71 lines
2.2 KiB
R
71 lines
2.2 KiB
R
#!/broad/tools/apps/R-2.6.0/bin/Rscript
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args <- commandArgs(TRUE)
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verbose = TRUE
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input = args[1]
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outputDir = args[2]
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annotationName = args[3]
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minBinCutoff = as.numeric(args[4])
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c <- read.table(input, header=T)
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#
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# Plot TiTv ratio as a function of the annotation
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#
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gt = c[c$numVariants>minBinCutoff & c$category==0,]
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novel = c[c$numVariants>minBinCutoff & c$category==1,]
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dbsnp = c[c$numVariants>minBinCutoff & c$category==2,]
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d = c[c$numVariants>minBinCutoff,]
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cmin = min(d$titv)
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cmax = max(d$titv)
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outfile = paste(outputDir, "binnedTiTv.", annotationName, ".pdf", sep="")
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pdf(outfile, height=7, width=7)
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par(cex=1.1)
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plot(gt$value,gt$titv,xlab=annotationName,ylab="Ti/Tv ratio",pch=20);
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m = weighted.mean(gt$value,gt$numVariants/sum(gt$numVariants))
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ma = gt[gt$value > m,]
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mb = gt[gt$value < m,]
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m75 = weighted.mean(ma$value,ma$numVariants/sum(ma$numVariants))
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m25 = weighted.mean(mb$value,mb$numVariants/sum(mb$numVariants))
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abline(v=m,lty=2)
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abline(v=m75,lty=2)
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abline(v=m25,lty=2)
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dev.off()
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outfile = paste(outputDir, "binnedTiTv_novel.", annotationName, ".pdf", sep="")
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pdf(outfile, height=7, width=7)
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par(cex=1.1)
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plot(gt$value,gt$titv,xlab=annotationName,ylab="Ti/Tv ratio",pch=20,yim=c(cmin,cmax));
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m = weighted.mean(gt$value,gt$numVariants/sum(gt$numVariants))
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ma = gt[gt$value > m,]
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mb = gt[gt$value < m,]
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m75 = weighted.mean(ma$value,ma$numVariants/sum(ma$numVariants))
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m25 = weighted.mean(mb$value,mb$numVariants/sum(mb$numVariants))
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abline(v=m,lty=2)
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abline(v=m75,lty=2)
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abline(v=m25,lty=2)
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points(novel$value,novel$titv,col="green",pch=20)
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points(dbsnp$value,dbsnp$titv,col="blue",pch=20)
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legend("topleft", c("overall","novel","dbsnp"),col=c("black","green","blue"),pch=c(20,20,20))
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dev.off()
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outfile = paste(outputDir, "binnedTiTv_quartiles.", annotationName, ".pdf", sep="")
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pdf(outfile, height=7, width=7)
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par(cex=1.1)
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plot(gt$value,gt$titv,xlab=annotationName,ylab="Ti/Tv ratio",pch=20,xlim=c(0,80))
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abline(v=m,lty=2)
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abline(v=m75,lty=2)
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abline(v=m25,lty=2)
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dev.off()
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outfile = paste(outputDir, "binnedTiTv_hist.", annotationName, ".pdf", sep="")
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pdf(outfile, height=7, width=7)
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par(cex=1.1)
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plot(gt$value,gt$numVariants,xlab=annotationName,ylab="num Variants in bin",type="h");
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dev.off() |