The R-based ecosystem, and its open-source methods for data manipulation, modeling and interpretation, is key for effective and reproducible research. This is certainly true in experiments relying on quantitative mass spectrometry. This relatively new and rapidly evolving field must overcome many sources of unwanted variation. It has many unsolved challenges, both in the appropriate use of the existing methods and tools, and in developing methods that address specialized problems. This talk will illustrate our R-based efforts to promote sound statistical practice, and build a community of competent practitioners. First, we will present Cardinal, a comprehensive tool for quantitative mass spectrometry-based imaging, as well as MSstats, a general but flexible framework for mass spectrometry-based proteomics. We will highlight the importance of these tools for pharmaceutical research in an example of statistical characterization of therapeutic protein modifications. Second, we will detail our efforts of building a community of competent users through a world-wide series of short courses, intended for experimentalists and computational scientists alike.