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Now with dbSNP rate 

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@6010 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
depristo 2011-06-17 13:21:40 +00:00
parent dd1d9cd76f
commit 285da580f3
1 changed files with 31 additions and 6 deletions
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37
R/exomeQC.R
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@ -143,11 +143,12 @@ addSection <- function(name) {
} }
createMetricsBySamples <- function(VariantEvalRoot) { createMetricsBySamples <- function(VariantEvalRoot) {
byAFEval <- expandVEReport(gsa.read.gatkreport(paste(VariantEvalRoot, ".bySample.eval", sep=""))) bySampleEval <- expandVEReport(gsa.read.gatkreport(paste(VariantEvalRoot, ".bySample.eval", sep="")))
r = merge(byAFEval$TiTvVariantEvaluator, byAFEval$CountVariants) r = merge(bySampleEval$TiTvVariantEvaluator, bySampleEval$CountVariants)
r = merge(r, bySampleEval$CompOverlap)
if ( ! is.na(preQCFile) ) { if ( ! is.na(preQCFile) ) {
preQCMetrics <- read.table(preQCFile, header=T) preQCMetrics <- read.table(preQCFile, header=T)
r = merge(merge(byAFEval$TiTvVariantEvaluator, byAFEval$CountVariants), preQCMetrics) r = merge(r, preQCMetrics)
} }
# order the samples by nSNPs -- it's the natural ordering. # order the samples by nSNPs -- it's the natural ordering.
x = subset(r, Novelty=="all") x = subset(r, Novelty=="all")
@ -170,7 +171,7 @@ perSamplePlots <- function(metricsBySamples) {
sampleTextLabelScale <- scale_size("Highlighted samples", to=c(3,5), breaks=c(1,2), labels=c("regular", "highlighted")) sampleTextLabelScale <- scale_size("Highlighted samples", to=c(3,5), breaks=c(1,2), labels=c("regular", "highlighted"))
xAxis <- scale_x_discrete("Sample (ordered by nSNPs)", formatter=function(x) "") xAxis <- scale_x_discrete("Sample (ordered by nSNPs)", formatter=function(x) "")
myRug <- geom_rug(position="jitter") myRug <- geom_rug(position="jitter")
#myRug <- geom_rug(aes(x = NULL)) #myRug <- geom_rug(aes(x=NULL), position="jitter")
measures = c("nSNPs", "tiTvRatio", "nSingletons", "nIndels", "nInsertions", "nDeletions", "deletionInsertionRatio") measures = c("nSNPs", "tiTvRatio", "nSingletons", "nIndels", "nInsertions", "nDeletions", "deletionInsertionRatio")
name = "by sample" name = "by sample"
@ -196,7 +197,31 @@ perSamplePlots <- function(metricsBySamples) {
p <- p + xAxis p <- p + xAxis
print(p) print(p)
} }
# known / novel ratio by sample
# TODO -- would ideally not conflate SNPs and Indels
d = subset(metricsBySamples, Novelty == "all" & CompRod == "dbsnp")
title <- opts(title = "Novelty rate by sample")
# distribution
p <- ggplot(data=d, aes(x=compRate))
p <- p + title
p <- p + geom_density(alpha=0.5)
p <- p + geom_rug(aes(y=NULL, position="jitter"))
p <- p + scale_x_continuous("Percent of variants in dbSNP")
# how do we remove the labels?
print(p)
p <- ggplot(data=d, aes(x=Sample, y=compRate))
p <- p + title
p <- p + geom_smooth(alpha=0.5, aes(group=Novelty))
p <- p + sampleTextLabel + sampleTextLabelScale
p <- p + geom_rug(aes(x=NULL, position="jitter"))
#p <- p + myRug
# how do we remove the labels?
p <- p + xAxis
print(p)
for ( novelty in c("all", "known", "novel") ) { for ( novelty in c("all", "known", "novel") ) {
# TODO -- how can I color it as before? # TODO -- how can I color it as before?
# TODO -- add marginal distributions? # TODO -- add marginal distributions?