Derivation from first principles of the statistical distribution of the mass peak intensities of MS data

Despite the widespread use of mass spectrometry (MS) in a broad range of disciplines, the nature of MS data remains very poorly understood, and this places important constraints on the quality of MS data analysis as well as on the effectiveness of MS instrument design. In the following, a procedure for calculating the statistical distribution of the mass peak intensity for MS instruments that use analog-to-digital converters (ADCs) and electron multipliers is presented. It is demonstrated that the physical processes underlying the data-generation process, from the generation of the ions to the signal induced at the detector, and on to the digitization of the resulting voltage pulse, result in data that can be well-approximated by a Gaussian distribution whose mean and variance are determined by physically meaningful instrumental parameters. This allows for a very precise understanding of the signal-to-noise ratio of mass peak intensities and suggests novel ways of improving it. Moreover, it is a prerequisite for being able to address virtually all data analytical problems in downstream analyses in a statistically rigorous manner. The model is validated with experimental data.