
-}
-
-.slide-menu-wrapper .slide-menu-overlay.active {
-  width: 100%;
-  height: 100%;
-  opacity: 0.7;
-  transition: opacity 0.3s;
-}
-
-/*
- * Hide menu for pdf printing
- */
-body.print-pdf .slide-menu-wrapper .slide-menu,
-body.print-pdf .reveal .slide-menu-button,
-body.print-pdf .slide-menu-wrapper .slide-menu-overlay {
-  display: none;
-}
+.slide-menu-wrapper {
+  font-family: 'Source Sans Pro', Helvetica, sans-serif;
+}
+
+.slide-menu-wrapper .slide-menu {
+  background-color: #333;
+  z-index: 200;
+  position: fixed;
+  top: 0;
+  width: 300px;
+  height: 100%;
+  /*overflow-y: scroll;*/
+  transition: transform 0.3s;
+  font-size: 16px;
+  font-weight: normal;
+}
+
+.slide-menu-wrapper .slide-menu.slide-menu--wide {
+  width: 500px;
+}
+
+.slide-menu-wrapper .slide-menu.slide-menu--third {
+  width: 33%;
+}
+
+.slide-menu-wrapper .slide-menu.slide-menu--half {
+  width: 50%;
+}
+
+.slide-menu-wrapper .slide-menu.slide-menu--full {
+  width: 95%;
+}
+
+/*
+ * Slides menu
+ */
+
+.slide-menu-wrapper .slide-menu-items {
+  margin: 0;
+  padding: 0;
+  width: 100%;
+  border-bottom: solid 1px #555;
+}
+
+.slide-menu-wrapper .slide-menu-item,
+.slide-menu-wrapper .slide-menu-item-vertical {
+  display: block;
+  text-align: left;
+  padding: 10px 18px;
+  color: #aaa;
+  cursor: pointer;
+}
+
+.slide-menu-wrapper .slide-menu-item-vertical {
+  padding-left: 30px;
+}
+
+.slide-menu-wrapper .slide-menu--wide .slide-menu-item-vertical,
+.slide-menu-wrapper .slide-menu--third .slide-menu-item-vertical,
+.slide-menu-wrapper .slide-menu--half .slide-menu-item-vertical,
+.slide-menu-wrapper .slide-menu--full .slide-menu-item-vertical,
+.slide-menu-wrapper .slide-menu--custom .slide-menu-item-vertical {
+  padding-left: 50px;
+}
+
+.slide-menu-wrapper .slide-menu-item {
+  border-top: solid 1px #555;
+}
+
+.slide-menu-wrapper .active-menu-panel li.selected {
+  background-color: #222;
+  color: white;
+}
+
+.slide-menu-wrapper .active-menu-panel li.active {
+  color: #eee;
+}
+
+.slide-menu-wrapper .slide-menu-item.no-title .slide-menu-item-title,
+.slide-menu-wrapper .slide-menu-item-vertical.no-title .slide-menu-item-title {
+  font-style: italic;
+}
+
+.slide-menu-wrapper .slide-menu-item-number {
+  color: #999;
+  padding-right: 6px;
+}
+
+.slide-menu-wrapper .slide-menu-item i.far,
+.slide-menu-wrapper .slide-menu-item i.fas,
+.slide-menu-wrapper .slide-menu-item-vertical i.far,
+.slide-menu-wrapper .slide-menu-item-vertical i.fas,
+.slide-menu-wrapper .slide-menu-item svg.svg-inline--fa,
+.slide-menu-wrapper .slide-menu-item-vertical svg.svg-inline--fa {
+  padding-right: 12px;
+  display: none;
+}
+
+.slide-menu-wrapper .slide-menu-item.past i.fas.past,
+.slide-menu-wrapper .slide-menu-item-vertical.past i.fas.past,
+.slide-menu-wrapper .slide-menu-item.active i.fas.active,
+.slide-menu-wrapper .slide-menu-item-vertical.active i.fas.active,
+.slide-menu-wrapper .slide-menu-item.future i.far.future,
+.slide-menu-wrapper .slide-menu-item-vertical.future i.far.future,
+.slide-menu-wrapper .slide-menu-item.past svg.svg-inline--fa.past,
+.slide-menu-wrapper .slide-menu-item-vertical.past svg.svg-inline--fa.past,
+.slide-menu-wrapper .slide-menu-item.active svg.svg-inline--fa.active,
+.slide-menu-wrapper .slide-menu-item-vertical.active svg.svg-inline--fa.active,
+.slide-menu-wrapper .slide-menu-item.future svg.svg-inline--fa.future,
+.slide-menu-wrapper .slide-menu-item-vertical.future svg.svg-inline--fa.future {
+  display: inline-block;
+}
+
+.slide-menu-wrapper .slide-menu-item.past i.fas.past,
+.slide-menu-wrapper .slide-menu-item-vertical.past i.fas.past,
+.slide-menu-wrapper .slide-menu-item.future i.far.future,
+.slide-menu-wrapper .slide-menu-item-vertical.future i.far.future,
+.slide-menu-wrapper .slide-menu-item.past svg.svg-inline--fa.past,
+.slide-menu-wrapper .slide-menu-item-vertical.past svg.svg-inline--fa.past,
+.slide-menu-wrapper .slide-menu-item.future svg.svg-inline--fa.future,
+.slide-menu-wrapper .slide-menu-item-vertical.future svg.svg-inline--fa.future {
+  opacity: 0.4;
+}
+
+.slide-menu-wrapper .slide-menu-item.active i.fas.active,
+.slide-menu-wrapper .slide-menu-item-vertical.active i.fas.active,
+.slide-menu-wrapper .slide-menu-item.active svg.svg-inline--fa.active,
+.slide-menu-wrapper .slide-menu-item-vertical.active svg.svg-inline--fa.active {
+  opacity: 0.8;
+}
+
+.slide-menu-wrapper .slide-menu--left {
+  left: 0;
+  -webkit-transform: translateX(-100%);
+  -ms-transform: translateX(-100%);
+  transform: translateX(-100%);
+}
+
+.slide-menu-wrapper .slide-menu--left.active {
+  -webkit-transform: translateX(0);
+  -ms-transform: translateX(0);
+  transform: translateX(0);
+}
+
+.slide-menu-wrapper .slide-menu--right {
+  right: 0;
+  -webkit-transform: translateX(100%);
+  -ms-transform: translateX(100%);
+  transform: translateX(100%);
+}
+
+.slide-menu-wrapper .slide-menu--right.active {
+  -webkit-transform: translateX(0);
+  -ms-transform: translateX(0);
+  transform: translateX(0);
+}
+
+.slide-menu-wrapper {
+  transition: transform 0.3s;
+}
+
+/*
+ * Toolbar
+ */
+.slide-menu-wrapper .slide-menu-toolbar {
+  height: 60px;
+  width: 100%;
+  font-size: 12px;
+  display: table;
+  table-layout: fixed; /* ensures equal width */
+  margin: 0;
+  padding: 0;
+  border-bottom: solid 2px #666;
+}
+
+.slide-menu-wrapper .slide-menu-toolbar > li {
+  display: table-cell;
+  line-height: 150%;
+  text-align: center;
+  vertical-align: middle;
+  cursor: pointer;
+  color: #aaa;
+  border-radius: 3px;
+}
+
+.slide-menu-wrapper .slide-menu-toolbar > li.toolbar-panel-button i,
+.slide-menu-wrapper
+  .slide-menu-toolbar
+  > li.toolbar-panel-button
+  svg.svg-inline--fa {
+  font-size: 1.7em;
+}
+
+.slide-menu-wrapper .slide-menu-toolbar > li.active-toolbar-button {
+  color: white;
+  text-shadow: 0 1px black;
+  text-decoration: underline;
+}
+
+.slide-menu-toolbar > li.toolbar-panel-button:hover {
+  color: white;
+}
+
+.slide-menu-toolbar
+  > li.toolbar-panel-button:hover
+  span.slide-menu-toolbar-label,
+.slide-menu-wrapper
+  .slide-menu-toolbar
+  > li.active-toolbar-button
+  span.slide-menu-toolbar-label {
+  visibility: visible;
+}
+
+/*
+ * Panels
+ */
+.slide-menu-wrapper .slide-menu-panel {
+  position: absolute;
+  width: 100%;
+  visibility: hidden;
+  height: calc(100% - 60px);
+  overflow-x: hidden;
+  overflow-y: auto;
+  color: #aaa;
+}
+
+.slide-menu-wrapper .slide-menu-panel.active-menu-panel {
+  visibility: visible;
+}
+
+.slide-menu-wrapper .slide-menu-panel h1,
+.slide-menu-wrapper .slide-menu-panel h2,
+.slide-menu-wrapper .slide-menu-panel h3,
+.slide-menu-wrapper .slide-menu-panel h4,
+.slide-menu-wrapper .slide-menu-panel h5,
+.slide-menu-wrapper .slide-menu-panel h6 {
+  margin: 20px 0 10px 0;
+  color: #fff;
+  line-height: 1.2;
+  letter-spacing: normal;
+  text-shadow: none;
+}
+
+.slide-menu-wrapper .slide-menu-panel h1 {
+  font-size: 1.6em;
+}
+.slide-menu-wrapper .slide-menu-panel h2 {
+  font-size: 1.4em;
+}
+.slide-menu-wrapper .slide-menu-panel h3 {
+  font-size: 1.3em;
+}
+.slide-menu-wrapper .slide-menu-panel h4 {
+  font-size: 1.1em;
+}
+.slide-menu-wrapper .slide-menu-panel h5 {
+  font-size: 1em;
+}
+.slide-menu-wrapper .slide-menu-panel h6 {
+  font-size: 0.9em;
+}
+
+.slide-menu-wrapper .slide-menu-panel p {
+  margin: 10px 0 5px 0;
+}
+
+.slide-menu-wrapper .slide-menu-panel a {
+  color: #ccc;
+  text-decoration: underline;
+}
+
+.slide-menu-wrapper .slide-menu-panel a:hover {
+  color: white;
+}
+
+.slide-menu-wrapper .slide-menu-item a {
+  text-decoration: none;
+}
+
+.slide-menu-wrapper .slide-menu-custom-panel {
+  width: calc(100% - 20px);
+  padding-left: 10px;
+  padding-right: 10px;
+}
+
+.slide-menu-wrapper .slide-menu-custom-panel .slide-menu-items {
+  width: calc(100% + 20px);
+  margin-left: -10px;
+  margin-right: 10px;
+}
+
+/*
+ * Theme and Transitions buttons
+ */
+
+.slide-menu-wrapper div[data-panel='Themes'] li,
+.slide-menu-wrapper div[data-panel='Transitions'] li {
+  display: block;
+  text-align: left;
+  cursor: pointer;
+  color: #848484;
+}
+
+/*
+ * Menu controls
+ */
+.reveal .slide-menu-button {
+  position: fixed;
+  left: 30px;
+  bottom: 30px;
+  z-index: 30;
+  font-size: 24px;
+}
+
+/*
+ * Menu overlay
+ */
+
+.slide-menu-wrapper .slide-menu-overlay {
+  position: fixed;
+  z-index: 199;
+  top: 0;
+  left: 0;
+  overflow: hidden;
+  width: 0;
+  height: 0;
+  background-color: #000;
+  opacity: 0;
+  transition: opacity 0.3s, width 0s 0.3s, height 0s 0.3s;
+}
+
+.slide-menu-wrapper .slide-menu-overlay.active {
+  width: 100%;
+  height: 100%;
+  opacity: 0.7;
+  transition: opacity 0.3s;
+}
+
+/*
+ * Hide menu for pdf printing
+ */
+body.print-pdf .slide-menu-wrapper .slide-menu,
+body.print-pdf .reveal .slide-menu-button,
+body.print-pdf .slide-menu-wrapper .slide-menu-overlay {
+  display: none;
+}
diff --git a/docs/site_libs/revealjs/plugin/reveal-menu/menu.js b/docs/site_libs/revealjs/plugin/reveal-menu/menu.js
index 5369df3..d89082a 100644
--- a/docs/site_libs/revealjs/plugin/reveal-menu/menu.js
+++ b/docs/site_libs/revealjs/plugin/reveal-menu/menu.js
@@ -1 +1 @@
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0===r.transitions&&(r.transitions=!1),!0===r.transitions?r.transitions=["None","Fade","Slide","Convex","Concave","Zoom"]:!1===r.transitions||Array.isArray(r.transitions)&&r.transitions.every((function(e){return"string"==typeof e}))||(console.error("reveal.js-menu error: transitions config value must be 'true' or an array of strings, eg ['None', 'Fade', 'Slide')"),r.transitions=!1),i&&i<=9&&(r.transitions=!1),void 0===r.openButton&&(r.openButton=!0),void 0===r.openSlideNumber&&(r.openSlideNumber=!1),void 0===r.keyboard&&(r.keyboard=!0),void 0===r.sticky&&(r.sticky=!1),void 0===r.autoOpen&&(r.autoOpen=!0),void 0===r.delayInit&&(r.delayInit=!1),void 0===r.openOnInit&&(r.openOnInit=!1)}var s=!0;function l(){s=!1}function c(){O("nav.slide-menu").addEventListener("mousemove",(function e(t){O("nav.slide-menu").removeEventListener("mousemove",e),s=!0}))}function u(e){var t=function(e){for(var t=0,n=0;e&&!isNaN(e.offsetLeft)&&!isNaN(e.offsetTop);)t+=e.offsetLeft-e.scrollLeft,n+=e.offsetTop-e.scrollTop,e=e.offsetParent;return{top:n,left:t}}(e).top-e.offsetParent.offsetTop;if(t<0)return-t;var n=e.offsetParent.offsetHeight-(e.offsetTop-e.offsetParent.scrollTop+e.offsetHeight);return n<0?n:0}function f(e){var t=u(e);t&&(l(),e.scrollIntoView(t>0),c())}function d(e){l(),e.offsetParent.scrollTop=e.offsetTop,c()}function p(e){l(),e.offsetParent.scrollTop=e.offsetTop-e.offsetParent.offsetHeight+e.offsetHeight,c()}function h(e){e.classList.add("selected"),f(e),r.sticky&&r.autoOpen&&E(e)}function m(e){if(b())switch(e.stopImmediatePropagation(),e.keyCode){case 72:case 37:!function(){var e=parseInt(O(".active-toolbar-button").getAttribute("data-button"))-1;e<0&&(e=T-1);S(null,O('.toolbar-panel-button[data-button="'+e+'"]').getAttribute("data-panel"))}();break;case 76:case 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li.slide-menu-item"))&&h(o);break;case 33:case 85:var t=A(".active-menu-panel .slide-menu-items li").filter((function(e){return u(e)>0})),n=A(".active-menu-panel .slide-menu-items li").filter((function(e){return 0==u(e)})),r=t.length>0&&Math.abs(u(t[t.length-1]))0&&(p(r),r=(n=A(".active-menu-panel .slide-menu-items li").filter((function(e){return 0==u(e)})))[0]==r?t[t.length-1]:n[0]),A(".active-menu-panel .slide-menu-items li").forEach((function(e){e.classList.remove("selected")})),h(r),d(r));break;case 34:case 68:n=A(".active-menu-panel .slide-menu-items li").filter((function(e){return 0==u(e)}));var i=A(".active-menu-panel .slide-menu-items li").filter((function(e){return u(e)<0})),a=i.length>0&&Math.abs(u(i[0]))0&&(d(a),a=(n=A(".active-menu-panel .slide-menu-items li").filter((function(e){return 0==u(e)})))[n.length-1]==a?i[0]:n[n.length-1]),A(".active-menu-panel .slide-menu-items li").forEach((function(e){e.classList.remove("selected")})),h(a),p(a));break;case 36:A(".active-menu-panel .slide-menu-items li").forEach((function(e){e.classList.remove("selected")})),(o=O(".active-menu-panel .slide-menu-items li:first-of-type"))&&(o.classList.add("selected"),f(o));break;case 35:var o;A(".active-menu-panel .slide-menu-items li").forEach((function(e){e.classList.remove("selected")})),(o=O(".active-menu-panel .slide-menu-items:last-of-type li:last-of-type"))&&(o.classList.add("selected"),f(o));break;case 32:case 13:var s;(s=O(".active-menu-panel .slide-menu-items li.selected"))&&E(s,!0);break;case 27:g(null,!0)}var l}function v(e){(e&&e.preventDefault(),b())||(O("body").classList.add("slide-menu-active"),O(".reveal").classList.add("has-"+r.effect+"-"+r.side),O(".slide-menu").classList.add("active"),O(".slide-menu-overlay").classList.add("active"),r.themes&&(A('div[data-panel="Themes"] 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li.slide-menu-item-vertical").forEach((function(t){t.classList.remove("past"),t.classList.remove("active"),t.classList.remove("future");var n=parseInt(t.getAttribute("data-slide-h")),r=parseInt(t.getAttribute("data-slide-v"));n",s.appendChild(k("br"),O("i",s)),s.appendChild(k("span",{class:"slide-menu-toolbar-label"},e),O("i",s)),s.onclick=i,d.appendChild(s),s},i=function(e,i,a,o,s){function l(e,t){if(""===e)return null;var n=t?O(e,i):O(e);return n?n.textContent:null}var c=i.getAttribute("data-menu-title")||l(".menu-title",i)||l(r.titleSelector,i);if(!c&&r.useTextContentForMissingTitles&&(c=i.textContent.trim())&&(c=c.split("\n").map((function(e){return e.trim()})).join(" ").trim().replace(/^(.{16}[^\s]*).*/,"$1").replace(/&/g,"&").replace(//g,">").replace(/"/g,""").replace(/'/g,"'")+"..."),!c){if(r.hideMissingTitles)return"";e+=" no-title",c="Slide "+(a+1)}var u=k("li",{class:e,"data-item":a,"data-slide-h":o,"data-slide-v":void 0===s?0:s});if(r.markers&&(u.appendChild(k("i",{class:"fas fa-check-circle fa-fw past"})),u.appendChild(k("i",{class:"fas fa-arrow-alt-circle-right fa-fw active"})),u.appendChild(k("i",{class:"far fa-circle fa-fw future"}))),r.numbers){var f=[],d="h.v";switch("string"==typeof r.numbers?d=r.numbers:"string"==typeof n.slideNumber&&(d=n.slideNumber),d){case"c":f.push(a+1);break;case"c/t":f.push(a+1,"/",t.getTotalSlides());break;case"h/v":f.push(o+1),"number"!=typeof s||isNaN(s)||f.push("/",s+1);break;default:f.push(o+1),"number"!=typeof s||isNaN(s)||f.push(".",s+1)}u.appendChild(k("span",{class:"slide-menu-item-number"},f.join("")+". "))}return u.appendChild(k("span",{class:"slide-menu-item-title"},c)),u},o=function(e){s&&(A(".active-menu-panel .slide-menu-items li.selected").forEach((function(e){e.classList.remove("selected")})),e.currentTarget.classList.add("selected"))},l=O(".reveal").parentElement,c=k("div",{class:"slide-menu-wrapper"});l.appendChild(c);var u=k("nav",{class:"slide-menu slide-menu--"+r.side});"string"==typeof r.width&&(-1!=["normal","wide","third","half","full"].indexOf(r.width)?u.classList.add("slide-menu--"+r.width):(u.classList.add("slide-menu--custom"),u.style.width=r.width)),c.appendChild(u),L();var f=k("div",{class:"slide-menu-overlay"});c.appendChild(f),f.onclick=function(){g(null,!0)};var d=k("ol",{class:"slide-menu-toolbar"});O(".slide-menu").appendChild(d),e("Slides","Slides","fa-images","fas",S,!0),r.custom&&r.custom.forEach((function(t,n,r){e(t.title,"Custom"+n,t.icon,null,S)})),r.themes&&e("Themes","Themes","fa-adjust","fas",S),r.transitions&&e("Transitions","Transitions","fa-sticky-note","fas",S);var p=k("li",{id:"close",class:"toolbar-panel-button"});if(p.appendChild(k("i",{class:"fas fa-times"})),p.appendChild(k("br")),p.appendChild(k("span",{class:"slide-menu-toolbar-label"},"Close")),p.onclick=function(){g(null,!0)},d.appendChild(p),function e(){if(document.querySelector("section[data-markdown]:not([data-markdown-parsed])"))setTimeout(e,100);else{var t=k("div",{"data-panel":"Slides",class:"slide-menu-panel active-menu-panel"});t.appendChild(k("ul",{class:"slide-menu-items"})),u.appendChild(t);var n=O('.slide-menu-panel[data-panel="Slides"] > .slide-menu-items'),r=0;A(".slides > section").forEach((function(e,t){var a=A("section",e);if(a.length>0)a.forEach((function(e,a){var o=i(0===a?"slide-menu-item":"slide-menu-item-vertical",e,r,t,a);o&&n.appendChild(o),r++}));else{var o=i("slide-menu-item",e,r,t);o&&n.appendChild(o),r++}})),A(".slide-menu-item, .slide-menu-item-vertical").forEach((function(e){e.onclick=x})),w()}}(),t.addEventListener("slidechanged",w),r.custom){var h=function(){this.status>=200&&this.status<300?(this.panel.innerHTML=this.responseText,C(this.panel)):I(this)},E=function(){I(this)},C=function(e){A("ul.slide-menu-items li.slide-menu-item",e).forEach((function(e,t){e.setAttribute("data-item",t+1),e.onclick=x,e.addEventListener("mouseenter",o)}))},I=function(e){var t="
