SWING is a network inference framework that identifies associations between genes using time-series gene expression data. SWING is based on multivariate Granger causality and sliding window regression and is currently implemented in python.
For source code-related documentation, check our sphinx documentation in the docs/_build/html folder. For general implementation details, please read the Supporting Information section of Finkle et al 2018.
Please see the jupyter notebook in the examples/ for a working pipeline.
Finkle JD, Wu JJ, and Bagheri N. “Windowed Granger Causal Inference Strategy Improves Discovery of Gene Regulatory Networks.” Proceedings of the National Academy of Sciences, February 12, 2018, 201710936. https://doi.org/10.1073/pnas.1710936115.
- Python 3.6+
SWING is available via github and is a python package. Here is an example installation script:
git clone [email protected]:bagherilab/SWING.git
cd SWING
python setup.py install
Please report bugs or submit your suggestions on the official SWING git repo: https://github.com/bagherilab/SWING