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...

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Detalles Bibliográficos
Autores principales: Reshef, Yakir, Rumker, Laurie, Kang, Joyce B., Nathan, Aparna, Korsunsky, Ilya, Asgari, Samira, Murray, Megan B., Moody, D. Branch, Raychaudhuri, Soumya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Article
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

Internet

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

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