    ERROR: The attempt to fetch "+e.responseURL+" failed with HTTP status "+e.status+" ("+e.statusText+").
    Remember that you need to serve the presentation HTML from a HTTP server.
    ";e.panel.innerHTML=t};r.custom.forEach((function(e,t,n){var r=k("div",{"data-panel":"Custom"+t,class:"slide-menu-panel slide-menu-custom-panel"});e.content?(r.innerHTML=e.content,C(r)):e.src&&function(e,t){var n=new XMLHttpRequest;n.panel=e,n.arguments=Array.prototype.slice.call(arguments,2),n.onload=h,n.onerror=E,n.open("get",t,!0),n.send(null)}(r,e.src),u.appendChild(r)}))}if(r.themes){var P=k("div",{class:"slide-menu-panel","data-panel":"Themes"});u.appendChild(P);var M=k("ul",{class:"slide-menu-items"});P.appendChild(M),r.themes.forEach((function(e,t){var n={class:"slide-menu-item","data-item":""+(t+1)};e.theme&&(n["data-theme"]=e.theme),e.highlightTheme&&(n["data-highlight-theme"]=e.highlightTheme);var r=k("li",n,e.name);M.appendChild(r),r.onclick=x}))}if(r.transitions){P=k("div",{class:"slide-menu-panel","data-panel":"Transitions"});u.appendChild(P);M=k("ul",{class:"slide-menu-items"});P.appendChild(M),r.transitions.forEach((function(e,t){var n=k("li",{class:"slide-menu-item","data-transition":e.toLowerCase(),"data-item":""+(t+1)},e);M.appendChild(n),n.onclick=x}))}if(r.openButton){var R=k("div",{class:"slide-menu-button"}),j=k("a",{href:"#"});j.appendChild(k("i",{class:"fas fa-bars"})),R.appendChild(j),O(".reveal").appendChild(R),R.onclick=v}if(r.openSlideNumber)O("div.slide-number").onclick=v;A(".slide-menu-panel .slide-menu-items li").forEach((function(e){e.addEventListener("mouseenter",o)}))}if(r.keyboard){if(document.addEventListener("keydown",m,!1),window.addEventListener("message",(function(e){var t;try{t=JSON.parse(e.data)}catch(e){}t&&"triggerKey"===t.method&&m({keyCode:t.args[0],stopImmediatePropagation:function(){}})})),n.keyboardCondition&&"function"==typeof n.keyboardCondition){var N=n.keyboardCondition;n.keyboardCondition=function(e){return N(e)&&(!b()||77==e.keyCode)}}else n.keyboardCondition=function(e){return!b()||77==e.keyCode};t.addKeyBinding({keyCode:77,key:"M",description:"Toggle menu"},y)}r.openOnInit&&v(),a=!0}function O(e,t){return t||(t=document),t.querySelector(e)}function A(e,t){return t||(t=document),Array.prototype.slice.call(t.querySelectorAll(e))}function k(e,t,n){var r=document.createElement(e);return t&&Object.getOwnPropertyNames(t).forEach((function(e){r.setAttribute(e,t[e])})),n&&(r.innerHTML=n),r}function I(e,t){var n=O("link#"+e),r=n.parentElement,i=n.nextElementSibling;n.remove();var a=n.cloneNode();a.setAttribute("href",t),a.onload=function(){L()},r.insertBefore(a,i)}function P(e,t,n){n.call()}function M(){var e,a,o,s=!i||i>=9;t.isSpeakerNotes()&&window.location.search.endsWith("controls=false")&&(s=!1),s&&(r.delayInit||C(),e="menu-ready",(o=document.createEvent("HTMLEvents",1,2)).initEvent(e,!0,!0),function(e,t){for(var n in t)e[n]=t[n]}(o,a),document.querySelector(".reveal").dispatchEvent(o),n.postMessageEvents&&window.parent!==window.self&&window.parent.postMessage(JSON.stringify({namespace:"reveal",eventName:e,state:t.getState()}),"*"))}return{id:"menu",init:function(e){o(n=(t=e).getConfig()),P(r.path+"menu.css","stylesheet",(function(){void 0===r.loadIcons||r.loadIcons?P(r.path+"font-awesome/css/all.css","stylesheet",M):M()}))},toggle:y,openMenu:v,closeMenu:g,openPanel:S,isOpen:b,initialiseMenu:C,isMenuInitialised:function(){return a}}}}));
diff --git a/docs/site_libs/revealjs/plugin/reveal-menu/plugin.yml b/docs/site_libs/revealjs/plugin/reveal-menu/plugin.yml
index 3f4b90a..de1c0bc 100644
--- a/docs/site_libs/revealjs/plugin/reveal-menu/plugin.yml
+++ b/docs/site_libs/revealjs/plugin/reveal-menu/plugin.yml
@@ -1,9 +1,9 @@
-name: RevealMenu
-script: [menu.js, quarto-menu.js]
-stylesheet: [menu.css, quarto-menu.css]
-config:
-  menu:
-    side: "left"
-    useTextContentForMissingTitles: true
-    markers: false
-    loadIcons: false
+name: RevealMenu
+script: [menu.js, quarto-menu.js]
+stylesheet: [menu.css, quarto-menu.css]
+config:
+  menu:
+    side: "left"
+    useTextContentForMissingTitles: true
+    markers: false
+    loadIcons: false
diff --git a/docs/site_libs/revealjs/plugin/reveal-menu/quarto-menu.css b/docs/site_libs/revealjs/plugin/reveal-menu/quarto-menu.css
index eec145c..16bf2c5 100644
--- a/docs/site_libs/revealjs/plugin/reveal-menu/quarto-menu.css
+++ b/docs/site_libs/revealjs/plugin/reveal-menu/quarto-menu.css
@@ -1,68 +1,68 @@
-.slide-menu-wrapper .slide-tool-item {
-  display: block;
-  text-align: left;
-  padding: 10px 18px;
-  color: #aaa;
-  cursor: pointer;
-  border-top: solid 1px #555;
-}
-
-.slide-menu-wrapper .slide-tool-item a {
-  text-decoration: none;
-}
-
-.slide-menu-wrapper .slide-tool-item kbd {
-  font-family: monospace;
-  margin-right: 10px;
-  padding: 3px 8px;
-  color: inherit;
-  border: 1px solid;
-  border-radius: 5px;
-  border-color: #555;
-}
-
-.slide-menu-wrapper .slide-menu-toolbar > li.active-toolbar-button {
-  text-decoration: none;
-}
-
-.reveal .slide-menu-button {
-  left: 8px;
-  bottom: 8px;
-}
-
-.reveal .slide-menu-button .fas::before,
-.reveal .slide-chalkboard-buttons .fas::before,
-.slide-menu-wrapper .slide-menu-toolbar .fas::before {
-  display: inline-block;
-  height: 2.2rem;
-  width: 2.2rem;
-  content: "";
-  vertical-align: -0.125em;
-  background-repeat: no-repeat;
-  background-size: 2.2rem 2.2rem;
-}
-
-.reveal .slide-chalkboard-buttons .fas::before {
-  height: 1.45rem;
-  width: 1.45rem;
-  background-size: 1.45rem 1.45rem;
-  vertical-align: 0.1em;
-}
-
-.slide-menu-wrapper .slide-menu-toolbar .fas::before {
-  height: 1.8rem;
-  width: 1.8rem;
-  background-size: 1.8rem 1.8rem;
-}
-
-.slide-menu-wrapper .slide-menu-toolbar .fa-images::before {
-  background-image: url('data:image/svg+xml,');
-}
-
-.slide-menu-wrapper .slide-menu-toolbar .fa-gear::before {
-  background-image: url('data:image/svg+xml,');
-}
-
-.slide-menu-wrapper .slide-menu-toolbar .fa-times::before {
-  background-image: url('data:image/svg+xml,');
-}
+.slide-menu-wrapper .slide-tool-item {
+  display: block;
+  text-align: left;
+  padding: 10px 18px;
+  color: #aaa;
+  cursor: pointer;
+  border-top: solid 1px #555;
+}
+
+.slide-menu-wrapper .slide-tool-item a {
+  text-decoration: none;
+}
+
+.slide-menu-wrapper .slide-tool-item kbd {
+  font-family: monospace;
+  margin-right: 10px;
+  padding: 3px 8px;
+  color: inherit;
+  border: 1px solid;
+  border-radius: 5px;
+  border-color: #555;
+}
+
+.slide-menu-wrapper .slide-menu-toolbar > li.active-toolbar-button {
+  text-decoration: none;
+}
+
+.reveal .slide-menu-button {
+  left: 8px;
+  bottom: 8px;
+}
+
+.reveal .slide-menu-button .fas::before,
+.reveal .slide-chalkboard-buttons .fas::before,
+.slide-menu-wrapper .slide-menu-toolbar .fas::before {
+  display: inline-block;
+  height: 2.2rem;
+  width: 2.2rem;
+  content: "";
+  vertical-align: -0.125em;
+  background-repeat: no-repeat;
+  background-size: 2.2rem 2.2rem;
+}
+
+.reveal .slide-chalkboard-buttons .fas::before {
+  height: 1.45rem;
+  width: 1.45rem;
+  background-size: 1.45rem 1.45rem;
+  vertical-align: 0.1em;
+}
+
+.slide-menu-wrapper .slide-menu-toolbar .fas::before {
+  height: 1.8rem;
+  width: 1.8rem;
+  background-size: 1.8rem 1.8rem;
+}
+
+.slide-menu-wrapper .slide-menu-toolbar .fa-images::before {
+  background-image: url('data:image/svg+xml,');
+}
+
+.slide-menu-wrapper .slide-menu-toolbar .fa-gear::before {
+  background-image: url('data:image/svg+xml,');
+}
+
+.slide-menu-wrapper .slide-menu-toolbar .fa-times::before {
+  background-image: url('data:image/svg+xml,');
+}
diff --git a/docs/site_libs/revealjs/plugin/reveal-menu/quarto-menu.js b/docs/site_libs/revealjs/plugin/reveal-menu/quarto-menu.js
index e5c53c4..3b143df 100644
--- a/docs/site_libs/revealjs/plugin/reveal-menu/quarto-menu.js
+++ b/docs/site_libs/revealjs/plugin/reveal-menu/quarto-menu.js
@@ -1,46 +1,46 @@
-window.revealMenuToolHandler = function (handler) {
-  return function (event) {
-    event.preventDefault();
-    handler();
-    Reveal.getPlugin("menu").closeMenu();
-  };
-};
-
-window.RevealMenuToolHandlers = {
-  fullscreen: revealMenuToolHandler(function () {
-    const element = document.documentElement;
-    const requestMethod =
-      element.requestFullscreen ||
-      element.webkitRequestFullscreen ||
-      element.webkitRequestFullScreen ||
-      element.mozRequestFullScreen ||
-      element.msRequestFullscreen;
-    if (requestMethod) {
-      requestMethod.apply(element);
-    }
-  }),
-  speakerMode: revealMenuToolHandler(function () {
-    Reveal.getPlugin("notes").open();
-  }),
-  keyboardHelp: revealMenuToolHandler(function () {
-    Reveal.toggleHelp(true);
-  }),
-  overview: revealMenuToolHandler(function () {
-    Reveal.toggleOverview(true);
-  }),
-  toggleChalkboard: revealMenuToolHandler(function () {
-    RevealChalkboard.toggleChalkboard();
-  }),
-  toggleNotesCanvas: revealMenuToolHandler(function () {
-    RevealChalkboard.toggleNotesCanvas();
-  }),
-  downloadDrawings: revealMenuToolHandler(function () {
-    RevealChalkboard.download();
-  }),
-  togglePdfExport: revealMenuToolHandler(function () {
-    PdfExport.togglePdfExport();
-  }),
-  toggleScrollView: revealMenuToolHandler(function() {
-    Reveal.getPlugin("quarto-support").toggleScrollView();
-  })
-};
+window.revealMenuToolHandler = function (handler) {
+  return function (event) {
+    event.preventDefault();
+    handler();
+    Reveal.getPlugin("menu").closeMenu();
+  };
+};
+
+window.RevealMenuToolHandlers = {
+  fullscreen: revealMenuToolHandler(function () {
+    const element = document.documentElement;
+    const requestMethod =
+      element.requestFullscreen ||
+      element.webkitRequestFullscreen ||
+      element.webkitRequestFullScreen ||
+      element.mozRequestFullScreen ||
+      element.msRequestFullscreen;
+    if (requestMethod) {
+      requestMethod.apply(element);
+    }
+  }),
+  speakerMode: revealMenuToolHandler(function () {
+    Reveal.getPlugin("notes").open();
+  }),
+  keyboardHelp: revealMenuToolHandler(function () {
+    Reveal.toggleHelp(true);
+  }),
+  overview: revealMenuToolHandler(function () {
+    Reveal.toggleOverview(true);
+  }),
+  toggleChalkboard: revealMenuToolHandler(function () {
+    RevealChalkboard.toggleChalkboard();
+  }),
+  toggleNotesCanvas: revealMenuToolHandler(function () {
+    RevealChalkboard.toggleNotesCanvas();
+  }),
+  downloadDrawings: revealMenuToolHandler(function () {
+    RevealChalkboard.download();
+  }),
+  togglePdfExport: revealMenuToolHandler(function () {
+    PdfExport.togglePdfExport();
+  }),
+  toggleScrollView: revealMenuToolHandler(function() {
+    Reveal.getPlugin("quarto-support").toggleScrollView();
+  })
+};
diff --git a/docs/site_libs/revealjs/plugin/search/plugin.js b/docs/site_libs/revealjs/plugin/search/plugin.js
index fe38343..5cdca96 100644
--- a/docs/site_libs/revealjs/plugin/search/plugin.js
+++ b/docs/site_libs/revealjs/plugin/search/plugin.js
@@ -1,243 +1,243 @@
-/*!
- * Handles finding a text string anywhere in the slides and showing the next occurrence to the user
- * by navigatating to that slide and highlighting it.
- *
- * @author Jon Snyder , February 2013
- */
-
-const Plugin = () => {
-
-	// The reveal.js instance this plugin is attached to
-	let deck;
-
-	let searchElement;
-	let searchButton;
-	let searchInput;
-
-	let matchedSlides;
-	let currentMatchedIndex;
-	let searchboxDirty;
-	let hilitor;
-
-	function render() {
-
-		searchElement = document.createElement( 'div' );
-		searchElement.classList.add( 'searchbox' );
-		searchElement.style.position = 'absolute';
-		searchElement.style.top = '10px';
-		searchElement.style.right = '10px';
-		searchElement.style.zIndex = 10;
-
-		//embedded base64 search icon Designed by Sketchdock - http://www.sketchdock.com/:
-		searchElement.innerHTML = `
-		`;
-
-		searchInput = searchElement.querySelector( '.searchinput' );
-		searchInput.style.width = '240px';
-		searchInput.style.fontSize = '14px';
-		searchInput.style.padding = '4px 6px';
-		searchInput.style.color = '#000';
-		searchInput.style.background = '#fff';
-		searchInput.style.borderRadius = '2px';
-		searchInput.style.border = '0';
-		searchInput.style.outline = '0';
-		searchInput.style.boxShadow = '0 2px 18px rgba(0, 0, 0, 0.2)';
-		searchInput.style['-webkit-appearance']  = 'none';
-
-		deck.getRevealElement().appendChild( searchElement );
-
-		// searchButton.addEventListener( 'click', function(event) {
-		// 	doSearch();
-		// }, false );
-
-		searchInput.addEventListener( 'keyup', function( event ) {
-			switch (event.keyCode) {
-				case 13:
-					event.preventDefault();
-					doSearch();
