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Interpretable factor models of single-cell RNA-seq via variational autoencoders
MOTIVATION: Single-cell RNA-seq makes possible the investigation of variability in gene expression among cells, and dependence of variation on cell type. Statistical inference methods for such analyses must be scalable, and ideally interpretable. RESULTS: We present an approach based on a modificati...
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| 出版年: | Bioinformatics |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Oxford University Press
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7267837/ https://ncbi.nlm.nih.gov/pubmed/32176273 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btaa169 |
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