An information-theoretic approach to single cell sequencing analysis.

ABSTRACT:

Background

Single-cell sequencing (sc-Seq) experiments are producing increasingly large data sets. However, large data sets do not necessarily contain large amounts of information.

Results

Here, we formally quantify the information obtained from a sc-Seq experiment and show that it corresponds to an intuitive notion of gene expression heterogeneity. We demonstrate a natural relation between our notion of heterogeneity and that of cell type, decomposing heterogeneity into that component attributable to differential expression between cell types (inter-cluster heterogeneity) and that remaining (intra-cluster heterogeneity). We test our definition of heterogeneity as the objective function of a clustering algorithm, and show that it is a useful descriptor for gene expression pa

SUBMITTER: Casey MJ 

PROVIDER: S-EPMC10422744 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature