diff --git a/R/plot_residualError_OtherCovariate.R b/R/plot_residualError_OtherCovariate.R
index 23bdd7e1f..e387a2613 100644
--- a/R/plot_residualError_OtherCovariate.R
+++ b/R/plot_residualError_OtherCovariate.R
@@ -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))
 }
diff --git a/R/plot_residualError_QualityScoreCovariate.R b/R/plot_residualError_QualityScoreCovariate.R
index 00436c8b3..7b3c166bf 100644
--- a/R/plot_residualError_QualityScoreCovariate.R
+++ b/R/plot_residualError_QualityScoreCovariate.R
@@ -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()