variant-pharmacogenomics
$
npx mdskill add InternScience/scp/variant-pharmacogenomicsQueries PharmGKB for pharmacogenomic annotations linking variants to drug response and dosing
- Identifies how genetic variants affect drug efficacy, toxicity, and dosage requirements
- Uses the PharmGKB (clinPGx) API to retrieve clinical annotations and guidelines
- Evaluates evidence levels and guidelines (CPIC, DPWG, FDA) to prioritize results
- Returns structured data including drugs, genes, evidence, and related clinical resources
SKILL.md
.github/skills/variant-pharmacogenomicsView on GitHub ↗
---
name: variant-pharmacogenomics
description: "Query PharmGKB (clinPGx) for pharmacogenomic clinical annotations — how a variant affects drug response, dosing, and adverse reactions."
license: MIT license
metadata:
skill-author: PJLab
---
# PharmGKB (clinPGx) — Pharmacogenomic Annotations
## Usage
### Tool Description
```tex
Query PharmGKB clinical annotations API to find drug-gene-variant interactions.
Database: PharmGKB / clinPGx (https://www.pharmgkb.org/)
API: GET https://api.clinpgx.org/v1/data/clinicalAnnotation?location.fingerprint={rsid}&view=base
Args:
rs_id (str): dbSNP rsID (e.g. "rs7412")
Return:
Clinical annotations: related drugs (chemicals), evidence level (1A/1B/2A/2B/3/4),
related diseases, gene (APOE etc.), phenotype categories (efficacy/toxicity/dosage/PK),
related guidelines and FDA labels.
Return Fields Explanation:
- relatedChemicals: 关联的药物/化合物名称和 PharmGKB ID
- levelOfEvidence.term: 证据级别 (1A=最强, 有CPIC/DPWG指南; 4=最弱, 个案报告)
- location.genes: 变异所在基因
- relatedDiseases: 关联疾病
- types: 注释类型 (Efficacy=疗效, Toxicity=毒性, Dosage=剂量, PK=药代动力学)
- relatedGuidelines: 关联的用药指南 (CPIC, DPWG 等)
- relatedLabels: 关联的 FDA 药品标签
```
### Query Example
```python
import requests
rs_id = "rs7412"
url = f"https://api.clinpgx.org/v1/data/clinicalAnnotation?location.fingerprint={rs_id}&view=base"
resp = requests.get(url, timeout=30).json()
if isinstance(resp, dict) and "data" in resp:
annotations = resp["data"]
elif isinstance(resp, list):
annotations = resp
else:
annotations = []
print(f"[PharmGKB] {rs_id} 药物基因组注释数: {len(annotations)}")
for i, ann in enumerate(annotations):
# 药物
drugs = [c.get("name", "") for c in ann.get("relatedChemicals", [])]
# 证据级别
evidence = ann.get("levelOfEvidence", {}).get("term", "N/A")
# 基因
genes = [g.get("symbol", "") for g in ann.get("location", {}).get("genes", [])]
# 疾病
diseases = [d.get("name", "") for d in ann.get("relatedDiseases", [])]
# 注释类型
ann_types = ann.get("types", [])
print(f"\n [{i+1}] 药物: {drugs}")
print(f" 证据级别: {evidence}")
print(f" 基因: {genes}")
print(f" 类型: {ann_types}")
if diseases:
print(f" 疾病: {diseases}")
```