skills/43-wentorai-research-plugins/skills/domains/biomedical/ensembl-rest-api/SKILL.md
Query gene, sequence, and variant data via the Ensembl REST API
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research ensembl-rest-apiInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Ensembl is a genome browser and annotation system maintained by EMBL-EBI and the Wellcome Sanger Institute, providing reference assemblies, gene annotations, variant data, and comparative genomics for over 300 vertebrate genomes. It is the genomic reference underpinning gget, PyEnsembl, and BioMart.
The REST API exposes Ensembl data via stateless HTTP. Researchers can look up genes by symbol or stable ID, retrieve genomic/cDNA/protein sequences, query variant annotations (rsIDs, clinical significance, consequences), access cross-references (HGNC, UniProt, RefSeq, OMIM), and obtain assembly metadata. Responses in JSON or XML.
No authentication required. All endpoints are publicly accessible. Users needing higher throughput can register for an API token.
Retrieve gene metadata: coordinates, biotype, canonical transcript.
GET https://rest.ensembl.org/lookup/symbol/{species}/{symbol}| Parameter | Type | Required | Description |
|---------------|--------|----------|--------------------------------------------------|
| species | string | Yes | Species name (e.g., homo_sapiens) |
| symbol | string | Yes | Gene symbol (e.g., BRCA1, TP53) |
| expand | int | No | Set to 1 to include transcripts and translations |
| content-type | string | Yes | application/json or text/xml |
curl "https://rest.ensembl.org/lookup/symbol/homo_sapiens/BRCA1?content-type=application/json"
{
"display_name": "BRCA1",
"description": "BRCA1 DNA repair associated [Source:HGNC Symbol;Acc:HGNC:1100]",
"object_type": "Gene", "species": "homo_sapiens",
"assembly_name": "GRCh38", "biotype": "protein_coding",
"seq_region_name": "17", "start": 43044292, "end": 43170245, "strand": -1,
"id": "ENSG00000012048", "canonical_transcript": "ENST00000357654.9"
}
Retrieve genomic, cDNA, CDS, or protein sequences by Ensembl stable ID.
GET https://rest.ensembl.org/sequence/id/{id}| Parameter | Type | Required | Description |
|----------------|--------|----------|-------------------------------------------------------|
| id | string | Yes | Ensembl stable ID (e.g., ENSG00000012048) |
| type | string | No | genomic, cdna, cds, or protein |
| expand_5prime | int | No | Expand 5' flanking region by N bases |
| expand_3prime | int | No | Expand 3' flanking region by N bases |
| content-type | string | Yes | application/json or text/plain (FASTA) |
curl "https://rest.ensembl.org/sequence/id/ENSG00000012048?content-type=application/json&type=genomic"
{
"id": "ENSG00000012048", "query": "ENSG00000012048",
"desc": "chromosome:GRCh38:17:43044292:43170245:-1",
"molecule": "DNA",
"seq": "AAAGCGTGGGAATTACAGATAAATTAAAACTGTGGAACCCCTTTCCTCGGCTGCCGCCAAGGTGTTCGG..."
}
Map a gene symbol to Ensembl stable IDs and external database identifiers.
GET https://rest.ensembl.org/xrefs/symbol/{species}/{symbol}species (required), symbol (required), external_db (optional filter, e.g., UniProt)curl "https://rest.ensembl.org/xrefs/symbol/homo_sapiens/TP53?content-type=application/json"
[{"type":"gene","id":"ENSG00000141510"},{"type":"gene","id":"LRG_321"}]Use xrefs/id/{id} to expand an Ensembl ID to all external cross-references (UniProt, HGNC, RefSeq, OMIM).
Retrieve variant data by rsID: mappings, alleles, consequence, clinical significance.
GET https://rest.ensembl.org/variation/{species}/{id}species (required), id (required, e.g., rs699)curl "https://rest.ensembl.org/variation/homo_sapiens/rs699?content-type=application/json"
{
"name": "rs699", "var_class": "SNP",
"most_severe_consequence": "missense_variant",
"clinical_significance": ["benign"],
"evidence": ["Frequency","1000Genomes","Cited","ESP","Phenotype_or_Disease","ExAC","TOPMed","gnomAD"],
"mappings": [{"location":"1:230710048-230710048","allele_string":"A/G","strand":1,"assembly_name":"GRCh38"}]
}
GET https://rest.ensembl.org/info/assembly/{species}assembly_name ("GRCh38.p14"), assembly_date ("2013-12"), assembly_accession ("GCA_000001405.29"), full karyotype array (1-22, X, Y, MT), and 347 top_level_region entries.X-RateLimit-Limit, X-RateLimit-Remaining, X-RateLimit-Reset on every response./lookup/id, /sequence/id): accept up to 1000 IDs per request.https://grch37.rest.ensembl.orgimport requests
BASE = "https://rest.ensembl.org"
HEADERS = {"Content-Type": "application/json"}
gene = requests.get(f"{BASE}/lookup/symbol/homo_sapiens/BRCA1", headers=HEADERS).json()
print(f"{gene['display_name']} ({gene['id']}) chr{gene['seq_region_name']}:{gene['start']}-{gene['end']}")
seq = requests.get(f"{BASE}/sequence/id/{gene['id']}?type=cds", headers=HEADERS).json()
print(f"CDS length: {len(seq['seq'])} bp")
import requests
ids = ["ENSG00000012048", "ENSG00000141510", "ENSG00000157764"] # BRCA1, TP53, BRAF
resp = requests.post(
"https://rest.ensembl.org/lookup/id",
headers={"Content-Type": "application/json", "Accept": "application/json"},
json={"ids": ids}
)
for ens_id, info in resp.json().items():
print(f"{info['display_name']:10s} chr{info['seq_region_name']}:{info['start']}-{info['end']}")
import requests
for rsid in ["rs699", "rs1042522", "rs334"]:
v = requests.get(
f"https://rest.ensembl.org/variation/homo_sapiens/{rsid}",
headers={"Content-Type": "application/json"}
).json()
loc = v["mappings"][0]["location"] if v.get("mappings") else "N/A"
print(f"{v['name']:12s} {v['var_class']:5s} {v['most_severe_consequence']:25s} {loc}")
tools
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文(用于「文献综述工具选型」与「一键安装/运行」)。
development
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
documentation
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
tools
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.