RT Journal Article
SR Electronic
T1 EmpiReS: Differential Analysis of Gene Expression and Alternative Splicing
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.08.23.234237
DO 10.1101/2020.08.23.234237
A1 Gergely Csaba
A1 Evi Berchtold
A1 Armin Hadziahmetovic
A1 Markus Gruber
A1 Constantin Ammar
A1 Ralf Zimmer
YR 2020
UL http://biorxiv.org/content/early/2020/08/24/2020.08.23.234237.abstract
AB While absolute quantification is challenging in high-throughput measurements, changes of features between conditions can often be determined with high precision. Therefore, analysis of fold changes is the standard method, but often, a doubly differential analysis of changes of changes is required. Differential alternative splicing is an example of a doubly differential analysis, i.e. fold changes between conditions for different isoforms of a gene. EmpiRe is a quantitative approach for various kinds of omics data based on fold changes for appropriate features of biological objects. Empirical error distributions for these fold changes are estimated from Replicate measurements and used to quantify feature fold changes and their directions. We assess the performance of EmpiRe to detect differentially expressed genes applied to RNA-Seq using simulated data. It achieved higher precision than established tools at nearly the same recall level. Furthermore, we assess the detection of alternatively Spliced genes via changes of isoform fold changes (EmpiReS) on distribution-free simulations and experimentally validated splicing events. EmpiReS achieves the best precision-recall values for simulations based on different biological datasets. We propose EmpiRe(S) as a general, quantitative and fast approach with high reliability and an excellent trade-off between sensitivity and precision in (doubly) differential analyses.Competing Interest StatementThe authors have declared no competing interest.