By providing a comprehensive view of protein dynamics, quantitative proteomics has emerged as a powerful tool for a better understanding of disease mechanisms. Here, we present a general workflow for identifying and comparing molecular subtypes of disease using proteomics data using R software. We describe steps for data preprocessing, feature selection, determination of subtypes, and functional interpretation of subtypes. These analyses can help us understand the nature of heterogeneous diseases, which is crucial for accurate diagnosis and personalized treatment. For complete details on the use and execution of this protocol, please refer to Chen et al.1.
Keywords: bioinformatics; cancer; proteomics.
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