-					searchboxDirty = false;
-					break;
-				default:
-					searchboxDirty = true;
-			}
-		}, false );
-
-		closeSearch();
-
-	}
-
-	function openSearch() {
-		if( !searchElement ) render();
-
-		searchElement.style.display = 'inline';
-		searchInput.focus();
-		searchInput.select();
-	}
-
-	function closeSearch() {
-		if( !searchElement ) render();
-
-		searchElement.style.display = 'none';
-		if(hilitor) hilitor.remove();
-	}
-
-	function toggleSearch() {
-		if( !searchElement ) render();
-
-		if (searchElement.style.display !== 'inline') {
-			openSearch();
-		}
-		else {
-			closeSearch();
-		}
-	}
-
-	function doSearch() {
-		//if there's been a change in the search term, perform a new search:
-		if (searchboxDirty) {
-			var searchstring = searchInput.value;
-
-			if (searchstring === '') {
-				if(hilitor) hilitor.remove();
-				matchedSlides = null;
-			}
-			else {
-				//find the keyword amongst the slides
-				hilitor = new Hilitor("slidecontent");
-				matchedSlides = hilitor.apply(searchstring);
-				currentMatchedIndex = 0;
-			}
-		}
-
-		if (matchedSlides) {
-			//navigate to the next slide that has the keyword, wrapping to the first if necessary
-			if (matchedSlides.length && (matchedSlides.length <= currentMatchedIndex)) {
-				currentMatchedIndex = 0;
-			}
-			if (matchedSlides.length > currentMatchedIndex) {
-				deck.slide(matchedSlides[currentMatchedIndex].h, matchedSlides[currentMatchedIndex].v);
-				currentMatchedIndex++;
-			}
-		}
-	}
-
-	// Original JavaScript code by Chirp Internet: www.chirp.com.au
-	// Please acknowledge use of this code by including this header.
-	// 2/2013 jon: modified regex to display any match, not restricted to word boundaries.
-	function Hilitor(id, tag) {
-
-		var targetNode = document.getElementById(id) || document.body;
-		var hiliteTag = tag || "EM";
-		var skipTags = new RegExp("^(?:" + hiliteTag + "|SCRIPT|FORM)$");
-		var colors = ["#ff6", "#a0ffff", "#9f9", "#f99", "#f6f"];
-		var wordColor = [];
-		var colorIdx = 0;
-		var matchRegex = "";
-		var matchingSlides = [];
-
-		this.setRegex = function(input)
-		{
-			input = input.trim();
-			matchRegex = new RegExp("(" + input + ")","i");
-		}
-
-		this.getRegex = function()
-		{
-			return matchRegex.toString().replace(/^\/\\b\(|\)\\b\/i$/g, "").replace(/\|/g, " ");
-		}
-
-		// recursively apply word highlighting
-		this.hiliteWords = function(node)
-		{
-			if(node == undefined || !node) return;
-			if(!matchRegex) return;
-			if(skipTags.test(node.nodeName)) return;
-
-			if(node.hasChildNodes()) {
-				for(var i=0; i < node.childNodes.length; i++)
-					this.hiliteWords(node.childNodes[i]);
-			}
-			if(node.nodeType == 3) { // NODE_TEXT
-				var nv, regs;
-				if((nv = node.nodeValue) && (regs = matchRegex.exec(nv))) {
-					//find the slide's section element and save it in our list of matching slides
-					var secnode = node;
-					while (secnode != null && secnode.nodeName != 'SECTION') {
-						secnode = secnode.parentNode;
-					}
-
-					var slideIndex = deck.getIndices(secnode);
-					var slidelen = matchingSlides.length;
-					var alreadyAdded = false;
-					for (var i=0; i < slidelen; i++) {
-						if ( (matchingSlides[i].h === slideIndex.h) && (matchingSlides[i].v === slideIndex.v) ) {
-							alreadyAdded = true;
-						}
-					}
-					if (! alreadyAdded) {
-						matchingSlides.push(slideIndex);
-					}
-
-					if(!wordColor[regs[0].toLowerCase()]) {
-						wordColor[regs[0].toLowerCase()] = colors[colorIdx++ % colors.length];
-					}
-
-					var match = document.createElement(hiliteTag);
-					match.appendChild(document.createTextNode(regs[0]));
-					match.style.backgroundColor = wordColor[regs[0].toLowerCase()];
-					match.style.fontStyle = "inherit";
-					match.style.color = "#000";
-
-					var after = node.splitText(regs.index);
-					after.nodeValue = after.nodeValue.substring(regs[0].length);
-					node.parentNode.insertBefore(match, after);
-				}
-			}
-		};
-
-		// remove highlighting
-		this.remove = function()
-		{
-			var arr = document.getElementsByTagName(hiliteTag);
-			var el;
-			while(arr.length && (el = arr[0])) {
-				el.parentNode.replaceChild(el.firstChild, el);
-			}
-		};
-
-		// start highlighting at target node
-		this.apply = function(input)
-		{
-			if(input == undefined || !input) return;
-			this.remove();
-			this.setRegex(input);
-			this.hiliteWords(targetNode);
-			return matchingSlides;
-		};
-
-	}
-
-	return {
-
-		id: 'search',
-
-		init: reveal => {
-
-			deck = reveal;
-			deck.registerKeyboardShortcut( 'CTRL + Shift + F', 'Search' );
-
-			document.addEventListener( 'keydown', function( event ) {
-				if( event.key == "F" && (event.ctrlKey || event.metaKey) ) { //Control+Shift+f
-					event.preventDefault();
-					toggleSearch();
-				}
-			}, false );
-
-		},
-
-		open: openSearch
-
-	}
-};
-
+/*!
+ * Handles finding a text string anywhere in the slides and showing the next occurrence to the user
+ * by navigatating to that slide and highlighting it.
+ *
+ * @author Jon Snyder , February 2013
+ */
+
+const Plugin = () => {
+
+	// The reveal.js instance this plugin is attached to
+	let deck;
+
+	let searchElement;
+	let searchButton;
+	let searchInput;
+
+	let matchedSlides;
+	let currentMatchedIndex;
+	let searchboxDirty;
+	let hilitor;
+
+	function render() {
+
+		searchElement = document.createElement( 'div' );
+		searchElement.classList.add( 'searchbox' );
+		searchElement.style.position = 'absolute';
+		searchElement.style.top = '10px';
+		searchElement.style.right = '10px';
+		searchElement.style.zIndex = 10;
+
+		//embedded base64 search icon Designed by Sketchdock - http://www.sketchdock.com/:
+		searchElement.innerHTML = `
+		`;
+
+		searchInput = searchElement.querySelector( '.searchinput' );
+		searchInput.style.width = '240px';
+		searchInput.style.fontSize = '14px';
+		searchInput.style.padding = '4px 6px';
+		searchInput.style.color = '#000';
+		searchInput.style.background = '#fff';
+		searchInput.style.borderRadius = '2px';
+		searchInput.style.border = '0';
+		searchInput.style.outline = '0';
+		searchInput.style.boxShadow = '0 2px 18px rgba(0, 0, 0, 0.2)';
+		searchInput.style['-webkit-appearance']  = 'none';
+
+		deck.getRevealElement().appendChild( searchElement );
+
+		// searchButton.addEventListener( 'click', function(event) {
+		// 	doSearch();
+		// }, false );
+
+		searchInput.addEventListener( 'keyup', function( event ) {
+			switch (event.keyCode) {
+				case 13:
+					event.preventDefault();
+					doSearch();
+					searchboxDirty = false;
+					break;
+				default:
+					searchboxDirty = true;
+			}
+		}, false );
+
+		closeSearch();
+
+	}
+
+	function openSearch() {
+		if( !searchElement ) render();
+
+		searchElement.style.display = 'inline';
+		searchInput.focus();
+		searchInput.select();
+	}
+
+	function closeSearch() {
+		if( !searchElement ) render();
+
+		searchElement.style.display = 'none';
+		if(hilitor) hilitor.remove();
+	}
+
+	function toggleSearch() {
+		if( !searchElement ) render();
+
+		if (searchElement.style.display !== 'inline') {
+			openSearch();
+		}
+		else {
+			closeSearch();
+		}
+	}
+
+	function doSearch() {
+		//if there's been a change in the search term, perform a new search:
+		if (searchboxDirty) {
+			var searchstring = searchInput.value;
+
+			if (searchstring === '') {
+				if(hilitor) hilitor.remove();
+				matchedSlides = null;
+			}
+			else {
+				//find the keyword amongst the slides
+				hilitor = new Hilitor("slidecontent");
+				matchedSlides = hilitor.apply(searchstring);
+				currentMatchedIndex = 0;
+			}
+		}
+
+		if (matchedSlides) {
+			//navigate to the next slide that has the keyword, wrapping to the first if necessary
+			if (matchedSlides.length && (matchedSlides.length <= currentMatchedIndex)) {
+				currentMatchedIndex = 0;
+			}
+			if (matchedSlides.length > currentMatchedIndex) {
+				deck.slide(matchedSlides[currentMatchedIndex].h, matchedSlides[currentMatchedIndex].v);
+				currentMatchedIndex++;
+			}
+		}
+	}
+
+	// Original JavaScript code by Chirp Internet: www.chirp.com.au
+	// Please acknowledge use of this code by including this header.
+	// 2/2013 jon: modified regex to display any match, not restricted to word boundaries.
+	function Hilitor(id, tag) {
+
+		var targetNode = document.getElementById(id) || document.body;
+		var hiliteTag = tag || "EM";
+		var skipTags = new RegExp("^(?:" + hiliteTag + "|SCRIPT|FORM)$");
+		var colors = ["#ff6", "#a0ffff", "#9f9", "#f99", "#f6f"];
+		var wordColor = [];
+		var colorIdx = 0;
+		var matchRegex = "";
+		var matchingSlides = [];
+
+		this.setRegex = function(input)
+		{
+			input = input.trim();
+			matchRegex = new RegExp("(" + input + ")","i");
+		}
+
+		this.getRegex = function()
+		{
+			return matchRegex.toString().replace(/^\/\\b\(|\)\\b\/i$/g, "").replace(/\|/g, " ");
+		}
+
+		// recursively apply word highlighting
+		this.hiliteWords = function(node)
+		{
+			if(node == undefined || !node) return;
+			if(!matchRegex) return;
+			if(skipTags.test(node.nodeName)) return;
+
+			if(node.hasChildNodes()) {
+				for(var i=0; i < node.childNodes.length; i++)
+					this.hiliteWords(node.childNodes[i]);
+			}
+			if(node.nodeType == 3) { // NODE_TEXT
+				var nv, regs;
+				if((nv = node.nodeValue) && (regs = matchRegex.exec(nv))) {
+					//find the slide's section element and save it in our list of matching slides
+					var secnode = node;
+					while (secnode != null && secnode.nodeName != 'SECTION') {
+						secnode = secnode.parentNode;
+					}
+
+					var slideIndex = deck.getIndices(secnode);
+					var slidelen = matchingSlides.length;
+					var alreadyAdded = false;
+					for (var i=0; i < slidelen; i++) {
+						if ( (matchingSlides[i].h === slideIndex.h) && (matchingSlides[i].v === slideIndex.v) ) {
+							alreadyAdded = true;
+						}
+					}
+					if (! alreadyAdded) {
+						matchingSlides.push(slideIndex);
+					}
+
+					if(!wordColor[regs[0].toLowerCase()]) {
+						wordColor[regs[0].toLowerCase()] = colors[colorIdx++ % colors.length];
+					}
+
+					var match = document.createElement(hiliteTag);
+					match.appendChild(document.createTextNode(regs[0]));
+					match.style.backgroundColor = wordColor[regs[0].toLowerCase()];
+					match.style.fontStyle = "inherit";
+					match.style.color = "#000";
+
+					var after = node.splitText(regs.index);
+					after.nodeValue = after.nodeValue.substring(regs[0].length);
+					node.parentNode.insertBefore(match, after);
+				}
+			}
+		};
+
+		// remove highlighting
+		this.remove = function()
+		{
+			var arr = document.getElementsByTagName(hiliteTag);
+			var el;
+			while(arr.length && (el = arr[0])) {
+				el.parentNode.replaceChild(el.firstChild, el);
+			}
+		};
+
+		// start highlighting at target node
+		this.apply = function(input)
+		{
+			if(input == undefined || !input) return;
+			this.remove();
+			this.setRegex(input);
+			this.hiliteWords(targetNode);
+			return matchingSlides;
+		};
+
+	}
+
+	return {
+
+		id: 'search',
+
+		init: reveal => {
+
+			deck = reveal;
+			deck.registerKeyboardShortcut( 'CTRL + Shift + F', 'Search' );
+
+			document.addEventListener( 'keydown', function( event ) {
+				if( event.key == "F" && (event.ctrlKey || event.metaKey) ) { //Control+Shift+f
+					event.preventDefault();
+					toggleSearch();
+				}
+			}, false );
+
+		},
+
+		open: openSearch
+
+	}
+};
+
 export default Plugin;
\ No newline at end of file
diff --git a/docs/site_libs/revealjs/plugin/search/search.esm.js b/docs/site_libs/revealjs/plugin/search/search.esm.js
index df84b6b..9ba9e1d 100644
--- a/docs/site_libs/revealjs/plugin/search/search.esm.js
+++ b/docs/site_libs/revealjs/plugin/search/search.esm.js
@@ -1,7 +1,7 @@
-/*!
- * Handles finding a text string anywhere in the slides and showing the next occurrence to the user
- * by navigatating to that slide and highlighting it.
- *
- * @author Jon Snyder , February 2013
- */
-const e=()=>{let e,t,n,l,i,o,r;function s(){t=document.createElement("div"),t.classList.add("searchbox"),t.style.position="absolute",t.style.top="10px",t.style.right="10px",t.style.zIndex=10,t.innerHTML='\n\t\t',n=t.querySelector(".searchinput"),n.style.width="240px",n.style.fontSize="14px",n.style.padding="4px 6px",n.style.color="#000",n.style.background="#fff",n.style.borderRadius="2px",n.style.border="0",n.style.outline="0",n.style.boxShadow="0 2px 18px rgba(0, 0, 0, 0.2)",n.style["-webkit-appearance"]="none",e.getRevealElement().appendChild(t),n.addEventListener("keyup",(function(t){if(13===t.keyCode)t.preventDefault(),function(){if(o){var t=n.value;""===t?(r&&r.remove(),l=null):(r=new c("slidecontent"),l=r.apply(t),i=0)}l&&(l.length&&l.length<=i&&(i=0),l.length>i&&(e.slide(l[i].h,l[i].v),i++))}(),o=!1;else o=!0}),!1),d()}function a(){t||s(),t.style.display="inline",n.focus(),n.select()}function d(){t||s(),t.style.display="none",r&&r.remove()}function c(t,n){var l=document.getElementById(t)||document.body,i=n||"EM",o=new RegExp("^(?:"+i+"|SCRIPT|FORM)$"),r=["#ff6","#a0ffff","#9f9","#f99","#f6f"],s=[],a=0,d="",c=[];this.setRegex=function(e){e=e.trim(),d=new RegExp("("+e+")","i")},this.getRegex=function(){return d.toString().replace(/^\/\\b\(|\)\\b\/i$/g,"").replace(/\|/g," ")},this.hiliteWords=function(t){if(null!=t&&t&&d&&!o.test(t.nodeName)){if(t.hasChildNodes())for(var n=0;n{e=n,e.registerKeyboardShortcut("CTRL + Shift + F","Search"),document.addEventListener("keydown",(function(e){"F"==e.key&&(e.ctrlKey||e.metaKey)&&(e.preventDefault(),t||s(),"inline"!==t.style.display?a():d())}),!1)},open:a}};export{e as default};
+/*!
+ * Handles finding a text string anywhere in the slides and showing the next occurrence to the user
+ * by navigatating to that slide and highlighting it.
+ *
+ * @author Jon Snyder , February 2013
+ */
+const e=()=>{let e,t,n,l,i,o,r;function s(){t=document.createElement("div"),t.classList.add("searchbox"),t.style.position="absolute",t.style.top="10px",t.style.right="10px",t.style.zIndex=10,t.innerHTML='\n\t\t',n=t.querySelector(".searchinput"),n.style.width="240px",n.style.fontSize="14px",n.style.padding="4px 6px",n.style.color="#000",n.style.background="#fff",n.style.borderRadius="2px",n.style.border="0",n.style.outline="0",n.style.boxShadow="0 2px 18px rgba(0, 0, 0, 0.2)",n.style["-webkit-appearance"]="none",e.getRevealElement().appendChild(t),n.addEventListener("keyup",(function(t){if(13===t.keyCode)t.preventDefault(),function(){if(o){var t=n.value;""===t?(r&&r.remove(),l=null):(r=new c("slidecontent"),l=r.apply(t),i=0)}l&&(l.length&&l.length<=i&&(i=0),l.length>i&&(e.slide(l[i].h,l[i].v),i++))}(),o=!1;else o=!0}),!1),d()}function a(){t||s(),t.style.display="inline",n.focus(),n.select()}function d(){t||s(),t.style.display="none",r&&r.remove()}function c(t,n){var l=document.getElementById(t)||document.body,i=n||"EM",o=new RegExp("^(?:"+i+"|SCRIPT|FORM)$"),r=["#ff6","#a0ffff","#9f9","#f99","#f6f"],s=[],a=0,d="",c=[];this.setRegex=function(e){e=e.trim(),d=new RegExp("("+e+")","i")},this.getRegex=function(){return d.toString().replace(/^\/\\b\(|\)\\b\/i$/g,"").replace(/\|/g," ")},this.hiliteWords=function(t){if(null!=t&&t&&d&&!o.test(t.nodeName)){if(t.hasChildNodes())for(var n=0;n{e=n,e.registerKeyboardShortcut("CTRL + Shift + F","Search"),document.addEventListener("keydown",(function(e){"F"==e.key&&(e.ctrlKey||e.metaKey)&&(e.preventDefault(),t||s(),"inline"!==t.style.display?a():d())}),!1)},open:a}};export{e as default};
