# jaspar-database

Queries the JASPAR database for transcription factor binding profiles. Useful when fetching PFM or PWM matrices and converting gene names into stable matrix IDs.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 2100 installs · ★ 3329
- Author: google-deepmind
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/google-deepmind/science-skills/tree/HEAD/skills/jaspar_database/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/jaspar-database

## What it does

The skill queries the JASPAR database through a bundled Python wrapper via `uv`. It retrieves raw Position Frequency Matrices (PFMs) and computes log-odds Position Weight Matrices (PWMs). The tool also predicts binding profiles from protein sequences and exports results in formats such as `meme`, `transfac`, `yaml`, and `json`.

The wrapper automatically enforces JASPAR rate limits. It breaks genomic regions larger than 100,000 bp into chunks so requests remain within API limits.

Running a motif lookup directly with a gene name fails. You must resolve symbols like `JUN` to a Matrix ID first using `resolve_tf_id` with an explicit `--tax-id`. JASPAR reports potential binding rather than tissue-specific chromatin availability, and it cannot predict the effects of specific protein mutations.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add google-deepmind/science-skills --skill jaspar-database -a claude-code
```
```bash
npx skills add google-deepmind/science-skills --skill jaspar_database -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/jaspar_database/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/jaspar_database/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add google-deepmind/science-skills --skill jaspar_database -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/jaspar_database/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add google-deepmind/science-skills --skill jaspar_database -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/jaspar_database/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install google-deepmind/science-skills jaspar_database
```

2. **Manually: put the files in place**
- File: `.github/skills/jaspar_database/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add google-deepmind/science-skills --skill jaspar_database -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/google-deepmind/science-skills --path skills/jaspar_database
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/jaspar_database/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add google-deepmind/science-skills --skill jaspar_database -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/google-deepmind/science-skills/tree/HEAD/skills/jaspar_database/SKILL.md

## When to use it
- resolve gene symbols to stable JASPAR Matrix IDs
- retrieve Position Frequency Matrices and calculate log-odds PWMs
- export motif profiles to MEME or TRANSFAC formats
- infer binding matrix profiles from protein sequences

## Example prompts
- Resolve the JASPAR Matrix ID for human transcription factor JUN using tax-id 9606
- Fetch the PFM motif for matrix MA0488.2 in meme format
- Calculate the PWM for matrix MA0488.2 with a pseudocount of 0.1

## Source text · SKILL.md · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 0c4d640f5d6e35ee.

BEGIN THIRD-PARTY FILE 0c4d640f5d6e35ee
````text
---
name: jaspar-database
description: >
    Query the JASPAR database for Transcription Factor (TF) binding profiles.
    Use when retrieving Position Frequency Matrices (PFMs) or Position Weight
    Matrices (PWMs) for specific TFs, resolving gene symbols to JASPAR Matrix
    IDs, or getting TF metadata. Supports multiple output formats (MEME,
    TRANSFAC, PFM, JASPAR, YAML).
---

# JASPAR Skill

JASPAR is the definitive open-access database for Transcription Factor (TF)
binding profiles, stored as Position Frequency Matrices (PFMs).

Use this skill to map abstract sequence motifs or genomic regions to specific
biological regulators (e.g., "what TFs bind here?" or "what is the motif for
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/jaspar_database_LICENSE.txt does not
    already exist in the workspace root directory then (1) prominently notify
    the user to check the terms at https://jaspar.elixir.no/ and
    https://jaspar.elixir.no/api/, then (2) create the file recording the
    notification text and timestamp.

## Core Rules

**CRITICAL**: You MUST respect the JASPAR API Terms of Use by adhering to the
following:

-   **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.
-   **Maximum API Window Size**: The genomic window for a single API query MUST
    NOT exceed 100,000 bp (100kb). The `jaspar_api.py` script automatically
    chunks larger requests for you to bypass this limitation when querying
    larger regions.
-   **Valid Matrix IDs**: `get_tf_motif`, `get_tf_metadata`, and `get_tf_pwm`
    require a stable JASPAR Matrix ID (e.g., `MA0488.2`). If a user provides a
    gene symbol (e.g., `JUN`), you must resolve it first using `resolve_tf_id`.
-   **Taxonomy Required**: Resolving IDs requires a `tax_id` to ensure targeted
    searches. Common IDs: Human=9606, Mouse=10090.
-   **Notification**: If this skill is used, ensure this is mentioned in the
    output.

## Utility Scripts

Run all commands using the bundled Python script:

### 1. Resolve TF to Matrix ID

Maps a transcription factor name to a stable Matrix ID. Required step before
fetching motifs if only a gene name is provided.

```bash
uv run scripts/jaspar_api.py resolve_tf_id --name "JUN" --tax-id 9606
```

### 2. Get TF Motif (PFM)

Retrieves the raw Position Frequency Matrix for a specific TF. Supports
`--format` flag.

```bash
uv run scripts/jaspar_api.py get_tf_motif --matrix-id "MA0488.2"
````
END THIRD-PARTY FILE 0c4d640f5d6e35ee

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