README.md

---
title: DeepVRegulome
emoji: 🧬
colorFrom: green
colorTo: blue
sdk: gradio
sdk_version: 5.33.0
app_file: app.py
pinned: true
license: cc-by-nc-4.0
models:
  - duttaprat/DeepVRegulome
tags:
  - biology
  - bioinformatics
  - genomics
  - regulatory-genomics
  - variant-effect-prediction
  - dnabert
  - transcription-factors
  - splice-sites
short_description: 464 DNABERT models for regulatory variant effect prediction
---

# DeepVRegulome Demo

<p align="center">
  <a href="https://github.com/DavuluriLab/DeepVRegulome">
    <img src="https://img.shields.io/badge/GitHub-Repo-181717?logo=github" alt="GitHub">
  </a>
  <a href="https://huggingface.co/duttaprat/DeepVRegulome">
    <img src="https://img.shields.io/badge/%F0%9F%A4%97-Models-yellow" alt="Hugging Face Models">
  </a>
  <a href="https://pypi.org/project/deepvregulome/">
    <img src="https://img.shields.io/pypi/v/deepvregulome?color=blue" alt="PyPI">
  </a>
  <a href="https://pepy.tech/projects/deepvregulome">
    <img src="https://static.pepy.tech/personalized-badge/deepvregulome?period=total&units=INTERNATIONAL_SYSTEM&left_color=BLACK&right_color=GREEN&left_text=downloads" alt="PyPI Downloads">
  </a>
  <a href="https://arxiv.org/abs/2511.09026">
    <img src="https://img.shields.io/badge/arXiv-2511.09026-b31b1b" alt="arXiv">
  </a>
  <a href="https://deepvregulome.streamlit.app">
    <img src="https://img.shields.io/badge/Full%20App-Streamlit-ff4b4b" alt="Streamlit">
  </a>
  <a href="https://creativecommons.org/licenses/by-nc/4.0/">
    <img src="https://img.shields.io/badge/license-CC--BY--NC--4.0-green" alt="License">
  </a>
</p>

<p align="center">
  <strong>Interactive regulatory variant-effect prediction using 464 fine-tuned DNABERT models</strong>
</p>

DeepVRegulome is a deep-learning framework for predicting the functional impact
of short genomic variants in non-coding regulatory regions.

The framework uses fine-tuned
[DNABERT](https://github.com/jerryji1993/DNABERT) models trained on ENCODE
ChIP-seq data to predict transcription-factor binding, histone-mark enrichment,
splice-site activity, and allele-specific regulatory effects.

This Hugging Face Space provides a lightweight interactive demonstration of the
DeepVRegulome prediction framework.

## Model Coverage

DeepVRegulome contains **464 fine-tuned DNABERT models**:

- **458 transcription-factor binding models**
- **4 histone-modification models**
- **1 splice-acceptor model**
- **1 splice-donor model**

The transcription-factor and histone models were trained using regulatory
regions derived from ENCODE ChIP-seq experiments.

## Features

### Binding Prediction

Select a transcription-factor or histone-mark model and enter a DNA sequence to
estimate its predicted binding or regulatory activity.

The interface accepts a standard **301 bp DNA sequence**, although shorter or
longer sequences may also be processed.

### Variant Effect Scoring

Compare reference and alternate DNA sequences to estimate how a genomic variant
changes predicted regulatory activity.

The output includes:

- Reference-allele probability
- Alternate-allele probability
- Change in predicted binding
- Log-odds-ratio variant-effect score
- Predicted gain or loss of regulatory activity

### Splice-Site Prediction (Added in PyPi package, Will be added in the Space)

The splice-acceptor and splice-donor models can be used to evaluate sequence
changes near exon–intron boundaries and identify variants that may alter
predicted splice-site activity.

## Using the Demo

1. Select **Binding Prediction** or **Variant Effect Scoring**.
2. Choose a model from the model menu.
3. Paste the required DNA sequence or sequences.
4. Click **Predict**.
5. Review the predicted probabilities and variant-effect results.

A random DNA-sequence generator is also available for quickly testing the
interface.

## Python Package

Install DeepVRegulome from PyPI:

```bash
pip install deepvregulome
```

## Links

- **Paper**: [arXiv:2511.09026](https://arxiv.org/abs/2511.09026)
- **Models**: [duttaprat/DeepVRegulome](https://huggingface.co/duttaprat/DeepVRegulome)
- **Code**: [GitHub](https://github.com/DavuluriLab/DeepVRegulome)
- **PyPI**: `pip install deepvregulome`
- **Full Web App**: [deepvregulome.streamlit.app](https://deepvregulome.streamlit.app)