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

We will discuss about “Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations”, Mircea et al., 2022, Genome Biology

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.