Spectral clustering of single-cell multi-omics data on multilayer graphs.

ABSTRACT:

Motivation

Single-cell sequencing technologies that simultaneously generate multimodal cellular profiles present opportunities for improved understanding of cell heterogeneity in tissues. How the multimodal information can be integrated to obtain a common cell type identification, however, poses a computational challenge. Multilayer graphs provide a natural representation of multi-omic single-cell sequencing datasets, and finding cell clusters may be understood as a multilayer graph partition problem.

Results

We introduce two spectral algorithms on multilayer graphs, spectral clustering on multilayer graphs and the weighted locally linear (WLL) method, to cluster cells in multi-omic single-cell sequencing datasets. We connect these algorithms through a unifying mathematical

SUBMITTER: Zhang S 

PROVIDER: S-EPMC9272806 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature