AutoSpectral is AutoSpill updated for the spectral flow era.
The goal of AutoSpectral is to provide you with the best possible spectral signatures of the fluorophores in your single-stained controls. Whether or not these accurately model your fully stained samples will depend on what you’ve chosen to use for the controls, how they were prepared and other factors such as machine condition and any divergence in handling between samples and controls.
More to the point, AutoSpectral is intended to make working with messy cell-based controls as easy as compensation beads. This should give you better accuracy and precision in your spectral definition and thus in your unmixing.
AutoSpectral aims to provide reproducible unmixing, meaning that anyone should be able to obtain reliably good (probably better) unmixing from the same set of controls. The aim is to remove the human “fiddling” part, which is slow and not always so scientific.
Plus, you can extract each cell’s individual autofluorescent background in a manner specific to that cell, producing better unmixing with less spread. Per-cell fluorescence spectral optimization can reduce unmixing errors.
At the moment, the following cytometers are supported:
- Cytek Aurora (“aurora”)
- Cytek Northern Lights (“auroraNL”)
- Sony ID7000 (“id7000”)
- BD FACSDiscoverS8 (“s8”)
- BD FACSDiscoverA8 (“a8”)
- BD FACSymphony A5 SE (“a5se”)
- Agilent NovoCyte Opteon (“opteon”)
- Beckman Coulter CytoFLEX mosaic (“mosaic”)
- ThermoFisher Attune Xenith (“xenith”)
Version 0.9.1
To install the latest, hopefully stable version, install using
devtools or remotes. You will need to install the Bioconductor
packages separately. As of version 0.9.1, AutoSpectral relies on
FlowSOM rather than EmbedSOM, so you will need to install FlowSOM
via Bioconductor.
# Install Bioconductor packages
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(c("flowWorkspace", "flowCore", "PeacoQC", "FlowSOM"))
# You'll need devtools or remotes to install from GitHub.
# install.packages("devtools")
devtools::install_github("DrCytometer/AutoSpectral")As of version 0.8.7, there is a Shiny helper tool to assist you in setting up your AutoSpectral control files. This is an interactive html app that opens in RStudio. Hopefully this makes things easier. It is new, so again, imperfect. To try it, visit AutoSpectralHelper. If you update AutoSpectral, I recommend downloading a new version of the app to ensure compatibility.
To install a specific release, e.g., a previous one, use the version number:
remotes::install_github("DrCytometer/AutoSpectral@v0.8.7")If you’re feeling adventurous or simply want early access to the latest
features, you can try the dev branch. At any given point, this may not
be working well.
AutoSpectral is open source. If you are interested in contributing, please visit Development for suggestions of where help is needed most.
You can install the development version of AutoSpectral from GitHub with:
devtools::install_github("DrCytometer/AutoSpectral@dev")AutoSpectral is pretty complex and newly released, so there will be bugs. Sorry. Thanks to all of you providing feedback. Please submit any and all issues either using the Issues page or via email at colibri-cytometry at gmail.
To submit a bug report, go to Issues.
For more general problems, like not being clear on how to do things, something doesn’t work well, or maybe you have an idea for something new or better, visit the Discussions page.
Since one of my recent updates broke things, I’ll be moving to using tagged releases that should be easier to install if the latest version has flaws. I’ve also set up a separate development branch, which will get the updates first. Things probably should have been that way from the start, but this is all new to me.
Please check the help pages and articles if you’re struggling to understand how to do something. There’s a lot of info there.
In particular, see the Full Workflow.
Resolved issues, bug patches and improvements will be announced via the NEWS and also tracked in the Updates and Issues article.
- Gating. The automated gating is not great. See the help page for tips. I’m working on an alternative.
- Please note that FCS 3.2 files from the S8 and A8 cytometers are not fully supported in flowCore. You may receive warnings, but things should still work.
- More stuff in progress will appear in the Development article.
- This is my first R package.
If you want to use data from another cytometer and are wiling to provide files for establishing the workflow, contact the author/maintainer. See existing information, which may also assist you in setting up your control file, in the cytometer database.
AutoSpectral relies on a database of information containing fluorophore
emission details. If your fluorophore is not detected automatically by
create.control.file() and you want to add it, visit the Google sheet
for the fluorophore
database
and add it there. New fluorophores will be incorporated into updates.
Similarly, there is a marker database to detect (and standardize) marker names if they appear in the single-stained FCS control file names. Feel free to add more markers or synonyms to the marker database.
This work has received funding from the KU Leuven C1 program, the European Union’s Horizon 2020 research and innovation programme under grant agreement No 874707 (EXIMIOUS), Wellcome Investigator Award 222442/A/21/Z, and UKRI Proactive Vaccinology Award MR/Y004450/1 (IMMPROVE).
AutoSpectral is provided under an AGPL3 licence.
Installation via GitHub should take only a minute or so. It takes less than that on a Dell i7 core laptop, but that might be because the dependencies are already installed.
Occasionally, the help gets corrupted. Just re-install if that happens. If you know why this happens, let me know.
Installation of AutoSpectralRcpp will take a couple of minutes because
the code needs to compile. You will also first have to install Rtools to
have a compiler, and that will take longer, probably 10 minutes or so.
For more details and benchmarking of specific functions with an example 40-color cell control data set, see the article on Speed.
See the article on “Speed for details on how to improve AutoSpectral’s performance on your system.
See the article Updates and Issues for more on this, or read the NEWS with the latest release.