Metadata-Version: 2.1
Name: scpca
Version: 0.2.0
Summary: Single-cell PCA.
Author: Harald Vohringer
Author-email: harald.voeh@gmail.com
Requires-Python: >=3.8.1,<3.11
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Provides-Extra: docs
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Requires-Dist: nbsphinx (==0.8.9) ; extra == "docs"
Requires-Dist: pyro-ppl (<1.8.4)
Requires-Dist: scanpy (>=1.8.2)
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Requires-Dist: torch (<2.0.0)
Description-Content-Type: text/markdown


# scPCA - A probabilistic factor model for single-cell data

![pypi](https://img.shields.io/pypi/v/scpca.svg)
![release workflow](https://github.com/sagar87/scPCA/actions/workflows/release.yaml/badge.svg)
![push workflow](https://github.com/sagar87/scPCA/actions/workflows/branch.yaml/badge.svg)

scPCA is a versatile matrix factorisation framework designed to analyze single-cell data across diverse experimental designs.

![scPCA schematic](https://github.com/sagar87/scPCA/blob/main/docs/scpca_schematic.png?raw=true)

*scPCA is a young project and breaking changes are to be expected.*

## Quick install

scPCA makes use `torch`, `pyro` and `anndata`. We highly recommend to run scPCA on a GPU device.

### Via Pypi

The easiest option to install `scpca` is throug Pypi. Simply type

```
$ pip install scpca
```


into your shell and hit enter.

* Free software: MIT license
* Documentation: https://sagar87.github.io/scPCA/index.html

## Credits

* Harald Vöhringer

