Individual skill
tooluniverse-data-integration-analysis
Integrate computed statistical results (DEGs, GWAS hits, associations) with biological context from ToolUniverse databases (UniProt, GO, Reactome, ClinVar, OpenTargets). Use for adding gene function/pathway/disease annotations to a result list, building biological narrative around statistical findings, and going beyond p-values to mechanism.
plugins/tooluniverse/skills/tooluniverse-data-integration-analysis/SKILL.md
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- Last checked
- Nov 9, 2026
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- Repository last updated
- Nov 8, 2026
- License
- Apache-2.0
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- agents Repository topic
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SKILL.mdcore · 8,615 bytes
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## COMPUTE, DON'T DESCRIBE
When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do -- execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.
# Data Integration Analysis
Bridge the gap between statistical results and biological understanding. After any computational analysis produces significant findings, this skill teaches how to interpret them using ToolUniverse's biological knowledge tools -- the key advantage over platforms that only do data analysis.
**IMPORTANT**: Always use English terms in tool calls (gene names, pathway names, organism names), even if the user writes in another language. Respond in the user's language.
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## When to Use This Skill
Apply when: