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Jaspar Database

Google DeepMindOfficialPublished by Google DeepMind

  • Skill
  • Tool integration
  • Science and research
  • Apache-2.0
  • Low risk
  • Has scripts

From the author

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).
— the description by Google DeepMind

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The jaspar-database skill provides a structured interface to interact with the JASPAR database, a resource for transcription factor (TF) binding profiles. It enables researchers to retrieve Position Frequency Matrices (PFMs), Position Weight Matrices (PWMs), and metadata for specific transcription factors. The skill includes helper scripts to resolve gene symbols to stable JASPAR Matrix IDs, convert motifs into various formats like MEME or TRANSFAC, and infer profiles from protein sequences, all while adhering to API usage guidelines.

What it does

  • Resolves gene symbols to stable JASPAR Matrix IDs using taxonomy identifiers.
  • Retrieves raw Position Frequency Matrices (PFMs) for specific transcription factors.
  • Converts PFMs into log-odds Position Weight Matrices (PWMs).
  • Fetches detailed metadata including TF class, family, and external database links.
  • Supports multiple output formats including MEME, TRANSFAC, PFM, and YAML.
  • Infers potential JASPAR matrix profiles from raw protein sequences.

When to use it

  • When you need to identify the binding motif for a specific transcription factor.
  • When you have a gene symbol and need to find its corresponding JASPAR Matrix ID.
  • When you require TF binding data in specific formats like MEME or TRANSFAC for downstream analysis.
  • When you need to convert a PFM into a PWM for scoring sequence motifs.

Advantages

  • Automated handling of API rate limits and request chunking.
  • Standardized workflow for resolving biological identifiers to database-specific IDs.
  • Supports a wide range of standard bioinformatics output formats.
  • Provides built-in tools for common motif transformations and sequence-based inference.

Usage examples

“Find the JASPAR Matrix ID for the human JUN transcription factor.”
The agent uses the resolve_tf_id command with tax-id 9606 to return the stable Matrix ID for JUN.
“Get the MEME format motif for matrix MA0488.2.”
The agent executes the get_tf_motif command with the specified matrix ID and the --format meme flag.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/google-deepmind/jaspar-database/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip jaspar-database.zip -d .agents/skills

Documentation by Google DeepMind

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.

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.

uv run scripts/jaspar_api.py get_tf_motif --matrix-id "MA0488.2"
uv run scripts/jaspar_api.py get_tf_motif --matrix-id "MA0488.2" --format meme
3. Get TF Metadata

Retrieves TF class, family, and links to external databases (e.g., UniProt). Supports --format flag.

uv run scripts/jaspar_api.py get_tf_metadata --matrix-id "MA0488.2"
uv run scripts/jaspar_api.py get_tf_metadata --matrix-id "MA0488.2" --format yaml
4. Compute PWM (Position Weight Matrix)

Fetches the PFM for a matrix and converts it to log-odds scores (PWM).

uv run scripts/jaspar_api.py get_tf_pwm --matrix-id "MA0488.2"
uv run scripts/jaspar_api.py get_tf_pwm --matrix-id "MA0488.2" --pseudocount 0.1
5. Infer Matrix from Protein Sequence

Infers potential JASPAR matrix profiles from a raw transcription factor protein sequence.

uv run scripts/jaspar_api.py infer_from_sequence --sequence "QAQLLPSHHVG"
6. Get TF Flexible Model (TFFM)

Retrieves metadata for a JASPAR TF Flexible Model. (Note: The JASPAR TFFM endpoints occasionally experience 500 Internal Server errors).

uv run scripts/jaspar_api.py get_tffm --tffm-id "TFFM0001.1"
Output Formats

The get_tf_motif and get_tf_metadata commands accept an optional --format flag. Supported formats: json (default), jsonp, jaspar, meme, transfac, pfm, yaml.

Anti-Patterns

  • DON'T pass gene symbols (e.g., JUN) to get_tf_motif. You must pass the MA... Matrix ID.

  • DON'T forget the --tax-id when resolving a TF name.

  • DON'T use this skill for determining tissue-specific epigenetic availability (JASPAR shows potential binding, not actual tissue expression context).

  • DON'T use this skill to model how a specific protein mutation affects binding.

Files

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python

Security

What our scanner noticed· Low risk

  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
Google DeepMind
Publisher
Google DeepMind (Official)
Source
google-deepmind/science-skills · skills/jaspar_database · commit 4de6786
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download jaspar-database.zip