TY - JOUR T1 - zingeR: unlocking RNA-seq tools for zero-inflation and single cell applications JF - bioRxiv DO - 10.1101/157982 SP - 157982 AU - Koen Van den Berge AU - Charlotte Soneson AU - Michael I. Love AU - Mark D. Robinson AU - Lieven Clement Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/06/30/157982.abstract N2 - Dropout in single cell RNA-seq (scRNA-seq) applications causes many transcripts to go undetected. It induces excess zero counts, which leads to power issues in differential expression (DE) analysis and has triggered the development of bespoke scRNA-seq DE tools that cope with zero-inflation. Recent evaluations, however, have shown that dedicated scRNA-seq tools provide no advantage compared to traditional bulk RNA-seq tools. We introduce zingeR, a zero-inflated negative binomial model that identifies excess zero counts and generates observation weights to unlock bulk RNA-seq pipelines for zero-inflation, boosting performance in scRNA-seq differential expression analysis. ER -