gene-disease-association

name: gene_disease_association description: "Gene-Disease Association Analysis - Analyze gene-disease associations: NCBI gene metadata, OpenTargets disease associations, TCGA expression, and Monarch phenotypes. Use this skill for medical genetics tasks involving get gene metadata by gene name get associated targets by disease efoId get gene expression across cancers get joint associated diseases by HPO ID list. Combines 4 tools from 4 SCP server(s)."

Gene-Disease Association Analysis

Discipline: Medical Genetics | Tools Used: 4 | Servers: 4

Description

Analyze gene-disease associations: NCBI gene metadata, OpenTargets disease associations, TCGA expression, and Monarch phenotypes.

Tools Used

• get_gene_metadata_by_gene_name from ncbi-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI
• get_associated_targets_by_disease_efoId from opentargets-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargets
• get_gene_expression_across_cancers from tcga-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA
• get_joint_associated_diseases_by_HPO_ID_list from monarch-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/16/Origene-Monarch

Workflow

1. Get gene metadata from NCBI
2. Get disease-target associations from OpenTargets
3. Analyze TCGA cancer expression
4. Check Monarch disease associations

Test Case

Input

{
    "gene_name": "TP53",
    "disease_efo": "EFO_0000311"
}

Expected Steps

1. Get gene metadata from NCBI
2. Get disease-target associations from OpenTargets
3. Analyze TCGA cancer expression
4. Check Monarch disease associations

Usage Example

Note: Replace <YOUR_SCP_HUB_API_KEY> with your own SCP Hub API Key. You can obtain one from the SCP Platform.

import asyncio
import json
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client

SERVERS = {
    "ncbi-server": "https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI",
    "opentargets-server": "https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargets",
    "tcga-server": "https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA",
    "monarch-server": "https://scp.intern-ai.org.cn/api/v1/mcp/16/Origene-Monarch"
}

async def connect(url, transport_type):
    transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "<YOUR_SCP_HUB_API_KEY>"})
    read, write, _ = await transport.__aenter__()
    ctx = ClientSession(read, write)
    session = await ctx.__aenter__()
    await session.initialize()
    return session, ctx, transport

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():
    # Connect to required servers
    sessions = {}
    sessions["ncbi-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI", "streamable-http")
    sessions["opentargets-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargets", "streamable-http")
    sessions["tcga-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA", "streamable-http")
    sessions["monarch-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/16/Origene-Monarch", "streamable-http")

    # Execute workflow steps
    # Step 1: Get gene metadata from NCBI
    result_1 = await sessions["ncbi-server"].call_tool("get_gene_metadata_by_gene_name", arguments={})
    data_1 = parse(result_1)
    print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

    # Step 2: Get disease-target associations from OpenTargets
    result_2 = await sessions["opentargets-server"].call_tool("get_associated_targets_by_disease_efoId", arguments={})
    data_2 = parse(result_2)
    print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

    # Step 3: Analyze TCGA cancer expression
    result_3 = await sessions["tcga-server"].call_tool("get_gene_expression_across_cancers", arguments={})
    data_3 = parse(result_3)
    print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")

    # Step 4: Check Monarch disease associations
    result_4 = await sessions["monarch-server"].call_tool("get_joint_associated_diseases_by_HPO_ID_list", 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())