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

View ORCID ProfileKoen Van den Berge, View ORCID ProfileCharlotte Soneson, Michael I. Love, View ORCID ProfileMark D. Robinson, Lieven Clement
doi: https://doi.org/10.1101/157982
Koen Van den Berge
Department of Applied Mathematics, Computer Science and Statistics, Ghent University, BelgiumBioinformatics Institute Ghent, Ghent University, Ghent, Belgium
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  • ORCID record for Koen Van den Berge
Charlotte Soneson
Institute of Molecular Life Sciences, University of Zurich, Zurich, SwitzerlandSIB Swiss Institute of Bioinformatics, Zurich, Switzerland
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  • ORCID record for Charlotte Soneson
Michael I. Love
Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
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Mark D. Robinson
Institute of Molecular Life Sciences, University of Zurich, Zurich, SwitzerlandSIB Swiss Institute of Bioinformatics, Zurich, Switzerland
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Lieven Clement
Department of Applied Mathematics, Computer Science and Statistics, Ghent University, BelgiumBioinformatics Institute Ghent, Ghent University, Ghent, Belgium
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  • For correspondence: lieven.clement@ugent.be
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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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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted June 30, 2017.
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zingeR: unlocking RNA-seq tools for zero-inflation and single cell applications
Koen Van den Berge, Charlotte Soneson, Michael I. Love, Mark D. Robinson, Lieven Clement
bioRxiv 157982; doi: https://doi.org/10.1101/157982
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zingeR: unlocking RNA-seq tools for zero-inflation and single cell applications
Koen Van den Berge, Charlotte Soneson, Michael I. Love, Mark D. Robinson, Lieven Clement
bioRxiv 157982; doi: https://doi.org/10.1101/157982

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