Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding
SPACE (SPatial transcriptomics Analysis via Cell Embedding)
SPACE is implemented in Pytorch framework.
SPACE can be run on CPU devices, and running SPACE on GPU devices if available is recommended.
Please install Pytorch in advance by following the instructions on : https://pytorch.org/get-started/locally/
Please install PyTorch Geometric in advance by following the instructions on : https://pytorch-geometric.readthedocs.io/en/latest/install/installation.html
pip install space-srt
install the latest develop version
git clone https://github.com/zhangqf-lab/SPACE.git
cd SPACE
python setup.py install
A brief tutorial can be found here.(Still in progress)
If you use SPACE in your research, please cite our paper:
Li, Y., Zhang J., Gao, X., and Zhang, Q.C. Tissue module discovery in single-cell resolution spatial transcriptomics data via cell- cell interaction-aware cell embedding. Cell Systems 2024 (paper)