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M3Drop: dropout-based feature selection for scRNASeq
MOTIVATION: Most genomes contain thousands of genes, but for most functional responses, only a subset of those genes are relevant. To facilitate many single-cell RNASeq (scRNASeq) analyses the set of genes is often reduced through feature selection, i.e. by removing genes only subject to technical n...
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| Publicat a: | Bioinformatics |
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| Autors principals: | , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Oxford University Press
2019
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6691329/ https://ncbi.nlm.nih.gov/pubmed/30590489 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/bty1044 |
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