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The Python package for a spatial multi-omics integration algorithm called SpaMV.

Project description

SpaMV: An interpretable spatial multi-omics data integration and dimension reduction algorithm

Installation

  1. Create and activate a conda environment with python 3.12
conda env create spamv python==3.12
conda activate spamv
  1. Before you install our package, please make sure you have installed the pyg-lib package.
# For CPU users
pip install pyg-lib -f https://data.pyg.org/whl/torch-2.6.0+cpu.html
# For GPU users
pip install pyg-lib -f https://data.pyg.org/whl/torch-2.6.0+cuda118.html
  1. Then you could install our package as follows:
pip install spamv

Tutorial

We provide two jupyter notebooks (Tutorial_simulation.ipynb and Tutorial_realworld.ipynb) to reproduce the results in our paper. Before you run them, please make sure that you have downloaded the simulated data and/or real-world data from our Zenodo repositoy.

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