Metadata-Version: 2.4
Name: GenKI
Version: 0.1.0
Summary: GenKI
Home-page: https://github.com/yjgeno/GenKI
Author: Yongjian Yang, TAMU
Author-email: yjyang027@tamu.edu
License: MIT
Keywords: neural network,graph neural network,variational graph neural network,computational-biology,single-cell,gene knock-out,gene regulatory network
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: anndata>=0.8.0
Requires-Dist: matplotlib>=3.5.1
Requires-Dist: numpy>=1.21.6
Requires-Dist: pandas>=1.4.2
Requires-Dist: ray>=1.11.0
Requires-Dist: scanpy>=1.9.1
Requires-Dist: scipy>=1.8.0
Requires-Dist: statsmodels>=0.13.2
Requires-Dist: scikit_learn>=1.0.2
Requires-Dist: tqdm>=4.64.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
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# GenKI (Gene Knock-out Inference)
A VGAE (Variational Graph Auto-Encoder) based model to learn perturbation using scRNA-seq data. <br>
<span style="color:red;">New!</span> Data has been added. <br>
[Paper](https://doi.org/10.1093/nar/gkad450)
<br/>
<p align="center">
    <img src="logo.jpg" alt="drawing" width="300"/>
</p>
<br/>

### Prerequisites
Before installing GenKI, install [PyTorch](https://pytorch.org/get-started/locally/) and [PyTorch Geometric](https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html) matching your CUDA version.

### Install GenKI with `pip` (PyPI):
```shell
pip install GenKI
```

Or install from source:
```shell
pip install git+https://github.com/yjgeno/GenKI.git
```

Or clone and install manually:
```shell
git clone https://github.com/yjgeno/GenKI.git
cd GenKI
pip install .
```

Alternatively, use `conda` to set up the full environment:
```shell
conda env create -f environment.yml
conda activate ogenki
```
<br/>

#### Tutorial
Virtual KO experiment:<br> https://github.com/yjgeno/GenKI/blob/master/notebook/Example.ipynb <br>
