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.
Please refer to the documentation.
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
See the changelog.
Feel free to contact us by mail. If you found a bug, please use the issue tracker.
@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}
}