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