The most commonly used methods for differential expression analysis may yield too many false positive results

RNA-seq studies are growing in size and popularity. Researchers from INSERM University of Bordeaux provide evidence that the most commonly used methods for differential expression analysis (DEA) may yield too many false positive results in some situations. They present dearseq, a new method for DEA that controls the false discovery rate (FDR) without making any assumption about the true distribution of RNA-seq data. The researchers show that dearseq controls the FDR while maintaining strong statistical power compared to the most popular methods. They demonstrate this behavior with mathematical proofs, simulations and a real data set from a study of tuberculosis, where our method produces fewer apparent false positives.

Availabilitydearseq is freely available on Bioconductor at: http://www.bioconductor.org/packages/release/bioc/html/dearseq.html

Gauthier M, Agniel D, Thiébaut R, Hejblum BP. (2020) dearseq: a variance component score test for RNA-seq differential analysis that effectively controls the false discovery rate. NAR Gen and Bioinform 2(4), lqaa093. [article]

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