Improving design and normalization of multiplex proteomics study

Abstract

Advances in multiplex mass spectrometry-based technologies have enabled high-throughput, quantitative proteome profiling of large cohort. However, certain experimental design configurations can amplify sample variability and introduce systematic biases. To address these challenges, we incorporated two novel features in a recent proteogenomic investigation: (1) the inclusion of two reference samples within each mass spectrometry run to serve as internal standards, and (2) the analysis of each specimen as technical replicates across two distinct mass spectrometry runs. Building on these enhancements, we present ProMix, a flexible analytical framework designed to fully leverage these supplementary experimental components. Using both simulated and real-world datasets, we demonstrate the improved performance of ProMix and highlight the advantages conferred by these refined experimental design strategies.