gi-enhancer

Predict enhancer activity in FASTA sequences via the Genomic Intelligence DeepSTARR API.

1.1k|257|Updated Feb 25, 2026
One-click install
npx skills add https://github.com/ClawBio/ClawBio --skill gi-enhancer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gi-enhancer
Source: https://github.com/ClawBio/ClawBio/tree/main/skills/gi-enhancer
Command: npx skills add https://github.com/ClawBio/ClawBio --skill gi-enhancer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests.

What problem does it solve?

Running DeepSTARR-style enhancer prediction locally requires Keras, GPU hardware, and tokenization expertise. This Skill removes that barrier by sending a FASTA sequence to the hosted Genomic Intelligence API and returning per-window enhancer activity scores in about one second, with full reproducibility artifacts.

Core Features & Use Cases

  • Hosted DeepSTARR inference: POSTs a single-record FASTA (50–500,000 bp) to /v1/tasks/enhancer/predict and receives per-window activity scores without local model setup.
  • Structured outputs: Generates a Markdown report, a full JSON result including rate-limit metadata, and a reproducibility directory with command.sh and environment.json.
  • Local validation: Rejects out-of-bounds sequence lengths before spending an API request and warns when input is shorter than the model's 249 bp context window.
  • Use Case: A researcher studying the Drosophila eve locus runs the bundled demo to confirm developmental enhancer signal, then submits their own candidate cis-regulatory regions for scoring.

Quick Start

Ask the agent to predict enhancer activity for your FASTA file using gi-enhancer with your GI_API_KEY configured, or run the bundled Drosophila eve demo.

Frequently Asked Questions about gi-enhancer

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

FAQPage Schema
How do I predict enhancer activity from a FASTA sequence?▼

Run the gi_enhancer.py CLI with --input pointing to a single-record FASTA file and --output for the results directory. The skill posts the sequence to the Genomic Intelligence /v1/tasks/enhancer/predict endpoint and writes a Markdown report plus JSON result with per-window activity scores.

What is DeepSTARR and what sequences does it work on?▼

DeepSTARR is a deep learning model trained on Drosophila S2 cell STARR-seq data to predict enhancer activity from DNA sequence. Scores for mammalian sequences remain informative as relative rankings, but absolute values are calibrated for fly chromatin.

Does gi-enhancer require an API key?▼

Yes, remote inference requires a Genomic Intelligence partner key supplied via the --api-key flag or the GI_API_KEY environment variable. A shared hackathon-tier key ships in the repo's .env.example, and individual keys can be requested from contact@genomicintelligence.ai.

What sequence length limits apply to enhancer prediction?▼

The API accepts sequences from 50 to 500,000 bp after whitespace stripping, enforced as a 422 validation error. The model context window is 249 bp, so shorter inputs are padded; the skill warns when input falls below that window.

Is it safe to upload patient genomic data to this API?▼

No, identifiable patient data should not be submitted without an appropriate data-use agreement, since sequences are uploaded to the hosted Genomic Intelligence API. The skill is intended for research and development use, not clinical or diagnostic decisions.