diff mutation_analysis.r @ 114:e7b550d52eb7 draft

Uploaded
author davidvanzessen
date Tue, 09 Aug 2016 07:20:41 -0400
parents ade5cf6fd2dc
children ede6c4ee5196
line wrap: on
line diff
--- a/mutation_analysis.r	Thu Aug 04 04:52:51 2016 -0400
+++ b/mutation_analysis.r	Tue Aug 09 07:20:41 2016 -0400
@@ -169,6 +169,8 @@
 
 setwd(outputdir)
 
+base.order = data.frame(base=c("A", "T", "C", "G"), order=1:4)
+
 calculate_result = function(i, gene, dat, matrx, f, fname, name){
 	tmp = dat[grepl(paste("^", gene, ".*", sep=""), dat$best_match),]
 
@@ -179,67 +181,67 @@
 	 
 	if(nrow(tmp) > 0){
 	  
-	  if(fname == "sum"){
+		if(fname == "sum"){
 		matrx[1,x] = round(f(tmp$VRegionMutations, na.rm=T), digits=1)
 		matrx[1,y] = round(f(tmp$VRegionNucleotides, na.rm=T), digits=1)
 		matrx[1,z] = round(f(matrx[1,x] / matrx[1,y]) * 100, digits=1)
-	  } else {
+		} else {
 		matrx[1,x] = round(f(tmp$VRegionMutations, na.rm=T), digits=1)
 		matrx[1,y] = round(f(tmp$VRegionNucleotides, na.rm=T), digits=1)
 		matrx[1,z] = round(f(tmp$VRegionMutations / tmp$VRegionNucleotides) * 100, digits=1)
-	  }
-	  
-	  matrx[2,x] = round(f(tmp$transitionMutations, na.rm=T), digits=1)
-	  matrx[2,y] = round(f(tmp$VRegionMutations, na.rm=T), digits=1)
-	  matrx[2,z] = round(matrx[2,x] / matrx[2,y] * 100, digits=1)
-	  
-	  matrx[3,x] = round(f(tmp$transversionMutations, na.rm=T), digits=1)
-	  matrx[3,y] = round(f(tmp$VRegionMutations, na.rm=T), digits=1)
-	  matrx[3,z] = round(matrx[3,x] / matrx[3,y] * 100, digits=1)
-	  
-	  matrx[4,x] = round(f(tmp$transitionMutationsAtGC, na.rm=T), digits=1)
-	  matrx[4,y] = round(f(tmp$totalMutationsAtGC, na.rm=T), digits=1)
-	  matrx[4,z] = round(matrx[4,x] / matrx[4,y] * 100, digits=1)
-	  
-	  matrx[5,x] = round(f(tmp$totalMutationsAtGC, na.rm=T), digits=1)
-	  matrx[5,y] = round(f(tmp$VRegionMutations, na.rm=T), digits=1)
-	  matrx[5,z] = round(matrx[5,x] / matrx[5,y] * 100, digits=1)
-	  
-	  matrx[6,x] = round(f(tmp$transitionMutationsAtAT, na.rm=T), digits=1)
-	  matrx[6,y] = round(f(tmp$totalMutationsAtAT, na.rm=T), digits=1)
-	  matrx[6,z] = round(matrx[6,x] / matrx[6,y] * 100, digits=1)
-	  
-	  matrx[7,x] = round(f(tmp$totalMutationsAtAT, na.rm=T), digits=1)
-	  matrx[7,y] = round(f(tmp$VRegionMutations, na.rm=T), digits=1)
-	  matrx[7,z] = round(matrx[7,x] / matrx[7,y] * 100, digits=1)
-	  
-	  matrx[8,x] = round(f(tmp$nonSilentMutationsFR, na.rm=T), digits=1)
-	  matrx[8,y] = round(f(tmp$silentMutationsFR, na.rm=T), digits=1)
-	  matrx[8,z] = round(matrx[8,x] / matrx[8,y], digits=1)
-	  
-	  matrx[9,x] = round(f(tmp$nonSilentMutationsCDR, na.rm=T), digits=1)
-	  matrx[9,y] = round(f(tmp$silentMutationsCDR, na.rm=T), digits=1)
-	  matrx[9,z] = round(matrx[9,x] / matrx[9,y], digits=1)
