Olabisi-Adeniyi Esther, McAlister Jason A, Ferretti Daniela, Cox Juergen, Geddes-McAlister Jennifer
Molecular and Cellular Biology, University of Guelph, Guelph, Ontario N1G 2W1, Canada.
Max Planck Institute of Biochemistry, Martinsried 82152, Germany.
J Proteome Res. 2025 Jun 6;24(6):2698-2708. doi: 10.1021/acs.jproteome.4c00963. Epub 2025 May 13.
Mass spectrometry-based proteomics experiments produce complex data sets requiring robust statistical testing and effective visualization tools to ensure meaningful conclusions are drawn. The publicly available proteomics data analysis platform, Perseus, is extensively used to perform such tasks, but opportunities to enhance visualization tools and promote accessibility of the data exist. In this study, we developed ProteoPlotter, a user-friendly, executable tool to complement Perseus for visualization of proteomics data sets. ProteoPlotter is built on the Shiny framework for R programming and enables illustration of multidimensional proteomics data. ProteoPlotter supports mapping of one-dimensional enrichment analyses, enhanced adaptability of volcano plots through incorporation of Gene Ontology terminology, visualization of 95% confidence intervals in principal component analysis plots using data ellipses, and customizable features. ProteoPlotter is designed for intuitive use by biological and computational researchers alike, providing descriptive instructions (i.e., Help Guide) for preparing and uploading Perseus output files. Herein, we demonstrate the application of ProteoPlotter toward microbial proteome remodeling under altered nutrient conditions and highlight the diversity of visualizations enabled with the platform for enhanced biological insights. Through its comprehensive data visualization capabilities, linked to the power of Perseus data handling and statistical analyses, ProteoPlotter facilitates enhanced visualization of proteomics data to drive new biological discoveries.
基于质谱的蛋白质组学实验会产生复杂的数据集,需要强大的统计测试和有效的可视化工具来确保得出有意义的结论。公开可用的蛋白质组学数据分析平台Perseus被广泛用于执行此类任务,但仍有机会增强可视化工具并提高数据的可访问性。在本研究中,我们开发了ProteoPlotter,这是一个用户友好的可执行工具,用于补充Perseus以可视化蛋白质组学数据集。ProteoPlotter基于R编程的Shiny框架构建,能够展示多维蛋白质组学数据。ProteoPlotter支持一维富集分析的映射,通过纳入基因本体学术语增强火山图的适应性,使用数据椭圆在主成分分析图中可视化95%置信区间,以及可定制功能。ProteoPlotter旨在供生物学和计算研究人员直观使用,提供用于准备和上传Perseus输出文件的描述性说明(即帮助指南)。在此,我们展示了ProteoPlotter在改变营养条件下微生物蛋白质组重塑中的应用,并强调了该平台实现的可视化多样性,以增强生物学见解。通过其全面的数据可视化功能,与Perseus数据处理和统计分析的能力相结合,ProteoPlotter有助于增强蛋白质组学数据的可视化,以推动新的生物学发现。