A Network Module for the Perseus Software for Computational Proteomics Facilitates Proteome Interaction Graph Analysis

• DOI: 10.1021/acs.jproteome.8b00927
• Publication Date: 2019-04-01T09:25:55Z
• Authors: Jan Daniel Rudolph; Jürgen Cox
• Keywords: 0301 basic medicine; 570; Proteome; computational proteomics; Ubiquitin-Protein Ligases; 610; Mice; 03 medical and health sciences; Neural Stem Cells; Protein Interaction Mapping; Animals; Humans; Gene Regulatory Networks; network analysis; Perseus; Polycomb Repressive Complex 1; 0303 health sciences; Tumor Suppressor Proteins; Polycomb Repressive Complex 2; Computational Biology; Mouse Embryonic Stem Cells; Data Interpretation, Statistical; Protein Processing, Post-Translational; Ubiquitin Thiolesterase; Software

ABSTRACTProteomics data analysis strongly benefits from not studying single proteins in isolation but taking their multivariate interdependence into account. We introduce PerseusNet, the new Perseus network module for the biological analysis of proteomics data. Proteomics is commonly used to generate networks, e.g. with affinity purification experiments, but networks are also used to explore proteomics data. PerseusNet supports the biomedical researcher for both modes of data analysis with a multitude of activities. For affinity purification, a volcano plot-based statistical analysis method for network generation is featured which is scalable to large numbers of baits. For posttranslational modifications of proteins, such as phosphorylation, a collection of dedicated network analysis tools helps elucidating cellular signaling events. Co-expression network analysis of proteomics data adopts established tools from transcriptome co-expression analysis. PerseusNet is extensible through a plug-in architecture in a multi-lingual way, integrating analyses in C#, Python and R and is freely available at http://www.perseus-framework.org.