tooluniverse-gwas-snp-interpretation-0045b7 — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited tooluniverse-gwas-snp-interpretation-0045b7 (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
SNP interpretation: a GWAS hit is a REGION, not a single causal variant. The lead SNP may not be causal — it may be in LD with the causal variant. Always check LD structure and functional annotation before concluding a specific SNP is mechanistically responsible. Use LDlink_get_proxies(variant="rs...", population="EUR") to retrieve the high-R² LD proxies (needs a free LDLINK_TOKEN) — a proxy in a coding/regulatory region is a better mechanistic candidate than the lead SNP itself. Fine-mapping (SuSiE, FINEMAP credible sets) narrows the causal set but rarely identifies a single variant with certainty. L2G scores integrate eQTL, chromatin interaction, and distance data to predict the causal gene — a lead SNP mapping to gene A may actually regulate gene B 500 kb away via a distal enhancer.
LOOK UP DON'T GUESS: never assume a SNP's functional consequence, mapped gene, or population frequency — always call gwas_get_snp_by_id and OpenTargets_get_variant_info to retrieve current annotations.
Interpret genetic variants (SNPs) from GWAS studies by aggregating evidence from multiple sources to provide comprehensive clinical and biological context.
Use Cases:
The skill provides a comprehensive interpretation of SNPs by:
User Input: rs7903146
↓
[1] SNP Lookup
→ Get location, consequence, MAF
→ gwas_get_snp_by_id
↓
[2] Association Search
→ Find all trait/disease associations
→ gwas_get_associations_for_snp
↓
[3] Fine-Mapping (Optional)
→ Get credible set membership
→ OpenTargets_get_variant_credible_sets
↓
[4] Gene Predictions
→ Extract L2G scores for causal genes
→ (embedded in credible sets)
↓
[5] Clinical Summary
→ Aggregate evidence
→ Identify key traits and genes
↓
Output: Comprehensive Interpretation Reportrs_id (str): dbSNP rs identifierinclude_credible_sets (bool, default=True): Query fine-mapping datap_threshold (float, default=5e-8): Genome-wide significance thresholdmax_associations (int, default=100): Maximum associations to retrieveReturns SNPInterpretationReport containing:
{
'rs_id': 'rs7903146',
'chromosome': '10',
'position': 112998590,
'ref_allele': 'C',
'alt_allele': 'T',
'consequence': 'intron_variant',
'mapped_genes': ['TCF7L2'],
'maf': 0.293
}[
{
'trait': 'Type 2 diabetes',
'p_value': 1.2e-128,
'beta': '0.28 unit increase',
'study_id': 'GCST010555',
'pubmed_id': '33536258',
'effect_allele': 'T'
},
...
][
{
'study_id': 'GCST90476118',
'trait': 'Renal failure',
'finemapping_method': 'SuSiE-inf',
'p_value': 3.5e-42,
'predicted_genes': [
{'gene': 'TCF7L2', 'score': 0.863}
],
'region': '10:112950000-113050000'
},
...
]Genome-wide significant associations with 100 traits/diseases:
- Type 2 diabetes
- Diabetic retinopathy
- HbA1c levels
...
Identified in 20 fine-mapped loci.
Predicted causal genes: TCF7L2See QUICK_START.md for platform-specific examples.
gwas_get_snp_by_id: Get SNP annotationgwas_get_associations_for_snp: Get all trait associationsOpenTargets_get_variant_info: Get variant details with population frequenciesOpenTargets_get_variant_credible_sets: Get fine-mapping credible sets with L2Ginclude_credible_sets=True for clinical decisions~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.