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scenic-gene-regulatory-network

Infer gene regulatory networks from single-cell RNA sequencing data.

32|5|Updated Mar 12, 2026
Search Tags:#gene regulatory network#grn#single-cell rna-seq#scenic#regulon#transcription factor#auc
One-click install
npx skills add https://github.com/Starlitnightly/omicclaw --skill scenic-gene-regulatory-network
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scenic-gene-regulatory-network
Source: https://github.com/Starlitnightly/omicclaw/tree/main/src/omicverse_skills/skills/single-scenic-grn
Command: npx skills add https://github.com/Starlitnightly/omicclaw --skill scenic-gene-regulatory-network

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the complex process of inferring gene regulatory networks (GRNs) from single-cell RNA sequencing data, identifying transcription factor activity and regulons.

Core Features & Use Cases

  • GRN Inference: Predicts transcription factor to target gene links using advanced methods like RegDiffusion.
  • Regulon Pruning & Scoring: Validates predicted links using cisTarget databases and quantifies regulon activity per cell (AUCell).
  • Use Case: Analyze scRNA-seq data to discover master regulators controlling cell identity in a specific cell type, or to understand the transcriptional logic of cellular differentiation.

Quick Start

Run the SCENIC skill on your AnnData object to infer gene regulatory networks and score regulon activity.

Frequently Asked Questions about scenic-gene-regulatory-network

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I infer gene regulatory networks from single-cell RNA-seq data?▼

Inferring gene regulatory networks from scRNA-seq data requires a multi-stage pipeline involving GRN inference, regulon pruning with cisTarget databases, and AUCell scoring to identify transcription factor activity and master regulators.

What is needed to identify cell-type-specific master regulators using AUCell?▼

Identifying cell-type-specific master regulators using AUCell requires raw count data, HVG-filtered genes, and species-specific cisTarget databases to accurately prune regulons and score transcription factor activity per cell.

Can I use SCENIC to understand transcriptional logic during cellular differentiation?▼

Yes, you can use SCENIC to understand the transcriptional logic of cellular differentiation by predicting transcription factor to target gene links and quantifying regulon activity across differentiating cell populations.

What is the best way to validate predicted transcription factor to target gene links?▼

Validating predicted transcription factor to target gene links is best achieved through regulon pruning using species-specific cisTarget databases, which filters direct regulatory interactions from initial GRN inference results.

Do I need species-specific cisTarget databases for single-cell gene regulatory network inference?▼

Yes, species-specific cisTarget databases are required for accurate gene regulatory network inference, as they provide the necessary motif track information to prune predicted transcription factor links during the regulon validation stage.

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