A method for detecting high Fst genomic regions adapted from Ruegg et al. (2014), 10.1111/mec.12842. Applied in 10.1093/jhered/esab049
This method is to identify genomic regions that are elevated in Fst from RADseq data between a pair of populations. Coverage and SNP density are not uniform in experiments of this type. The method accounts for loci length and SNP density to clearly identify genomic regions in which Fst is elevated. See the original Ruegg et al. (2014) paper for details. Original code by Eric Anderson is available here: http://datadryad.org/resource/doi:10.5061/dryad.73gj4
Originally designed from Swainson's Thrush, I have adapted the code for a chromosome level assembly of rainbow trout.
To use this code yourself, you'll need to make a few changes. Primarily, the number of chromosomes and names need to be changed in numerous locations. The sex chromosomes need some special consideration. Otherwise these are the basic steps.
angsd -bam combinedPop -out genotypes -doSaf 1 -doPost 2 -GL 2 -doMaf 2 -doMajorMinor 1 -minMaf 0.05 -minInd 22 -minMapQ 30 -minQ 30 -SNP_pval 2e-3 -anc ../omyV6Chr.fasta -postCutoff 0.95 -doGeno 2 gunzip -c genotypes.geno.gz | cut -f 1-28 > out.geno
Whole genome resequencing data is not continuous in the amount of coverage over a genome. To work with 10X coverage whole genome resequencing data, I have altered some of the swainysmoother scripts. The original processPileup.sh filters for 10X, and with the data I worked with this did not produce many overlaps of any length between individuals. Therefore, I made a processPileup5x.sh file (see exampleWGS directory). Furthermore, the swainysmoother "swainyPrepper" script will spend a long time looking for overlap with very small fragments of continuous coverage, so I put together a simple bash/baseR script pair to filter .dat files (exampleWGS directory, subDat.sh, sub.R). I examined the length of segments of continuous coverage with the "evaluateDat" scripts in exampleWGS. These steps are going to be fairly unique to each case examined. I also created a "driveSwainySmootherWGS.sh" script to run "swainyPrepperWGS.R" and produce results with the 5x filtered data.
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