Esther Olabisi-Adeniyi, Jason A McAlister, Daniela Ferretti, Juergen Cox, Jennifer Geddes-McAlister
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引用次数: 0
Abstract
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.
期刊介绍:
Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".