Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.
8.3
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Excellent bioinformatics skill for differential gene expression analysis. The SKILL.md is extremely comprehensive with clear quick-start code, detailed step-by-step workflow guidance, common analysis patterns, troubleshooting, and visualization examples. The structure is superb: concise overview followed by progressive detail, with proper referencing to external files for API and workflow documentation. Task knowledge is outstanding - provides complete working code for data loading, DESeq2 fitting, statistical testing, result interpretation, and visualization. The skill addresses a genuinely complex bioinformatics task that would require significant tokens and domain expertise for a CLI agent to execute properly, making it highly novel and cost-effective. Description coverage is strong, clearly indicating when to use this skill. Minor room for improvement in novelty score as some Python-savvy users could potentially accomplish this with documentation, but the integrated workflow, troubleshooting guidance, and domain-specific best practices provide substantial value beyond raw API access.
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