Title |
Genotype-free demultiplexing of pooled single-cell RNA-seq
|
---|---|
Published in |
Genome Biology, December 2019
|
DOI | 10.1186/s13059-019-1852-7 |
Pubmed ID | |
Authors |
Jun Xu, Caitlin Falconer, Quan Nguyen, Joanna Crawford, Brett D. McKinnon, Sally Mortlock, Anne Senabouth, Stacey Andersen, Han Sheng Chiu, Longda Jiang, Nathan J. Palpant, Jian Yang, Michael D. Mueller, Alex W. Hewitt, Alice Pébay, Grant W. Montgomery, Joseph E. Powell, Lachlan J.M Coin |
Abstract |
A variety of methods have been developed to demultiplex pooled samples in a single cell RNA sequencing (scRNA-seq) experiment which either require hashtag barcodes or sample genotypes prior to pooling. We introduce scSplit which utilizes genetic differences inferred from scRNA-seq data alone to demultiplex pooled samples. scSplit also enables mapping clusters to original samples. Using simulated, merged, and pooled multi-individual datasets, we show that scSplit prediction is highly concordant with demuxlet predictions and is highly consistent with the known truth in cell-hashing dataset. scSplit is ideally suited to samples without external genotype information and is available at: https://github.com/jon-xu/scSplit. |
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United States | 7 | 18% |
United Kingdom | 3 | 8% |
Germany | 3 | 8% |
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France | 2 | 5% |
New Zealand | 1 | 3% |
Sweden | 1 | 3% |
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Demographic breakdown
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Members of the public | 17 | 45% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
Geographical breakdown
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---|---|---|
Unknown | 166 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 38 | 23% |
Student > Ph. D. Student | 31 | 19% |
Student > Master | 14 | 8% |
Student > Bachelor | 10 | 6% |
Professor | 6 | 4% |
Other | 19 | 11% |
Unknown | 48 | 29% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 25 | 15% |
Immunology and Microbiology | 11 | 7% |
Medicine and Dentistry | 11 | 7% |
Computer Science | 8 | 5% |
Other | 21 | 13% |
Unknown | 48 | 29% |