[](https://github.com/gao-lab/SLAT/stargazers)
[](https://pypi.org/project/scslat)
[](https://pepy.tech/project/scSLAT)
[](https://github.com/gao-lab/SLAT/actions/workflows/build.yml)
[](https://slat.readthedocs.io/en/latest/?badge=latest)
[](https://opensource.org/licenses/MIT)
# scSLAT: single cell spatial alignment tools
**scSLAT** package implements the **SLAT** (**S**patial **L**inked **A**lignment **T**ool) model to align single cell spatial omics data.
## Directory structure
```
.
├── scSLAT/ # Main Python package
├── env/ # Extra environment
├── data/ # Data files
├── evaluation/ # SLAT evaluation pipeline
├── benchmark/ # Benchmark pipeline
├── case/ # Case studies in paper
├── docs/ # Documentation files
├── resource/ # Other useful resource
├── pyproject.toml # Python package metadata
└── README.md
```
## [Tutorial](https://slat.readthedocs.io/en/latest/tutorials.html)
Tutorial of `scSLAT` is [here](https://slat.readthedocs.io/en/latest/tutorials.html), if you have any question please open an issue on github
<img src='docs/_static/imgalignment.gif' width='400'>
## Installation
### PyPI
> **Note**
> Installing `scSLAT` within a new [conda environment](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) is recommended.
> **Warning**
> Old NVIDIA driver may raise error.
First, we create a clean environment and install `scSLAT` from PyPI. Then we also need install dependencies for `pyg` manually via `install_pyg_dependencies`.
```bash
conda create -n scSLAT python=3.11 -y && conda activate scSLAT
pip install scSLAT
install_pyg_dependencies
```
### Docker
You can pull the docker image directly from [Docker Hub](https://hub.docker.com/repository/docker/huhansan666666/slat) or refer to the [`Dockerfile`](Dockerfile) to build it.
``` bash
docker pull huhansan666666/slat:latest
```
### Development version
For development purpose, clone this repo and install:
```bash
git clone git@github.com:gao-lab/SLAT.git && cd SLAT
pip install -e ".[dev,docs]"
install_pyg_dependencies
```
## Reproduce manuscript results
1. Please follow the [`env/README.md`](env/README.md) to install all dependencies. Please checkout the repository to v0.2.1 before install `scSLAT`.
2. Download and pre-process data follow the [`data/README.md`](data/README.md).
3. Whole benchmark and evaluation procedure can be found in [`/benchmark`](benchmark/README.md) and [`/evaluation`](evaluation/README.md), respectively.
4. Every case study is recorded in the [`/case`](case/README.md) directory in the form of jupyter notebook.
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