Infer gene regulatory networks from single-cell RNA sequencing data.
npx skills add https://github.com/omicverse/omicverse --skill single-scenic-grn
Please help me install this Agent Skill. Skill: single-scenic-grn Source: https://github.com/omicverse/omicverse/tree/main/.claude/skills/single-scenic-grn Command: npx skills add https://github.com/omicverse/omicverse --skill single-scenic-grn
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.
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.
High-intent search queries and answers about installing and using this skill.
This Skill uses deep learning-based RegDiffusion to predict transcription factor to target gene links from your raw scRNA-seq counts, then prunes predicted regulons using cisTarget motif enrichment.
Reconstructing gene regulatory networks for specific cell types requires scRNA-seq raw counts alongside access to cisTarget databases and species-specific motif annotations for accurate network inference and regulon activity scoring.
RegDiffusion identifies transcription factors and target genes by applying deep learning to predict TF-target links from single-cell transcriptomics datasets, revealing core regulatory factors across diverse cell types.
Yes, you can use scRNA-seq data to find master regulators driving differentiation by scoring regulon activity in individual cells, which identifies master regulators specific to cell types for research.
Gene regulatory network inference ensures compatibility with species-specific gene annotations, requiring matching cisTarget databases and motif annotations to accurately reconstruct regulatory networks for your target organism.
You need cisTarget databases for regulon identification to perform motif enrichment, which prunes inferred networks to focus on direct regulatory relationships between transcription factors and their target genes.
omicverseInfer transcription factor regulatory networks and score regulon activities from single-cell RNA-seq data.
StarlitnightlyInfer gene regulatory networks from single-cell RNA sequencing data.
KetomihineReconstruct developmental trajectories from scRNA-seq data using Monocle 3 in R.
StarlitnightlyRun SCENIC regulon inference on single-cell AnnData objects.
