Co-varying neighborhood analysis identifies cell populations associated with phenotypes of interest...
Co-varying neighborhood analysis identifies cell populations associated with phenotypes of interest from single-cell transcriptomics
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New York: Nature Publishing Group US
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Language
English
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New York: Nature Publishing Group US
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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, such as clinical phenotypes. Current statistical approaches typically map cells to clusters and then assess differences in cluster abundance. Here we present co-varying neighborhood analysi...
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Co-varying neighborhood analysis identifies cell populations associated with phenotypes of interest from single-cell transcriptomics
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TN_cdi_proquest_journals_2640594016
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2640594016
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ISSN
1087-0156
E-ISSN
1546-1696
DOI
10.1038/s41587-021-01066-4
