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Covarying neighborhood analysis identifies cell populations associated with phenotypes of interest from single-cell transcriptomics
As single-cell datasets grow in sample size, there is a critical need to characterize cell states that vary across samples and associate with sample attributes like clinical phenotypes. Current statistical approaches typically map cells to clusters then assess differences in cluster abundance. We pr...
| Autores principales: | , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8930733/ https://www.ncbi.nlm.nih.gov/pubmed/34675423 http://dx.doi.org/10.1038/s41587-021-01066-4 |