Selecting Deferentially Expressed Genes in RNASeq data analysis

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

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7.2 years ago

Sreeraj Thamban ▴ 300

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 • 4.5k views

ADD COMMENT • link updated 7.2 years ago by Kevin Blighe 88k • written 7.2 years ago by Sreeraj Thamban ▴ 300

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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 REPLY • link 7.2 years ago by Panagiotis Moulos ▴ 20

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

ADD REPLY • link 7.2 years ago by Sreeraj Thamban ▴ 300

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