Installation

Install by PyPi

Step 1:

Prepare conda environment for SOAPy:

conda create -n SOAPy_st python=3.9
conda activate SOAPy_st

Step 2:

Install SOAPy using pip:

pip install SOAPy_st

Install by github

Download the file from github:

cd SOAPy_st
python setup.py build
python setup.py install

Requirements of SOAPy

Those will be installed automatically when using pip.

anndata==0.9.1
ctxcore==0.2.0
esda==2.4.3
geopandas==0.14.3
libpysal==4.8.1
networkx==2.8.6
numba==0.60.0
opencv-python==4.8.1.78
pyscenic==0.12.1
s-dbw==0.4.0
shapely==2.0.3
scanpy==1.10.3
scikit-image==0.19.3
scikit-learn==1.1.2
scikit-misc==0.3.1
scipy==1.13.1
seaborn==0.13.2
statsmodels==0.13.2
tensorly==0.8.1
torch==1.12.0
torchaudio==0.12.0
torchvision==0.13.0
matplotlib
numpy
pandas
tqdm

If you want to use unsupervised spatial domain partitioning methods, please refer to the tutorial to install torch_geometric and its dependencies: https://pytorch-geometric.readthedocs.io/en/latest/install/installation.html .

The versions used in our tests are as follows:

torch_geometric==2.6.1
torch-cluster==1.6.0
torch-scatter==2.1.0
torch-sparse==0.6.16
torch-spline-conv==1.2.1

Install rpy2 for spatial domain (optional)

install r-base by conda:

conda install -c conda-forge r-base

In the R console, run the following command to install the mclust package:

install.packages("mclust")

Exit the r console after installation, install rpy2 by pip:

pip install rpy2