Analysis of Quantitative MS-based Proteomics Experiments using MSstats and MSstatsTMT


Recent advances in the techniques and technologies used in Mass Spectrometry (MS)-based proteomics have greatly increased the variety and complexity of experimental designs in the field. Experiments can differ in the labeling method (label-free vs tandem mass tag), acquisition type (DDA/DIA/SRM/PRM), biological question of interest, and differing numbers of conditions and replicates. Statistical methods used to analyze these experiments need to be flexible enough to fit these design complexities, while being robust enough to not overfit to one specific design. The MSstats family of R packages is widely used to analyze the results of MS-based proteomics experiments and has been shown to outperform other methods on a variety of experimental designs. In this webinar we will review the core workflow and methods behind MSstats and its extensions, highlighting critical choices that need to be made in each step of the analysis. We will review how different analysis choices affect the final protein-level conclusions made on the experiment and discuss how to avoid potential analysis pitfalls. After reviewing the methods in MSstats, we will present a hands-on session using MSstatsShiny, where participants are provided with two datasets (label-free DIA and TMT-DDA) and are invited to follow along.

Webinar link