Metadata-Version: 2.4
Name: SpaMV
Version: 1.0.21
Summary: The Python package for a spatial multi-omics integration algorithm called SpaMV.
Author-email: Yang Liu <yangliu1214@hkbu.edu.hk>
License-Expression: MIT
Project-URL: Homepage, https://github.com/enderlogic/SpaMV
Project-URL: Issues, https://github.com/enderlogic/SpaMV/issues
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: pyro-ppl
Requires-Dist: scanpy
Requires-Dist: torch_geometric
Requires-Dist: squidpy==1.6.2
Requires-Dist: dask[dataframe]==2024.11.2
Requires-Dist: numpy<2.3
Requires-Dist: rpy2
Requires-Dist: scikit-misc

# 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
```

2) 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
```

3) 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.
