GIST

Leveraging Graph Information for Spatially Informed Patient Data Analysis with GIST

install GIST packages

pip install git+https://github.com/InfOmics/GIST.git

Or

git clone https://github.com/InfOmics/GIST.git

Create an environment if necessary

conda create -n gist  -y
conda activate gist
conda install  -c conda-forge python==3.10.0 r-base==4.3.1 rpy2=3.5.11  pip -y

pip install torch==2.1.0 

pip install torch_sparse -f https://data.pyg.org/whl/torch-2.1.0+cu121.html
pip install torch_scatter -f https://data.pyg.org/whl/torch-2.1.0+cu121.html
pip install torch_cluster -f https://data.pyg.org/whl/torch-2.1.0+cu121.html
pip install torch_spline_conv -f https://data.pyg.org/whl/torch-2.1.0+cu121.html

pip install torch-geometric==2.7.0 torchaudio==2.1.0 torchvision==0.16.0 
pip install -r requirements.txt

Rscript -e 'install.packages("remotes", repos="https://cran.r-project.org")'

Rscript -e 'remotes::install_version("mclust", version = "6.0.1", repos="https://cran.r-project.org")'

Verify R home is in the conda environment

which R

/home/youruser/anaconda3/envs/gist/lib/R

run_GIST.py contains the GIST pipeline.

python run_GIST.py &> output.log

Data Availability

The spatial transcriptomics datasets are available at: https://doi.org/10.5281/zenodo.15277298

Download the DLPFC 151673 data:

        wget https://zenodo.org/records/19056154/files/Data.zip
        unzip Data.zip
        rm Data.zip

Reference

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}.

Information on the conda installation.

To ensure reproducibilty and easier setup we provide the conda quick installation

Install Miniconda

   mkdir -p ~/miniconda3
   wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
   bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
   rm ~/miniconda3/miniconda.sh

Make conda available

source ~/miniconda3/bin/activate

Verify conda installation

conda --version

Initialize conda

 conda init --all
 conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main
 conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r
 conda config --add channels conda-forge