SpaDOT 1.0.4b2

Package for paper: Optimal transport modeling uncovers spatial domain dynamics in spatiotemporal transcriptomics

SpaDOT

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

• System Requirements
• Installation
• License
• Citing Our Work

System Requirements

Hardware requirements

It is recommended to run SpaDOT on a GPU to achieve faster execution times.

Dependencies

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 toolkit and nvidia cudnn when 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.

Installation

The most convenient way is to install with pip.

pip install SpaDOT

To upgrade to a newer release use the --upgrade flag.

pip install --upgrade SpaDOT

For more information, a detailed documentation on installation is provided here.

License

This project is covered under the MIT license.

Citing Our Work