How does it assess study quality?

Studies are ranked into three quality tiers based on sample size, statistical power (OR detection), ancestry diversity, and the availability of summary statistics.

Can it handle multi-ancestry meta-analysis?

Yes, it includes specialized workflows for multi-ancestry comparison and recommends specific statistical models to account for population heterogeneity.

Does it calculate the I² statistic?

Yes, it automatically calculates the I² statistic and Cochran's Q to help researchers determine the level of heterogeneity and select the appropriate meta-analysis model.

What data sources does this skill use?

It integrates real-time data from the NHGRI-EBI GWAS Catalog and Open Targets Genetics to provide comprehensive study metadata and association results.

GWAS Study Explorer & Meta-Analysis

Name: GWAS Study Explorer & Meta-Analysis
Author: mims-harvard

bymims-harvard

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1,150

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데이터 과학 및 ML

Analyzes and compares genome-wide association studies (GWAS) to perform meta-analyses, assess replication, and evaluate genetic architecture across diverse cohorts.

This skill empowers researchers and bioinformaticians to conduct deep-dive analyses of genetic association data by integrating the NHGRI-EBI GWAS Catalog and Open Targets Genetics. It facilitates the systematic comparison of study designs, effect sizes, and ancestry diversity while providing robust statistical frameworks for meta-analysis, including fixed-effects and random-effects models. Whether identifying consistently replicated loci for complex diseases or investigating sources of heterogeneity like population stratification, this skill streamlines the synthesis of multi-study genetic data into actionable scientific insights.

주요 기능

01Systematic replication analysis across discovery and independent cohorts

02Automated meta-analysis using fixed-effects and random-effects models

03Integration with NHGRI-EBI GWAS Catalog and Open Targets Genetics

04Study quality tiering based on sample size, power, and ancestry diversity

051,150 GitHub stars

06Statistical heterogeneity assessment using the I² statistic

사용 사례

01Performing locus-specific meta-analysis to assess the consistency of effect sizes across multiple studies

02Conducting comprehensive trait analysis to identify all associated genetic loci for a specific disease

03Evaluating ancestry-specific genetic architecture to identify shared or population-specific signals

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add mims-harvard/tooluniverse tooluniverse-gwas-study-explorer

For use in Claude.ai and ChatGPT

Download Skill