Comprehensive evaluation of methods for differential expression analysis of metatranscriptomics data
Hunyong Cho, Yixiang Qu, Chengwen Li, Boyang Tang, Ruiqi Lyu, Bridget M. Lin, Jeffrey M. Roach, M. Andrea Azcárate-Peril, Apoena Aguiar Ribeiro, Michael I. Love, Kimon Divaris, Di Wu
The paper evaluates ten differential expression methods for metatranscriptomics data using real and simulated datasets, finding the logistic-beta test has highest sensitivity and reasonable type I error control.
Briefings in Bioinformatics · Jul 21, 2023Peer-reviewedBioinformatics