DANSy is our analytical platform that combines n-gram analysis with network theory and applies it to protein domain architectures. This is a method that abstracts the functional and structural properties to represent and study sets of proteins without relying on protein-protein interaction networks.
How to cite: Please cite our bioRxiv paper, which contains further details and specific applications of DANSy.
Documentation: https://naeglelab.github.io/DANSy/
DANSy was developed in and supports Python 3.9, and we have successfully used it in Python 3.10. It should be compatible with later version, but this has not been tested.
DANSy is pip installable, and we recommend creating a conda virtual environment for its installation:
conda create -n dansy python=3.10
conda activate dansy
pip install dansy
conda deactivate
Alternatively, to get the latest developments, you can clone the repo and create a virtual environment containing all the dependencies for DANSy using the following:
conda create env -f dansy.yml
Activate the environment using conda activate dansy for specific scripts or select the dansy kernel for jupyter notebooks.
DANSy relies on reference files generated by CoDIAC. Please see our Configuring the DANSy workspace page in our documentation for details on generating the reference file and setting up DANSy to look for the generated file.
For examples on how to get started please visit the Examples in our documentation.
For specific applications of DANSy, please see our DANSy_Applications repo. There, you will find Jupyter notebooks on applications on the whole proteome, the convergence of grammar during the evolution of reversible post-translational modification systems, and cancer fusions genes.