Tooluniverse Gwas Trait To Gene
This skill translates GWAS traits into potential genes, accelerating genetic discovery and understanding disease mechanisms.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add tooluniverse-gwas-trait-to-gene npx -- -y @trustedskills/tooluniverse-gwas-trait-to-gene
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"tooluniverse-gwas-trait-to-gene": {
"command": "npx",
"args": [
"-y",
"@trustedskills/tooluniverse-gwas-trait-to-gene"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill helps discover genes associated with diseases and traits by analyzing data from genome-wide association studies (GWAS). It leverages two primary resources: the GWAS Catalog and Open Targets Genetics, which provides locus-to-gene (L2G) predictions integrating eQTL, chromatin interaction, and distance data. The tool prioritizes gene candidates for validation rather than presenting them as confirmed causal genes.
When to use it
- Clinical Research: Identifying genes associated with conditions like type 2 diabetes, coronary artery disease, or Alzheimer's disease susceptibility.
- Drug Target Discovery: Prioritizing potential drug targets based on genetic evidence and L2G scores.
- Functional Genomics: Mapping disease-associated variants to candidate genes and analyzing the genetic architecture of complex traits.
Key capabilities
- GWAS Catalog Search: Searches the GWAS Catalog for associations related to a given trait or disease.
- SNP Aggregation: Collects genome-wide significant SNPs (p < 5e-8).
- Gene Mapping: Extracts mapped genes from GWAS associations.
- Locus-to-Gene (L2G) Scoring: Uses L2G scores from Open Targets Genetics to rank potential gene candidates. A score above 0.5 is considered a strong prediction.
- Evidence Ranking: Ranks candidate genes based on p-value, replication across studies, and fine-mapping data.
Example prompts
- "What genes are associated with type 2 diabetes?"
- "Find genetic risk factors for coronary artery disease."
- "Which genes contribute to Alzheimer's disease susceptibility?"
Tips & gotchas
- Always retrieve current data: Use
gwas_search_associationsandOpenTargets_get_study_credible_setsto obtain the latest information, as associations are updated with new GWAS publications. Do not assume trait-to-gene mappings or L2G scores. - Replication is key: A single GWAS study with p < 5e-8 is suggestive; replication across independent cohorts is required for high confidence.
- Ancestry matters: Effect sizes and implicated genes can vary across ancestries due to differing LD patterns.
Tags
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