tooluniverse-gwas-study-explorer
This skill enables systematic comparison of genome-wide association studies for any trait, aggregating effect sizes across studies and evaluating replication success. It integrates GWAS Catalog and Open Targets Genetics data to identify consistently replicated loci, detect heterogeneity from population and design differences, and assess study quality by sample size and ancestry diversity.
GWAS Study Deep Dive & Meta-Analysis compares genome-wide association studies for the same trait and assesses replication across cohorts.
AI-generated summary based on this skill's SKILL.md
Install
mims-harvard/ToolUniverse/tooluniverse-gwas-study-explorer · repository language: Python
git clone https://github.com/mims-harvard/ToolUniverse
cp -r ToolUniverse/skills/tooluniverse-gwas-study-explorer ~/.claude/skills/tooluniverse-gwas-study-explorerFrequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
How does tooluniverse-gwas-study-explorer compare GWAS studies for the same trait?
tooluniverse-gwas-study-explorer systematically compares genome-wide association studies by integrating GWAS Catalog and Open Targets Genetics data. It aggregates effect sizes across multiple studies for any trait, enabling you to assess replication success across cohorts and identify which loci replicate consistently versus appear in single studies.
How to check if GWAS findings replicate using this tool?
tooluniverse-gwas-study-explorer evaluates GWAS reproducibility by comparing effect sizes and significance across independent cohorts. It detects heterogeneity from population and design differences, assesses study quality by sample size and ancestry diversity, and distinguishes replicated loci from novel findings to determine which associations hold across populations.
Can tooluniverse-gwas-study-explorer perform meta-analysis across GWAS cohorts?
Yes. tooluniverse-gwas-study-explorer aggregates effect sizes from multiple GWAS studies through meta-analysis, enabling you to combine results across cohorts. It calculates heterogeneity metrics and detects sources of variation from ancestry and study design, supporting both discovery and replication workflows.
What does tooluniverse-gwas-study-explorer reveal about ancestry-specific genetic signals?
tooluniverse-gwas-study-explorer identifies replicated loci and assesses ancestry-specific genetic signals by comparing GWAS results across populations. It evaluates genetic risk score transferability and detects population stratification effects, helping you understand whether associations are universal or ancestry-specific.
How does this tool investigate heterogeneity in genome-wide association studies?
tooluniverse-gwas-study-explorer investigates sources of heterogeneity by analyzing effect size variation across studies. It quantifies I-squared heterogeneity metrics and traces variation to population differences, study design factors, and sample composition, enabling you to understand why associations may differ between cohorts.
SKILL.md
rendered from the published skill — quoted content, verbatim
GWAS Study Deep Dive & Meta-Analysis
Compare GWAS studies, perform meta-analyses, and assess replication across cohorts
Overview
The GWAS Study Deep Dive & Meta-Analysis skill enables comprehensive comparison of genome-wide association studies (GWAS) for the same trait, meta-analysis of genetic loci across studies, and systematic assessment of replication and study quality. It integrates data from the NHGRI-EBI GWAS Catalog and Open Targets Genetics to provide a complete picture of the genetic architecture of complex traits.
Key Capabilities
- Study Comparison: Compare all GWAS studies for a trait, assessing sample sizes, ancestries, and platforms
- Meta-Analysis: Aggregate effect sizes across studies and calculate
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skills/tooluniverse-gwas-study-explorer/.env.template
skills/tooluniverse-gwas-study-explorer/SKILL.md
skills/tooluniverse-gwas-study-explorer/python_implementation.py
skills/tooluniverse-gwas-study-explorer/test_skill_comprehensive.py