Best Way To Normalize Rna-Seq Data

Question

[Edalat]

Hi all,

I have several RNA-seq data(all of them have replication),after RNA-seq analysis,I want to perform met-analysis (for given a set of genes that are up-regulated or down regulate under drug conditions), I am wondering the best way to normalize the data - just calculate RPKM values or I should perform some sort of upper normalization? If so, what is the best way to do this?

[Devon Ryan]

How about "none of the above" and you instead add a "batch" or "experiment" factor to your design.

Answer 1

[Steven Lakin]

Use the R packages DESeq2 or EdgeR and let the packages do the normalization for you; it is the easiest approach and they are based on tested methods. RPKM is generally not an acceptable measure to use in current methodology; the statistics have come a long way since that calculation was developed. Alternatively, if you really know what you're doing with the stats, you could use a generalized linear mixed model, which has been shown to produce slightly more accurate rankings for differential expression because it takes into account random effects (though take this with a grain of salt, since it's mostly simulated data).