encode-ccres-database

Query ENCODE SCREEN cCREs by coordinates, accessions, and biosample filters.

2.7k|283|Updated May 13, 2026

Search Tags:#graphql #genomics #gwas #encode #gene expression #regulatory elements #biosample metadata

Ready to run

npx skills add https://github.com/google-deepmind/science-skills --skill encode-ccres-database

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: encode-ccres-database
Source: https://github.com/google-deepmind/science-skills/tree/main/skills/encode_ccres_database
Command: npx skills add https://github.com/google-deepmind/science-skills --skill encode-ccres-database

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Researchers need a fast way to find and contextualize human regulatory DNA elements (cCREs) and the experimental evidence behind them across assemblies and biosamples.

Core Features & Use Cases

cCRE discovery and ranking: Search cCREs by genomic coordinates, accessions, or CTCF signal ranges using the SCREEN GraphQL API.
Functional context retrieval: Fetch cCRE details (including max Z-scores across assays) and associated biosample assay information, with support for identifying high-confidence Type A biosamples.
Downstream biological linkage: Retrieve nearby genes, orthologous cCREs across assemblies, linked genes, ENTEx allelic imbalance annotations, gene expression (TPM/FPKM), and GWAS-related summaries.
Direct ENCODE Portal access: Run custom REST API queries for experiments and downloadable dataset metadata when SCREEN does not cover the needed object type.

Quick Start

Run a coordinate-based search for candidate cis-regulatory elements on chr11 from 5205263 to 5207263 and save the results to a JSON file in /tmp.

Frequently Asked Questions about encode-ccres-database

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

FAQPage Schema

How do I query ENCODE cCREs by genomic coordinates and biosample signals?▼

To query ENCODE cCREs by genomic coordinates, you provide the chromosome, start, and end positions along with assembly and biosample signal filters like CTCF ranges to the SCREEN GraphQL API, returning parsed JSON of matching regulatory elements.

Can I find nearby genes and GWAS summaries for candidate cis-regulatory elements?▼

Yes, you can retrieve nearby genes, linked genes, and GWAS-related summaries for candidate cis-regulatory elements by running downstream biological linkage queries that output parsed JSON for efficient extraction.

What is the best way to access ENCODE experiment metadata when SCREEN does not cover the object type?▼

The best way to access ENCODE experiment metadata not covered by SCREEN is to run custom REST API queries directly against the ENCODE Portal, retrieving downloadable dataset metadata and experiment details.

Do I need to use jq to parse ENCODE GraphQL API responses?▼

Using jq to parse ENCODE GraphQL API responses is recommended because the helper scripts output parsed JSON specifically designed for efficient jq-based extraction without loading entire HTTP responses into context.

How do I identify high-confidence Type A biosamples from ENCODE cCRE assay data?▼

You identify high-confidence Type A biosamples by applying biosample enrichment filters to the cCRE details and associated assay information, retrieving biosample metadata that supports functional context ranking.

Does querying orthologous cCREs across assemblies require specific accessions?▼

Querying orthologous cCREs across assemblies does not strictly require specific accessions; you can search by genomic coordinates or accessions to retrieve orthologous candidate cis-regulatory elements and ENTEx allelic imbalance annotations.