This pulls GWAS study data from NHGRI-EBI GWAS Catalog and Open Targets Genetics to compare genome-wide association studies for the same trait. You can run meta-analyses across cohorts, calculate heterogeneity statistics like I² to see if effect sizes are consistent, and check which loci actually replicate across populations. The workflow is compute-first: retrieve associations with the ToolUniverse tools, then run Python code to aggregate effect sizes, generate forest plots, and assess study quality by sample size and ancestry. Useful when you need to know if a genetic signal holds up across studies or if you're seeing population-specific effects versus methodological noise. The documentation is thorough on when heterogeneity means you shouldn't trust a combined estimate.
npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-gwas-study-explorer