ANGSD: Analysis of next generation Sequencing Data

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Fst PCA: Difference between revisions

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;THIS PAGE IS OBSOLETE, PLEASE SEE FST AND PCA in the sidebar for the latest versions
Matteo Fumagalli has been working on methods to estimate Fst and doing PCA/Covariance based on ANGSD output files.
Matteo Fumagalli has been working on methods to estimate Fst and doing PCA/Covariance based on ANGSD output files.


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=cite=
=cite=
If you use these methods, you should cite the m. fumagalli paper http://www.ncbi.nlm.nih.gov/pubmed/23979584
If you use these methods, you should cite the m. fumagalli paper http://www.ncbi.nlm.nih.gov/pubmed/23979584
=New Fancy Method=
<pre>
  nRep <- 100
      nPop1 <- 24
      nPop2 <- 16
      cmd <- paste("msms -ms",nPop1+nPop2,nRep,"-t 930 -r 400 -I 2",nPop1,nPop2,"0 -g 1 9.70406 -n 1 2 -n 2 1 -ma x 0.0 0.0 x -ej 0.07142857 2 1  >msoutput.txt ",sep=" ")
      system(cmd)
      ##system("msms -ms 40 1 -t 930 -r 400 -I 2 20 20 0 -g 1 9.70406 -n 1 2 -n 2 1 -ma x 0.0 0.0 x -ej 0.07142857 2 1  >msoutput.txt  ")
source("../R/readms.output.R")
  to2dSFS <- function(p1.d,p2.d,nPop1,nPop2)
        sapply(0:nPop1,function(x) table(factor(p2.d[p1.d==x],levels=0:nPop2)))
  source("../R/readms.output.R")
        a<- read.ms.output(file="msoutput.txt")
       
        p1.d <- unlist((sapply(a$gam,function(x) colSums(x[1:nPop1,]))))
        p2.d <- unlist((sapply(a$gam,function(x) colSums(x[-c(1:nPop1),]))))
        par(mfrow=c(1,2))
        barplot(table(p1.d))
        barplot(table(p2.d))
        sfs.2d <- t(sapply(0:nPop1,function(x) table(factor(p2.d[p1.d==x],levels=0:nPop2))))
  system("../misc/msToGlf -in msoutput.txt -out raw -singleOut 1 -regLen 0 -depth 8 -err 0.005")
      system("../misc/splitgl raw.glf.gz 20 1 12 >pop1.glf.gz")
      system("../misc/splitgl raw.glf.gz 20 13 20 >pop2.glf.gz")
      system("echo \"1 250000000\" >fai.fai")
      system("../angsd -glf pop1.glf.gz -nind 12 -doSaf 1 -out pop1 -fai fai.fai -issim 1")
      system("../angsd -glf pop2.glf.gz -nind 8 -doSaf 1 -out pop2 -fai fai.fai -issim 1")
      system("../misc/realSFS pop1.saf.idx >pop1.saf.idx.ml")
      system("../misc/realSFS pop2.saf.idx >pop2.saf.idx.ml")
      system("../misc/realSFS pop1.saf.idx pop2.saf.idx -maxIter 500 -p 20  >pop1.pop2.saf.idx.ml")
</pre>

Latest revision as of 15:21, 30 July 2015

THIS PAGE IS OBSOLETE, PLEASE SEE FST AND PCA in the sidebar for the latest versions

Matteo Fumagalli has been working on methods to estimate Fst and doing PCA/Covariance based on ANGSD output files.

The main documentation for this is found here: https://github.com/mfumagalli/ngsTools

Fst

  1. Generate .saf files from each population using ANGSD SFS Estimation
    1. using a 2D-SFS as a prior, estimated using ngs2dSFS
    2. using marginal spectra as priors, estimated using realSFS

PCA

More information here: https://github.com/mfumagalli/ngsTools#ngscovar

cite

If you use these methods, you should cite the m. fumagalli paper http://www.ncbi.nlm.nih.gov/pubmed/23979584

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