The Perseus computational platform for comprehensive analysis of (prote)omics data

Nat Methods. 2016 Sep;13(9):731-40. doi: 10.1038/nmeth.3901. Epub 2016 Jun 27.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • Computer Graphics
  • Databases, Protein
  • Machine Learning
  • Mass Spectrometry / methods*
  • Protein Processing, Post-Translational
  • Proteins / chemistry*
  • Proteomics / methods*
  • Software*
  • Workflow

Substances

  • Proteins