scMEGA: Single-cell Multiomic Enhancer-based Gene Regulatory Network Inference

Abstract

The increasing availability of single-cell multi-omics data allows to quantitatively characterize gene regulation. We here describe scMEGA (Single-cell Multiomic Enhancer-based Gene Regulatory Network Inference) to infer gene regulatory networks by combining single-cell gene expression and chromatin accessibility profiles. This enables to study of complex gene regulation mechanisms for dynamic biological processes, such as cellular differentiation and disease-driven cellular remodeling. We provide a case study on gene regulatory networks controlling myofibroblast activation in human myocardial infarction.