Content area
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 Web End =http://www.perseus-framework. http://www.perseus-framework.org Web End =org ) to support biological and biomedical researchers in interpreting protein quantication, interactionand post-translational modication 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 classication and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workow environment that provides complete documentation of computational methods used in a publication.