ensembl-annotation

Query Ensembl's REST API for variant effects, regulatory features, and gene annotations.

26|5|Updated Mar 8, 2026
One-click install
npx skills add https://github.com/ammawla/encode-toolkit --skill ensembl-annotation
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ensembl-annotation
Source: https://github.com/ammawla/encode-toolkit/tree/main/plugin/skills/ensembl-annotation
Command: npx skills add https://github.com/ammawla/encode-toolkit --skill ensembl-annotation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, json, and includes scripts (resource) components.

What problem does it solve?

This Skill addresses the challenge of annotating genetic variants and gene information efficiently using Ensembl's comprehensive API. It simplifies tasks such as querying variant effects, regulatory features, coordinate conversions, and gene cross-references from Ensembl's extensive genomic databases.

Core Features & Use Cases

  • Variant Effect Prediction (VEP): Annotate variants with their predicted impact, regulatory overlap, and pathogenicity scores using Ensembl's VEP service. For example, assess the consequence of a SNP on gene function or regulatory regions.
  • Regulatory Feature Overlap: Identify regulatory elements like enhancers, promoters, or CTCF sites within specific genomic regions, aiding in the interpretation of non-coding variants.
  • Coordinate Liftover: Convert genomic coordinates between GRCh37 and GRCh38, ensuring compatibility with diverse datasets and annotations.
  • Gene Lookup & Cross-References: Retrieve detailed gene metadata and cross-reference identifiers between Ensembl IDs and external databases, supporting downstream functional analyses.
  • Phenotype Associations: Access disease and phenotype links to genomic regions or genes, supporting genotype-phenotype correlation efforts.

A typical application would involve annotating GWAS variants with predicted effects, regulatory context, and gene relationships to interpret their biological significance efficiently.

Quick Start

Query the Ensembl REST API to get annotations for a specific variant or gene and interpret the data to understand the variant’s potential functional impact.

Frequently Asked Questions about ensembl-annotation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I annotate genetic variants with Ensembl using a REST API?

To annotate genetic variants with Ensembl, you query the REST API to retrieve variant effect predictions, consequence impacts, and pathogenicity scores. This provides programmatic access to assess variant functional impact and regulatory overlap for genomics interpretation.

What is the best way to convert genomic coordinates between GRCh37 and GRCh38?

The best way to convert genomic coordinates between GRCh37 and GRCh38 is using the coordinate liftover functionality. It queries the Ensembl API to remap coordinates, ensuring dataset compatibility and accurate cross-reference annotations across different genome assemblies.

Can I identify regulatory features like enhancers and promoters within a genomic region?

Yes, you can identify regulatory features like enhancers, promoters, and CTCF sites within a genomic region. This Skill queries the Ensembl regulatory API to detect overlapping regulatory elements, aiding in the interpretation of non-coding genetic variants.

Does this Ensembl annotation tool require complex bioinformatics software to run?

No, this Ensembl annotation tool requires minimal setup and does not need complex bioinformatics software. It relies only on standard Python requests and json libraries to query the Ensembl REST API, integrating seamlessly into existing bioinformatics pipelines.

How do I retrieve gene metadata and cross-references from Ensembl IDs?

You retrieve gene metadata and cross-references by querying the Ensembl API with Ensembl gene IDs. This provides detailed gene information and maps identifiers to external databases, supporting downstream functional analysis and genotype-phenotype correlation.