# HG changeset patch
# User yhoogstrate
# Date 1389260301 18000
# Node ID 61e42740b13ac81da18e792f4ae4f97468b84a1c
# Parent  149a52c74f39827286b5e0b799126c71d2927f36
Uploaded

diff -r 149a52c74f39 -r 61e42740b13a edgeR_DGE.xml
--- a/edgeR_DGE.xml	Thu Jan 09 04:30:24 2014 -0500
+++ b/edgeR_DGE.xml	Thu Jan 09 04:38:21 2014 -0500
@@ -64,8 +64,6 @@
 output_8            = args[11]
 
 
-
-
 library(edgeR)
 raw_data <- read.delim(designmatrix,header=T,stringsAsFactors=T)
 
@@ -149,10 +147,10 @@
 
 lrt <- glmLRT(fit, contrast=cont[,1])
 print(paste("Exporting to file: ",output_1,sep=""))
-write.table(file=output_1,topTags(lrt,n=nrow(read_counts))$table,sep="\t",row.names=T)
+write.table(file=output_1,topTags(lrt,n=nrow(read_counts))\$table,sep="\t",row.names=T)
 write.table(file=output_2,cpm(dge,normalized.lib.sizes=TRUE),sep="\t")
 ## todo EXPORT FPKM
-write.table(file=output_4,dge$counts,sep="\t")
+write.table(file=output_4,dge\$counts,sep="\t")
 
 
 
@@ -160,8 +158,8 @@
   print("Creating MA plots...")
   
   
-  etable <- topTags(lrt, n=nrow(dge))$table
-  etable <- etable[order(etable$FDR), ]
+  etable <- topTags(lrt, n=nrow(dge))\$table
+  etable <- etable[order(etable\$FDR), ]
   pdf(output_7)
   with(etable, plot(logCPM, logFC, pch=20, main="edgeR: Fold change vs abundance"))
   with(subset(etable, FDR<0.05), points(logCPM, logFC, pch=20, col="red"))