diff --git a/docs/site_libs/revealjs/plugin/search/search.js b/docs/site_libs/revealjs/plugin/search/search.js
index aa3ad93..5a2191b 100644
--- a/docs/site_libs/revealjs/plugin/search/search.js
+++ b/docs/site_libs/revealjs/plugin/search/search.js
@@ -1,7 +1,7 @@
-!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?module.exports=t():"function"==typeof define&&define.amd?define(t):(e="undefined"!=typeof globalThis?globalThis:e||self).RevealSearch=t()}(this,(function(){"use strict";
-/*!
-	 * Handles finding a text string anywhere in the slides and showing the next occurrence to the user
-	 * by navigatating to that slide and highlighting it.
-	 *
-	 * @author Jon Snyder , February 2013
-	 */return()=>{let e,t,n,i,o,l,r;function s(){t=document.createElement("div"),t.classList.add("searchbox"),t.style.position="absolute",t.style.top="10px",t.style.right="10px",t.style.zIndex=10,t.innerHTML='\n\t\t',n=t.querySelector(".searchinput"),n.style.width="240px",n.style.fontSize="14px",n.style.padding="4px 6px",n.style.color="#000",n.style.background="#fff",n.style.borderRadius="2px",n.style.border="0",n.style.outline="0",n.style.boxShadow="0 2px 18px rgba(0, 0, 0, 0.2)",n.style["-webkit-appearance"]="none",e.getRevealElement().appendChild(t),n.addEventListener("keyup",(function(t){if(13===t.keyCode)t.preventDefault(),function(){if(l){var t=n.value;""===t?(r&&r.remove(),i=null):(r=new c("slidecontent"),i=r.apply(t),o=0)}i&&(i.length&&i.length<=o&&(o=0),i.length>o&&(e.slide(i[o].h,i[o].v),o++))}(),l=!1;else l=!0}),!1),d()}function a(){t||s(),t.style.display="inline",n.focus(),n.select()}function d(){t||s(),t.style.display="none",r&&r.remove()}function c(t,n){var i=document.getElementById(t)||document.body,o=n||"EM",l=new RegExp("^(?:"+o+"|SCRIPT|FORM)$"),r=["#ff6","#a0ffff","#9f9","#f99","#f6f"],s=[],a=0,d="",c=[];this.setRegex=function(e){e=e.trim(),d=new RegExp("("+e+")","i")},this.getRegex=function(){return d.toString().replace(/^\/\\b\(|\)\\b\/i$/g,"").replace(/\|/g," ")},this.hiliteWords=function(t){if(null!=t&&t&&d&&!l.test(t.nodeName)){if(t.hasChildNodes())for(var n=0;n{e=n,e.registerKeyboardShortcut("CTRL + Shift + F","Search"),document.addEventListener("keydown",(function(e){"F"==e.key&&(e.ctrlKey||e.metaKey)&&(e.preventDefault(),t||s(),"inline"!==t.style.display?a():d())}),!1)},open:a}}}));
+!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?module.exports=t():"function"==typeof define&&define.amd?define(t):(e="undefined"!=typeof globalThis?globalThis:e||self).RevealSearch=t()}(this,(function(){"use strict";
+/*!
+	 * Handles finding a text string anywhere in the slides and showing the next occurrence to the user
+	 * by navigatating to that slide and highlighting it.
+	 *
+	 * @author Jon Snyder , February 2013
+	 */return()=>{let e,t,n,i,o,l,r;function s(){t=document.createElement("div"),t.classList.add("searchbox"),t.style.position="absolute",t.style.top="10px",t.style.right="10px",t.style.zIndex=10,t.innerHTML='\n\t\t',n=t.querySelector(".searchinput"),n.style.width="240px",n.style.fontSize="14px",n.style.padding="4px 6px",n.style.color="#000",n.style.background="#fff",n.style.borderRadius="2px",n.style.border="0",n.style.outline="0",n.style.boxShadow="0 2px 18px rgba(0, 0, 0, 0.2)",n.style["-webkit-appearance"]="none",e.getRevealElement().appendChild(t),n.addEventListener("keyup",(function(t){if(13===t.keyCode)t.preventDefault(),function(){if(l){var t=n.value;""===t?(r&&r.remove(),i=null):(r=new c("slidecontent"),i=r.apply(t),o=0)}i&&(i.length&&i.length<=o&&(o=0),i.length>o&&(e.slide(i[o].h,i[o].v),o++))}(),l=!1;else l=!0}),!1),d()}function a(){t||s(),t.style.display="inline",n.focus(),n.select()}function d(){t||s(),t.style.display="none",r&&r.remove()}function c(t,n){var i=document.getElementById(t)||document.body,o=n||"EM",l=new RegExp("^(?:"+o+"|SCRIPT|FORM)$"),r=["#ff6","#a0ffff","#9f9","#f99","#f6f"],s=[],a=0,d="",c=[];this.setRegex=function(e){e=e.trim(),d=new RegExp("("+e+")","i")},this.getRegex=function(){return d.toString().replace(/^\/\\b\(|\)\\b\/i$/g,"").replace(/\|/g," ")},this.hiliteWords=function(t){if(null!=t&&t&&d&&!l.test(t.nodeName)){if(t.hasChildNodes())for(var n=0;n{e=n,e.registerKeyboardShortcut("CTRL + Shift + F","Search"),document.addEventListener("keydown",(function(e){"F"==e.key&&(e.ctrlKey||e.metaKey)&&(e.preventDefault(),t||s(),"inline"!==t.style.display?a():d())}),!1)},open:a}}}));
diff --git a/docs/site_libs/revealjs/plugin/zoom/plugin.js b/docs/site_libs/revealjs/plugin/zoom/plugin.js
index 960fb81..5a8bfd7 100644
--- a/docs/site_libs/revealjs/plugin/zoom/plugin.js
+++ b/docs/site_libs/revealjs/plugin/zoom/plugin.js
@@ -1,264 +1,264 @@
-/*!
- * reveal.js Zoom plugin
- */
-const Plugin = {
-
-	id: 'zoom',
-
-	init: function( reveal ) {
-
-		reveal.getRevealElement().addEventListener( 'mousedown', function( event ) {
-			var defaultModifier = /Linux/.test( window.navigator.platform ) ? 'ctrl' : 'alt';
-
-			var modifier = ( reveal.getConfig().zoomKey ? reveal.getConfig().zoomKey : defaultModifier ) + 'Key';
-			var zoomLevel = ( reveal.getConfig().zoomLevel ? reveal.getConfig().zoomLevel : 2 );
-
-			if( event[ modifier ] && !reveal.isOverview() ) {
-				event.preventDefault();
-
-				zoom.to({
-					x: event.clientX,
-					y: event.clientY,
-					scale: zoomLevel,
-					pan: false
-				});
-			}
-		} );
-
-	},
-
-	destroy: () => {
-
-		zoom.reset();
-
-	}
-
-};
-
-export default () => Plugin;
-
-/*!
- * zoom.js 0.3 (modified for use with reveal.js)
- * http://lab.hakim.se/zoom-js
- * MIT licensed
- *
- * Copyright (C) 2011-2014 Hakim El Hattab, http://hakim.se
- */
-var zoom = (function(){
-
-	// The current zoom level (scale)
-	var level = 1;
-
-	// The current mouse position, used for panning
-	var mouseX = 0,
-		mouseY = 0;
-
-	// Timeout before pan is activated
-	var panEngageTimeout = -1,
-		panUpdateInterval = -1;
-
-	// Check for transform support so that we can fallback otherwise
-	var supportsTransforms = 	'transform' in document.body.style;
-
-	if( supportsTransforms ) {
-		// The easing that will be applied when we zoom in/out
-		document.body.style.transition = 'transform 0.8s ease';
-	}
-
-	// Zoom out if the user hits escape
-	document.addEventListener( 'keyup', function( event ) {
-		if( level !== 1 && event.keyCode === 27 ) {
-			zoom.out();
-		}
-	} );
-
-	// Monitor mouse movement for panning
-	document.addEventListener( 'mousemove', function( event ) {
-		if( level !== 1 ) {
-			mouseX = event.clientX;
-			mouseY = event.clientY;
-		}
-	} );
-
-	/**
-	 * Applies the CSS required to zoom in, prefers the use of CSS3
-	 * transforms but falls back on zoom for IE.
-	 *
-	 * @param {Object} rect
-	 * @param {Number} scale
-	 */
-	function magnify( rect, scale ) {
-
-		var scrollOffset = getScrollOffset();
-
-		// Ensure a width/height is set
-		rect.width = rect.width || 1;
-		rect.height = rect.height || 1;
-
-		// Center the rect within the zoomed viewport
-		rect.x -= ( window.innerWidth - ( rect.width * scale ) ) / 2;
-		rect.y -= ( window.innerHeight - ( rect.height * scale ) ) / 2;
-
-		if( supportsTransforms ) {
-			// Reset
-			if( scale === 1 ) {
-				document.body.style.transform = '';
-			}
-			// Scale
-			else {
-				var origin = scrollOffset.x +'px '+ scrollOffset.y +'px',
-					transform = 'translate('+ -rect.x +'px,'+ -rect.y +'px) scale('+ scale +')';
-
-				document.body.style.transformOrigin = origin;
-				document.body.style.transform = transform;
-			}
-		}
-		else {
-			// Reset
-			if( scale === 1 ) {
-				document.body.style.position = '';
-				document.body.style.left = '';
-				document.body.style.top = '';
-				document.body.style.width = '';
-				document.body.style.height = '';
-				document.body.style.zoom = '';
-			}
-			// Scale
-			else {
-				document.body.style.position = 'relative';
-				document.body.style.left = ( - ( scrollOffset.x + rect.x ) / scale ) + 'px';
-				document.body.style.top = ( - ( scrollOffset.y + rect.y ) / scale ) + 'px';
-				document.body.style.width = ( scale * 100 ) + '%';
-				document.body.style.height = ( scale * 100 ) + '%';
-				document.body.style.zoom = scale;
-			}
-		}
-
-		level = scale;
-
-		if( document.documentElement.classList ) {
-			if( level !== 1 ) {
-				document.documentElement.classList.add( 'zoomed' );
-			}
-			else {
-				document.documentElement.classList.remove( 'zoomed' );
-			}
-		}
-	}
-
-	/**
-	 * Pan the document when the mosue cursor approaches the edges
-	 * of the window.
-	 */
-	function pan() {
-		var range = 0.12,
-			rangeX = window.innerWidth * range,
-			rangeY = window.innerHeight * range,
-			scrollOffset = getScrollOffset();
-
-		// Up
-		if( mouseY < rangeY ) {
-			window.scroll( scrollOffset.x, scrollOffset.y - ( 1 - ( mouseY / rangeY ) ) * ( 14 / level ) );
-		}
-		// Down
-		else if( mouseY > window.innerHeight - rangeY ) {
-			window.scroll( scrollOffset.x, scrollOffset.y + ( 1 - ( window.innerHeight - mouseY ) / rangeY ) * ( 14 / level ) );
-		}
-
-		// Left
-		if( mouseX < rangeX ) {
-			window.scroll( scrollOffset.x - ( 1 - ( mouseX / rangeX ) ) * ( 14 / level ), scrollOffset.y );
-		}
-		// Right
-		else if( mouseX > window.innerWidth - rangeX ) {
-			window.scroll( scrollOffset.x + ( 1 - ( window.innerWidth - mouseX ) / rangeX ) * ( 14 / level ), scrollOffset.y );
-		}
-	}
-
-	function getScrollOffset() {
-		return {
-			x: window.scrollX !== undefined ? window.scrollX : window.pageXOffset,
-			y: window.scrollY !== undefined ? window.scrollY : window.pageYOffset
-		}
-	}
-
-	return {
-		/**
-		 * Zooms in on either a rectangle or HTML element.
-		 *
-		 * @param {Object} options
-		 *   - element: HTML element to zoom in on
-		 *   OR
-		 *   - x/y: coordinates in non-transformed space to zoom in on
-		 *   - width/height: the portion of the screen to zoom in on
-		 *   - scale: can be used instead of width/height to explicitly set scale
-		 */
-		to: function( options ) {
-
-			// Due to an implementation limitation we can't zoom in
-			// to another element without zooming out first
-			if( level !== 1 ) {
-				zoom.out();
-			}
-			else {
-				options.x = options.x || 0;
-				options.y = options.y || 0;
-
-				// If an element is set, that takes precedence
-				if( !!options.element ) {
-					// Space around the zoomed in element to leave on screen
-					var padding = 20;
-					var bounds = options.element.getBoundingClientRect();
-
-					options.x = bounds.left - padding;
-					options.y = bounds.top - padding;
-					options.width = bounds.width + ( padding * 2 );
-					options.height = bounds.height + ( padding * 2 );
-				}
-
-				// If width/height values are set, calculate scale from those values
-				if( options.width !== undefined && options.height !== undefined ) {
-					options.scale = Math.max( Math.min( window.innerWidth / options.width, window.innerHeight / options.height ), 1 );
-				}
-
-				if( options.scale > 1 ) {
-					options.x *= options.scale;
-					options.y *= options.scale;
-
-					magnify( options, options.scale );
-
-					if( options.pan !== false ) {
-
-						// Wait with engaging panning as it may conflict with the
-						// zoom transition
-						panEngageTimeout = setTimeout( function() {
-							panUpdateInterval = setInterval( pan, 1000 / 60 );
-						}, 800 );
-
-					}
-				}
-			}
-		},
-
-		/**
-		 * Resets the document zoom state to its default.
-		 */
-		out: function() {
-			clearTimeout( panEngageTimeout );
-			clearInterval( panUpdateInterval );
-
-			magnify( { x: 0, y: 0 }, 1 );
-
-			level = 1;
-		},
-
-		// Alias
-		magnify: function( options ) { this.to( options ) },
-		reset: function() { this.out() },
-
-		zoomLevel: function() {
-			return level;
-		}
-	}
-
-})();
+/*!
+ * reveal.js Zoom plugin
+ */
+const Plugin = {
+
+	id: 'zoom',
+
+	init: function( reveal ) {
+
+		reveal.getRevealElement().addEventListener( 'mousedown', function( event ) {
+			var defaultModifier = /Linux/.test( window.navigator.platform ) ? 'ctrl' : 'alt';
+
+			var modifier = ( reveal.getConfig().zoomKey ? reveal.getConfig().zoomKey : defaultModifier ) + 'Key';
+			var zoomLevel = ( reveal.getConfig().zoomLevel ? reveal.getConfig().zoomLevel : 2 );
+
+			if( event[ modifier ] && !reveal.isOverview() ) {
+				event.preventDefault();
+
+				zoom.to({
+					x: event.clientX,
+					y: event.clientY,
+					scale: zoomLevel,
+					pan: false
+				});
+			}
+		} );
+
+	},
+
+	destroy: () => {
+
+		zoom.reset();
+
+	}
+
+};
+
+export default () => Plugin;
+
+/*!
+ * zoom.js 0.3 (modified for use with reveal.js)
+ * http://lab.hakim.se/zoom-js
+ * MIT licensed
+ *
+ * Copyright (C) 2011-2014 Hakim El Hattab, http://hakim.se
+ */
+var zoom = (function(){
+
+	// The current zoom level (scale)
+	var level = 1;
+
+	// The current mouse position, used for panning
+	var mouseX = 0,
+		mouseY = 0;
+
+	// Timeout before pan is activated
+	var panEngageTimeout = -1,
+		panUpdateInterval = -1;
+
+	// Check for transform support so that we can fallback otherwise
+	var supportsTransforms = 	'transform' in document.body.style;
+
+	if( supportsTransforms ) {
+		// The easing that will be applied when we zoom in/out
+		document.body.style.transition = 'transform 0.8s ease';
+	}
+
+	// Zoom out if the user hits escape
+	document.addEventListener( 'keyup', function( event ) {
+		if( level !== 1 && event.keyCode === 27 ) {
+			zoom.out();
+		}
+	} );
+
+	// Monitor mouse movement for panning
+	document.addEventListener( 'mousemove', function( event ) {
+		if( level !== 1 ) {
+			mouseX = event.clientX;
+			mouseY = event.clientY;
+		}
+	} );
+
+	/**
+	 * Applies the CSS required to zoom in, prefers the use of CSS3
+	 * transforms but falls back on zoom for IE.
+	 *
+	 * @param {Object} rect
+	 * @param {Number} scale
+	 */
+	function magnify( rect, scale ) {
+
+		var scrollOffset = getScrollOffset();
+
+		// Ensure a width/height is set
+		rect.width = rect.width || 1;
+		rect.height = rect.height || 1;
+
+		// Center the rect within the zoomed viewport
+		rect.x -= ( window.innerWidth - ( rect.width * scale ) ) / 2;
+		rect.y -= ( window.innerHeight - ( rect.height * scale ) ) / 2;
