62 lines
1.5 KiB
R
Executable File
62 lines
1.5 KiB
R
Executable File
#!/usr/bin/env Rscript
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args <- commandArgs(TRUE)
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base_name = args[1]
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input = args[2]
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d <- read.table(input, header=T)
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# separate the data into filtered and unfiltered
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d.filtered <- d[d$filter_type=="filtered",]
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d.unfiltered <- d[d$filter_type=="unfiltered",]
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if (nrow(d.filtered) > 0) {
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d.display <- d.filtered
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} else {
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d.display <- d.unfiltered
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}
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#
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# Plot histograms of the known versus novel Ti/Tv
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#
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outfile = paste(base_name, ".histograms.png", sep="")
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if (nrow(d.filtered) > 0) {
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nFilterTypes <- 2
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} else {
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nFilterTypes <- 1
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}
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bitmap(outfile, width=600, height=(300 * nFilterTypes), units="px")
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par(cex=1.1, mfrow=c(1 * nFilterTypes,2))
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nbreaks <- 20
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color <- "grey"
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xlim <- c(0,4)
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hist(d.unfiltered$known_titv, nbreaks, col=color, xlim=xlim)
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hist(d.unfiltered$novel_titv, nbreaks, col=color, xlim=xlim)
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if (nrow(d.filtered) > 0) {
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hist(d.filtered$known_titv, nbreaks, col=color, xlim=xlim)
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hist(d.filtered$novel_titv, nbreaks, col=color, xlim=xlim)
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}
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dev.off()
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#
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# Plot samples in order of novel Ti/Tv versus known Ti/Tv
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#
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outfile = paste(base_name, ".novel_vs_known_titv.png", sep="")
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bitmap(outfile, width=600, height=600, units="px")
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d.display <- d.display[order(d.display$novel_titv),]
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plot(1:length(d.display$known_titv),d.display$known_titv,type="b",col="blue",ylim=c(0,4), xlab="Sample #", ylab="Ti / Tv")
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points(1:length(d.display$novel_titv),d.display$novel_titv,type="b",col="red",ylim=c(0,4))
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legend("bottomright", c("known","novel"), col=c("blue","red"), pch=21)
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dev.off()
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