A general and flexible method for signal extraction from single-cell RNA-seq data
Single-cell RNA sequencing (scRNA-seq) data provides information on transcriptomic heterogeneity within cell populations. Here, Risso et al develop ZINB-WaVE for low-dimensional representations of scRNA-seq data that account for zero inflation, over-dispersion, and the count nature of the data.
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2018-01-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-017-02554-5 |
| _version_ | 1818992612030283776 |
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| author | Davide Risso Fanny Perraudeau Svetlana Gribkova Sandrine Dudoit Jean-Philippe Vert |
| author_facet | Davide Risso Fanny Perraudeau Svetlana Gribkova Sandrine Dudoit Jean-Philippe Vert |
| author_sort | Davide Risso |
| collection | DOAJ |
| description | Single-cell RNA sequencing (scRNA-seq) data provides information on transcriptomic heterogeneity within cell populations. Here, Risso et al develop ZINB-WaVE for low-dimensional representations of scRNA-seq data that account for zero inflation, over-dispersion, and the count nature of the data. |
| first_indexed | 2024-12-20T20:28:55Z |
| format | Article |
| id | doaj.art-73054fb866f04910a8b3edfde47347e8 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-20T20:28:55Z |
| publishDate | 2018-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-73054fb866f04910a8b3edfde47347e82022-12-21T19:27:24ZengNature PortfolioNature Communications2041-17232018-01-019111710.1038/s41467-017-02554-5A general and flexible method for signal extraction from single-cell RNA-seq dataDavide Risso0Fanny Perraudeau1Svetlana Gribkova2Sandrine Dudoit3Jean-Philippe Vert4Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Cornell MedicineDivision of Biostatistics, School of Public Health, University of CaliforniaLaboratoire de Probabilités et Modèles Aléatoires, Université Paris DiderotDivision of Biostatistics, School of Public Health, University of CaliforniaCBIO-Centre for Computational Biology, MINES ParisTech, PSL Research UniversitySingle-cell RNA sequencing (scRNA-seq) data provides information on transcriptomic heterogeneity within cell populations. Here, Risso et al develop ZINB-WaVE for low-dimensional representations of scRNA-seq data that account for zero inflation, over-dispersion, and the count nature of the data.https://doi.org/10.1038/s41467-017-02554-5 |
| spellingShingle | Davide Risso Fanny Perraudeau Svetlana Gribkova Sandrine Dudoit Jean-Philippe Vert A general and flexible method for signal extraction from single-cell RNA-seq data Nature Communications |
| title | A general and flexible method for signal extraction from single-cell RNA-seq data |
| title_full | A general and flexible method for signal extraction from single-cell RNA-seq data |
| title_fullStr | A general and flexible method for signal extraction from single-cell RNA-seq data |
| title_full_unstemmed | A general and flexible method for signal extraction from single-cell RNA-seq data |
| title_short | A general and flexible method for signal extraction from single-cell RNA-seq data |
| title_sort | general and flexible method for signal extraction from single cell rna seq data |
| url | https://doi.org/10.1038/s41467-017-02554-5 |
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