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pharmacogenomics_analysis

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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).

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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

{
    "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.

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())