biolord - biological representation disentanglement

A deep generative framework for disentangling known and unknown attributes in single-cell data.

We assume partial supervision over known attributes (categorical or ordered) along with single-cell measurements. Given the partial supervision biolord finds a decomposed latent space, and provides a generative model to obtain single-cell measurements for different cell states.

For more details read our pubication in Nature Biotechnology.

The biolord pipeline

Getting started

Please refer to the documentation.

Installation

There are several alternative options to install biolord:

Install the latest release of biolord from PyPI:
```
pip install biolord
```

Install the latest development version:

pip install git+https://github.com/nitzanlab/biolord.git@main

Release notes

See the changelog.

Contact

Feel free to contact us by mail. If you found a bug, please use the issue tracker.

Citation

@article{piran2024disentanglement,
  title={Disentanglement of single-cell data with biolord},
  author={Piran, Zoe and Cohen, Niv and Hoshen, Yedid and Nitzan, Mor},
  journal={Nature Biotechnology},
  pages={1--6},
  year={2024},
  publisher={Nature Publishing Group US New York}
}

nitzanlab / biolord