inferelator 0.4.0

Inferelator: Network Inference

inferelator

The inferelator is a package for gene regulatory network inference that is based on regularized regression. It is maintained by the Bonneau lab in the Systems Biology group of the Flatiron Institute.

This repository is the actively developed inferelator package for python; it works for both single-cell and bulk transcriptome experiments. Includes AMuSR (Castro et al 2019), elements of InfereCLaDR (Tchourine et al 2018), and single-cell workflows (Jackson et al 2020).

To install the python packages needed for the inferelator, run pip install -r requirements.txt. To install the python packages needed for the inferelator multiprocessing functionality, run pip install -r requirements-multiprocessing.txt. To install this package, clone the inferelator GitHub repository and run python setup.py install, or run pip install inferelator.

Basic workflows for Bacillus subtilis and Saccharomyces cerevisiae are included with a tutorial.

All current example data and scripts are available from Zenodo