Question: Selecting Deferentially Expressed Genes in RNASeq data analysis - DESEq2 and Cuffdiff
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gravatar for Sreeraj Thamban
3.2 years ago by
Indian Institute of Science Education and Research
Sreeraj Thamban220 wrote:

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

rna-seq deseq2 • 2.9k views
ADD COMMENTlink modified 3.2 years ago by Kevin Blighe67k • written 3.2 years ago by Sreeraj Thamban220
1

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.

ADD REPLYlink written 3.2 years ago by Panagiotis Moulos20

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

ADD REPLYlink written 3.2 years ago by Sreeraj Thamban220
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