+
+		if( supportsTransforms ) {
+			// Reset
+			if( scale === 1 ) {
+				document.body.style.transform = '';
+			}
+			// Scale
+			else {
+				var origin = scrollOffset.x +'px '+ scrollOffset.y +'px',
+					transform = 'translate('+ -rect.x +'px,'+ -rect.y +'px) scale('+ scale +')';
+
+				document.body.style.transformOrigin = origin;
+				document.body.style.transform = transform;
+			}
+		}
+		else {
+			// Reset
+			if( scale === 1 ) {
+				document.body.style.position = '';
+				document.body.style.left = '';
+				document.body.style.top = '';
+				document.body.style.width = '';
+				document.body.style.height = '';
+				document.body.style.zoom = '';
+			}
+			// Scale
+			else {
+				document.body.style.position = 'relative';
+				document.body.style.left = ( - ( scrollOffset.x + rect.x ) / scale ) + 'px';
+				document.body.style.top = ( - ( scrollOffset.y + rect.y ) / scale ) + 'px';
+				document.body.style.width = ( scale * 100 ) + '%';
+				document.body.style.height = ( scale * 100 ) + '%';
+				document.body.style.zoom = scale;
+			}
+		}
+
+		level = scale;
+
+		if( document.documentElement.classList ) {
+			if( level !== 1 ) {
+				document.documentElement.classList.add( 'zoomed' );
+			}
+			else {
+				document.documentElement.classList.remove( 'zoomed' );
+			}
+		}
+	}
+
+	/**
+	 * Pan the document when the mosue cursor approaches the edges
+	 * of the window.
+	 */
+	function pan() {
+		var range = 0.12,
+			rangeX = window.innerWidth * range,
+			rangeY = window.innerHeight * range,
+			scrollOffset = getScrollOffset();
+
+		// Up
+		if( mouseY < rangeY ) {
+			window.scroll( scrollOffset.x, scrollOffset.y - ( 1 - ( mouseY / rangeY ) ) * ( 14 / level ) );
+		}
+		// Down
+		else if( mouseY > window.innerHeight - rangeY ) {
+			window.scroll( scrollOffset.x, scrollOffset.y + ( 1 - ( window.innerHeight - mouseY ) / rangeY ) * ( 14 / level ) );
+		}
+
+		// Left
+		if( mouseX < rangeX ) {
+			window.scroll( scrollOffset.x - ( 1 - ( mouseX / rangeX ) ) * ( 14 / level ), scrollOffset.y );
+		}
+		// Right
+		else if( mouseX > window.innerWidth - rangeX ) {
+			window.scroll( scrollOffset.x + ( 1 - ( window.innerWidth - mouseX ) / rangeX ) * ( 14 / level ), scrollOffset.y );
+		}
+	}
+
+	function getScrollOffset() {
+		return {
+			x: window.scrollX !== undefined ? window.scrollX : window.pageXOffset,
+			y: window.scrollY !== undefined ? window.scrollY : window.pageYOffset
+		}
+	}
+
+	return {
+		/**
+		 * Zooms in on either a rectangle or HTML element.
+		 *
+		 * @param {Object} options
+		 *   - element: HTML element to zoom in on
+		 *   OR
+		 *   - x/y: coordinates in non-transformed space to zoom in on
+		 *   - width/height: the portion of the screen to zoom in on
+		 *   - scale: can be used instead of width/height to explicitly set scale
+		 */
+		to: function( options ) {
+
+			// Due to an implementation limitation we can't zoom in
+			// to another element without zooming out first
+			if( level !== 1 ) {
+				zoom.out();
+			}
+			else {
+				options.x = options.x || 0;
+				options.y = options.y || 0;
+
+				// If an element is set, that takes precedence
+				if( !!options.element ) {
+					// Space around the zoomed in element to leave on screen
+					var padding = 20;
+					var bounds = options.element.getBoundingClientRect();
+
+					options.x = bounds.left - padding;
+					options.y = bounds.top - padding;
+					options.width = bounds.width + ( padding * 2 );
+					options.height = bounds.height + ( padding * 2 );
+				}
+
+				// If width/height values are set, calculate scale from those values
+				if( options.width !== undefined && options.height !== undefined ) {
+					options.scale = Math.max( Math.min( window.innerWidth / options.width, window.innerHeight / options.height ), 1 );
+				}
+
+				if( options.scale > 1 ) {
+					options.x *= options.scale;
+					options.y *= options.scale;
+
+					magnify( options, options.scale );
+
+					if( options.pan !== false ) {
+
+						// Wait with engaging panning as it may conflict with the
+						// zoom transition
+						panEngageTimeout = setTimeout( function() {
+							panUpdateInterval = setInterval( pan, 1000 / 60 );
+						}, 800 );
+
+					}
+				}
+			}
+		},
+
+		/**
+		 * Resets the document zoom state to its default.
+		 */
+		out: function() {
+			clearTimeout( panEngageTimeout );
+			clearInterval( panUpdateInterval );
+
+			magnify( { x: 0, y: 0 }, 1 );
+
+			level = 1;
+		},
+
+		// Alias
+		magnify: function( options ) { this.to( options ) },
+		reset: function() { this.out() },
+
+		zoomLevel: function() {
+			return level;
+		}
+	}
+
+})();
diff --git a/docs/site_libs/revealjs/plugin/zoom/zoom.esm.js b/docs/site_libs/revealjs/plugin/zoom/zoom.esm.js
index c2bb6a5..8543e2f 100644
--- a/docs/site_libs/revealjs/plugin/zoom/zoom.esm.js
+++ b/docs/site_libs/revealjs/plugin/zoom/zoom.esm.js
@@ -1,11 +1,11 @@
-/*!
- * reveal.js Zoom plugin
- */
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-/*!
- * zoom.js 0.3 (modified for use with reveal.js)
- * http://lab.hakim.se/zoom-js
- * MIT licensed
- *
- * Copyright (C) 2011-2014 Hakim El Hattab, http://hakim.se
- */export{t as default};
+/*!
+ * reveal.js Zoom plugin
+ */
+const e={id:"zoom",init:function(e){e.getRevealElement().addEventListener("mousedown",(function(t){var n=/Linux/.test(window.navigator.platform)?"ctrl":"alt",i=(e.getConfig().zoomKey?e.getConfig().zoomKey:n)+"Key",d=e.getConfig().zoomLevel?e.getConfig().zoomLevel:2;t[i]&&!e.isOverview()&&(t.preventDefault(),o.to({x:t.clientX,y:t.clientY,scale:d,pan:!1}))}))},destroy:()=>{o.reset()}};var t=()=>e,o=function(){var e=1,t=0,n=0,i=-1,d=-1,l="transform"in document.body.style;function s(t,o){var n=r();if(t.width=t.width||1,t.height=t.height||1,t.x-=(window.innerWidth-t.width*o)/2,t.y-=(window.innerHeight-t.height*o)/2,l)if(1===o)document.body.style.transform="";else{var i=n.x+"px "+n.y+"px",d="translate("+-t.x+"px,"+-t.y+"px) scale("+o+")";document.body.style.transformOrigin=i,document.body.style.transform=d}else 1===o?(document.body.style.position="",document.body.style.left="",document.body.style.top="",document.body.style.width="",document.body.style.height="",document.body.style.zoom=""):(document.body.style.position="relative",document.body.style.left=-(n.x+t.x)/o+"px",document.body.style.top=-(n.y+t.y)/o+"px",document.body.style.width=100*o+"%",document.body.style.height=100*o+"%",document.body.style.zoom=o);e=o,document.documentElement.classList&&(1!==e?document.documentElement.classList.add("zoomed"):document.documentElement.classList.remove("zoomed"))}function c(){var o=.12*window.innerWidth,i=.12*window.innerHeight,d=r();nwindow.innerHeight-i&&window.scroll(d.x,d.y+(1-(window.innerHeight-n)/i)*(14/e)),twindow.innerWidth-o&&window.scroll(d.x+(1-(window.innerWidth-t)/o)*(14/e),d.y)}function r(){return{x:void 0!==window.scrollX?window.scrollX:window.pageXOffset,y:void 0!==window.scrollY?window.scrollY:window.pageYOffset}}return l&&(document.body.style.transition="transform 0.8s ease"),document.addEventListener("keyup",(function(t){1!==e&&27===t.keyCode&&o.out()})),document.addEventListener("mousemove",(function(o){1!==e&&(t=o.clientX,n=o.clientY)})),{to:function(t){if(1!==e)o.out();else{if(t.x=t.x||0,t.y=t.y||0,t.element){var n=t.element.getBoundingClientRect();t.x=n.left-20,t.y=n.top-20,t.width=n.width+40,t.height=n.height+40}void 0!==t.width&&void 0!==t.height&&(t.scale=Math.max(Math.min(window.innerWidth/t.width,window.innerHeight/t.height),1)),t.scale>1&&(t.x*=t.scale,t.y*=t.scale,s(t,t.scale),!1!==t.pan&&(i=setTimeout((function(){d=setInterval(c,1e3/60)}),800)))}},out:function(){clearTimeout(i),clearInterval(d),s({x:0,y:0},1),e=1},magnify:function(e){this.to(e)},reset:function(){this.out()},zoomLevel:function(){return e}}}();
+/*!
+ * zoom.js 0.3 (modified for use with reveal.js)
+ * http://lab.hakim.se/zoom-js
+ * MIT licensed
+ *
+ * Copyright (C) 2011-2014 Hakim El Hattab, http://hakim.se
+ */export{t as default};
diff --git a/docs/site_libs/revealjs/plugin/zoom/zoom.js b/docs/site_libs/revealjs/plugin/zoom/zoom.js
index 7ac2127..fe4839f 100644
--- a/docs/site_libs/revealjs/plugin/zoom/zoom.js
+++ b/docs/site_libs/revealjs/plugin/zoom/zoom.js
@@ -1,11 +1,11 @@
-!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?module.exports=t():"function"==typeof define&&define.amd?define(t):(e="undefined"!=typeof globalThis?globalThis:e||self).RevealZoom=t()}(this,(function(){"use strict";
-/*!
-	 * reveal.js Zoom plugin
-	 */const e={id:"zoom",init:function(e){e.getRevealElement().addEventListener("mousedown",(function(o){var n=/Linux/.test(window.navigator.platform)?"ctrl":"alt",i=(e.getConfig().zoomKey?e.getConfig().zoomKey:n)+"Key",d=e.getConfig().zoomLevel?e.getConfig().zoomLevel:2;o[i]&&!e.isOverview()&&(o.preventDefault(),t.to({x:o.clientX,y:o.clientY,scale:d,pan:!1}))}))},destroy:()=>{t.reset()}};var t=function(){var e=1,o=0,n=0,i=-1,d=-1,l="transform"in document.body.style;function s(t,o){var n=r();if(t.width=t.width||1,t.height=t.height||1,t.x-=(window.innerWidth-t.width*o)/2,t.y-=(window.innerHeight-t.height*o)/2,l)if(1===o)document.body.style.transform="";else{var i=n.x+"px "+n.y+"px",d="translate("+-t.x+"px,"+-t.y+"px) scale("+o+")";document.body.style.transformOrigin=i,document.body.style.transform=d}else 1===o?(document.body.style.position="",document.body.style.left="",document.body.style.top="",document.body.style.width="",document.body.style.height="",document.body.style.zoom=""):(document.body.style.position="relative",document.body.style.left=-(n.x+t.x)/o+"px",document.body.style.top=-(n.y+t.y)/o+"px",document.body.style.width=100*o+"%",document.body.style.height=100*o+"%",document.body.style.zoom=o);e=o,document.documentElement.classList&&(1!==e?document.documentElement.classList.add("zoomed"):document.documentElement.classList.remove("zoomed"))}function c(){var t=.12*window.innerWidth,i=.12*window.innerHeight,d=r();nwindow.innerHeight-i&&window.scroll(d.x,d.y+(1-(window.innerHeight-n)/i)*(14/e)),owindow.innerWidth-t&&window.scroll(d.x+(1-(window.innerWidth-o)/t)*(14/e),d.y)}function r(){return{x:void 0!==window.scrollX?window.scrollX:window.pageXOffset,y:void 0!==window.scrollY?window.scrollY:window.pageYOffset}}return l&&(document.body.style.transition="transform 0.8s ease"),document.addEventListener("keyup",(function(o){1!==e&&27===o.keyCode&&t.out()})),document.addEventListener("mousemove",(function(t){1!==e&&(o=t.clientX,n=t.clientY)})),{to:function(o){if(1!==e)t.out();else{if(o.x=o.x||0,o.y=o.y||0,o.element){var n=o.element.getBoundingClientRect();o.x=n.left-20,o.y=n.top-20,o.width=n.width+40,o.height=n.height+40}void 0!==o.width&&void 0!==o.height&&(o.scale=Math.max(Math.min(window.innerWidth/o.width,window.innerHeight/o.height),1)),o.scale>1&&(o.x*=o.scale,o.y*=o.scale,s(o,o.scale),!1!==o.pan&&(i=setTimeout((function(){d=setInterval(c,1e3/60)}),800)))}},out:function(){clearTimeout(i),clearInterval(d),s({x:0,y:0},1),e=1},magnify:function(e){this.to(e)},reset:function(){this.out()},zoomLevel:function(){return e}}}();
-/*!
-	 * zoom.js 0.3 (modified for use with reveal.js)
-	 * http://lab.hakim.se/zoom-js
-	 * MIT licensed
-	 *
-	 * Copyright (C) 2011-2014 Hakim El Hattab, http://hakim.se
-	 */return()=>e}));
+!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?module.exports=t():"function"==typeof define&&define.amd?define(t):(e="undefined"!=typeof globalThis?globalThis:e||self).RevealZoom=t()}(this,(function(){"use strict";
+/*!
+	 * reveal.js Zoom plugin
+	 */const e={id:"zoom",init:function(e){e.getRevealElement().addEventListener("mousedown",(function(o){var n=/Linux/.test(window.navigator.platform)?"ctrl":"alt",i=(e.getConfig().zoomKey?e.getConfig().zoomKey:n)+"Key",d=e.getConfig().zoomLevel?e.getConfig().zoomLevel:2;o[i]&&!e.isOverview()&&(o.preventDefault(),t.to({x:o.clientX,y:o.clientY,scale:d,pan:!1}))}))},destroy:()=>{t.reset()}};var t=function(){var e=1,o=0,n=0,i=-1,d=-1,l="transform"in document.body.style;function s(t,o){var n=r();if(t.width=t.width||1,t.height=t.height||1,t.x-=(window.innerWidth-t.width*o)/2,t.y-=(window.innerHeight-t.height*o)/2,l)if(1===o)document.body.style.transform="";else{var i=n.x+"px "+n.y+"px",d="translate("+-t.x+"px,"+-t.y+"px) scale("+o+")";document.body.style.transformOrigin=i,document.body.style.transform=d}else 1===o?(document.body.style.position="",document.body.style.left="",document.body.style.top="",document.body.style.width="",document.body.style.height="",document.body.style.zoom=""):(document.body.style.position="relative",document.body.style.left=-(n.x+t.x)/o+"px",document.body.style.top=-(n.y+t.y)/o+"px",document.body.style.width=100*o+"%",document.body.style.height=100*o+"%",document.body.style.zoom=o);e=o,document.documentElement.classList&&(1!==e?document.documentElement.classList.add("zoomed"):document.documentElement.classList.remove("zoomed"))}function c(){var t=.12*window.innerWidth,i=.12*window.innerHeight,d=r();nwindow.innerHeight-i&&window.scroll(d.x,d.y+(1-(window.innerHeight-n)/i)*(14/e)),owindow.innerWidth-t&&window.scroll(d.x+(1-(window.innerWidth-o)/t)*(14/e),d.y)}function r(){return{x:void 0!==window.scrollX?window.scrollX:window.pageXOffset,y:void 0!==window.scrollY?window.scrollY:window.pageYOffset}}return l&&(document.body.style.transition="transform 0.8s ease"),document.addEventListener("keyup",(function(o){1!==e&&27===o.keyCode&&t.out()})),document.addEventListener("mousemove",(function(t){1!==e&&(o=t.clientX,n=t.clientY)})),{to:function(o){if(1!==e)t.out();else{if(o.x=o.x||0,o.y=o.y||0,o.element){var n=o.element.getBoundingClientRect();o.x=n.left-20,o.y=n.top-20,o.width=n.width+40,o.height=n.height+40}void 0!==o.width&&void 0!==o.height&&(o.scale=Math.max(Math.min(window.innerWidth/o.width,window.innerHeight/o.height),1)),o.scale>1&&(o.x*=o.scale,o.y*=o.scale,s(o,o.scale),!1!==o.pan&&(i=setTimeout((function(){d=setInterval(c,1e3/60)}),800)))}},out:function(){clearTimeout(i),clearInterval(d),s({x:0,y:0},1),e=1},magnify:function(e){this.to(e)},reset:function(){this.out()},zoomLevel:function(){return e}}}();
+/*!
+	 * zoom.js 0.3 (modified for use with reveal.js)
+	 * http://lab.hakim.se/zoom-js
+	 * MIT licensed
+	 *
+	 * Copyright (C) 2011-2014 Hakim El Hattab, http://hakim.se
+	 */return()=>e}));
diff --git a/images/Bioconductor.svg b/images/Bioconductor.svg
index 5d9ea80..c1ab5bc 100644
--- a/images/Bioconductor.svg
+++ b/images/Bioconductor.svg
@@ -1,83 +1,83 @@
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
diff --git a/index.qmd b/index.qmd
index a5cc386..4a81ab0 100644
--- a/index.qmd
+++ b/index.qmd
@@ -1,3 +1,175 @@
+<<<<<<< HEAD
+---
+format: html
+toc: true
+toc-location: right
+toc-depth: 4
+sidebar: false
+---
+![](images/WebsiteBanner.png){width="100%"}
+
+
    
