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V-SVA: an R Shiny application for detecting and annotating hidden sources of variation in single-cell RNA-seq data
SUMMARY: Single-cell RNA-sequencing (scRNA-seq) technology enables studying gene expression programs from individual cells. However, these data are subject to diverse sources of variation, including ‘unwanted’ variation that needs to be removed in downstream analyses (e.g. batch effects) and ‘wanted...
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| Publicado no: | Bioinformatics |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7267827/ https://ncbi.nlm.nih.gov/pubmed/32119082 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btaa128 |
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