title: The Perseus computational platform for comprehensive analysis of (prote)omics data.
abstract: A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.
authors.affiliation: Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany.
authors.forename: Stefka
authors.initials: S
authors.lastname: Tyanova
authors.affiliation: Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany.
authors.forename: Tikira
authors.initials: T
authors.lastname: Temu
authors.affiliation: Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany.
authors.forename: Pavel
authors.identifier: 0000-0002-2653-1702
authors.initials: P
authors.lastname: Sinitcyn
authors.affiliation: Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany.
authors.forename: Arthur
authors.initials: A
authors.lastname: Carlson
authors.affiliation: Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, California, USA.
authors.forename: Marco Y
authors.identifier: 0000-0002-9490-2261
authors.initials: MY
authors.lastname: Hein
authors.affiliation: Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
authors.forename: Tamar
authors.initials: T
authors.lastname: Geiger
authors.affiliation: Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
authors.forename: Matthias
authors.initials: M
authors.lastname: Mann
authors.affiliation: Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany.
authors.forename: Jürgen
authors.initials: J
authors.lastname: Cox
mesh_terms: D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D030562:Databases, Protein; D000069550:Machine Learning; D013058:Mass Spectrometry / Q000379:methods*; D011499:Protein Processing, Post-Translational; D011506:Proteins / Q000737:chemistry*; D040901:Proteomics / Q000379:methods*; D012984:Software; D057188:Workflow
chemical_list: D011506:Proteins