190 lines
6.1 KiB
R
190 lines
6.1 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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annotationName = args[2]
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minBinCutoff = as.numeric(args[3])
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medianNumVariants = args[4]
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c <- read.table(input, header=T)
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all = c[c$numVariants>minBinCutoff & c$category=="all",]
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novel = c[c$numVariants>minBinCutoff & c$category=="novel",]
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dbsnp = c[c$numVariants>minBinCutoff & c$category=="dbsnp",]
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truth = c[c$numVariants>minBinCutoff & c$category=="truth",]
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#
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# Calculate min, max, medians
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#
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d = c[c$numVariants>minBinCutoff,]
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ymin = min(d$titv)
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ymax = max(d$titv)
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xmin = min(d$value)
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xmax = max(d$value)
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m = weighted.mean(all$value,all$numVariants/sum(all$numVariants))
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ma = all[all$value > m,]
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mb = all[all$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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if(medianNumVariants == "true") {
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vc = cumsum( all$numVariants/sum(all$numVariants) )
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m10 = all$value[ max(which(vc<=0.10)) ]
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m25 = all$value[ max(which(vc<=0.25)) ]
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m = all$value[ max(which(vc<=0.5)) ]
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m75 = all$value[ min(which(vc>=0.75)) ]
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m90 = all$value[ min(which(vc>=0.90)) ]
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}
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#
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# Plot TiTv ratio as a function of the annotation
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#
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outfile = paste(input, ".TiTv.pdf", sep="")
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pdf(outfile, height=7, width=7)
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par(cex=1.1)
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plot(all$value,all$titv,xlab=annotationName,ylab="Ti/Tv Ratio",pch=20,ylim=c(ymin,ymax),xaxt="n",ps=14);
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axis(1,axTicks(1), format(axTicks(1), scientific=F))
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abline(v=m,lty=2,col="red")
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abline(v=m75,lty=3)
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abline(v=m25,lty=3)
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text(m, ymin, "50", col="red", cex=0.6);
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text(m75, ymin, "75", col="black", cex=0.6);
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text(m25, ymin, "25", col="black", cex=0.6);
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if(medianNumVariants == "true") {
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abline(v=m90,lty=3)
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abline(v=m10,lty=3)
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text(m10, ymin, "10", col="black", cex=0.6);
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text(m90, ymin, "90", col="black", cex=0.6);
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}
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points(novel$value,novel$titv,col="green",pch=20)
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points(dbsnp$value,dbsnp$titv,col="blue",pch=20)
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if( sum(all$truePositive==0) != length(all$truePositive) ) {
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points(truth$value,truth$titv,col="magenta",pch=20)
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legend("topleft", c("all","novel","dbsnp","truth"),col=c("black","green","blue","magenta"),pch=c(20,20,20,20))
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} else {
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legend("topleft", c("all","novel","dbsnp"),col=c("black","green","blue"),pch=c(20,20,20))
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}
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dev.off()
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#
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# Plot TiTv ratio as a function of the annotation, log scale on the x-axis
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#
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outfile = paste(input, ".TiTv_log.pdf", sep="")
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pdf(outfile, height=7, width=7)
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par(cex=1.1)
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plot(all$value,all$titv,xlab=annotationName,log="x",ylab="Ti/Tv Ratio",pch=20,ylim=c(ymin,ymax),xaxt="n",ps=14);
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axis(1,axTicks(1), format(axTicks(1), scientific=F))
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abline(v=m,lty=2,col="red")
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abline(v=m75,lty=3)
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abline(v=m25,lty=3)
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text(m, ymin, "50", col="red", cex=0.6);
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text(m75, ymin, "75", col="black", cex=0.6);
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text(m25, ymin, "25", col="black", cex=0.6);
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if(medianNumVariants == "true") {
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abline(v=m90,lty=3)
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abline(v=m10,lty=3)
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text(m10, ymin, "10", col="black", cex=0.6);
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text(m90, ymin, "90", col="black", cex=0.6);
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}
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points(novel$value,novel$titv,col="green",pch=20)
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points(dbsnp$value,dbsnp$titv,col="blue",pch=20)
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if( sum(all$truePositive==0) != length(all$truePositive) ) {
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points(truth$value,truth$titv,col="magenta",pch=20)
