Only edgeR and NOIseq were implemented for DE analysis in tappAS, while DESeq2 was excluded from the DE module. Is there any rationale behind this choice?

Only edgeR and NOIseq were implemented for DE analysis…

NOISeq is an R package for QC of RNA-Seq data and DE analysis that was developed by our group, and we routinely use it to perform our own analyses. We also included edgeR because it is one of the reference tools in the field, and even though it performs very similarly to DESeq2 (see this blog post by Mike Love for a more thorough description), it includes the TMM normalization method. TMM is one of the most suitable methods for normalization prior to DE analysis, outperforming global scaling methods such as TPM or RPKM, which remove important differences between samples and should be used only for within-sample comparisons (see our group’s review paper on best practices for RNA-Seq analysis for more info). NOISeq also includes the possibility to run edgeR’s TMM function using a wrapper.

Finally, it has been shown that DESeq2 is less optimal in terms of runtime/memory efficiency in comparison to edgeR (see this paper), but we’re considering implementing it in future releases of the application.

Category: Application