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

Junyao Jiang, Pin Lyu, Jinlian Li, Sunan Huang, Jiawang Tao, Seth Blackshaw, Jiang Qian, Jie Wang

Research output: Contribution to journalArticlepeer-review

Abstract

Recently, single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) have been developed to separately measure transcriptomes and chromatin accessibility profiles at the single-cell resolution. However, few methods can reliably integrate these data to perform regulatory network analysis. Here, we developed integrated regulatory network analysis (IReNA) for network inference through the integrated analysis of scRNA-seq and scATAC-seq data, network modularization, transcription factor enrichment, and construction of simplified intermodular regulatory networks. Using public datasets, we showed that integrated network analysis of scRNA-seq data with scATAC-seq data is more precise to identify known regulators than scRNA-seq data analysis alone. Moreover, IReNA outperformed currently available methods in identifying known regulators. IReNA facilitates the systems-level understanding of biological regulatory mechanisms and is available at https://github.com/jiang-junyao/IReNA.

Original languageEnglish (US)
Article number105359
JournaliScience
Volume25
Issue number11
DOIs
StatePublished - Nov 18 2022

Keywords

  • Biochemistry
  • molecular network
  • transcriptomics

ASJC Scopus subject areas

  • General

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