ensembl-database
Query Ensembl genome database REST API for 250+ species.
Skill by beita6969
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: backend, research
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/ensembl-database
What's inside
- Skill name
ensembl-database- Description
- Query Ensembl genome database REST API for 250+ species. Gene lookups, sequence retrieval, variant analysis, comparative genomics, orthologs, VEP predictions, for genomic research.
- License
- MIT
- Metadata
- skill-author: K-Dense Inc.
- Instructions
- 304 lines in SKILL.md · view on GitHub
Before installing
- Instructions call the network
Files (1)
- SKILL.md
SKILL.md (first lines)
# Ensembl Database
## Overview
Access and query the Ensembl genome database, a comprehensive resource for vertebrate genomic data maintained by EMBL-EBI. The database provides gene annotations, sequences, variants, regulatory information, and comparative genomics data for over 250 species. Current release is 115 (September 2025).
## When to Use This Skill
This skill should be used when:
- Querying gene information by symbol or Ensembl ID
- Retrieving DNA, transcript, or protein sequences
- Analyzing genetic variants using the Variant Effect Predictor (VEP)
- Finding orthologs and paralogs across species
- Accessing regulatory features and genomic annotations
- Converting coordinates between genome assemblies (e.g., GRCh37 to GRCh38)
- Performing comparative genomics analyses
- Integrating Ensembl data into genomic research pipelines
## Core Capabilities
### 1. Gene Information Retrieval
Query gene data by symbol, Ensembl ID, or external database identifiers.
**Common operations:**
- Look up gene information by symbol (e.g., "BRCA2", "TP53")
- Retrieve transcript and protein information
- Get gene coordinates and chromosomal locations
- Access cross-references to external databases (UniProt, RefSeq, etc.)
**Using the ensembl_rest package:**
```python
from ensembl_rest import EnsemblClient
client = EnsemblClient()
# Look up gene by symbol
gene_data = client.symbol_lookup(
species='human',
symbol='BRCA2'
)
# Get detailed gene information
gene_info = client.lookup_id(
id='ENSG00000139618', # BRCA2 Ensembl ID
expand=True
)
```
**Direct REST API (no package):**
```python
import requests
server = "https://rest.ensembl.org"
# Symbol lookup
response = requests.get(
f"{server}/lookup/symbol/homo_sapiens/BRCA2",
headers={"Content-Type": "application/json"}
)
gene_data = response.json()
```
### 2. Sequence Retrieval
Fetch genomic, transcript, or protein sequences in various formats (JSON, FASTA, plain text).
**Operations:**
- Get DNA sequences for genes or genomic regions
- Retrieve transcript sequences (cDNA)
- Access protein sequences
- Extract sequences with flanking regions or modifications
**Example:**
```python
# Using ensembl_rest package
sequence = client.sequence_id(
id='ENSG00000139618', # Gene ID
content_type='application/json'
)
# Get sequence for a genomic region
region_seq = client.sequence_region(
species='human',
region='7:140424943-140624564' # chromosome:start-end
)
```
### 3. Variant Analysis
Query genetic variation data and predict variant consequences using the Variant Effect Predictor (VEP).
**Capabilities:**
- Look up variants by rsID or genomic coordinates
- Predict functional consequences of variants
- Access population frequency data
- Retrieve phenotype associations
**VEP example:**
```python
# Predict variant consequences
vep_result = client.vep_hgvs(
species='human',
hgvs_notation='ENST00000380152.7:c.803C>T'
)
# Query variant by rsID
variant = client.variation_id(
species='human',
id='rs699'
)
```
### 4. Comparative Genomics
Perform cross-species comparisons to identify orthologs, paralogs, and evolutionary relationships.
**Operations:**From beita6969/ScienceClaw, MIT.
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Signals
- Stars
- 1,019
- Forks
- 109
- Open issues
- 1
- Last commit (this folder)
- Mar 12, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/beita6969/ScienceClaw
- Website
- scienceclaw.science
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Same skill elsewhere
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ensembl-database skill. Agent Mart. https://agentmart.dev/skills/beita6969-ensembl-database (last updated 2026-10-24)