-	  
-	  if(fname == "sum"){
-		  matrx[10,x] = round(f(rowSums(tmp[,c("FR2.IMGT.Nb.of.nucleotides", "FR3.IMGT.Nb.of.nucleotides")], na.rm=T)), digits=1)
-		  matrx[10,y] = round(f(tmp$VRegionNucleotides, na.rm=T), digits=1)
-		  matrx[10,z] = round(matrx[10,x] / matrx[10,y], digits=1)
-		  
-		  matrx[11,x] = round(f(rowSums(tmp[,c("CDR1.IMGT.Nb.of.nucleotides", "CDR2.IMGT.Nb.of.nucleotides")], na.rm=T)), digits=1)
-		  matrx[11,y] = round(f(tmp$VRegionNucleotides, na.rm=T), digits=1)
-		  matrx[11,z] = round(matrx[11,x] / matrx[11,y], digits=1)
-	  }
-  }
+		}
+
+		matrx[2,x] = round(f(tmp$transitionMutations, na.rm=T), digits=1)
+		matrx[2,y] = round(f(tmp$VRegionMutations, na.rm=T), digits=1)
+		matrx[2,z] = round(matrx[2,x] / matrx[2,y] * 100, digits=1)
+
+		matrx[3,x] = round(f(tmp$transversionMutations, na.rm=T), digits=1)
+		matrx[3,y] = round(f(tmp$VRegionMutations, na.rm=T), digits=1)
+		matrx[3,z] = round(matrx[3,x] / matrx[3,y] * 100, digits=1)
+
+		matrx[4,x] = round(f(tmp$transitionMutationsAtGC, na.rm=T), digits=1)
+		matrx[4,y] = round(f(tmp$totalMutationsAtGC, na.rm=T), digits=1)
+		matrx[4,z] = round(matrx[4,x] / matrx[4,y] * 100, digits=1)
+
+		matrx[5,x] = round(f(tmp$totalMutationsAtGC, na.rm=T), digits=1)
+		matrx[5,y] = round(f(tmp$VRegionMutations, na.rm=T), digits=1)
+		matrx[5,z] = round(matrx[5,x] / matrx[5,y] * 100, digits=1)
+
+		matrx[6,x] = round(f(tmp$transitionMutationsAtAT, na.rm=T), digits=1)
+		matrx[6,y] = round(f(tmp$totalMutationsAtAT, na.rm=T), digits=1)
+		matrx[6,z] = round(matrx[6,x] / matrx[6,y] * 100, digits=1)
+
+		matrx[7,x] = round(f(tmp$totalMutationsAtAT, na.rm=T), digits=1)
+		matrx[7,y] = round(f(tmp$VRegionMutations, na.rm=T), digits=1)
+		matrx[7,z] = round(matrx[7,x] / matrx[7,y] * 100, digits=1)
+
+		matrx[8,x] = round(f(tmp$nonSilentMutationsFR, na.rm=T), digits=1)
+		matrx[8,y] = round(f(tmp$silentMutationsFR, na.rm=T), digits=1)
+		matrx[8,z] = round(matrx[8,x] / matrx[8,y], digits=1)
+
+		matrx[9,x] = round(f(tmp$nonSilentMutationsCDR, na.rm=T), digits=1)
+		matrx[9,y] = round(f(tmp$silentMutationsCDR, na.rm=T), digits=1)
+		matrx[9,z] = round(matrx[9,x] / matrx[9,y], digits=1)
+
+		if(fname == "sum"){
+			matrx[10,x] = round(f(rowSums(tmp[,c("FR2.IMGT.Nb.of.nucleotides", "FR3.IMGT.Nb.of.nucleotides")], na.rm=T)), digits=1)
+			matrx[10,y] = round(f(tmp$VRegionNucleotides, na.rm=T), digits=1)
+			matrx[10,z] = round(matrx[10,x] / matrx[10,y], digits=1)
+
+			matrx[11,x] = round(f(rowSums(tmp[,c("CDR1.IMGT.Nb.of.nucleotides", "CDR2.IMGT.Nb.of.nucleotides")], na.rm=T)), digits=1)
+			matrx[11,y] = round(f(tmp$VRegionNucleotides, na.rm=T), digits=1)
+			matrx[11,z] = round(matrx[11,x] / matrx[11,y], digits=1)
+		}
+	}
   
