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).'
i18n:
  zh:
    description: 转录组分析：查询、序列、单倍型。
---

# 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
```json
{
    "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](https://scphub.intern-ai.org.cn).

```python
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())
```