TDEase: An Open-Source Data Visualization Software Framework for Targeted Proteoform Characterization by Top-Down...

Area of Science:

• Proteomics
• Biochemistry
• Computational Biology

Background:

• Top-down proteomics (TDP) enables intact protein and proteoform characterization.
• Existing TDP software often presents fragmented workflows and limited interactive visualization.
• Non-expert users face challenges with steep learning curves in current TDP tools.

Purpose of the Study:

• To introduce TDEase, an integrated analytical framework to streamline TDP data interpretation.
• To enhance TDP data analysis through automated processing and interactive visualization.
• To focus on targeted proteoform characterization, initially integrating with the TopPIC suite.

Main Methods:

• TDEase employs a modular architecture with TDPipe for multi-process data processing and TDVis for interactive visualization.
• TDPipe automates mainstream TDP algorithms via a user-configurable pipeline for reproducible processing.
• TDVis generates dynamic dashboards for multidimensional data exploration, including feature maps and PTM analysis.

Main Results:

• Demonstrated TDEase capabilities in proteoform identification and comparative analysis using histone datasets.
• TDPipe ensures seamless and reproducible data processing.
• TDVis and TDVisWeb provide interactive, web-based visualization for enhanced data exploration.

Conclusions:

• TDEase offers a comprehensive solution to challenges in TDP data interpretation.
• The open-source Python framework facilitates future development and integration of new data types.
• TDEase empowers researchers with efficient and accessible tools for proteoform analysis.