[BioC] Best way of presenting "absolute" expression values (edgeR)

[Sindre Lee]

Hi!

We want to classify a new type of glands by ranking genes by expression 
level using RNAseq. We don't have any good controls, so we just want to 
see a ranked list of genes.

I have used Cufflinks RPKM values, but if I want to use edgeR, is this 
a valid way of doing it using featureCounts:

fc <- featureCounts(files=targets$Targets,nthreads=8, 
isGTFAnnotationFile=TRUE, GTF.attrType="gene_id", 
GTF.featureType="exon", useMetaFeatures=TRUE, annot.ext="genes.gtf")

x <- DGEList(counts=fc$counts, genes=fc$annotation)

expr <- calcNormFactors(x)

expr_norm <- rpkm(expr, log=FALSE,gene.length=x$genes$Length) # Getting 
gene length from FeatureCounts, using rkpm() in the edgeR package, not 
Rsubread..



Then just write out this table..


Thanks!