tooluniverse-population-genetics
Analyze genetic variation at the population level using integrated access to gnomAD, 1000 Genomes, GWAS Catalog, and clinical variant databases. Compute Hardy-Weinberg equilibrium, Fst divergence, and constraint metrics to interpret allele frequencies, disease associations, and evolutionary patterns across ancestry groups.
tooluniverse-population-genetics lets you query allele frequencies, GWAS associations, and population-level genetic variation across cohorts like gnomAD and 1000 Genomes.
AI-generated summary based on this skill's SKILL.md
Install
mims-harvard/ToolUniverse/tooluniverse-population-genetics · repository language: Python
git clone https://github.com/mims-harvard/ToolUniverse
cp -r ToolUniverse/skills/tooluniverse-population-genetics ~/.claude/skills/tooluniverse-population-geneticsFrequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
How do I look up allele frequency in gnomAD and 1000 Genomes with tooluniverse-population-genetics?
tooluniverse-population-genetics provides integrated allele frequency lookup across gnomAD and 1000 Genomes cohorts. Search by variant position or gene name to retrieve population-level frequencies stratified by ancestry group, enabling cross-population comparison and identification of rare or population-specific variants.
Can tooluniverse-population-genetics test Hardy-Weinberg equilibrium?
Yes. tooluniverse-population-genetics includes Hardy-Weinberg equilibrium testing and calculation of population genetics statistics. Input genotype counts or allele frequencies to assess deviation from equilibrium, detect population substructure, or identify potential genotyping artifacts.
What GWAS associations and disease trait signals does tooluniverse-population-genetics find?
tooluniverse-population-genetics integrates GWAS Catalog data to retrieve published associations between genetic variants and diseases or traits. Query by variant, gene, or phenotype to interpret genetic signals, review effect sizes, and link to original studies.
How does tooluniverse-population-genetics assess variant pathogenicity?
tooluniverse-population-genetics combines constraint metrics (pLI, LOEUF), functional annotation (VEP), and clinical databases (ClinVar) to evaluate pathogenicity. Cross-reference variant consequences, population frequency, and expert classifications to support clinical interpretation.
Can I analyze population structure and evolutionary constraint with this tool?
tooluniverse-population-genetics supports Fst divergence analysis, ancestry inference, and evolutionary constraint scoring. Examine selection pressure, population differentiation, and haplotype diversity across cohorts to characterize population structure and evolutionary patterns.
What constraint scores and functional annotations are available?
tooluniverse-population-genetics provides gene constraint scores (pLI, LOEUF), variant consequence predictions (VEP), regulatory scoring (RegulomeDB), and pathogenicity measures (CADD). Combine these annotations to prioritize variants for functional or clinical follow-up.
SKILL.md
rendered from the published skill — quoted content, verbatim
Population Genetics Analysis
MC Strategy: Population genetics MC questions often test whether you know a specific theorem or result. COMPUTE the answer first (use popgen_calculator.py or write Python), then match to options. Don't try to reason about which option "sounds right."
Analyze population-level genetic variation, allele frequencies, GWAS associations, clinical significance, and evolutionary constraints using ToolUniverse tools.
When to Use
Activate this skill when the user asks about: - Allele frequencies across populations (gnomAD, 1000 Genomes) - GWAS associations for diseases/traits - Clinical variant interpretation (ClinVar, VEP) - Gene-level constraint metrics (pLI, LOEUF, o/e ratios) - Selection, drift, linkage disequilibrium, or population structure -
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skills/tooluniverse-population-genetics/SKILL.md
skills/tooluniverse-population-genetics/scripts/popgen_calculator.py