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bioRxiv · 10.1101/157982

zingeR: unlocking RNA-seq tools for zero-inflation and single cell applications

Van den Berge, K.·Soneson, C.·Love, M. I.·Robinson, M. D.·Clement, L.
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Abstract

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.

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Van den Berge, K., Soneson, C., Love, M. I., Robinson, M. D., Clement, L.. 2017-06-30. zingeR: unlocking RNA-seq tools for zero-inflation and single cell applications. https://doi.org/10.1101/157982

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