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Histogram of covariate values now goes from 0 to max value which makes it look nicer in most cases. 

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2259 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
rpoplin 2009-12-04 14:44:03 +00:00
parent 985daec76e
commit 855face681
2 changed files with 5 additions and 5 deletions
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6
R/plot_residualError_OtherCovariate.R
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@ -55,15 +55,15 @@ hst=subset(data.frame(e$Covariate, e$nBases), e.nBases != 0)
hst2=subset(data.frame(f$Covariate, f$nBases), f.nBases != 0)
if( is.numeric(c$Covariate) ) {
if( length(hst$e.Covariate) == 0 ) {
plot(hst2$f.Covariate, hst2$f.nBases, type="h", lwd=2, col="cornflowerblue", main=paste(covariateName,"histogram"), xlab=covariateName, ylab="Count",yaxt="n",xlim=c(min(c$Covariate),max(c$Covariate)))
plot(hst2$f.Covariate, hst2$f.nBases, type="h", lwd=2, col="cornflowerblue", main=paste(covariateName,"histogram"), ylim=c(0, max(hst2$f.nBases)), xlab=covariateName, ylab="Count",yaxt="n",xlim=c(min(c$Covariate),max(c$Covariate)))
} else {
plot(hst$e.Covariate, hst$e.nBases, type="h", lwd=2, main=paste(covariateName,"histogram"), xlab=covariateName, ylab="Count",yaxt="n",xlim=c(min(c$Covariate),max(c$Covariate)))
plot(hst$e.Covariate, hst$e.nBases, type="h", lwd=2, main=paste(covariateName,"histogram"), xlab=covariateName, ylim=c(0, max(hst$e.nBases)),ylab="Number of Bases",yaxt="n",xlim=c(min(c$Covariate),max(c$Covariate)))
points(hst2$f.Covariate, hst2$f.nBases, type="h", lwd=2, col="cornflowerblue")
}
axis(2,axTicks(2), format(axTicks(2), scientific=F))
} 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=7, main=paste(covariateName,"histogram"), xlab=covariateName, ylab="Count",yaxt="n",xaxt="n")
plot(1:length(hst$c.Covariate), hst$c.nBases, type="h", lwd=7, 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)])
axis(2,axTicks(2), format(axTicks(2), scientific=F))
}

4
R/plot_residualError_QualityScoreCovariate.R
View File

@ -39,7 +39,7 @@ outfile = paste(input, ".quality_emp_hist.pdf", sep="")
pdf(outfile, height=7, width=7)
hst=subset(data.frame(e$Qempirical, e$nBases), e.nBases != 0)
hst2=subset(data.frame(f$Qempirical, f$nBases), f.nBases != 0)
plot(hst$e.Qempirical, hst$e.nBases, type="h", lwd=4, xlim=c(0,40), main="Empirical quality score histogram", xlab="Empirical quality score", ylab="Count",yaxt="n")
plot(hst$e.Qempirical, hst$e.nBases, type="h", lwd=4, xlim=c(0,40), ylim=c(0,max(hst$e.nBases)), main="Empirical quality score histogram", xlab="Empirical quality score", ylab="Number of Bases",yaxt="n")
points(hst2$f.Qempirical, hst2$f.nBases, type="h", lwd=4, col="maroon1")
axis(2,axTicks(2), format(axTicks(2), scientific=F))
dev.off()
@ -52,7 +52,7 @@ outfile = paste(input, ".quality_rep_hist.pdf", sep="")
pdf(outfile, height=7, width=7)
hst=subset(data.frame(e$Qreported, e$nBases), e.nBases != 0)
hst2=subset(data.frame(f$Qreported, f$nBases), f.nBases != 0)
plot(hst$e.Qreported, hst$e.nBases, type="h", lwd=4, xlim=c(0,40), main="Reported quality score histogram", xlab="Reported quality score", ylab="Count",yaxt="n")
plot(hst$e.Qreported, hst$e.nBases, type="h", lwd=4, xlim=c(0,40), ylim=c(0,max(hst$e.nBases)), main="Reported quality score histogram", xlab="Reported quality score", ylab="Number of Bases",yaxt="n")
points(hst2$f.Qreported, hst2$f.nBases, type="h", lwd=4, col="maroon1")
axis(2,axTicks(2), format(axTicks(2), scientific=F))
dev.off()