+[![AGPL-3.0][agpl3-shield]][agpl3]
+[![CC BY-SA 4.0][cc-by-sa-shield]][cc-by-sa]
+
    
+
+Cytometry in R is a free weekly mini-course being offered both in-person and online by the [Flow Cytometry Shared Resource](https://www.medschool.umaryland.edu/cibr/core/umgccc_flow/) staff at the [University of Maryland Greenebaum Comprehensive Cancer Center](https://www.umms.org/umgccc). Its primary audience is for those with prior flow cytometry knowledge, who have limited previous experience with the programming language [R](https://www.r-project.org/). However, we welcome everyone regardless of their existing  flow cytometry  or coding experience.  
+
+This course is a passion project arising from our desire to contribute back to the community. We are excited that so many of you have chosen to sign up, and look forward to helping you get started on your own learning journeys.
+
+For more information on topics-covered, please see our [schedule](/Schedule.qmd).
+
+If you did not previously complete the interest form, and would like to be added to our mailing list, please complete the form [here](https://docs.google.com/forms/d/e/1FAIpQLScPK4V_WNSgQvZNq7aIHpoiX8pi3kiuCfI0Tp7hQkVJS3HPtQ/viewform?usp=publish-editor)
+
+
    
+
+# About
+
+![](images/Signatures.png){width=75%}
+
+### Motivation 
+
+While many cytometry enthusiast express an interest in learning how to carry out flow cytometry analyses in R, they often do not know where to start. Additionally, many of the limited existing resources are focused towards users with intermediate bioinformatic skills, contributing to a greater barrier for entry for those just starting out. Our motivation in offering this mini-course tailored towards beginners is to make the learning journey smoother than the one we ourselves experienced. 
+
+
    
