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.
8.1
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Excellent skill for gene regulatory network inference. The description clearly explains when and how to use arboreto for transcriptomics analysis. SKILL.md provides comprehensive task knowledge with working code examples for basic inference, algorithm selection, distributed computing, and multiple real-world use cases (single-cell, bulk RNA-seq, comparative analysis). Structure is well-organized with a clear overview, quick start, and logical sections that reference separate files for detailed topics. The skill demonstrates solid novelty—GRN inference requires domain-specific knowledge of bioinformatics algorithms, proper data formatting, distributed computing setup, and parameter tuning that would be challenging and token-intensive for a general CLI agent. Minor improvements could include more explicit handling of edge cases and data preprocessing steps, but overall this is a high-quality, production-ready skill.
davila7
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