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Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations.

ABSTRACT: The ability to discover new cell phenotypes by unsupervised clustering of single-cell transcriptomes has revolutionized biology. Currently, there is no principled way to decide whether a cluster of cells contains meaningful subpopulations that should be further resolved. Here, we present phiclust (ϕ_clust), a clusterability measure derived from random matrix theory that can be used to identify cell clusters with non-random substructure, testably leading to the discovery of previously overlooked phenotypes.

SUBMITTER: Mircea M

PROVIDER: S-EPMC8751334 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations.

Mircea Maria M Hochane Mazène M Fan Xueying X Chuva de Sousa Lopes Susana M SM Garlaschelli Diego D Semrau Stefan S

Genome biology 20220110 1

The ability to discover new cell phenotypes by unsupervised clustering of single-cell transcriptomes has revolutionized biology. Currently, there is no principled way to decide whether a cluster of cells contains meaningful subpopulations that should be further resolved. Here, we present phiclust (ϕ<sub>clust</sub>), a clusterability measure derived from random matrix theory that can be used to identify cell clusters with non-random substructure, testably leading to the discovery of previously o ...[more]

PMID: 35012604

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