Metadata-Version: 2.1
Name: regLM
Version: 0.0.post1.dev60+ge201547.d20240725
Summary: Add a short description here!
Home-page: https://https://github.com/Genentech/regLM
Author: Genentech, Inc.
Author-email: lal.avantika@gene.com
License: MIT
Project-URL: Documentation, https://genentech.github.io/regLM/
Project-URL: Source, https://github.com/Genentech/regLM
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Requires-Python: >=3.8
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
License-File: LICENSE.txt
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: torch<2.0
Requires-Dist: torchmetrics
Requires-Dist: pytorch-lightning<2.0
Requires-Dist: bpnet-lite<0.6.0
Requires-Dist: captum==0.5.0
Requires-Dist: enformer_pytorch<0.8.7
Provides-Extra: testing
Requires-Dist: setuptools; extra == "testing"
Requires-Dist: pytest; extra == "testing"
Requires-Dist: pytest-cov; extra == "testing"


# regLM
regLM is a toolkit for training hyenaDNA-based autoregressive language models on DNA sequences and generating novel regulatory elements.

![regLM schematic](fig1.png)

## Documentation

[Documentation](https://genentech.github.io/regLM)

## Tutorials

[Tutorials](tutorials)

## Installation

### 1. Install HyenaDNA
To use regLM, first install HyenaDNA from GitHub following the instructions: https://github.com/HazyResearch/hyena-dna

### 2. Install regLM
```
git clone https://github.com/Genentech/regLM.git
cd regLM
pip install .
```

## Preprint

https://www.biorxiv.org/content/10.1101/2024.02.14.580373

Code used to perform the experiments in the regLM paper, along with trained model weights and synthetic sequences, are available at [Zenodo](https://doi.org/10.5281/zenodo.10669334).
