Leveraging Graph Information for Spatially Informed Patient Data Analysis with GIST
Create an environment if necessary
conda create -n gist python==3.10.0 r-base==4.3.1 -y
conda activate gist
Verify R home is in the conda environment
which R
/home/youruser/anaconda3/envs/gist/lib/R
install requirements
pip install -r requirements.txt
Install mclust packages
Rscript -e 'install.packages("mclust", repos="https://cran.r-project.org", type="source")'
install GIST packages
pip install git+https://github.com/gospelnnadi/GIST.git
run_GIST.py contains the GIST pipeline. python run_GIST.py &> output.log
The spatial transcriptomics datasets are available at: https://doi.org/10.5281/zenodo.15277298
G. O. Nnadi, V. Bonnici, S. Avesani, E. Viesi and R. Giugno, "Leveraging Graph Information for Spatially Informed Patient Data Analysis with GIST," 2025 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Tainan, Taiwan, 2025, pp. 1-8, doi: 10.1109/CIBCB66090.2025.11177089. keywords: {Measurement;Computational modeling;Transcriptomics;Computer architecture;Contrastive learning;Brain modeling;Spatial databases;Graph neural networks;Indexes;Gene expression;Domain identification;Graph representation;Spatial transcriptomics}.