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legend("topleft", c("all","novel","dbsnp","truth"),col=c("black","green","blue","magenta"),pch=c(20,20,20,20))
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} else {
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legend("topleft", c("all","novel","dbsnp"),col=c("black","green","blue"),pch=c(20,20,20))
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}
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dev.off()
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#
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# Plot dbsnp and true positive rate as a function of the annotation
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#
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ymin = min(all$dbsnp)
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ymax = max(all$dbsnp)
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outfile = paste(input, ".truthRate.pdf", sep="")
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pdf(outfile, height=7, width=7)
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par(cex=1.1)
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yLabel = "DBsnp Rate"
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if( sum(all$truePositive==0) != length(all$truePositive) ) {
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t = all[all$truePositive>0,]
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yLabel = "DBsnp/True Positive Rate"
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ymin = min(min(all$dbsnp),min(t$truePositive))
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ymax = max(max(all$dbsnp),max(t$truePositive))
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}
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plot(all$value,all$dbsnp,xlab=annotationName,ylab=yLabel,pch=20,ylim=c(ymin,ymax),xaxt="n",ps=14);
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axis(1,axTicks(1), format(axTicks(1), scientific=F))
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abline(v=m,lty=2,col="red")
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abline(v=m75,lty=3)
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abline(v=m25,lty=3)
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text(m, ymin, "50", col="red", cex=0.6);
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text(m75, ymin, "75", col="black", cex=0.6);
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text(m25, ymin, "25", col="black", cex=0.6);
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if(medianNumVariants == "true") {
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abline(v=m90,lty=3)
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abline(v=m10,lty=3)
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text(m10, ymin, "10", col="black", cex=0.6);
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text(m90, ymin, "90", col="black", cex=0.6);
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}
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if( sum(all$truePositive==0) != length(all$truePositive) ) {
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points(t$value,t$truePositive,col="magenta",pch=20);
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legend("topleft", c("dbsnp","truth"),col=c("black","magenta"),pch=c(20,20))
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}
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dev.off()
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#
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# Plot dbsnp and true positive rate as a function of the annotation, log scale on the x-axis
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#
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outfile = paste(input, ".truthRate_log.pdf", sep="")
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pdf(outfile, height=7, width=7)
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par(cex=1.1)
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yLabel = "DBsnp Rate"
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if( sum(all$truePositive==0) != length(all$truePositive) ) {
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yLabel = "DBsnp/Truth Rate"
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}
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plot(all$value,all$dbsnp,xlab=annotationName,log="x",ylab=yLabel,ylim=c(ymin,ymax),pch=20,xaxt="n",ps=14);
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axis(1,axTicks(1), format(axTicks(1), scientific=F))
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abline(v=m,lty=2,col="red")
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abline(v=m75,lty=3)
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abline(v=m25,lty=3)
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text(m, ymin, "50", col="red", cex=0.6);
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text(m75, ymin, "75", col="black", cex=0.6);
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text(m25, ymin, "25", col="black", cex=0.6);
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if(medianNumVariants == "true") {
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abline(v=m90,lty=3)
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abline(v=m10,lty=3)
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text(m10, ymin, "10", col="black", cex=0.6);
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text(m90, ymin, "90", col="black", cex=0.6);
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}
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if( sum(all$truePositive==0) != length(all$truePositive) ) {
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points(t$value,t$truePositive,col="magenta",pch=20);
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legend("topleft", c("dbsnp","truth"),col=c("black","magenta"),pch=c(20,20))
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}
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dev.off()
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#
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# Plot histogram of the annotation's value
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#
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outfile = paste(input, ".Histogram.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(all$value,all$numVariants,xlab=annotationName,ylab="Num variants in bin",type="h",xaxt="n",ps=14,lwd=4);
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axis(1,axTicks(1), format(axTicks(1), scientific=F))
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dev.off()
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#
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# Plot histogram of the annotation's value, log scale on x-axis
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#
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outfile = paste(input, ".Histogram_log.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(all$value,all$numVariants,xlab=annotationName,log="x",ylab="Num variants in bin",type="h",xaxt="n",ps=14,lwd=4);
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axis(1,axTicks(1), format(axTicks(1), scientific=F))
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dev.off() |