A gene regulatory network method based on single-cell multi-omics data

The interactions between chromatin, transcri-ption factors, and genes give rise to complex regulatory circuits that can be represented as gene regulatory networks (GRNs). To date, many methods have been proposed for constructing regulatory networks based on scRNA-seq data, which map GRNs using single-cell transcriptomics data. Here, we introduce single-cell epigenomic ATAC-seq data to construct more accurate GRNs from multi-omics perspective. We constructed the GRN in mouse hematopoietic cells, using mouse peripheral blood ATAC-seq data to establish benchmark GRNs to infer the GRN of specific clusters. Finally, we conducted network analysis on the constructed GRNs.