KEGNI (Knowledge graph-Enhanced Gene regulatory Network Inference) is a knowledge-guided framework for inferring cell type-specific gene regulatory networks (GRNs) from scRNA-seq data by integrating prior biological knowledge.
To get started quickly, run the following scripts:
bash run_mESC.sh
bash run_pbmc_naiveCD4T.sh All required data files—including scRNA-seq datasets, ground truth networks, and cell type-specific knowledge graphs—can be downloaded from: Zenodo Repository
We provide several tutorials and user guide for construct cell type specific knowledge graph, benchmark with multi-omics methods with ground truth from cistrome, GO enrichment results and ARI (Adjusted Rand Index) calculations.