84 lines
2.7 KiB
R
84 lines
2.7 KiB
R
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#!/broad/tools/apps/R-2.6.0/bin/Rscript
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args <- commandArgs(TRUE)
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docBase <- args[1]
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locusStats <- cat(docBase,".sample_locus_statistics")
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targetStats <- cat(docBase,".sample_interval_statistics")
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sampleSum <- cat(docBase,".sample_summary_statistics")
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sampleStats <- cat(docBase,".sample_statistics")
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targetSum <- cat(docBase(".sample_interval_summary"))
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PlotDepths <- function(X) {
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Y <- as.matrix(X)
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colors <- rainbow(nrow(Y),gamma=0.8)
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plot(Y[1,],col=colors[1],type="b",xlab="",xaxt="n",ylab="Number of Loci")
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axis(1,labels=FALSE)
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labels <- colnames(X)
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text(1:ncol(Y),par("usr")[3]-0.25,srt=45,adj=1,labels=labels,xpd=TRUE)
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for ( jj in 2:nrow(Y) ) {
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points(Y[jj,],col=colors[jj],type="b")
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}
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ymax = par("usr")[4]
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xmax = par("usr")[2]
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legend(y=0.95*ymax,x=0.8*xmax,col=colors,rownames(X),lty=c(1))
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}
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PlotLocusQuantiles <- function(X) {
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Y <- as.matrix(X)
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Y <- Y/sum(Y[1,])
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Z <- matrix(nrow=nrow(Y),ncol=ncol(Y))
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for ( ii in 1:nrow(Y) ) {
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for ( jj in 1:ncol(Y) ) {
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# see how much density is in the remaining columns
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Z[ii,jj] = sum(Y[ii,jj:ncol(Y)])
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}
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}
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medians = matrix(nrow=1,ncol=ncol(Z))
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quan90 = matrix(nrow=1,ncol=ncol(Z))
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for ( cc in 1:ncol(Z) ) {
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medians[cc] = median(Z[,cc])
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quan90[cc] = quantile(Z[,cc],0.9)
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}
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plot(t(medians),xlab="",xaxt="n",ylab="Proportion of loci with >X coverage",type="b",col="blue")
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axis(1,labels=FALSE)
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parseColNames <- function(K) {
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M = matrix(nrow=1,ncol=length(labels))
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number = 0
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for ( lab in K ) {
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number = 1 + number
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M[1,number] = unlist(strsplit(lab,split="_"))[2]
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}
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return(M)
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}
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labels <- parseColNames(colnames(X))
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text(1:length(labels),par("usr")[3]-0.05,srt=90,adj=1,labels=labels,xpd=TRUE)
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points(t(quan90),type="b",col="red")
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legend(x=floor(0.6*length(labels)),y=1,c("50% of samples","90% of samples"),col=c("red","blue"),lty=c(1,1))
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}
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HistogramMedians <- function(X) {
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hist(as.numeric(as.matrix(unlist(X[1:nrow(X)-1,5]))),floor(nrow(X)/2),xlab="Median Coverage",ylab="Number of Samples", main="Median coverage acrosss samples",col="grey")
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}
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HeatmapLocusTable <- function(X) {
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Y <- as.matrix(X)
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heatmap(Y,Rowv=NA,Colv=NA)
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}
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PlotMeanMeadianQuartiles <- function(X) {
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colors <- rainbow(4,start=0.6,end=0.9,gamma=1)
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means = as.numeric(as.matrix(unlist(X[1:nrow(X)-1,3])))
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medians = as.numeric(as.matrix(unlist(X[1:nrow(X)-1,5])))
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thirdQ = as.numeric(as.matrix(unlist(X[1:nrow(X)-1,4])))
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firstQ = as.numeric(as.matrix(unlist(X[1:nrow(X)-1,6])))
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plot(means,xlab="",ylab="Depth of Coverage",xaxt="n",col=colors[1],pch=3,type="b")
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points(firstQ,col=colors[2],pch=2,type="b")
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points(medians,col=colors[3],pch=1,type="b")
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points(thirdQ,col=colors[4],pch=2,type="b")
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axis(1,labels=FALSE)
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labels <- X[1:nrow(X)-1,1]
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text(1:nrow(X)-1,par("usr")[3]-0.25,srt=45,adj=1,labels=labels,xpd=TRUE)
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}
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