transcriptome-analysis

name: transcriptome_analysis description: "Transcriptome Analysis Pipeline - Analyze transcriptome: Ensembl transcript lookup, sequence retrieval, haplotype analysis, and UCSC track data. Use this skill for transcriptomics tasks involving get lookup id get sequence id get transcript haplotypes get track data. Combines 4 tools from 2 SCP server(s)."

Transcriptome Analysis Pipeline

Discipline: Transcriptomics | Tools Used: 4 | Servers: 2

Description

Analyze transcriptome: Ensembl transcript lookup, sequence retrieval, haplotype analysis, and UCSC track data.

Tools Used

• get_lookup_id from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl
• get_sequence_id from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl
• get_transcript_haplotypes from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl
• get_track_data from ucsc-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC

Workflow

1. Look up transcript details
2. Get transcript sequence
3. Analyze transcript haplotypes
4. Get UCSC track data

Test Case

Input

{
    "transcript_id": "ENST00000269305",
    "species": "homo_sapiens",
    "genome": "hg38"
}

Expected Steps

1. Look up transcript details
2. Get transcript sequence
3. Analyze transcript haplotypes
4. Get UCSC track data

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 = {
    "ensembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl",
    "ucsc-server": "https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC"
}

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["ensembl-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl", "streamable-http")
    sessions["ucsc-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC", "streamable-http")

    # Execute workflow steps
    # Step 1: Look up transcript details
    result_1 = await sessions["ensembl-server"].call_tool("get_lookup_id", arguments={})
    data_1 = parse(result_1)
    print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

    # Step 2: Get transcript sequence
    result_2 = await sessions["ensembl-server"].call_tool("get_sequence_id", arguments={})
    data_2 = parse(result_2)
    print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

    # Step 3: Analyze transcript haplotypes
    result_3 = await sessions["ensembl-server"].call_tool("get_transcript_haplotypes", arguments={})
    data_3 = parse(result_3)
    print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")

    # Step 4: Get UCSC track data
    result_4 = await sessions["ucsc-server"].call_tool("get_track_data", 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())