# Encode Ccres Database

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

- Repository: https://github.com/google-deepmind/science-skills (3377 stars)
- Category: Engineering
- License: Apache-2.0
- Last updated: 2026-10-23
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add google-deepmind/science-skills --skill encode-ccres-database -g -a claude-code -y`
Codex: `npx skills add google-deepmind/science-skills --skill encode-ccres-database -g -a codex -y`
Cursor: `npx skills add google-deepmind/science-skills --skill encode-ccres-database -g -a cursor -y`
Gemini CLI: `npx skills add google-deepmind/science-skills --skill encode-ccres-database -g -a gemini-cli -y`

## Description

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.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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

```bash
# 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**.

The rest: https://github.com/google-deepmind/science-skills/blob/HEAD/skills/encode_ccres_database/SKILL.md