Metadata-Version: 2.1
Name: vipcca
Version: 0.2.6
Summary: single cell integration
Home-page: https://github.com/jhu99/vipcca
Author: Jialu Hu
Author-email: jialuhu@umich.edu
License: MIT
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: scanpy
Requires-Dist: tensorflow (==2.4.0)
Requires-Dist: anndata
Requires-Dist: scipy
Requires-Dist: pandas
Requires-Dist: seaborn
Requires-Dist: keras
Requires-Dist: python-igraph
Requires-Dist: louvain
Requires-Dist: h5py
Requires-Dist: future

# VIPCCA

 [![Documentation Status](https://readthedocs.org/projects/vipcca/badge/?version=latest)](https://vipcca.readthedocs.io/en/latest/?badge=latest) ![PyPI](https://img.shields.io/pypi/v/vipcca?color=blue) [![Downloads](https://pepy.tech/badge/vipcca)](https://pepy.tech/project/vipcca) ![GitHub Repo stars](https://img.shields.io/github/stars/jhu99/vipcca?color=yellow)

### Installation

- Create conda environment

  ```shell
  $ conda create -n vipcca python=3.8
  $ conda activate vipcca
  ```

- Install VIPCCA from pypi

  ```shell
  $ pip install vipcca
  ```

- Alternatively, install the develop version of VIPCCA from GitHub source code

  ```shell
  $ git clone https://github.com/jhu99/vipcca.git
  $ cd ./vipcca/
  $ python -m pip install .
  ```

**Note**: Please make sure your python version >= 3.7, and install tensorflow-gpu if GPU is available on your your machine.

### Usage of vipcca

For a quick start, please first download our test [data](http://141.211.10.196/result/test/papers/vipcca/data.tar.gz), then follow our guide about the usage of VIPCCA in the [**Tutorial and Documentation**](https://vipcca.readthedocs.io/en/latest/) pages.





