Single-cell multi-omics analysis identifies context-specific gene regulatory gates and mechanisms.

ABSTRACT: There is a growing interest in inferring context specific gene regulatory networks from single-cell RNA sequencing (scRNA-seq) data. This involves identifying the regulatory relationships between transcription factors (TFs) and genes in individual cells, and then characterizing these relationships at the level of specific cell types or cell states. In this study, we introduce scGATE (single-cell gene regulatory gate) as a novel computational tool for inferring TF-gene interaction networks and reconstructing Boolean logic gates involving regulatory TFs using scRNA-seq data. In contrast to current Boolean models, scGATE eliminates the need for individual formulations and likelihood calculations for each Boolean rule (e.g. AND, OR, XOR). By employing a Bayesian framework, scGATE infers the Bo

SUBMITTER: Malekpour SA 

PROVIDER: S-EPMC11036345 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature