TISCOPE enables integrative and comparative analyses of spatial omics data to reveal condition-associated tissue modules
- We recommend creating a virtual environment using Python 3.11:
conda create -n tiscope python=3.11
conda activate tiscope
- (Skip if PyTorch is already installed) install PyTorch following the PyTorch installation guide. For example, on a machine with
cuda 12.x:
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu126
- (Skip if PyG is already installed) Install PyG following the PyG installation guide, usually:
pip install torch_geometric
- Install dependencies:
pip install 'scanpy[leiden]' louvain squidpy ipykernel
- Install TISCOPE:
Via Pypi:
pip install tiscope
or git clone and install
git clone git://github.com/ericli0419/TISCOPE.git
cd tiscope
pip install -e .
Please refer to the Documentation and Tutorial
See the changelog.
