This chapter guides the user through an analysis pipeline that includes preprocessing raw mass spectrometry data into a user-friendly quantitative protein report and statistical analysis. We use a publicly available dataset as a working example that covers two prominent strategies for mass spectrometry-based proteomics, the extensively used data-dependent acquisition (DDA) and the emerging data-independent acquisition (DIA) technology. We use MaxQuant for DDA data and Spectronaut for DIA data preprocessing. Both software packages are well-established tools in the field. We perform subsequent analysis in the R software environment which offers a large repertoire of tools for data analysis and visualization. The chapter will aid lab scientists with some familiarity with R to reproducibly analyze their experiments using state-of-the-art bioinformatics methods.
Pham, T. V., & Jimenez, C. R. (2019). Quantitative analysis of mass spectrometry-based proteomics data. In Neuromethods (Vol. 146, pp. 129-142). (Neuromethods). Humana Press Inc.. https://doi.org/10.1007/978-1-4939-9662-9_12