Selecting Deferentially Expressed Genes in RNASeq data analysis - DESEq2 and Cuffdiff

Question

[Sreeraj Thamban]

Hi all, During Differential gene expression analysis of RNASeq data (DESEq2 or Cufdiff) which is best method to filter differentially expressed genes? Should I go with all the genes having adjusted P value < 0.05 or should I filter them based on a log2 Fold change cut-off?

Thank you

[Panagiotis Moulos]

You can also try an integrated approach like metaseqR with more than one algorithms and combined p-values. In this way you don't have to struggle with comparisons as the method combines the "advantages" of many algorithms towards the optimization of precision-recall tradeoff. Disclaimer: I am the author of that package.

[Sreeraj Thamban]

Thank you Moulos, I will definitely give metaseqR a try.