Article

Axes of inter-sample variability among transcriptional neighborhoods reveal disease-associated cell states in single-cell data

2021-04-20

Abstract excerpt

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 cell-type clusters and examine sample differences through that lens alone. Here we present covarying neighborhood analysis (CNA), an unbiased method to identify cell populations...

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Literature Corpus work: d6ecb851-bad4-533a-836a-b90e52f1a0ec
DOI: 10.1101/2021.04.19.440534

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