Abstract
Isobaric labeling of biospecimens followed by mass spectrometry (MS) has become the method of choice for large-scale, untargeted, quantitative proteomic profiling. However, subtle variation in experimental conditions can amplify sample variability and introduce systematic biases. Motivated by the challenges and opportunities arose in a recent proteogenomic study, we developed ProMix, a flexible analytical framework designed to improve protein normalization by leveraging two key experimental design features: (1) the inclusion of an additional reference sample to serve as an internal standard, and (2) the incorporation of replicates of each specimen. ProMix can utilize either or both features. Through applications to both simulated and real data sets, we demonstrate the improved performance of ProMix and highlight the advantages of the enhanced experimental design strategies.