| Literature DB >> 34747401 |
David Vanderwall1, Poudel Suresh2, Yingxue Fu3, Ji-Hoon Cho3, Timothy I Shaw4, Ashutosh Mishra3, Anthony A High3, Junmin Peng5, Yuxin Li6.
Abstract
With recent advances in mass spectrometry-based proteomics technologies, deep profiling of hundreds of proteomes has become increasingly feasible. However, deriving biological insights from such valuable datasets is challenging. Here we introduce a systems biology-based software JUMPn, and its associated protocol to organize the proteome into protein co-expression clusters across samples and protein-protein interaction (PPI) networks connected by modules (e.g., protein complexes). Using the R/Shiny platform, the JUMPn software streamlines the analysis of co-expression clustering, pathway enrichment, and PPI module detection, with integrated data visualization and a user-friendly interface. The main steps of the protocol include installation of the JUMPn software, the definition of differentially expressed proteins or the (dys)regulated proteome, determination of meaningful co-expression clusters and PPI modules, and result visualization. While the protocol is demonstrated using an isobaric labeling-based proteome profile, JUMPn is generally applicable to a wide range of quantitative datasets (e.g., label-free proteomics). The JUMPn software and protocol thus provide a powerful tool to facilitate biological interpretation in quantitative proteomics.Entities:
Mesh:
Substances:
Year: 2021 PMID: 34747401 PMCID: PMC9185798 DOI: 10.3791/62796
Source DB: PubMed Journal: J Vis Exp ISSN: 1940-087X Impact factor: 1.424