Skip to content
forked from theislab/DRVI

Unsupervised Deep Disentangled Representation of Single-Cell Omics

License

Notifications You must be signed in to change notification settings

maarten-devries/DRVI

 
 

Repository files navigation

DRVI

Build Tests Documentation Python Version

Unsupervised Deep Disentangled Representation of Single-Cell Omics

DRVI concept

Getting started

Please refer to the documentation. In particular, the

System requirements

We recommend running DRVI on a recent Linux distribution. DRVI is actively tested on the latest LTS version of Ubuntu (currently 24.04 LTS).

For optimal performance, we highly recommend using a GPU with CUDA capabilities. While CPU-based systems are supported, GPU-powered systems are strongly recommended for optimal performance.

Installation

You need to have Python 3.10, 3.11, or 3.12 installed on your system. If you don't have Python installed, we recommend installing Mambaforge.

There are several options to install drvi:

  1. Install the latest release of drvi-py from PyPI, which should take around two minutes:
pip install drvi-py
  1. Install the latest development version:
pip install git+https://github.com/theislab/drvi.git@main

Please be sure to install a version of PyTorch that is compatible with your GPU. Dependencies are installed automatically, please take a look at the versions for different dependencies in pyproject.toml if needed.

Release notes

See the changelog.

Contact

If you found a bug, please use the issue tracker.

Citation

If DRVI is helpful in your research, please consider citing the following paper:

Moinfar, A. A. & Theis, F. J. Unsupervised deep disentangled representation of single-cell omics. bioRxiv 2024.11.06.622266 (2024) doi:10.1101/2024.11.06.622266.

Reproducibility

Code, notebooks, and instructions to reproduce the results from the paper are available at the reproducibility repository.

About

Unsupervised Deep Disentangled Representation of Single-Cell Omics

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 100.0%