--- name: comprehensive-variant-annotation-69b56b766d1f description: "Given an rsID, query multiple databases (dbSNP, FAVOR, GWAS Catalog, ClinVar, gnomAD, PharmGKB, ClinGen) for comprehensive annotation. Use when user asks a general question about a variant without specifying which aspect." license: MIT license metadata: skill-author: PJLab --- # Comprehensive Variant Annotation ## Usage ### 1. Tool Descriptions This skill chains 7 public genomics database APIs sequentially to build a comprehensive annotation for a given variant. Use this when the user asks a general/vague question like "帮我查一下 rs7412" or "tell me about rs7412". **Tool 1: dbSNP — Variant Basic Info & ClinVar RCV Records** ```tex Query NCBI dbSNP REST API to get SNP basic information and ClinVar clinical records. API: GET https://api.ncbi.nlm.nih.gov/variation/v0/refsnp/{rsid_number} Args: rs_id (str): dbSNP rsID (e.g. "rs7412") Return: primary_snapshot_data: allele_annotations (gene associations, functional impact, ClinVar RCV clinical records), placements_with_allele (GRCh38 coordinates). ``` **Tool 2: FAVOR — Functional Annotation & Scores** ```tex Query FAVOR (GenoHub) API to get functional annotation and conservation scores. API: GET https://api.genohub.org/v1/rsids/{rsid} Return: Functional prediction scores (CADD, REVEL, etc.), conservation scores, gene annotations, variant effect predictions, and variant_id for gnomAD. ``` **Tool 3: gnomAD — Population Allele Frequency** ```tex Query gnomAD GraphQL API for population allele frequencies. API: POST https://gnomad.broadinstitute.org/api Note: Requires variant_id (chr-pos-ref-alt format) from FAVOR Step 2. Return: Allele frequencies across populations (global, AFR, AMR, ASJ, EAS, FIN, NFE, SAS, etc.) ``` **Tool 4: GWAS Catalog — Trait Associations** ```tex Query EBI GWAS Catalog REST API for GWAS statistical associations. API: GET https://www.ebi.ac.uk/gwas/rest/api/associations/search/findByRsId?rsId={rsid} Return: associations: pvalue, risk allele, associated trait/disease, source study. ``` **Tool 5: ClinVar — Clinical Pathogenicity (extracted from dbSNP Step 1)** ```tex Extract ClinVar RCV records from dbSNP response (already obtained in Step 1). Return: Clinical significance (Pathogenic/Benign/VUS/drug-response), review status, associated diseases, RCV accession numbers. ``` **Tool 6: PharmGKB — Pharmacogenomic Annotations** ```tex Query PharmGKB clinPGx API for drug-gene-variant interactions. API: GET https://api.clinpgx.org/v1/data/clinicalAnnotation?location.fingerprint={rsid}&view=base Return: Related drugs, evidence level (1A-4), related diseases, annotation types. ``` **Tool 7: ClinGen — Cross-Database ID Mapping** ```tex Query ClinGen Allele Registry for cross-database identifiers. API: GET https://reg.genome.network/alleles?dbSNP.rs={rs_id} Headers: Accept: application/json Return: CA ID, ClinVar IDs, COSMIC ID, gnomAD IDs, external cross-references. ``` ### 2. Comprehensive Variant Annotation Query 7 databases for a given rsID, then save all results into a single JSON file `{rsID}_annotation.json`. ```python import requests import json from datetime import datetime rs_id = "rs7412" results = {"query_rsid": rs_id, "timestamp": datetime.now().isoformat()} def safe_request(name, func, fallback=None): """统一的容错请求包装器。任一数据库超时/报错不会中断整个流程。""" try: return func() except requests.exceptions.Timeout: print(f"[{name}] ⚠ 连接超时，跳过") results.setdefault("errors", {})[name] = "timeout" return fallback except Exception as e: print(f"[{name}] ⚠ 请求失败: {e}，跳过") results.setdefault("errors", {})[name] = str(e) return fallback # ── Step 1: dbSNP — 变异基本信息 + ClinVar RCV ── rsid_num = rs_id.replace("rs", "") dbsnp_url = f"https://api.ncbi.nlm.nih.gov/variation/v0/refsnp/{rsid_num}" dbsnp = safe_request("dbSNP", lambda: requests.get(dbsnp_url, timeout=30).json(), fallback={}) results["dbsnp"] = dbsnp print(f"[dbSNP] {rs_id} 查询{'成功' if dbsnp else '失败'}") # 从 dbSNP 提取 ClinVar RCV 记录（Step 5） snapshot = dbsnp.get("primary_snapshot_data", {}) clinvar_records = [] for ann in snapshot.get("allele_annotations", []): for clin in ann.get("clinical", []): clinvar_records.append({ "accession": clin.get("accession_version", ""), "significances": clin.get("clinical_significances", []), "diseases": clin.get("disease_names", []), "review_status": clin.get("review_status", "") }) results["clinvar"] = clinvar_records print(f"[ClinVar] RCV 记录数: {len(clinvar_records)}") # ── Step 2: FAVOR — 功能注释与评分 ── favor_url = f"https://api.genohub.org/v1/rsids/{rs_id}" favor = safe_request("FAVOR", lambda: requests.get(favor_url, timeout=30).json(), fallback={}) results["favor"] = favor print(f"[FAVOR] 功能注释{'获取成功' if favor else '获取失败'}") # 从 FAVOR 提取 variant_id 用于 gnomAD 查询 variant_id = None favor_results = favor if isinstance(favor, list) else favor.get("results", [favor]) if favor else [] if favor_results and isinstance(favor_results, list): first = favor_results[0] if favor_results else {} chrom = str(first.get("chromosome", "")) pos = str(first.get("position", "")) ref = first.get("ref", "") alt = first.get("alt", "") if chrom and pos and ref and alt: variant_id = f"{chrom}-{pos}-{ref}-{alt}" # ── Step 3: gnomAD — 人群等位基因频率 ── if variant_id: gnomad_query = """ query($variantId: String!) { variant(variantId: $variantId, dataset: gnomad_r4) { variant_id genome { ac an af populations { id ac an af } } } } """ gnomad_data = safe_request("gnomAD", lambda: requests.post( "https://gnomad.broadinstitute.org/api", json={"query": gnomad_query, "variables": {"variantId": variant_id}}, timeout=30 ).json(), fallback={}) results["gnomad"] = (gnomad_data or {}).get("data", {}).get("variant", {}) genome = results["gnomad"].get("genome", {}) if results["gnomad"] else {} print(f"[gnomAD] AF={genome.get('af', 'N/A')}") else: results["gnomad"] = {"error": "无法从 FAVOR 提取 variant_id"} print("[gnomAD] 跳过: 无 variant_id") # ── Step 4: GWAS Catalog — 关联表型 ── gwas_url = f"https://www.ebi.ac.uk/gwas/rest/api/associations/search/findByRsId?rsId={rs_id}" gwas = safe_request("GWAS Catalog", lambda: requests.get(gwas_url, headers={"Accept": "application/json"}, timeout=30).json(), fallback={}) associations = (gwas or {}).get("_embedded", {}).get("associations", []) results["gwas_catalog"] = { "association_count": len(associations), "associations": associations } print(f"[GWAS Catalog] 关联数={len(associations)}") # ── Step 6: PharmGKB — 药物基因组注释 ── pgx_url = f"https://api.clinpgx.org/v1/data/clinicalAnnotation?location.fingerprint={rs_id}&view=base" pgx_resp = safe_request("PharmGKB", lambda: requests.get(pgx_url, timeout=30).json(), fallback=[]) pgx_annotations = pgx_resp if isinstance(pgx_resp, list) else (pgx_resp or {}).get("data", []) results["pharmgkb"] = pgx_annotations print(f"[PharmGKB] 药物基因组注释数: {len(pgx_annotations)}") # ── Step 7: ClinGen — 跨数据库 ID 映射 ── # 注意: ClinGen Allele Registry 服务器可能响应较慢，使用 60s 超时 + 重试 clingen_url = f"https://reg.genome.network/alleles?dbSNP.rs={rs_id}" clingen_resp = None for attempt in range(2): # 最多重试 1 次 clingen_resp = safe_request("ClinGen", lambda: requests.get(clingen_url, headers={"Accept": "application/json"}, timeout=60).json(), fallback=None) if clingen_resp is not None: break print(f"[ClinGen] 第 {attempt+1} 次尝试失败，重试中...") if clingen_resp is not None: if not isinstance(clingen_resp, list): clingen_resp = [clingen_resp] # 过滤同义变异 clingen_alleles = [] for allele in clingen_resp: titles = allele.get("communityStandardTitle", []) if titles and any("=" in t for t in titles): continue clingen_alleles.append({ "ca_id": allele.get("@id", "").split("/")[-1], "title": titles, "externalRecords": allele.get("externalRecords", {}) }) results["clingen"] = clingen_alleles print(f"[ClinGen] 等位基因数: {len(clingen_alleles)}") else: results["clingen"] = {"error": "ClinGen API 连接超时，可稍后单独使用 variant-cross-database-ids skill 重试"} print("[ClinGen] ⚠ 所有尝试均超时，已跳过") # ── 保存结果到 JSON 文件 ── output_file = f"{rs_id}_annotation.json" with open(output_file, "w", encoding="utf-8") as f: json.dump(results, f, indent=2, ensure_ascii=False) # 汇总报告 errors = results.get("errors", {}) if errors: print(f"\n⚠ 以下数据库查询失败: {list(errors.keys())}，其余数据库结果正常") print(f"✓ 结果已保存: {output_file}") ``` --- Source attribution: InternScience Original project: https://github.com/InternScience/scp/blob/cea5398564032aea65a78e246d06c30ae945e03f/skills/comprehensive-variant-annotation/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2024 Anthropic, PBC Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: InternScience Original project: https://github.com/InternScience/scp/blob/cea5398564032aea65a78e246d06c30ae945e03f/skills/comprehensive-variant-annotation/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Education & Research, Healthcare & Life Sciences Roles: Data Scientist, Health Informatics, Researcher Specialties: API Tools: Clingen, Clinvar, Favor, Pharmgkb, Dbsnp, Gnomad, Gwas Catalog Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 03e5444d99c41db4581d3293e366a725a9561d4108481c7bc32666092434bc1b