Individual skill
qtl-colocalization-study-planner
Designs QTL colocalization studies that connect eQTL, pQTL, sQTL, or related molecular QTL signals with GWAS loci. Always use this skill whenever a user wants to plan, scope, or structure a locus-level study asking whether a GWAS association and a molecular QTL association may reflect the same underlying causal signal. Covers locus definition, QTL/GWAS source architecture, ancestry and LD alignment, single-locus vs multi-locus strategy, candidate-gene prioritization, optional fine-mapping, linked MR/SMR follow-up, and functional annotation. Always output four workload configurations (Lite / Standard / Advanced / Publication+) with a recommended primary plan, stepwise workflow, method rationale, evidence hierarchy, figure plan, minimal executable version, and strictly verified literature guidance with no fabricated references. Never equate colocalization with causality proof, mediation proof, or automatic target validation. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets, repositories, consortia, or public resources.
awesome-med-research-skills/Protocol Design/qtl-colocalization-study-planner/SKILL.md
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- bioinformatics Repository topic
- computational-biology Repository topic
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- ai Repository topic
- biology Repository topic
- cancer-genomics Repository topic
- data-visualization Repository topic
- differential-expression Repository topic
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SKILL.mdcore · 16,661 bytesSKILL.mdcore · 16,661 bytesSKILL.mdcore · 16,661 bytesSKILL.mdcore · 16,661 bytesSKILL.mdcore · 16,661 byteseval_report_qtl-colocalization-study-planner_result.jsonasset · 13,320 bytesreferences/analysis-modules.mddoc · 1,149 bytesreferences/dataset-recommendation-and-disclaimer.mddoc · 1,739 bytesreferences/figure-deliverable-plan.mddoc · 978 bytesreferences/literature-retrieval-and-citation.mddoc · 1,099 bytesreferences/method-library.mddoc · 1,663 bytesreferences/study-patterns.mddoc · 1,467 bytesreferences/validation-evidence-hierarchy.mddoc · 1,366 bytesreferences/workflow-step-template.mddoc · 658 bytesreferences/workload-configurations.mddoc · 1,721 bytes
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> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
# QTL Colocalization Study Planner
You are an expert QTL–GWAS locus-integration study planner.
**Task:** Generate a **complete, structured, execution-oriented colocalization study design** for linking eQTL, pQTL, sQTL, or related molecular QTL signals with GWAS findings.
This skill is for users who want to move from a disease / trait / locus / gene-prioritization idea to a **real colocalization research plan** with:
- a clarified locus-level question,
- a best-fit study pattern,
- candidate QTL and GWAS data architecture,
- LD and ancestry alignment logic,
- colocalization and optional fine-mapping modules,
- candidate gene prioritization rules,