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Welcome to the GWAS Workshop 2.0 wiki!
Disclaimer: All of the data in this workshop is imaginary. However, it is reflective of how an actual dataset can look. For the sake of better understanding this workshop (and also for fun), here is the "story," with the data!
The population in this study is a population of LU Wolves! We are studying their individual genotypes to find which Single Nucleotide Polymorphisms- or SNPs- within their genomes contribute most to a LU Wolf's spirit. In other words, the "phenotype" we are studying is a quantification of how much (or how little) spirit a LU Wolf has! To find out which SNPs are most significant, we will be conducting a Genome Wide Association Study (GWAS) on this population.
Another Disclaimer: PLEASE DO NOT SKIP AROUND THE TUTORIAL. OTHERWISE SOME STEPS MAY NOT WORK!!!!
- Extremely important tool for examining the relationship between specific genes and phenotypes
- Examines Single Nucleotide Polymorphisms (SNPs), which are small variations in the genome, and tests for their association with the phenotype being studied.
- Very efficient as it can screen the hundreds of thousands of SNPs across a large group of subjects to find where these SNPs are. Once this information has been identified, various statistical anaylses and representations can be done to analyze these results.
- GWAS is useful as it can help find precisely what parts of the genome are associated with certain diseases, drug responses, or other risk factors to more efficiently and accurately develop treatments for these diseases. It can also be applied to specific individuals to test their genetic predisposition to a disease or predict their reaction to a drug.
- R is available for Linux, Windows, and Mac OS
- The first step is to download R: https://www.r-project.org/about.html
- Then we can download R Studio: https://posit.co/downloads/
- Download R Studio Desktop, the free open source edition.
- Download and unzip the file called New_GWAS_Workshop.zip from the home page of this repo, then place it on your desktop.
PLINK2 is available for Linux, Windows, and Mac OS. While we are going to be using it through R, it is actually a command line program. So, we will be using system prompts within R studio to run plink when it is ready.
- Go to the PLINK2 installation website: https://www.cog-genomics.org/plink/2.0/
- Download the appropriate PLINK2 installation file based on your device.
- After the file has downloaded, unzip it. Move the plink2 file to the previous folder with the GWAS data, named "New_GWAS_Workshop"