ComplexBrowser: a tool for identification and quantification of protein complexes in large-scale proteomics datasets

Wojciech Michalak, Vasileios Tsiamis, Veit Schwammle, Adelina Rogowska-Wrzesinska*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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We have developed ComplexBrowser, an open source, online platform for supervised analysis of quantitative proteomic data (label free and isobaric mass tag based) that focuses on protein complexes. The software uses manually curated information from CORUM and Complex Portal databases to identify protein complex components. For the first time, we provide a Complex Fold Change (CFC) factor that identifies up- and down-regulated complexes based on the level of complex subunits co-regulation. The software provides interactive visualisation of protein complexes' composition and expression for exploratory analysis and incorporates a quality control step that includes normalisation and statistical analysis based on the limma package. ComplexBrowser was tested on two published studies identifying changes in protein expression within either human adenocarcinoma tissue or activated mouse T-cells. The analysis revealed 1,519 and 332 protein complexes, of which 233 and 41 were found co-ordinately regulated in the respective studies. The adopted approach provided evidence for a shift to glucose-based metabolism and high proliferation in adenocarcinoma tissues, and the identification of chromatin remodelling complexes involved in mouse T-cell activation. The results correlate with the original interpretation of the experiments and provide novel biological details about the protein complexes affected. ComplexBrowser is, to our knowledge, the first tool to automate quantitative protein complex analysis for high-throughput studies, providing insights into protein complex regulation within minutes of analysis.A fully functional demo version of ComplexBrowser is available online via http: // source code can be downloaded from:

Original languageEnglish
JournalMolecular and Cellular Proteomics
Issue number11
Pages (from-to)2324-2334
Number of pages12
Publication statusPublished - Nov 2019

Bibliographical note

Published under license by The American Society for Biochemistry and Molecular Biology, Inc.


  • Protein complex analysis
  • bioinformatics software
  • protein-protein interactions
  • proteomics
  • quality control and metrics
  • quantification


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