IReNA

IReNA integrates scRNA-seq and scATAC-seq data to infer gene regulatory networks and characterize transcriptional and epigenetic regulatory mechanisms at single-cell resolution.

Key Features:

• Data Integration: Combines single-cell RNA sequencing (scRNA-seq) and single-cell ATAC-seq (scATAC-seq) data to link transcriptomic and chromatin accessibility information at single-cell resolution.
• Network Inference: Reconstructs gene regulatory networks by leveraging both transcriptomic profiles and chromatin accessibility signals.
• Modularization: Performs modular regulatory network analysis to identify modules and the key transcription factors governing module-specific regulation.
• Transcription Factor Enrichment: Conducts transcription factor enrichment analysis to pinpoint candidate regulatory factors driving observed expression patterns.
• Simplified Intermodular Networks: Constructs simplified intermodular regulatory networks to represent regulatory relationships between modules.

Scientific Applications:

• Enhanced Network Analysis: Uses integrated scRNA-seq and scATAC-seq data to improve identification of known regulators through combined transcriptomic and chromatin-accessibility evidence.
• Biological Insights: Provides systems-level insights into regulatory mechanisms applicable to developmental biology, disease modeling, and other studies of gene regulation.

Methodology:

Integration of scRNA-seq and scATAC-seq data; network inference combining transcriptomic and chromatin accessibility profiles; modular regulatory network analysis to identify transcription factors and regulatory relationships; transcription factor enrichment analysis; construction of simplified intermodular regulatory networks; validation using public datasets.