IReNA: Integrated regulatory network analysis of single-cell transcriptomes and chromatin accessibility profiles

Area of Science:

• Genomics
• Systems Biology
• Bioinformatics

Background:

• Single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) provide valuable single-cell resolution data.
• Current methods struggle to reliably integrate scRNA-seq and scATAC-seq data for comprehensive regulatory network analysis.

Purpose of the Study:

• To develop an integrated method for analyzing combined scRNA-seq and scATAC-seq data.
• To enable precise identification of gene regulatory networks at the single-cell level.

Main Methods:

• Developed Integrated Regulatory Network Analysis (IReNA) for network inference.
• Incorporated network modularization, transcription factor enrichment, and simplified intermodular network construction.
• Utilized public scRNA-seq and scATAC-seq datasets for validation.

Main Results:

• Integrated analysis of scRNA-seq and scATAC-seq data identified known regulators with higher precision than scRNA-seq alone.
• IReNA demonstrated superior performance compared to existing methods in identifying key regulators.
• The method facilitates a systems-level understanding of biological regulatory mechanisms.

Conclusions:

• IReNA offers a robust framework for integrating multi-omics single-cell data.
• The developed approach enhances the accuracy of regulatory network inference.
• IReNA is a valuable tool for advancing systems biology research.