## Installation

CellART can be installed via two approaches: using pip or directly from the GitHub repository.

### Installing through pip
You can install the stable release of CellART directly from pip. First, ensure you have set up a compatible Python environment using `conda` or any other package manager. Then, execute the following commands:

```shell
$ conda create -n cellart python=3.10
$ conda activate cellart
$ pip install cellart
```

> **_NOTE:_**  Due to differences in GPU models and CUDA versions, you may need to manually reinstall PyTorch and Tensorflow to ensure compatibility. CellART relies heavily on GPU acceleration for efficient processing of large-scale spatial transcriptomics datasets.


### Installing from GitHub

```shell
# Clone the repository
$ git clone https://github.com/YangLabHKUST/CellART.git

# Navigate to the cloned directory
$ cd CellART

# Install the package
$ pip install .
```