Population Genetics Analysis
SkillProductivityPopulation Genetics Analysis - Analyze population genetics: Ensembl variation populations, linkage disequilibrium, and variant frequency data. Use this skill for population genetics tasks involving get info variation populations get ld get variation get variant recoder. Combines 4 tools from 1 SCP server(s).
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Then ask your AI: use the Population Genetics Analysis skill
What this skill tells your AI
The instructions your AI receives, as published by internscience/scp in skills/population_genetics/SKILL.md and read by ahel’s review.
Discipline: Population Genetics | Tools Used: 4 | Servers: 1
Description
Analyze population genetics: Ensembl variation populations, linkage disequilibrium, and variant frequency data.
Tools Used
get_info_variation_populationsfromensembl-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensemblget_ldfromensembl-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensemblget_variationfromensembl-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensemblget_variant_recoderfromensembl-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl
Workflow
- Get variation populations
- Calculate LD for variant
- Get variant details
- Recode variant identifiers
Test Case
Input
{
"variant_id": "rs699",
"species": "homo_sapiens",
"population": "1000GENOMES:phase_3:CEU"
}
Expected Steps
- Get variation populations
- Calculate LD for variant
- Get variant details
- Recode variant identifiers
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"
}
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")
# Execute workflow steps
# Step 1: Get variation populations
result_1 = await sessions["ensembl-server"].call_tool("get_info_variation_populations", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Calculate LD for variant
result_2 = await sessions["ensembl-server"].call_tool("get_ld", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Get variant details
result_3 = await sessions["ensembl-server"].call_tool("get_variation", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Recode variant identifiers
result_4 = await sessions["ensembl-server"].call_tool("get_variant_recoder", 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())
Signals
- GitHub stars
- 167
- Forks
- 9
- Last commit
- Jun 2026
Advanced
- Catalog kind
- skill
- Gateway key
population-genetics- Source
- github.com/internscience/scp