RT Journal Article SR Electronic T1 dearseq: a variance component score test for RNA-Seq differential analysis that effectively controls the false discovery rate JF bioRxiv FD Cold Spring Harbor Laboratory SP 635714 DO 10.1101/635714 A1 Gauthier, Marine A1 Agniel, Denis A1 ThiƩbaut, Rodolphe A1 Hejblum, Boris P. YR 2019 UL http://biorxiv.org/content/early/2019/05/20/635714.abstract AB RNA-seq studies are growing in size and popularity. We provide evidence that the most commonly used methods for differential expression analysis (DEA) may yield too many false positive results in some situations. We present dearseq, a new method for DEA which controls the FDR without making any assumption about the true distribution of RNA-seq data. We show that dearseq controls the FDR while maintaining strong statistical power compared to the most popular methods. We 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.