Metadata-Version: 2.4
Name: scGCA
Version: 0.1.1
Summary: Single-Cell Genome-Wide Chromatin Accessibility
Home-page: https://github.com/ZengFLab/scGCA
Author: Feng Zeng
Author-email: zengfeng@xmu.edu.cn
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: dill==0.3.8
Requires-Dist: scanpy
Requires-Dist: pytorch-ignite
Requires-Dist: datatable
Requires-Dist: scipy
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: pandas
Requires-Dist: pyro-ppl
Requires-Dist: jax[cuda12]
Requires-Dist: pyfaidx
Requires-Dist: pyBigWig
Requires-Dist: biopython
Requires-Dist: leidenalg
Requires-Dist: python-igraph
Requires-Dist: networkx
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: fa2-modified
Requires-Dist: zuko
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# scGCA
 Genomewide chromatin accessibility for single-cell data.

## Installation
1. Create a virtual environment
```bash
conda create -n scGCA python=3.10 scipy numpy pandas scikit-learn && conda activate scGCA
```

2. Install [PyTorch](https://pytorch.org/get-started/locally/) following the official instruction. 
```bash
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126
```

3. Install scGCA
```bash
pip3 install scGCA
```

