# Pharmacogenomics Analysis

> Pharmacogenomics Analysis - Pharmacogenomics analysis: FDA pharmacogenomics info, variant effects, ClinVar pathogenicity, and gene expression. Use this skill for pharmacogenomics tasks involving get pharmacogenomics info by drug name get vep hgvs clinvar search get gene expression across cancers. Combines 4 tools from 4 SCP server(s).

- Skill: `gabrielmoreira/pharmacogenomics-analysis` (Agent Skill)
- Install (CLI): `npx skillmds@latest add gabrielmoreira/pharmacogenomics-analysis`
- Raw SKILL.md: https://api.skillmd.com/api/skills/gabrielmoreira/pharmacogenomics-analysis/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: gabrielmoreira (https://skillmd.com/u/gabrielmoreira)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/gabrielmoreira/pharmacogenomics-analysis

---


# Pharmacogenomics Analysis

**Discipline**: Pharmacogenomics | **Tools Used**: 4 | **Servers**: 4

## Description

Pharmacogenomics analysis: FDA pharmacogenomics info, variant effects, ClinVar pathogenicity, and gene expression.

## Tools Used

- **`get_pharmacogenomics_info_by_drug_name`** from `fda-drug-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug`
- **`get_vep_hgvs`** from `ensembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl`
- **`clinvar_search`** from `search-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search`
- **`get_gene_expression_across_cancers`** from `tcga-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA`

## Workflow

1. Get FDA pharmacogenomics info
2. Predict effect of CYP2C9 variants
3. Search ClinVar for CYP2C9 variants
4. Check CYP2C9 expression across cancers

## Test Case

### Input
```json
{
    "drug_name": "warfarin",
    "gene": "CYP2C9"
}
```

### Expected Steps
1. Get FDA pharmacogenomics info
2. Predict effect of CYP2C9 variants
3. Search ClinVar for CYP2C9 variants
4. Check CYP2C9 expression across cancers

## Usage Example

> **Note:** Replace `sk-b04409a1-b32b-4511-9aeb-22980abdc05c` with your own SCP Hub API Key. You can obtain one from the [SCP Platform](https://scphub.intern-ai.org.cn).

```python
import asyncio
import json
from contextlib import AsyncExitStack
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client

SERVERS = {
    "fda-drug-server": "https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug",
    "ensembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl",
    "search-server": "https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search",
    "tcga-server": "https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA"
}

async def connect(url, stack):
    transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "sk-b04409a1-b32b-4511-9aeb-22980abdc05c"})
    read, write, _ = await stack.enter_async_context(transport)
    ctx = ClientSession(read, write)
    session = await stack.enter_async_context(ctx)
    await session.initialize()
    return session

def parse(result):
    try:
        if hasattr(result, 'content') and result.content:
            c = result.content[0]
            if hasattr(c, 'text'):
                try: return json.loads(c.text)
                except: return c.text
        return str(result)
    except: return str(result)

async def main():
    async with AsyncExitStack() as stack:
        # Connect to required servers
        sessions = {}
        sessions["fda-drug-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", stack)
        sessions["ensembl-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl", stack)
        sessions["search-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search", stack)
        sessions["tcga-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA", stack)

        # Execute workflow steps
        # Step 1: Get FDA pharmacogenomics info
        result_1 = await sessions["fda-drug-server"].call_tool("get_pharmacogenomics_info_by_drug_name", arguments={})
        data_1 = parse(result_1)
        print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

        # Step 2: Predict effect of CYP2C9 variants
        result_2 = await sessions["ensembl-server"].call_tool("get_vep_hgvs", arguments={})
        data_2 = parse(result_2)
        print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

        # Step 3: Search ClinVar for CYP2C9 variants
        result_3 = await sessions["search-server"].call_tool("clinvar_search", arguments={})
        data_3 = parse(result_3)
        print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")

        # Step 4: Check CYP2C9 expression across cancers
        result_4 = await sessions["tcga-server"].call_tool("get_gene_expression_across_cancers", arguments={})
        data_4 = parse(result_4)
        print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")

        # Cleanup
        print("Workflow complete!")

if __name__ == "__main__":
    asyncio.run(main())
```