External and simple implementation of scVI. This repository shows a minimal implementation of the scVI model using scvi-tools in an externally deployed package.
This package was initialized using the cookicutter-scverse template. We advise all external projects to use the cookicutter template.
Please refer to the documentation. In particular, the
You need to have Python 3.8 or newer installed on your system. If you don't have Python installed, we recommend installing Mambaforge.
There are several alternative options to install simple-scvi:
- Install the latest development version:
pip install git+https://github.com/adamgayoso/simple-scvi.git@mainSee the changelog.
For questions and help requests, you can reach out in the scverse discourse. If you found a bug, please use the issue tracker.
@article{gayoso2022python,
title={A Python library for probabilistic analysis of single-cell omics data},
author={Gayoso, Adam and Lopez, Romain and Xing, Galen and Boyeau, Pierre and Valiollah Pour Amiri, Valeh and Hong, Justin and Wu, Katherine and Jayasuriya, Michael and Mehlman, Edouard and Langevin, Maxime and others},
journal={Nature biotechnology},
volume={40},
number={2},
pages={163--166},
year={2022},
publisher={Nature Publishing Group US New York}
}