Functional module detection through integration of single-cell RNA sequencing data with protein-protein interaction networks.

ABSTRACT:

Background

Recent advances in single-cell RNA sequencing have allowed researchers to explore transcriptional function at a cellular level. In particular, single-cell RNA sequencing reveals that there exist clusters of cells with similar gene expression profiles, representing different transcriptional states.

Results

In this study, we present SCPPIN, a method for integrating single-cell RNA sequencing data with protein-protein interaction networks that detects active modules in cells of different transcriptional states. We achieve this by clustering RNA-sequencing data, identifying differentially expressed genes, constructing node-weighted protein-protein interaction networks, and finding the maximum-weight connected subgraphs with an exact Steiner-tree approach. As case stud

SUBMITTER: Klimm F 

PROVIDER: S-EPMC7607865 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature