ProteoPlotter: An Executable Proteomics Visualization Tool Compatible with Perseus

Area of Science:

• Proteomics
• Bioinformatics
• Computational Biology

Background:

• Mass spectrometry-based proteomics generates complex data requiring robust statistical analysis and visualization.
• Existing tools like Perseus are widely used but have room for improved visualization and data accessibility.
• Effective visualization is crucial for drawing meaningful conclusions from large-scale proteomics datasets.

Purpose of the Study:

• To develop ProteoPlotter, a user-friendly tool to enhance visualization of proteomics data.
• To complement the Perseus platform with advanced, accessible visualization capabilities.
• To facilitate deeper biological insights through improved data representation.

Main Methods:

• Development of ProteoPlotter using the R programming language and Shiny framework.
• Implementation of multidimensional data illustration, including 1D enrichment analyses and adaptable volcano plots.
• Integration of Gene Ontology terminology and visualization of confidence intervals in PCA plots using data ellipses.

Main Results:

• ProteoPlotter provides intuitive visualization of complex proteomics data, complementing Perseus.
• The tool supports enhanced volcano plots with Gene Ontology integration and PCA plots with data ellipses.
• Demonstrated application in analyzing microbial proteome remodeling under altered nutrient conditions.

Conclusions:

• ProteoPlotter offers comprehensive and customizable visualization features for proteomics data.
• The tool enhances biological discovery by linking advanced visualization with Perseus data analysis.
• ProteoPlotter is designed for accessibility by both biological and computational researchers.