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A clustering-independent method for finding differentially expressed genes in single-cell transcriptome data
A common analysis of single-cell sequencing data includes clustering of cells and identifying differentially expressed genes (DEGs). How cell clusters are defined has important consequences for downstream analyses and the interpretation of results, but is often not straightforward. To address this d...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7455704/ https://www.ncbi.nlm.nih.gov/pubmed/32859930 http://dx.doi.org/10.1038/s41467-020-17900-3 |