skills/variant-population-frequency/SKILL.md
Query gnomAD for variant allele frequency across populations. Uses FAVOR to convert rsID→variant_id first, then queries gnomAD.
npx skillsauth add InternScience/scp variant-population-frequencyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Step 1: Query FAVOR to convert rsID → chr-pos-ref-alt format.
API: GET https://api.genohub.org/v1/rsids/{rs_id}
Step 2: Query gnomAD GraphQL API with the variant_id.
API: POST https://gnomad.broadinstitute.org/api (GraphQL)
Args:
rs_id (str): dbSNP rsID (e.g. "rs7412")
Return:
Overall AF, population-specific AF (exome + genome), homozygote counts.
import requests
rs_id = "rs7412"
# ── Step 1: FAVOR 获取 variant_id (chr-pos-ref-alt) ──
# 注意:FAVOR 可能返回多个变异(多等位基因位点),需遍历所有结果
favor_url = f"https://api.genohub.org/v1/rsids/{rs_id}"
favor_resp = requests.get(favor_url, timeout=30).json()
if not isinstance(favor_resp, list):
favor_resp = [favor_resp]
variant_ids = [item.get("variant_vcf", "") for item in favor_resp if item.get("variant_vcf")]
print(f"[FAVOR] 该rsID对应 {len(variant_ids)} 个变异: {variant_ids}")
# ── Step 2: gnomAD 查询人群频率(遍历所有变异) ──
query = """
query VariantQuery($variantId: String!) {
variant(variantId: $variantId, dataset: gnomad_r4) {
variant_id
rsid
exome {
ac
an
af
ac_hom
populations { id ac an ac_hom }
}
genome {
ac
an
af
ac_hom
populations { id ac an ac_hom }
}
}
}
"""
for variant_vcf in variant_ids:
print(f"\n── 查询 {variant_vcf} ──")
resp = requests.post(
"https://gnomad.broadinstitute.org/api",
json={"query": query, "variables": {"variantId": variant_vcf}},
timeout=30
).json()
v = resp.get("data", {}).get("variant", {})
if not v:
print(f"[gnomAD] {variant_vcf}: 未找到数据")
continue
print(f"[gnomAD] variant: {v.get('variant_id')}, rsid: {v.get('rsid')}")
for source in ["exome", "genome"]:
d = v.get(source, {})
if d:
print(f"[gnomAD] {source}: AF={d.get('af')}, AC={d.get('ac')}, AN={d.get('an')}, Hom={d.get('ac_hom')}")
for pop in (d.get("populations") or []):
if pop.get("an", 0) > 0:
af = pop["ac"] / pop["an"]
print(f" {pop['id']}: AF={af:.6f}, AC={pop['ac']}, AN={pop['an']}")
testing
Assess wind energy potential and perform site analysis using atmospheric science calculations.
tools
Scientific Literature Mining - Mine scientific literature: PubMed search, arXiv search, web search, and Tavily deep search. Use this skill for scientific informatics tasks involving pubmed search search literature search web tavily search. Combines 4 tools from 2 SCP server(s).
tools
Virus Genomics Analysis - Analyze virus genomics: NCBI virus dataset, annotation, taxonomy, and literature search. Use this skill for virology tasks involving get virus dataset report get virus annotation report get taxonomy search literature. Combines 4 tools from 2 SCP server(s).
tools
Virtual Screening Pipeline - Virtual screening: search PubChem by substructure, compute similarity, filter by drug-likeness, and predict binding affinity. Use this skill for drug discovery tasks involving search pubchem by smiles calculate smiles similarity calculate mol drug chemistry boltz binding affinity. Combines 4 tools from 3 SCP server(s).