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/ensembl-database

Ensembl REST API for gene/transcript/variant annotations in 300+ species. Gene info by symbol/ID, sequence, cross-refs (HGNC, RefSeq, UniProt), regulatory features. For bulk local use pyensembl; for pathways use kegg-database.

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Ensembl REST API for gene/transcript/variant annotations in 300+ species. Gene info by symbol/ID, sequence, cross-refs (HGNC, RefSeq, UniProt), regulatory features. For bulk local use pyensembl; for pathways use kegg-database.

SKILL.md

ensembl-database.SKILL.md
name: "ensembl-database"
description: "Ensembl REST API for gene/transcript/variant annotations in 300+ species. Gene info by symbol/ID, sequence, cross-refs (HGNC, RefSeq, UniProt), regulatory features. For bulk local use pyensembl; for pathways use kegg-database."
license: "Apache-2.0"

Ensembl Genome Database

Overview

Ensembl is a comprehensive genome annotation database covering 300+ vertebrate and non-vertebrate species. The Ensembl REST API provides programmatic access to gene models, transcript/protein sequences, variant annotations, cross-references, regulatory features, and comparative genomics without requiring any login or API key.

When to Use

  • Retrieving official gene and transcript annotations (stable IDs, biotype, genomic coordinates) for human or model organism genes
  • Converting between gene identifier namespaces (HGNC symbol ↔ Ensembl ID ↔ RefSeq ↔ UniProt)
  • Fetching genomic or cDNA/CDS/protein sequences for a gene or transcript
  • Looking up variant consequences and functional impact (VEP) for a list of SNPs
  • Querying regulatory features (promoters, enhancers, CTCF sites) in a genomic region
  • Performing comparative genomics queries (orthologs, paralogs, gene trees) across species
  • For local offline access to large genomic annotations, use `pyensembl` instead
  • For pathway and metabolic annotations, use `kegg-database` or `reactome-database` instead

Prerequisites

  • **Python packages**: `requests`
  • **Data requirements**: gene symbols, Ensembl stable IDs (ENSG…/ENST…/ENSP…), or genomic coordinates
  • **Environment**: internet connection required; no API key needed
  • **Rate limits**: max ~15 requests/second; use `expand=1` and batch endpoints to minimize calls
pip install requests

Quick Start

import requests

BASE = "https://rest.ensembl.org"
HEADERS = {"Content-Type": "application/json"}

def ensembl_get(endpoint, params=None):
    r = requests.get(f"{BASE}{endpoint}", headers=HEADERS, params=params)
    r.raise_for_status()
    return r.json()

# Look up human BRCA1
gene = ensembl_get("/lookup/symbol/homo_sapiens/BRCA1", params={"expand": 1})
print(f"ID: {gene['id']}, Chr: {gene['seq_region_name']}:{gene['start']}-{gene['end']}")
print(f"Transcripts: {len(gene.get('Transcript', []))}")

Core API

Query 1: Gene Lookup by Symbol or Stable ID

Retrieve gene metadata from a gene symbol or Ensembl stable ID.

import requests

BASE = "https://rest.ensembl.org"
HEADERS = {"Content-Type": "application/json"}

# By gene symbol
r = requests.get(
    f"{BASE}/lookup/symbol/homo_sapiens/TP53",
    headers=HEADERS,
    params={"expand": 1}
)
gene = r.json()
print(f"Ensembl ID : {gene['id']}")
print(f"Location   : {gene['seq_region_name']}:{gene['start']}-{gene['end']} ({gene['strand']})")
print(f"Biotype    : {gene['biotype']}")
print(f"Transcripts: {len(gene.get('Transcript', []))}")
# By stable ID (works for genes, transcripts, proteins)
r = requests.get(
    f"{BASE}/lookup/id/ENSG00000141510",
    headers=HEADERS,
    params={"expand": 0}
)
obj = r.json()
print(f"Symbol: {obj.get('display_name')}, Species: {obj.get('species')}")

Query 2: Batch Lookup

Retrieve information for multiple IDs in one call (POST endpoint).

import requests, json

BASE = "https://rest.ensembl.org"
HEADERS = {"Content-Type": "application/json"}

# Batch lookup by symbols
symbols = ["BRCA1", "BRCA2", "TP53", "EGFR", "MYC"]
r = requests.post(
    f"{BASE}/lookup/symbol/homo_sapiens",
    headers=HEADERS,
    data=json.dumps({"symbols": symbols})
)
results = r.json()
for sym, data in results.items():
    if data:
        print(f"{sym}: {data['id']} ({data['seq_region_name']}:{data['start']}-{data['end']})")

Query 3: Sequence Retrieval

Fetch genomic, cDNA, CDS, or protein sequences.

import requests

BASE = "https://rest.ensembl.org"
HEADERS = {"Content-Type": "text/plain"}

# Protein sequence for canonical transcript
r = requests.get(
    f"{BASE}/sequence/id/ENST00000269305",
    headers=HEADERS,
    params={"type": "protein"}
)
seq = r.text
print(f"Protein sequence ({len(seq)} aa): {seq[:60]}...")
# Genomic region sequence
HEADERS_JSON = {"Content-Type": "application/json"}
r = requests.get(
    f"{BASE}/sequence/region/human/17:43044295..43125364",
    headers=HEADERS_JSON,
    params={"coord_system_version": "GRCh38"}
)
result = r.json()
print(f"Retrieved {len(result['seq'])} bp of genomic sequence")

Query 4: Cross-References (ID Mapping)

Map Ensembl IDs to external database identifiers.

import requests

BASE = "https://rest.ensembl.org"
HEADERS = {"Content-Type": "application/json"}

# All xrefs for a gene
r = requests.get(
    f"{BASE}/xrefs/id/ENSG00000141510",
    headers=HEADERS
)
xrefs = r.json()

# Group by database
from collections import defaultdict
by_db = defaultdict(list)
for x in xrefs:
    by_db[x["dbname"]].append(x["primary_id"])

for db in ["HGNC", "RefSeq_gene_name", "Uniprot_gn", "MIM_gene"]:
    if db in by_db:
        print(f"{db}: {by_db[db]}")

Query 5: Variant Consequence Annotation (VEP)

Predict functional consequences of variants via REST VEP endpoint.

import requests, json

BASE = "https://rest.ensembl.org"
HEADERS = {"Content-Type": "application/json"}

# Annotate a list of hgvs notations
variants = ["17:g.43094692C>T", "13:g.32929387C>T"]
r = requests.post(
    f"{BASE}/vep/human/hgvs",
    headers=HEADERS,
    data=json.dumps({"hgvs_notations": variants})
)
for v in r.json():
    print(f"\nVariant: {v.get('input')}")
    for tc in v.get("transcript_consequences", [])[:2]:
        print(f"  Gene: {tc.get('gene_symbol')}, Impact: {tc.get('impact')}, Consequence: {tc.get('consequence_terms')}")
# Annotate by rsID
r = requests.get(
    f"{BASE}/vep/human/id/rs699",
    headers=HEADERS
)
v = r.json()[0]
print(f"rsID rs699 in gene: {v['transcript_consequences'][0]['gene_symbol']}")
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