Part 5 - Population genetics in R
1. Introduction
In this practical, we will use samples with two genotypes associated to two distinct phenotypes. Also, Our example assembly consists of two scaffolds, from two different chromosomes:
| Genotype label | Phenotype description |
|---|---|
| B | single-queen colony |
| b | multiple-queen colony |
The aim of our analysis is to test whether any parts of this assembly differ between the individuals from these two groups (B and b).
In the first part of the analysis, we are going to create a heat map of the genotypes of the individuals and we are going to run Principal Component Analysis (PCA) on these genotypes. This will allow us to test if any of the individuals cluster together by their B/b genotype. This will be done using the adegenet package in R.
In the second part, we are going to estimate the genetic differentiation between the two groups (B and b). We will do this analysis over a sliding window, to see if the differentiation between B and b are specific to any portion of the genome. We will also measure the genetic diversity among each of the groups, which may tell us something about the evolutionary history of the portions of genome represented in our assembly. This will be done using the PopGenome package in R.
2. Input into R
As before, create a directory for this practical (e.g.,
2024-10-01-population_genetics). Copy over the R markdown notebook
/shared/data/popgen/popgen.Rmd to your project directory. Create input/
subdirectory and symlink the snp.vcf.gz and snp.vcf.gz.tbi file we created
in the last practical to it. If you don’t have these files, you can use the
ones in: /shared/data/backup_vcf.
The output of the tree command should look like this:
2024-10-01-population_genetics
├── input
│ ├── snp.vcf.gz -> /home/alice/2024-09-30-genotyping/results/snp.vcf.gz
│ └── snp.vcf.gz.tbi -> /home/alice/2024-09-30-genotyping/results/snp.vcf.gz.tbi
└── popgen.Rmd
Next, open RStudio by clicking on the ‘RStudio’ link in your personal module
page (e.g., bt007.genomicscourse.com). Login using your username (e.g., bt007)
and the password that you use for ssh.
In RStudio, open the file popgen.Rmd and work through the rest of the
practical there.