--- a/mutation_analysis.r	Thu Jul 14 07:29:56 2016 -0400
+++ b/mutation_analysis.r	Tue Aug 02 08:30:23 2016 -0400
@@ -307,26 +307,28 @@
 	write.table(x=result, file=paste("mutations_", fname, ".txt", sep=""), sep=",",quote=F,row.names=T,col.names=F)
 }
 
+sum.table = read.table("mutations_sum.txt", sep=",", header=F)
+median.table = read.table("mutations_median.txt", sep=",", header=F)
+
+#sum.table["Median of Number of Mutations (%)",] = median.table[1,]
+
+new.table = sum.table[1,]
+new.table[2,] = median.table[1,]
+new.table[3:12,] = sum.table[2:11,]
+new.table[,1] = as.character(new.table[,1])
+new.table[2,1] = "Median of Number of Mutations (%)"
+
+#sum.table = sum.table[c("Number of Mutations (%)", "Median of Number of Mutations (%)", "Transition (%)", "Transversions (%)", "Transitions at G C (%)", "Targeting of C G (%)", "Transitions at A T (%)", "Targeting of A T (%)", "FR R/S (ratio)", "CDR R/S (ratio)", "nt in FR", "nt in CDR"),]
+
+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/") 
 }
 
-genesForPlot = gsub("[0-9]", "", dat$best_match)
-genesForPlot = data.frame(table(genesForPlot))
-colnames(genesForPlot) = c("Gene","Freq")
-genesForPlot$label = paste(genesForPlot$Gene, "-", genesForPlot$Freq)
-write.table(genesForPlot, "all.txt", sep="\t",quote=F,row.names=F,col.names=T)
-
-
-pc = ggplot(genesForPlot, aes(x = factor(1), y=Freq, fill=label))
-pc = pc + geom_bar(width = 1, stat = "identity")
-pc = pc + coord_polar(theta="y")
-pc = pc + xlab(" ") + ylab(" ") + ggtitle(paste("Classes", "( n =", sum(genesForPlot$Freq), ")"))
-
-png(filename="all.png")
-pc
-dev.off()
+dat = dat[!grepl("^unmatched", dat$best_match),]
 
 #blegh
 genesForPlot = dat[grepl("ca", dat$best_match),]$best_match
@@ -377,11 +379,6 @@
 
 write.table(dat, input, sep="\t",quote=F,row.names=F,col.names=T)
 
-
-
-
-
-
 dat$best_match_class = substr(dat$best_match, 0, 2)
 freq_labels = c("0", "0-2", "2-5", "5-10", "10-15", "15-20", "20")
 dat$frequency_bins = cut(dat$percentage_mutations, breaks=c(-Inf, 0, 2,5,10,15,20, Inf), labels=freq_labels)