Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.
7.7
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Excellent bioinformatics skill for gene regulatory network inference. The description clearly defines when to use arboreto (transcriptomics analysis, TF-target relationships), and the SKILL.md provides comprehensive coverage including quick start, algorithm selection, distributed computing, and practical use cases. Task knowledge is strong with working code examples, a ready-to-run script, and references to additional detailed documentation. Structure is clean with a logical flow and appropriate delegation of detailed content to reference files. Novelty is good - GRN inference requires specialized domain knowledge and computationally intensive algorithms that would be inefficient for a CLI agent to reproduce from scratch. Minor deductions: the skill is somewhat specialized (limits broader applicability) and while complex, the core inference workflow is relatively straightforward once the tool is understood.
K-Dense-AI
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