MAGMa: Your Comprehensive Tool for Differential Expression Analysis in Mass-Spectrometry Proteomic Data
Year: 2024
Type: preprint
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, M aximal A ggregation of G ood protein signal from Ma ss 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.
Institution: Cornell University
Language: English
Subfield: Spectroscopy
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4400134786