ensembl-database
google-deepmind/science-skills
Query Ensembl for gene IDs, sequences, structures, and variant effects.
What is ensembl-database?
Access the Ensembl genome database via REST API to resolve gene/transcript/protein identifiers, fetch genomic and protein sequences, retrieve exon structures, and predict variant consequences using Variant Effect Predictor (VEP). Use this when you need to translate between ID systems, look up genomic coordinates, or assess how variants affect genes.
- Resolve gene symbols and aliases to Ensembl IDs (ENSG/ENST/ENSP)
- Cross-reference IDs to external databases (UniProt, HGNC, RefSeq)
- Fetch genomic DNA sequences for coordinate ranges
- Retrieve transcript structures including exon boundaries and UTR regions
- Predict variant consequences and molecular effects using VEP with AlphaMissense, SIFT, PolyPhen, and other plugins
- Get protein sequences and transcription start sites (TSS)
How to install ensembl-database
npx skills add https://github.com/google-deepmind/science-skills --skill ensembl-database- uv package manager installed and on PATH
- License acknowledgment: user must review Ensembl terms at https://useast.ensembl.org and https://github.com/Ensembl/ensembl-rest/wiki before first use
How to use ensembl-database
- 1.Run resolve-gene to translate a gene symbol to ENSG ID: `uv run scripts/ensembl_api.py resolve-gene TP53`
- 2.Use map-id to cross-reference to external databases: `uv run scripts/ensembl_api.py map-id ENSG00000141510 --external-db UniProt`
- 3.Fetch genomic sequence with get-sequence for a coordinate range: `uv run scripts/ensembl_api.py get-sequence 17:7661779-7687550`
- 4.List transcripts for a gene with transcripts command, optionally filtering to MANE or canonical: `uv run scripts/ensembl_api.py transcripts ENSG00000141510 --only-mane`
- 5.Get transcript structure (exons, CDS, UTRs) with transcript-structure: `uv run scripts/ensembl_api.py transcript-structure ENST00000269305`
- 6.Predict variant effects with vep command: `uv run scripts/ensembl_api.py vep 9:21971147:T:C` and review the full VEP Predictions output
- 7.Retrieve protein sequences with protein-sequence: `uv run scripts/ensembl_api.py protein-sequence ENST00000269305`
Use cases
- Translating a gene symbol like TP53 to its Ensembl ID and RefSeq equivalents
- Fetching the DNA sequence for a genomic region to design primers or check variants
- Looking up all transcripts for a gene and filtering to MANE Select or canonical isoforms
- Predicting the functional impact of a genetic variant on protein-coding genes
- Retrieving exon coordinates to understand transcript structure and splice sites
- Bioinformaticians analyzing genomic data
- Researchers studying gene structure and variants
- Computational biologists building pipelines for variant interpretation
- Scientists working with human or other model organism genomes
ensembl-database FAQ
ENSG is the stable gene ID, ENST is a transcript (splicing isoform) ID, and ENSP is a protein ID. A single gene can have multiple transcripts, and each transcript can produce a protein.
The skill defaults to human (species='human'). You will be explicitly notified when this default is applied so you can override it if needed.
MANE Select is the consensus primary transcript agreed upon by Ensembl and NCBI for human genes. It is returned by default unless you request all alternative isoforms. For non-human species, the Canonical transcript is used instead.
Yes, add the `--assembly GRCh37` flag to commands like get-sequence. The skill will explicitly notify you when a non-default assembly is being used.
VEP accepts genomic coordinates (e.g., 9:21971147:T:C), rsIDs (e.g., rs699), and other standard variant notations. The output includes standard predictions (SIFT, PolyPhen) and open-license plugins (AlphaMissense, Conservation, Dosage Sensitivity, LOEUF, Loftee).
Full instructions (SKILL.md)
Source of truth, from google-deepmind/science-skills.
name: ensembl-database description: > Query the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP). Use this skill as a primary ID translator, genomic sequence database and variant effect prediction tool.
Ensembl Database: ID Mapping and Genomic Features
Prerequisites
uv: Read theuvskill and follow its Setup instructions to ensureuvis installed and on PATH.- User Notification: If .licenses/ensembl_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://useast.ensembl.org/index.html and https://github.com/Ensembl/ensembl-rest/wiki, then (2) create the file recording the notification text and timestamp.
Overview
The Ensembl database is a resource for genome annotation. This skill allows you to interact with the Ensembl REST API to resolve ambiguous symbols, cross-reference IDs (RefSeq, HGNC, UniProt, ENSG), fetch raw sequences, and retrieve detailed transcript structures.
Key Concepts:
- ENSG (Gene): Stable identifier for a human gene. Other species will have different three-letter species codes.
- ENST (Transcript): Stable identifier for a transcript (splicing isoform).
- ENSP (Protein): Stable identifier for a translated protein.
- MANE Select: The consensus primary transcript agreed upon by Ensembl and NCBI.
- Canonical: Ensembl's representative transcript (used if MANE is not available or non-human).
Core Rules
- Use the Wrapper: ALWAYS execute the provided helper scripts to query the database rather than accessing the database directly. The scripts automatically enforce the required rate limit gracefully.
- Default Species: If the species is absent or ambiguous in the prompt,
default to
"human". You MUST explicitly flag this default to the user to ensure they are aware. - Primary Transcripts: When listing transcripts for a gene, only return the MANE Select transcript (for human) or the Canonical transcript (for others) unless the user explicitly asks for all alternative isoforms. You MUST flag to the user when multiple transcripts are available and you are defaulting to the primary one.
- Assembly Handling: The default assembly is GRCh38. For GRCh37 requests,
you MUST use the
--assembly GRCh37flag. You MUST explicitly flag to the user when a non-default assembly is being used. - Output Location: The script writes full JSON/FASTA output to temporary
files in
/tmpby default, or to a user-specified file using the--outputflag. It also prints a concise summary to stdout. - Notification: If this skill is used, ensure this is mentioned in the output.
Available Commands
1. Resolve Gene ID — Resolve a symbol, alias, or RefSeq ID to ENSG ID(s). Automatically falls back to resolving synonyms if primary symbol is not found.
uv run scripts/ensembl_api.py resolve-gene TP53 --species human --output tp53.json
uv run scripts/ensembl_api.py resolve-gene PCL2 --output pcl2.json # Falls back to synonym resolution
2. Map ID to External Database — Cross-reference an Ensembl ID to UniProt, HGNC, RefSeq, etc.
uv run scripts/ensembl_api.py map-id ENSG00000141510 --external-db UniProt --output uniprot_map.json
uv run scripts/ensembl_api.py map-id ENST00000269305 --external-db RefSeq_mRNA --output refseq_map.json
3. Get Genomic Sequence — Fetch raw DNA for a coordinate window. Supports
GRCh37 via --assembly GRCh37.
uv run scripts/ensembl_api.py get-sequence 17:7661779-7687550 --species human --output seq.txt
uv run scripts/ensembl_api.py get-sequence chr9:21971100-21971200 --assembly GRCh37 --output seq_grch37.txt
4. Gene Summary — High-level metadata: symbol, biotype, description, chromosomal location.
uv run scripts/ensembl_api.py gene-summary ENSG00000141510 --output gene_summary.json
5. List Transcripts — All transcripts for a gene, with optional
--only-mane or --only-canonical filters. Output includes Transcript Support
Level (TSL).
uv run scripts/ensembl_api.py transcripts ENSG00000141510 --only-mane --output transcripts_mane.json
uv run scripts/ensembl_api.py transcripts ENSG00000141510 --only-canonical --output transcripts_canonical.json
uv run scripts/ensembl_api.py transcripts ENSG00000141510 --output transcripts_all.json
5b. Canonical TSS — Get the single coordinate of the Transcription Start Site (TSS) for the canonical transcript of a gene.
[!NOTE] Unlike the standard
transcriptscommand,canonical-tssaccepts both symbols (e.g.,TP53) and Ensembl IDs, and automatically resolves them. It also does the math for strand orientation (TSS isStartfor+strand andEndfor-strand), outputting the single integer coordinate directly.
uv run scripts/ensembl_api.py canonical-tss TP53 --output tp53_tss.json
uv run scripts/ensembl_api.py canonical-tss ENSG00000141510 --output tss.json
6. Transcript Structure — Exon coordinates, CDS boundaries, and computed 5'/3' UTR regions for a transcript.
uv run scripts/ensembl_api.py transcript-structure ENST00000269305 --output structure.json
7. Protein Info — ENSP ID and sequence length for a transcript.
uv run scripts/ensembl_api.py protein-info ENST00000269305 --output protein_info.json
8. Protein Sequence — Amino acid FASTA for a transcript (ENST) or protein (ENSP) ID.
uv run scripts/ensembl_api.py protein-sequence ENST00000269305 --output protein.fasta
uv run scripts/ensembl_api.py protein-sequence ENSP00000269305 --output protein_ensp.fasta
9. Variant Consequence (VEP) — Predict molecular consequences for a genomic variant. Includes open-licensed plugins: AlphaMissense, Conservation, DosageSensitivity, IntAct, MaveDB, OpenTargets, LoF (Loftee), NMD, UTRAnnotator, mutfunc, LOEUF.
uv run scripts/ensembl_api.py vep 9:21971147:T:C --species human --output vep.json
uv run scripts/ensembl_api.py vep rs699 --species human --output vep_rs699.json
Example VEP stdout output:
[*] Variant: 9:21971147:T>C
[*] Most severe consequence: missense_variant
[*] Found 15 transcript consequences.
[*] VEP Predictions:
- ENST00000304494 (CDKN2A): Consequence = missense_variant
- ENST00000304494 (CDKN2A): Amino Acids = N/S
- ENST00000304494 (CDKN2A): SIFT = deleterious (0.01)
- ENST00000304494 (CDKN2A): AlphaMissense Class = likely_benign
- ENST00000304494 (CDKN2A): AlphaMissense Pathogenicity = 0.2129
- ENST00000304494 (CDKN2A): Conservation = 2.05
- ENST00000304494 (CDKN2A): Dosage Sensitivity (Haplo) = 0.889228328567991
- ENST00000304494 (CDKN2A): Dosage Sensitivity (Triplo) = 0.135514349094646
- ENST00000304494 (CDKN2A): Loss of Function (LOEUF) = 0.791
Presenting VEP Results: After running the VEP command, you MUST present the full VEP Predictions list from stdout to the user. This list contains both standard VEP predictions (Consequence, Amino Acids, SIFT, PolyPhen) and open-license plugin results (AlphaMissense, Conservation, Dosage Sensitivity, LOEUF, Loftee LoF, NMD, UTRAnnotator, Mutfunc). Do NOT just summarize — show the complete list so the user can see all predictions. If the list is very long (many transcripts), show the MANE Select / canonical transcript rows in full and note that the complete data is in the JSON output.
Parsing Outputs
If the user needs detailed, nested structural data (like the precise integer coordinates of Exon 2 of a transcript) that isn't summarized in stdout:
- Locate the JSON file (either specified via
--outputor the temporary file path printed by the script). - Use terminal tools like
jqor write a quick, disposable python snippet to extract the specific data point requested. Do not attempt to read the entire JSON file into your context if it is very large.
Custom Queries
If you need to make an API call that the script does not support (e.g., fetching
protein domain annotations, coordinate mapping between assemblies, homology
searches, linkage disequilibrium, or phenotype lookups), read
references/ensembl_rest_api_reference.md for a complete reference of available
endpoints, parameters, and response fields.
CRITICAL: When writing custom scripts or using alternatives to the provided
scripts, you MUST respect the Ensembl REST API rate limits (maximum 15
requests per second) and handle 429 Too Many Requests errors gracefully (e.g.,
with exponential backoff).
Related skills
More from google-deepmind/science-skills and the wider catalog.

foldseek-structural-search
Search for structurally similar proteins using 3D coordinate files against PDB, AlphaFold, and other databases.

gnomad-database
Query the Genome Aggregation Database (gnomAD) for variant frequencies, gene constraints, and structural variants.

gtex-database
Access RNA expression baselines and eQTL data from GTEx across 54 normal human tissues.

human-protein-atlas-database
Query protein expression levels, subcellular localization, and tissue distribution from the Human Protein Atlas.

interpro-database
Query InterPro's unified protein domain database to identify families, domains, and annotate genomes with GO terms.

jaspar-database
Query JASPAR database for transcription factor binding profiles and position weight matrices.