phuEGO is a network-based method to reconstruct active signalling pathways from phosphoproteomics datasets. It combines three-layer network propagation with ego network decomposition to provide small networks comprising active functional signalling modules. PhuEGO boosts the signal-to-noise ratio from global phosphoproteomics datasets, enriches the resulting networks for functional phosphosites and allows the improved comparison and integration across datasets.
Refer to documentation for details on installation and executation. The package is currently distributed with PyPI. Check the Zenodo page for the premade support dataset, which contains processed reference network with semantic similarity, or the Nextflow pipeline to generate your customized support dataset.
Please cite phuEGO if you use it in your analysis.
phuEGO: A network-based method to reconstruct active signalling pathways from phosphoproteomics datasets
Girolamo Giudice, Haoqi Chen, Evangelia Petsalaki
bioRxiv, 2023
doi: 10.1101/2023.08.07.552249
The algorithm and initial scripts of phuEGO are developed by Girolamo Giudice (@girolamogiudice) and Evangelia Petsalaki at EMBL-EBI.
The Python package and command line interface are developed by Haoqi Chen (@haoqichen20) at EMBL-EBI.