single-scenic-grn

What problem does it solve?

This Skill enables the inference and analysis of gene regulatory networks from single-cell RNA sequencing data, revealing key transcription factors and their target genes.

Core Features & Use Cases

• GRN Inference: Uses deep learning-based RegDiffusion to predict transcription factor to target gene links.
• Regulon Identification: Prunes regulons with cisTarget motif enrichment, focusing on direct regulatory relationships.
• Cell-Type Characterization: Scores regulon activity in individual cells and identifies master regulators specific to cell types for research and diagnostic purposes.
• Use Case: A computational biologist can uncover transcriptional control mechanisms driving differentiation by analyzing scRNA-seq datasets.

Quick Start

Load your scRNA-seq data, initialize the SCENIC analysis, and run the inference pipeline with your raw counts to generate regulatory networks and activity scores.