myuanz/slat

Spatially-Linked Alignment Tool

scSLAT: single cell spatial alignment tools

scSLAT package implements the SLAT (Spatial Linked Alignment Tool) 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

Tutorial of scSLAT is here, if you have any question please open an issue on github

Installation

Docker

Dockerfile of scSLAT is available at env/Dockerfile. You can also pull the docker image from here by :

docker push huhansan666666/slat:latest

Development

Installing scSLAT within a new conda environment is recommended.

For development purpose, clone this repo and install:

git clone [email protected]:gao-lab/SLAT.git
cd SLAT
pip install -e ".[torch]"
pip install -e ".[pyg,dev,doc]"

Install from PyPI (Ongoing)

Fist we create a clean environment and install scSLAT from PyPI:

We need install dependency torch before install pyg.

conda create -n scSLAT python=3.8 -y && conda activate scSLAT
pip install scSLAT[torch]
pip install scSLAT[pyg]

Install from Conda (Ongoing)

We plan to provide a conda package of scSLAT in the near future.

Reproduce results

1. Please follow the env/README.md to install all dependencies. Please checkout the repository to v0.1.0 before install scSLAT:

git checkout tags/v0.1.0
pip install -e '.'

2. Download and pre-process data follow the data/README.md
3. Whole benchmark and evaluation procedure can be found in /benchmark and /evaluation, respectively.
4. Every case study is recorded in the /case directory in the form of jupyter notebook.