I have RNA-Seq counts which are FPKM/RPKM normalized. which package in R should i use for Differential gene expression. among many packages which package is better? is DGE using raw count is better or using FPKM/RPKM normalized counst are better ?
Thanks in anticipation.
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hafiz.talhamalik
which package in R should i use for Differential gene expression?
Assuming you mean to do diff.expr. with FPKM, I think Limma does a pretty good job. However ...
among many packages which package is better?
This question I think is hard to answer. The jury is out on this one!
is DGE using raw count is better or using FPKM/RPKM normalized counst are better ?
The author of the FPKM measurements himself called FPKM as "biased" and "wrong". So I would go for raw counts when possible. My pipeline usually includes htseq-count and DESeq2, but other couting programs and other differential expression analysis programs are fine!
Thanks.. but limma was built for micro-array is it good enough for RNA-seq ?
As far as I know, you can plug FPKM values in.
DESeq2 is a good package for DEG analysis in R. https://bioconductor.org/packages/release/bioc/html/DESeq2.html
If you are using R package for DEG analysis, then go ahead with raw counts. It is not recommended to perform DEG analysis on normalized count using DESeq2 because it performs internal normalization.
Thankyou so much.. and what about edgeR ?
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