DANCE documentation
DANCE is a Python toolkit to support deep learning models for analyzing single-cell gene expression at scale. It includes three modules at present:
Single-modality analysis
Single-cell multimodal omics
Spatially resolved transcriptomics
Our goal is to build up a deep learning community for single-cell analysis and provide GNN based architectures for users to further develop in single-cell analysis.
Getting started
To install the DANCE package, first make sure you have correctly set up dependencies such as PyTorch, PyG, and DGL. Then, simply install the DANCE package from PyPI via
pip install pydance
Alternatively, use our installation script provided in our Github repository to setup a dance conda environment with all necessary dependencies as well as DANCE.
git clone git@github.com:OmicsML/dance.git && cd dance
source install.sh cu117 # other options are [cpu,cu118]
Finally, you can checkout some example scripts we provided to reproduce some of the experiments from the original papers.