--- a/pattern_plots.r	Fri Dec 16 10:17:16 2016 -0500
+++ b/pattern_plots.r	Tue Dec 20 09:03:15 2016 -0500
@@ -47,6 +47,11 @@
 
 names(data1) = c("Class", "Type", "value")
 
+chk = is.na(data1$value)
+if(any(chk)){
+	data1[chk, "value"] = 0
+}
+
 data1 = data1[order(data1$Type),]
 
 write.table(data1, plot1.txt, quote=F, sep="\t", na="", row.names=F, col.names=T)
@@ -79,6 +84,11 @@
 
 names(data2) = c("Class", "Type", "value")
 
+chk = is.na(data2$value)
+if(any(chk)){
+	data2[chk, "value"] = 0
+}
+
 data2 = data2[order(data2$Type),]
 
 write.table(data2, plot2.txt, quote=F, sep="\t", na="", row.names=F, col.names=T)
@@ -94,9 +104,6 @@
 data3 = data3[,names(data3)[grepl("\\.x", names(data3))]]
 names(data3) = gsub(".x", "", names(data3))
 
-data3[is.na(data3)] = 0
-#data3[is.infinite(data3)] = 0
-
 data3["G/C transitions",] = round(data3["Transitions at G C (%)",] / (data3["C",] + data3["G",]) * 100, 1)
 
 data3["G/C transversions",] = round((data3["Targeting of G C (%)",] - data3["Transitions at G C (%)",]) / (data3["C",] + data3["G",]) * 100, 1)
@@ -115,6 +122,11 @@
 data3 = melt(t(data3[8:10,]))
 names(data3) = c("Class", "Type", "value")
 
+chk = is.na(data1$data3)
+if(any(chk)){
+	data3[chk, "value"] = 0
+}
+
 data3 = data3[order(data3$Type),]
 
 write.table(data3, plot3.txt, quote=F, sep="\t", na="", row.names=F, col.names=T)