Title |
Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications
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Published in |
Genome Biology, February 2018
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DOI | 10.1186/s13059-018-1406-4 |
Pubmed ID | |
Authors |
Koen Van den Berge, Fanny Perraudeau, Charlotte Soneson, Michael I. Love, Davide Risso, Jean-Philippe Vert, Mark D. Robinson, Sandrine Dudoit, Lieven Clement |
Abstract |
Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis. This has triggered the development of bespoke scRNA-seq DE methods to 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 a weighting strategy, based on a zero-inflated negative binomial model, that identifies excess zero counts and generates gene- and cell-specific weights to unlock bulk RNA-seq DE pipelines for zero-inflated data, boosting performance for scRNA-seq. |
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United Kingdom | 12 | 13% |
Australia | 7 | 8% |
Germany | 7 | 8% |
France | 5 | 5% |
Canada | 3 | 3% |
Switzerland | 3 | 3% |
Finland | 3 | 3% |
Austria | 2 | 2% |
Other | 9 | 10% |
Unknown | 23 | 25% |
Demographic breakdown
Type | Count | As % |
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Scientists | 54 | 59% |
Members of the public | 36 | 39% |
Science communicators (journalists, bloggers, editors) | 2 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 305 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 70 | 23% |
Researcher | 63 | 21% |
Student > Master | 32 | 10% |
Student > Bachelor | 22 | 7% |
Student > Postgraduate | 11 | 4% |
Other | 42 | 14% |
Unknown | 65 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 77 | 25% |
Agricultural and Biological Sciences | 64 | 21% |
Computer Science | 25 | 8% |
Mathematics | 14 | 5% |
Engineering | 11 | 4% |
Other | 43 | 14% |
Unknown | 71 | 23% |