MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale

Abstract

The <i>MSstats</i> R-Bioconductor family of packages is widely used for statistical analyses of quantitative bottom-up mass spectrometry-based proteomic experiments to detect differentially abundant proteins. It is applicable to a variety of experimental designs and data acquisition strategies and is compatible with many data processing tools used to identify and quantify spectral features. In the face of ever-increasing complexities of experiments and data processing strategies, the core package of the family, with the same name <i>MSstats</i>, has undergone a series of substantial updates. Its new version <i>MSstats</i> v4.0 improves the usability, versatility, and accuracy of statistical methodology, and the usage of computational resources. New converters integrate the output of upstream processing tools directly with <i>MSstats</i>, requiring less manual work by the user. The package's statistical models have been updated to a more robust workflow. Finally, <i>MSstats</i>' code has been substantially refactored to improve memory use and computation speed. Here we detail these updates, highlighting methodological differences between the new and old versions. An empirical comparison of <i>MSstats</i> v4.0 to its previous implementations, as well as to the packages <i>MSqRob</i> and <i>DEqMS</i>, on controlled mixtures and biological experiments demonstrated a stronger performance and better usability of <i>MSstats</i> v4.0 as compared to existing methods.