Overview

KSTAR is a Python package for inferring kinase actiivities from phosphoproteomic data. It requires the following steps, given a phosphoproteomic dataset of interest.

1. Network Generation: This produces an ensemble of binary, heuristically pruned kinase-substrate graphs to be used in subsequent analyses. For most users, pre-generated networks based on NetworKIN can be installed (see Getting Started).

2. Mapping Dataset to Reference Phosphoproteome: Given that the proteome is regularly updated, this step maps phosphopeptides identified in the dataset to the reference phosphoproteome to ensure site positions match the kinase-substrate networks.

3. Kinase Activity Calculation: Given sites identified in an experiment, for each experiment (column) in a dataset, calculate the likelihood that those sites were pulled randomly from the kinase-substrate networks.

4. Analysis/Plotting: Various plotting and analysis functions are provided to visualize and interpret KSTAR results.

For more details about the algorithm, as well as best use cases, see the original publication: KSTAR Paper