Determining gene specificity from multivariate single-cell RNA sequencing data.

ABSTRACT: An important application of single-cell genomics experiments is to identify genes specific to biological categories or experimental conditions. Although numerous approaches have been proposed to identify such genes, we consider an axiomatic approach based on defining properties that a specificity measure should have. This leads us to develop ember (Entropy Metrics for Biological ExploRation), which we show is the only method satisfying four key desired properties for a specificity measure. Applying ember to eight tissues from eight founder mouse strains, we find that gene specificity is often unintuitive: canonical markers can be supplanted, housekeeping genes are context-dependent, and mouse strain can drive unexpected cell type switching. Unsupervised learning on entropy metrics uncovers

SUBMITTER: Swarna NP 

PROVIDER: S-EPMC12667802 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature