Skills

Encode Ccres Database

Query the ENCODE Registry of cis-Regulatory Elements (cCREs) via the SCREEN GraphQL...

Install

npx skills add google-deepmind/science-skills --skill encode-ccres-database -g -a claude-code -y
Category
Engineering
Updated
12d ago
License
Apache-2.0
Context cost
Mediumabout 1,622 tokens
Runs scripts
Yes, review before use

What it does

Query the ENCODE Registry of cis-Regulatory Elements (cCREs) via the SCREEN GraphQL API, or make custom queries to the ENCODE Portal REST API for experiments and files (ChIP-seq peaks, etc.). Use when you want to query regulatory annotations or raw experimental data across human cell types.

ENCODE Database Skill

This skill allows you to query the ENCODE Registry of cCREs (candidate cis-Regulatory Elements) via the SCREEN GraphQL API. It helps identify functional non-coding DNA elements (like Promoters, Enhancers, and insulators) by analyzing biochemical signatures (DNase, H3K4me3, H3K27ac, CTCF).

Prerequisites

  1. uv: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH.
  2. User Notification: If .licenses/encode_ccres_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.encodeproject.org/help/rest-api/, then (2) create the file recording the notification text and timestamp.

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.
  • Parsing Output: Do NOT use cat to read the entire JSON output file into context, as it can be extremely large. You MUST use jq to efficiently parse and extract relevant fields.
  • Notification: If this skill is used, ensure this is mentioned in the output.

Quick Start

# Search cCREs by coordinates
uv run scripts/screen_api.py search --chromosome chr11 \
  --start 5205263 --end 5207263 \
  --output /tmp/search.json

# Get details for a specific cCRE
uv run scripts/screen_api.py details EH38E2941922 \
  --output /tmp/details.json

All subcommands write JSON to disk. Always save output in a temporary location like /tmp/.

Identifying High-Confidence ("Type A") Biosamples

Biosamples in ENCODE are often categorized by their data completeness. "Type A" (or high-confidence) biosamples are those that have experimental data for all four core epigenetic markers: DNase, H3K4me3, H3K27ac, and CTCF.

Read the whole SKILL.md on GitHub

More in Engineering