+
+While designing the course, we kept the following concepts in mind:
+
+- Beginning coders benefit both by having detailed examples that they can initially work through on their own time, as well as less defined problems that through troubleshooting enable the acquisition of the thought-process and skills needed for coding. 
+
+- Some topics will take individuals a longer time to fully grasp. Providing a format and resources that enable being able to revisit the material multiple times is incredibly helpful. Likewise, life is busy, and missing a workshop session is highly probable. If this happens, it shouldn't make or break the ability of the individual to understanding the rest of the course. 
+
+- Consistency is key, and being able to apply what you are learning to your own datasets, files, and questions of interest helps achieve this. 
+
+
    
+
+# Course Details
+
+![](images/subsetting.png){width=50%}
+
+Each week, the mini-course will cover a particular topic for an hour. This individual class is offered on multiple days, at different times, both in-person and online. We invite you to attend the one that best fits your schedule each week. If life gets busy and you can't make regular day, the online livestream recordings will be available on [YouTube](https://www.youtube.com/@CytometryInR). 
+
+
    
+
    
+
+### Course Materials
+
+![](images/histograms.png){width=50%}
+
+We will release the course materials for the upcoming week on Sundays 2200 EST (Monday 0300 GMT+0) via our [course website](https://umgcccfcsr.github.io/CytometryInR/) and [GitHub](https://github.com/UMGCCCFCSR/CytometryInR). These materials will normally be [Quarto Markdown](https://aeturrell.github.io/coding-for-economists/wrkflow-quarto.html) documents containing code, explanation, and other resources needed for that week. If you have your own data, you can use your own data! If you don't have any data, we will make sure to provide some of our own available data for each lesson so that you can use it and be able to follow along. 
+
+In our commitment to open-source and open-science, all teaching materials are freely offered under a [CC-BY-SA](https://creativecommons.org/licenses/by-sa/4.0/deed.en) license, while all code examples are offered under the [AGPL3-0](https://www.gnu.org/licenses/agpl-3.0.en.html) copyleft license. 
+
+
    
+
    
+
+### In-Person (Baltimore)
+
+![](images/PopUpLab.jpeg){width=33%}
+
+For those who are local and attending in person, the class will be offered on Monday, Tuesday and Thursday from 4-5 pm EST in [Bressler Research Building](https://www.google.com/maps/dir//Bressler+Research+Bldg,+Baltimore,+MD+21201/data=!4m6!4m5!1m1!4e2!1m2!1m1!1s0x89c803589865590b:0xd23603e6659b23f7?sa=X&ved=1t:707&ictx=111) Conference Room 7-035 (around the corner from the Flow Core). 
+
+We invite you to make whichever session best fits your schedule. If you have your own laptop, feel free to bring it. If you don't have a laptop, please reach out, the Flow Core has 6 laptops running Linux that we can lend out to participants for use during the session.
+
+For those who arrive early, we will have a limited number of second screens with provided mouse and keyboard that you can plug a laptop into via HDMI cable to set up a larger workstation. For those arriving later, the room has enough space (and electrical plugs) for up to 20 people, but you will need to balance a laptop on your lap.
+
+
    
+
    
+
+### Online (Worldwide)
+
+![](images/WorldwideSignups.png){width=66%}
+
+For those joining us virtually, we will have three separate livestreams throughout the week on [YouTube](https://www.youtube.com/@CytometryInR). These will be offered on:
+
+- Tuesday 2200 EST (Wednesday 0300 GMT+0)
+- Wednesday 1600 EST (Wednesday 2100 GMT+0)
+- Thursday 1000 EST (Thursday 1500 GMT+0)
+
+
    
+
    
+
+### Recordings 
+
+![](images/WorldwideSignups.png){width=66%}
+
+All three livestreams will be recorded and available on [YouTube](https://www.youtube.com/@CytometryInR) immediately afterwards. Our plan is to eventually circle back after the course and properly edit them (ie. less minutes of random background noise, highlighting the relevant lines of code, time-stamps, subtitles, translations, etc.) later on as time allows, so that they can serve as a more permanent resource. 
+
    
+
    
+
+### Discussion Forum
+
+![](/course/00_Homeworks/images/Discussion.png){width=66%}
+
+We will be using our GitHub [Discussions](https://github.com/UMGCCCFCSR/CytometryInR/discussions) page as a community forum. This will allow us to answer questions, and benefit from insights from others in the community. One advantage of having so many people signed up for the course is that if you have a question, someone else likely does as well, so go start a post and ask it!
+
+
    
+
    
+
+### Optional Take-Home Problems
+
+![](images/WorldwideSignups.png){width=66%}
+
+Each week, we will offer optional take-home problems. These are intended to allow you to work with your own data on similar problems, but in a not-so-structured manner. Challenges that you and overcome during the process will help grow your problem solving and debugging skills, and help solidify concepts covered during the course. 
+
+To get feedback on these problems, you can reach out to the community on the [Discussions page](https://github.com/UMGCCCFCSR/CytometryInR/discussions), or once far enough open a pull request to the [homework]() branch and we will provide additional feedback.  
+
+
    
+
    
+
+### Cost
+
+Is there a cost to participate? No, it's absolutely free! Is there a catch? Yes, you learn R, and may wind up with strong feelings about [flowframes](https://rdrr.io/bioc/flowCore/man/flowFrame-class.html) vs. [cytoframes](https://rdrr.io/bioc/flowWorkspace/man/cytoframe.html). This is also our first year offering this course, so we will sporadically ask you to fill out a feedback forms to help us improve. 
+
+![](https://imgs.xkcd.com/comics/flowchart_2x.png){width=25%}
+
+
+
    
+
    
+
+### Computing Requirements
+
+![](images/TidyData.png){width=50%}
+
+For those attending online, you will need a computer with internet access. Operating system shouldn't matter, as we will be offering code examples for Windows, Mac and Linux. As with all things flow-cytometry software, having a faster CPU with multiple cores, more RAM and greater storage space is generally helpful, but not a deal breaker.
+
+
    
+
+You will need to be able to install the required software ([R](https://cran.rstudio.com/), [Rtools](https://cran.r-project.org/bin/windows/Rtools/), [Positron](https://positron.posit.co/), [Quarto](https://quarto.org/), and [Git](https://git-scm.com/)) as well as install and compile R packages from the [CRAN](https://cran.r-project.org/) and [Bioconductor](https://www.bioconductor.org/) repositories (as well as a few GitHub-based R packages). Installation walkthroughs for each computer operating system can be found [here](course/00_WorkstationSetup/index.qmd).
+
+
+For those using university or company administered computers, please be aware that you may not have the necessary permissions to install these directly, and may need to reach out to your IT department to help get these initial requirements set up. If you are using your own computer, congratulations, you are your system administrator, and should already have the necessary permissions.
+
+
    
+
+For those attending in-person, we have set up a pop-up computer lab in the conference room. For those who arrive early, we have a limited number of second screens with provided mouse and keyboard that you can plug a laptop into via HDMI cable to set up a workstation. For those arriving later, the room has enough space (and electrical plugs) for 20 people, but you will need to balance a laptop on your lap. If you have your own laptop, feel free to bring it. If you don't have a laptop, the flow core has 6 loaner laptops running Linux that we can let participants use for that session. 
+
+
    
+
+# License
+
+In our commitment to open-science and open-source, all teaching materials are freely offered under a [CC-BY-SA](https://creativecommons.org/licenses/by-sa/4.0/deed.en) license, while all code examples are offered under the [AGPL3-0](https://www.gnu.org/licenses/agpl-3.0.en.html) copyleft license. 
+
+
    
