{"enrichment":{"faq":[{"a":"tooluniverse-gwas-trait-to-gene queries GWAS Catalog and Open Targets Genetics data to identify genetic variants associated with type 2 diabetes. It then ranks candidate genes using locus-to-gene (L2G) scores that combine eQTL, chromatin interaction, and distance evidence\u2014going beyond simple nearest-gene assignment. Results include p-values and replication counts to help prioritize the strongest associations.","q":"How does tooluniverse-gwas-trait-to-gene find genes associated with type 2 diabetes?"},{"a":"tooluniverse-gwas-trait-to-gene performs GWAS trait to gene mapping by connecting genome-wide significant loci to their causal genes. Rather than assigning variants to the nearest gene, it uses L2G scores that integrate eQTL data, chromatin interactions, and genomic distance. This multi-evidence approach improves accuracy in identifying true disease-causing genes from GWAS signals.","q":"What is GWAS trait to gene mapping and how does this skill perform it?"},{"a":"Yes. tooluniverse-gwas-trait-to-gene prioritizes drug targets by ranking genes based on genetic evidence strength. It combines L2G scores, replication counts across studies, and confidence levels to identify the most robust trait-gene associations. This genetic evidence helps guide target selection for drug discovery and reduces the risk of pursuing weak or non-replicated associations.","q":"Can tooluniverse-gwas-trait-to-gene help discover drug targets from genetic evidence?"},{"a":"tooluniverse-gwas-trait-to-gene maps GWAS variants to genes by integrating fine-mapping credible sets with locus-to-gene scoring. L2G scores combine eQTL evidence (which genes are regulated by variants), chromatin interactions (which regulatory elements contact genes), and distance metrics. This multi-layered approach narrows candidate genes from broad loci to likely causal targets.","q":"How does this skill map GWAS variants to genes using fine-mapping?"},{"a":"tooluniverse-gwas-trait-to-gene integrates GWAS Catalog data with Open Targets Genetics resources. It leverages eQTL databases, chromatin interaction maps, and genome-wide association study results to build L2G scores. These combined sources enable comprehensive trait-to-gene mapping and validation of genetic associations across multiple independent studies.","q":"What data sources does tooluniverse-gwas-trait-to-gene use for gene discovery?"},{"a":"tooluniverse-gwas-trait-to-gene validates associations by reporting replication counts and confidence levels from multiple studies. It returns p-values and evidence strength metrics that indicate whether associations are genome-wide significant and consistently observed across independent cohorts, helping distinguish robust findings from spurious signals.","q":"How can I validate trait-to-gene associations using this skill?"}],"shadow_tags":["variant-mapping","disease-genetics","fine-mapping","causal-inference","genetic-evidence","gwas-analysis","target-prioritization","multi-evidence-scoring","population-genetics","functional-genomics"],"summary_rewrite":"Identify genes associated with diseases and traits by querying GWAS Catalog and Open Targets Genetics data. This skill ranks candidate genes using locus-to-gene scores that combine eQTL, chromatin interaction, and distance evidence\u2014moving beyond simple nearest-gene approaches. Results include p-values, replication counts, and confidence levels to guide target prioritization for drug discovery and functional validation."},"files":[{"bytes":11894,"path":"skills/tooluniverse-gwas-trait-to-gene/SKILL.md","sha256":"a6c04b88ba2942d3683f1fcfba8000acbf852806855027c1d037b84f94175b87","url":"https://skillfed.io/files/mims-harvard/ToolUniverse/tooluniverse-gwas-trait-to-gene/8722b141/SKILL.md"}],"id":"mims-harvard/ToolUniverse/tooluniverse-gwas-trait-to-gene","links":{"html":"https://skillfed.io/mims-harvard/ToolUniverse/tooluniverse-gwas-trait-to-gene","md":"https://skillfed.io/mims-harvard/ToolUniverse/tooluniverse-gwas-trait-to-gene.md","repo":"https://github.com/mims-harvard/ToolUniverse"},"meta":{"agents_supported":[],"first_seen":"2026-07-28","forks":242,"language":"Python","last_updated":"2026-07-27","license":"Apache-2.0","name":"tooluniverse-gwas-trait-to-gene","publisher":"mims-harvard","stars":1595},"relations":{"similar":[{"id":"mims-harvard/ToolUniverse/tooluniverse-gwas-snp-interpretation"},{"id":"mims-harvard/ToolUniverse/tooluniverse-gwas-finemapping"},{"id":"mims-harvard/ToolUniverse/tooluniverse-gwas-drug-discovery"},{"id":"jaechang-hits/SciAgent-Skills/gwas-database"},{"id":"mims-harvard/ToolUniverse/tooluniverse-variant-to-mechanism"},{"id":"mims-harvard/ToolUniverse/tooluniverse-regulatory-variant-analysis"},{"id":"mims-harvard/ToolUniverse/tooluniverse-polygenic-risk-score"},{"id":"mims-harvard/ToolUniverse/tooluniverse-gwas-study-explorer"},{"id":"mims-harvard/ToolUniverse/tooluniverse-pathway-disease-genetics"},{"id":"mims-harvard/ToolUniverse/tooluniverse-population-genetics-1000genomes"}]},"slug":{"owner":"mims-harvard","repo":"ToolUniverse","skill":"tooluniverse-gwas-trait-to-gene"},"version":"8722b141"}