Metadata-Version: 2.1
Name: pychromvar
Version: 0.0.4
Summary: A python package for chromVAR
Author-email: Zhijian Li <lzj1769@gmail.com>
Requires-Python: >= 3.8
Description-Content-Type: text/markdown
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Intended Audience :: Science/Research
Requires-Dist: scikit-learn
Requires-Dist: anndata
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: mudata
Requires-Dist: scanpy
Requires-Dist: muon
Requires-Dist: biopython
Requires-Dist: MOODS-python
Requires-Dist: pysam
Requires-Dist: wget
Project-URL: Documentation, https://pychromvar.readthedocs.io/en/latest/
Project-URL: Source, https://github.com/lzj1769/pychromVAR

[![Stars](https://img.shields.io/github/stars/lzj1769/pychromVAR?logo=GitHub&color=yellow)](https://github.com/lzj1769/pychromVAR/stargazers)
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# pychromVAR 

pychromVAR is a python package for inferring transcription factor binding variability from scATAC-seq data by implmenting the algorithm proposed in [chromVAR](https://github.com/GreenleafLab/chromVAR). It is built on [anndata](https://anndata.readthedocs.io/en/latest/) and [mudata](https://mudata.readthedocs.io/en/latest/) therefore can work seamlessly with [Scanpy](https://scanpy.readthedocs.io/en/stable/index.html) and [Muon](https://gtca.github.io/muon/) pipeline. 

For more methodological details, please refer to the [paper](https://www.nature.com/articles/nmeth.4401). 

# Installation

The quickest and easiest way to get pychromvar is to to use pip:

```shell
pip install pychromvar
```

# Tutorial

You can find [here](https://pychromvar.readthedocs.io/en/latest/notebooks/multimodal_pbmc_3k.html) a tutorial how to use pychromVAR combined with Muon to analysis multimodal single-cell PBMC data.