+
    
+
+
    
+[![AGPL-3.0][agpl3-image]][agpl3]
+[![CC BY-SA 4.0][cc-by-sa-image]][cc-by-sa]
+
    
+
+[agpl3-shield]: https://img.shields.io/badge/license-AGPLv3-blue
+[cc-by-sa-shield]: https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg
+
+[cc-by-sa-image]: https://licensebuttons.net/l/by-sa/4.0/88x31.png
+[cc-by-sa]: http://creativecommons.org/licenses/by-sa/4.0/
+
+[agpl3-image]: https://www.gnu.org/graphics/agplv3-with-text-162x68.png
+[agpl3]: https://www.gnu.org/licenses/agpl-3.0.en.html
+
+
+
+=======
 ---
 format: html
 toc: true
@@ -168,3 +340,4 @@ In our commitment to open-science and open-source, all teaching materials are fr
 
 
 
+>>>>>>> 23a81a59a64966e782d820f6b60f087d577c3b25
diff --git a/styles.scss b/styles.scss
index 9290a7d..e94792f 100644
--- a/styles.scss
+++ b/styles.scss
@@ -1,269 +1,269 @@
-/*-- scss:defaults --*/
-// quarto-scss-analysis-annotation { "origin": "simplex (builtin theme)" }
-
-$theme: "simplex" !default;
-
-//
-// Color system
-//
-
-$white:    #fff !default;
-$gray-100: #f8f9fa !default;
-$gray-200: #ddd !default;
-$gray-300: #ccc !default;
-$gray-400: #bbb !default;
-$gray-500: #adb5bd !default;
-$gray-600: #777 !default;
-$gray-700: #444 !default;
-$gray-800: #373a3c !default;
-$gray-900: #212529 !default;
-$black:    #000 !default;
-
-$blue:    #007bff !default;
-$indigo:  #6610f2 !default;
-$purple:  #9b479f !default;
-$pink:    #e83e8c !default;
-$red:     #d9230f !default;
-$orange:  #d9831f !default;
-$yellow:  #ffc107 !default;
-$green:   #469408 !default;
-$teal:    #20c997 !default;
-$cyan:    #029acf !default;
-
-$primary:       $red !default;
-$secondary:     $white !default;
-$success:       $green !default;
-$info:          $cyan !default;
-$warning:       $orange !default;
-$caution:       $yellow !default;
-$danger:        $purple !default;
-$light:         $white !default;
-$dark:          $gray-800 !default;
-
-$min-contrast-ratio:   2.8 !default;
-
-// Body
-
-$body-bg:                   mix($white, $black, 99%) !default;
-
-$enable-shadows: true !default;
-
-// Fonts
-
-// stylelint-disable-next-line value-keyword-case
-$font-family-sans-serif:      "Open Sans", -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol" !default;
-
-// Dropdowns
-
-$dropdown-link-hover-color:         $white !default;
-$dropdown-link-hover-bg:            $primary !default;
-
-// Navs
-
-$nav-link-padding-y:                .9rem !default;
-$nav-link-disabled-color:           $gray-400 !default;
-$nav-tabs-border-color:             mix($white, $black, 93.5%) !default;
-
-// Navbar
-
-// Sidebar
-
-$sidebar-bg: $light;
-
-// Pagination
-
-$pagination-border-color:           $nav-tabs-border-color !default;
-$pagination-hover-color:            $white !default;
-$pagination-hover-bg:               $primary !default;
-$pagination-hover-border-color:     $primary !default;
-$pagination-disabled-color:         $gray-400 !default;
-$pagination-disabled-border-color:  $pagination-border-color !default;
-
-// Cards
-
-$card-border-color:                 $nav-tabs-border-color !default;
-
-// Popovers
-
-$popover-border-color:              $nav-tabs-border-color !default;
-
-// Modals
-
-$modal-content-border-color:        $nav-tabs-border-color !default;
-$modal-header-border-color:         $nav-tabs-border-color !default;
-
-// Progress bars
-
-$progress-bar-color:                $primary !default;
-
-// List group
-
-$list-group-border-color:           $nav-tabs-border-color !default;
-$list-group-disabled-bg:            $nav-tabs-border-color !default;
-
-// Breadcrumbs
-
-$breadcrumb-padding-y:              .375rem !default;
-$breadcrumb-padding-x:              .75rem !default;
-$breadcrumb-border-radius:          .25rem !default;
-
-$link-color: #2E5984 !default;
-
-/*-- scss:rules --*/
-
-
-// Variables
-
-$web-font-path: "https://fonts.googleapis.com/css2?family=Open+Sans:wght@400;700&display=swap" !default;
-@if $web-font-path {
-  @import url($web-font-path);
-}
-
-// Mixins
-
-@mixin btn-shadow($color){
-  @include gradient-y-three-colors(tint-color($color, 6%), $color, 6%, shade-color($color, 6%));
-  filter: none;
-  border: 1px solid shade-color($color, 13%);
-}
-
-// Navbar
-
-.navbar {
-  border-width: 1px;
-  border-style: solid;
-  border-color: shade-color($navbar-bg, 13%);
-
-  &-fixed-top {
-    border-width: 0 0 1px;
-  }
-
-  &-fixed-bottom {
-    border-style: solid;
-    border-top-width: 1px 0 0 0;
-  }
-
-  &.bg-primary {
-    border-color: shade-color($primary, 13%) !important;
-  }
-
-  &.bg-dark {
-    border-color: shade-color($dark, 13%) !important;
-  }
-
-  &.bg-light {
-    border-color: shade-color($white, 13%);
-  }
-}
-
-// Buttons
-
-.btn-primary,
-.btn-primary:hover {
-  @include btn-shadow($primary);
-}
-
-.btn-secondary,
-.btn-secondary:hover {
-  @include btn-shadow($secondary);
-}
-
-.btn-secondary:focus,
-.btn-secondary:not([disabled]):not(.disabled):active,
-.btn-secondary:not([disabled]):not(.disabled).active {
-  box-shadow: 0 0 0 .2rem rgba($gray-200, .5);
-}
-
-.btn-success,
-.btn-success:hover {
-  @include btn-shadow($success);
-}
-
-.btn-info,
-.btn-info:hover {
-  @include btn-shadow($info);
-}
-
-.btn-warning,
-.btn-warning:hover {
-  @include btn-shadow($warning);
-}
-
-.btn-danger,
-.btn-danger:hover {
-  @include btn-shadow($danger);
-}
-
-.btn-dark,
-.btn-dark:hover {
-  @include btn-shadow($dark);
-}
-
-.btn-light,
-.btn-light:hover {
-  @include btn-shadow($light);
-}
-
-.btn-outline-secondary {
-  color: $gray-400;
-  border-color: $gray-400;
-
-  &:hover {
-    color: $white;
-    background-color: $gray-400;
-  }
-}
-
-// Typography
-
-.text-secondary {
-  color: $gray-600 !important;
-}
-
-// Forms
-
-legend,
-label {
-  color: $headings-color;
-}
-
-// Navs
-
-.breadcrumb {
-  border: 1px solid shade-color($white, 13%);
-}
-
-
-.sidebar-bg {
-    background-color: $light;
-}
-
-.pagination {
-  .page-link:hover {
-    text-decoration: none;
-  }
-}
-
-// Indicators
-
-.badge {
-  &.bg-secondary,
-  &.bg-light {
-    color: $dark;
-  }
-}
-
-.bslib-sidebar-1 {
-  background-color: #ffffff !important; /* White background */
-}
-
-.sidebar {
-  background-color: #ffffff !important; /* White background */
-}
-
-.card-header {
-  background-color: #f8f9fa !important; /* White background */
-}
-
-
+/*-- scss:defaults --*/
+// quarto-scss-analysis-annotation { "origin": "simplex (builtin theme)" }
+
+$theme: "simplex" !default;
+
+//
+// Color system
+//
+
+$white:    #fff !default;
+$gray-100: #f8f9fa !default;
+$gray-200: #ddd !default;
+$gray-300: #ccc !default;
+$gray-400: #bbb !default;
+$gray-500: #adb5bd !default;
+$gray-600: #777 !default;
+$gray-700: #444 !default;
+$gray-800: #373a3c !default;
+$gray-900: #212529 !default;
+$black:    #000 !default;
+
+$blue:    #007bff !default;
+$indigo:  #6610f2 !default;
+$purple:  #9b479f !default;
+$pink:    #e83e8c !default;
+$red:     #d9230f !default;
+$orange:  #d9831f !default;
+$yellow:  #ffc107 !default;
+$green:   #469408 !default;
+$teal:    #20c997 !default;
+$cyan:    #029acf !default;
+
+$primary:       $red !default;
+$secondary:     $white !default;
+$success:       $green !default;
+$info:          $cyan !default;
+$warning:       $orange !default;
+$caution:       $yellow !default;
+$danger:        $purple !default;
+$light:         $white !default;
+$dark:          $gray-800 !default;
+
+$min-contrast-ratio:   2.8 !default;
+
+// Body
+
+$body-bg:                   mix($white, $black, 99%) !default;
+
+$enable-shadows: true !default;
+
+// Fonts
+
+// stylelint-disable-next-line value-keyword-case
+$font-family-sans-serif:      "Open Sans", -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol" !default;
+
+// Dropdowns
+
+$dropdown-link-hover-color:         $white !default;
+$dropdown-link-hover-bg:            $primary !default;
+
+// Navs
+
+$nav-link-padding-y:                .9rem !default;
+$nav-link-disabled-color:           $gray-400 !default;
+$nav-tabs-border-color:             mix($white, $black, 93.5%) !default;
+
+// Navbar
+
+// Sidebar
+
+$sidebar-bg: $light;
+
+// Pagination
+
+$pagination-border-color:           $nav-tabs-border-color !default;
+$pagination-hover-color:            $white !default;
+$pagination-hover-bg:               $primary !default;
+$pagination-hover-border-color:     $primary !default;
+$pagination-disabled-color:         $gray-400 !default;
+$pagination-disabled-border-color:  $pagination-border-color !default;
+
+// Cards
+
+$card-border-color:                 $nav-tabs-border-color !default;
+
+// Popovers
+
+$popover-border-color:              $nav-tabs-border-color !default;
+
+// Modals
+
+$modal-content-border-color:        $nav-tabs-border-color !default;
+$modal-header-border-color:         $nav-tabs-border-color !default;
+
+// Progress bars
+
+$progress-bar-color:                $primary !default;
+
+// List group
+
+$list-group-border-color:           $nav-tabs-border-color !default;
+$list-group-disabled-bg:            $nav-tabs-border-color !default;
+
+// Breadcrumbs
+
+$breadcrumb-padding-y:              .375rem !default;
+$breadcrumb-padding-x:              .75rem !default;
+$breadcrumb-border-radius:          .25rem !default;
+
+$link-color: #2E5984 !default;
+
+/*-- scss:rules --*/
+
+
+// Variables
+
+$web-font-path: "https://fonts.googleapis.com/css2?family=Open+Sans:wght@400;700&display=swap" !default;
+@if $web-font-path {
+  @import url($web-font-path);
+}
+
+// Mixins
+
+@mixin btn-shadow($color){
+  @include gradient-y-three-colors(tint-color($color, 6%), $color, 6%, shade-color($color, 6%));
+  filter: none;
+  border: 1px solid shade-color($color, 13%);
+}
+
+// Navbar
+
+.navbar {
+  border-width: 1px;
+  border-style: solid;
+  border-color: shade-color($navbar-bg, 13%);
+
+  &-fixed-top {
+    border-width: 0 0 1px;
+  }
+
+  &-fixed-bottom {
+    border-style: solid;
+    border-top-width: 1px 0 0 0;
+  }
+
+  &.bg-primary {
+    border-color: shade-color($primary, 13%) !important;
+  }
+
+  &.bg-dark {
+    border-color: shade-color($dark, 13%) !important;
+  }
+
+  &.bg-light {
+    border-color: shade-color($white, 13%);
+  }
+}
+
+// Buttons
+
+.btn-primary,
+.btn-primary:hover {
+  @include btn-shadow($primary);
+}
+
+.btn-secondary,
+.btn-secondary:hover {
+  @include btn-shadow($secondary);
+}
+
+.btn-secondary:focus,
+.btn-secondary:not([disabled]):not(.disabled):active,
+.btn-secondary:not([disabled]):not(.disabled).active {
+  box-shadow: 0 0 0 .2rem rgba($gray-200, .5);
+}
+
+.btn-success,
+.btn-success:hover {
+  @include btn-shadow($success);
+}
+
+.btn-info,
+.btn-info:hover {
+  @include btn-shadow($info);
+}
+
+.btn-warning,
+.btn-warning:hover {
+  @include btn-shadow($warning);
+}
+
+.btn-danger,
+.btn-danger:hover {
+  @include btn-shadow($danger);
+}
+
+.btn-dark,
+.btn-dark:hover {
+  @include btn-shadow($dark);
+}
+
+.btn-light,
+.btn-light:hover {
+  @include btn-shadow($light);
+}
+
+.btn-outline-secondary {
+  color: $gray-400;
+  border-color: $gray-400;
+
+  &:hover {
+    color: $white;
+    background-color: $gray-400;
+  }
+}
+
+// Typography
+
+.text-secondary {
+  color: $gray-600 !important;
+}
+
+// Forms
+
+legend,
+label {
+  color: $headings-color;
+}
+
+// Navs
+
+.breadcrumb {
+  border: 1px solid shade-color($white, 13%);
+}
+
+
+.sidebar-bg {
+    background-color: $light;
+}
+
+.pagination {
+  .page-link:hover {
+    text-decoration: none;
+  }
+}
+
+// Indicators
+
+.badge {
+  &.bg-secondary,
+  &.bg-light {
+    color: $dark;
+  }
+}
+
+.bslib-sidebar-1 {
+  background-color: #ffffff !important; /* White background */
+}
+
+.sidebar {
+  background-color: #ffffff !important; /* White background */
+}
+
+.card-header {
+  background-color: #f8f9fa !important; /* White background */
+}
+
+
 // quarto-scss-analysis-annotation { "origin": null }
\ No newline at end of file