Constructing cell-type-specific gene regulatory networks from cell-cell communication and a global gene regulatory network.

Cell type-specific gene regulatory networks (GRNs) can be accurately reconstructed by integrating bulk and single-cell RNA-seq data, with CTN achieving high inference accuracy.

• Why it matters: Understanding cellular heterogeneity, lineage decisions, and disease mechanisms requires precise GRN models; however, scRNA-seq data's sparsity and noise hinder reliable inference.
• What they did: The study developed CTN, a framework using bilateral self-representation matrix decomposition to combine bulk and single-cell RNA-seq data, enabling detailed cell type-level GRN reconstruction.
• The result: CTN successfully identifies key regulators and functional modules in hematopoietic differentiation and tumor microenvironments, advancing insights into cellular functions and disease processes.