# 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"))