MAGMa: Your Comprehensive Tool for Differential Expression Analysis in Mass-Spectrometry Proteomic Data.

Abstract

Proteomics, the study of proteins and their functions, plays a vital role in understanding biological processes. In this study, we sought to address the challenges in analyzing complex proteomic datasets, where subtle changes in protein abundance are difficult to detect. Utilizing a newly developed tool, Maximal Aggregation of Good protein signal from Mass spectrometric data (MAGMa), we demonstrated its superior performance in accurately identifying true signals while effectively filtering out noise. Here we show that MAGMa strikes a balance between sensitivity and specificity on benchmarking datasets, offering a robust solution for analyzing various quantitative proteomic datasets. These findings advance the field by providing researchers with a powerful tool to uncover subtle changes in protein abundance, contributing to our understanding of complex biological systems and potentially facilitating the discovery of new therapeutic targets.