Software for the manuscript "Optimal Transport Modeling Uncovers Spatial Domain Dynamics in Spatiotemporal Transcriptomics". First trial in wrapping a code pipeline using GitHub Copilot, inspired by Robert Langefeld from the Xiang Zhou Lab.
SpaDOT is an open-source computational method for identifying spatial domains and inferring their temporal dynamics across time points for spatiotemporal transcriptomics studies. Detailed documentation and tutorials are available at: https://marvinquiet.github.io/SpaDOT/.
Table of Contents
It is recommended to run SpaDOT on a GPU to achieve faster execution times.
SpaDOT requires the following:
- python (version 3.9 recommended)
- torch (v2.5.0)
- anndata (v0.9.1)
- scanpy (v1.9.8)
- numpy
- pandas
- wot
cuda toolkitandnvidia cudnnwhen using GPU resources, more information can be found here- torch_geometric, this package is dependent on torch version and cuda version.
Note: If using GPU resources, you might also need to install the CUDA Toolkit and NVIDIA cuDNN libraries. Detailed setup instructions can be found here. Please make sure to install a compatible version for PyTorch.
To fully leverage SpaDOT’s capabilities, installing R and the SPARK-X package is recommended for selecting spatially variable genes.
The most convenient way is to install with pip.
pip install SpaDOTTo upgrade to a newer release use the --upgrade flag.
pip install --upgrade SpaDOTFor more information, a detailed documentation on installation is provided here.
This project is covered under the MIT license.