We will load the tidyverse package, read in the data and then tweak it slightly. So for that we turn to R.ĭownload the file to your local machine (using scp or filezilla) and open up RStudioand we will start a new R script. Of course, you can only gain so much information by looking at a bunch of values like this - it makes much more sense to plot them. Now that we have created our per-snp F ST estimates, its a good time to have a look at the output using tools like head or less. So what did we do here? Well we calculated Weir & Cockerham’s F ST for each SNP and to do this, all we needed to do was provide the two sample files (separately!) using the -weir-fst-pop flag. You can see from this it calculates the mean F ST across all the SNPs we provided on chromsome 20. Vcftools will run for a few moments and then print some information to the screen. Vcftools -gzvcf $ \ -weir-fst-pop ppund \ -weir-fst-pop pnyer \ -out. - Comparative genomics with Orthofinder.- Demographic modeling with fastsimcoal2.- Estimating the site-frequency-spectrum.- Identifying selection with haplotype statistics.- Sliding window differentiation, variance and introgression.- Data manipulation and visualisation in R.- Checking for PCR duplication problems, contamination, etc.
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