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!