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Update to AnalyzeCovariates to make the histogram of PairedReadOrder look a little nicer 

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2575 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
rpoplin 2010-01-13 20:26:31 +00:00
parent 49c44e7b36
commit 7f97041875
1 changed files with 5 additions and 1 deletions
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6
R/plot_residualError_OtherCovariate.R
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@ -98,7 +98,11 @@ if( is.numeric(c$Covariate) ) {
} else { # Dinuc (and other non-numeric covariates) are different to make their plots look nice
hst=subset(data.frame(c$Covariate, c$nBases), c.nBases != 0)
plot(1:length(hst$c.Covariate), hst$c.nBases, type="h", lwd=lwdSize, main=paste(covariateName,"histogram"), ylim=c(0, max(hst$c.nBases)),xlab=covariateName, ylab="Number of Bases",yaxt="n",xaxt="n")
axis(1, at=seq(1,length(hst$c.Covariate),2), labels = hst$c.Covariate[seq(1,length(hst$c.Covariate),2)])
if( length(hst$c.Covariate) > 9 ) {
axis(1, at=seq(1,length(hst$c.Covariate),2), labels = hst$c.Covariate[seq(1,length(hst$c.Covariate),2)])
} else {
axis(1, at=seq(1,length(hst$c.Covariate),1), labels = hst$c.Covariate)
}
axis(2,axTicks(2), format(axTicks(2), scientific=F))
}
dev.off()