-  transitionTable = data.frame(A=zeros,C=zeros,G=zeros,T=zeros)
-  row.names(transitionTable) = c("A", "C", "G", "T")
-  transitionTable["A","A"] = NA
-  transitionTable["C","C"] = NA
-  transitionTable["G","G"] = NA
-  transitionTable["T","T"] = NA
+	transitionTable = data.frame(A=zeros,C=zeros,G=zeros,T=zeros)
+	row.names(transitionTable) = c("A", "C", "G", "T")
+	transitionTable["A","A"] = NA
+	transitionTable["C","C"] = NA
+	transitionTable["G","G"] = NA
+	transitionTable["T","T"] = NA
 
-  if(nrow(tmp) > 0){
+	if(nrow(tmp) > 0){
 		for(nt1 in nts){
 			for(nt2 in nts){
 				if(nt1 == nt2){
@@ -259,20 +261,40 @@
 				}
 			}
 		}
-  }
-  
-  
-  print(paste("writing value file: ", name, "_", fname, "_value.txt" ,sep=""))
-  
-  write.table(x=transitionTable, file=paste("transitions_", name ,"_", fname, ".txt", sep=""), sep=",",quote=F,row.names=T,col.names=NA)
-  write.table(x=tmp[,c("Sequence.ID", "best_match", "chunk_hit_percentage", "nt_hit_percentage", "start_locations")], file=paste("matched_", name , "_", fname, ".txt", sep=""), sep="\t",quote=F,row.names=F,col.names=T)
-  
-  cat(matrx[1,x], file=paste(name, "_", fname, "_value.txt" ,sep=""))
-  cat(nrow(tmp), file=paste(name, "_", fname, "_n.txt" ,sep=""))
-  
-  print(paste(fname, name, nrow(tmp)))
-  
-  matrx
+		transition = transitionTable
+		transition$id = names(transition)
+		
+		transition2 = melt(transition, id.vars="id")
+		
+		transition2 = merge(transition2, base.order, by.x="id", by.y="base")
+		transition2 = merge(transition2, base.order, by.x="variable", by.y="base")
+
+		transition2[is.na(transition2$value),]$value = 0
+		
+		png(filename=paste("transitions_stacked_", name, ".png", sep=""))
+		p = ggplot(transition2, aes(factor(reorder(id, order.x)), y=value, fill=factor(reorder(variable, order.y)))) + geom_bar(position="fill", stat="identity") #stacked bar
+		p = p + xlab("From base") + ylab("To base") + ggtitle("Mutations frequency from base to base") + guides(fill=guide_legend(title=NULL))
+		print(p)
+		dev.off()
+		
+		png(filename=paste("transitions_heatmap_", name, ".png", sep=""))
+		p = ggplot(transition2, aes(factor(reorder(id, order.x)), factor(reorder(variable, order.y)))) + geom_tile(aes(fill = value), colour="white") + scale_fill_gradient(low="white", high="steelblue") #heatmap
+		p = p + xlab("From base") + ylab("To base") + ggtitle("Mutations frequency from base to base")
+		print(p)
+		dev.off()
+	}
+
+	#print(paste("writing value file: ", name, "_", fname, "_value.txt" ,sep=""))
+
+	write.table(x=transitionTable, file=paste("transitions_", name ,"_", fname, ".txt", sep=""), sep=",",quote=F,row.names=T,col.names=NA)
+	write.table(x=tmp[,c("Sequence.ID", "best_match", "chunk_hit_percentage", "nt_hit_percentage", "start_locations")], file=paste("matched_", name , "_", fname, ".txt", sep=""), sep="\t",quote=F,row.names=F,col.names=T)
+
+	cat(matrx[1,x], file=paste(name, "_", fname, "_value.txt" ,sep=""))
+	cat(nrow(tmp), file=paste(name, "_", fname, "_n.txt" ,sep=""))
+
+	#print(paste(fname, name, nrow(tmp)))
+
+	matrx
 }
 
 nts = c("a", "c", "g", "t")
@@ -322,12 +344,6 @@
 
 write.table(x=new.table, file="mutations_sum.txt", sep=",",quote=F,row.names=F,col.names=F)
 
-
-
-if (!("ggplot2" %in% rownames(installed.packages()))) {
-	install.packages("ggplot2", repos="http://cran.xl-mirror.nl/") 
-}
-
 dat = dat[!grepl("^unmatched", dat$best_match),]
 
 #blegh