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WOMBAT-P: Benchmarking Label-Free Proteomics Data Analysis Workflows
David Bouyssié1,2, Pınar Altıner1, Salvador Capella-Gutierrez3
1Institut de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, Université Toulouse III─Paul Sabatier (UT3), 31062 Toulouse, France.
Journal of Proteome Research
|December 1, 2023
Summary
WOMBAT-P offers automated benchmarking for proteomics software, revealing significant differences in quantified proteins across workflows. This platform aids researchers in selecting optimal tools for their specific data analysis needs.
Area of Science:
- Proteomics
- Bioinformatics
- Computational Biology
Background:
- Proteomics research utilizes diverse software for data analysis, including peptide-spectrum matching, protein inference, quantification, and statistical analysis.
- The variety of algorithms and approaches leads to challenges in comparing different proteomics software solutions.
- A need exists for standardized, unbiased methods to evaluate and compare commonly used proteomics workflows.
Purpose of the Study:
- To introduce WOMBAT-P, a versatile platform for automated benchmarking and comparison of bottom-up label-free proteomics workflows.
- To simplify the processing of public proteomics data using the sample and data relationship format for proteomics (SDRF-Proteomics).
- To facilitate efficient comparisons of diverse analytical outputs from annotated local or public ProteomeXchange datasets.
Main Methods:
- Developed WOMBAT-P, a platform for automated benchmarking of proteomics software.
- Utilized SDRF-Proteomics for streamlined processing of public and local proteomics data.
- Evaluated WOMBAT-P using experimental ground truth data and a realistic biological dataset.
Main Results:
- Uncovered significant disparities and limited overlap in quantified proteins across different proteomics workflows.
- Demonstrated WOMBAT-P's capability for rapid execution and seamless comparison of workflows.
- Generated valuable benchmarking metrics to guide researchers in software selection.
Conclusions:
- WOMBAT-P provides essential insights into the performance of various proteomics software solutions.
- The platform aids researchers in choosing the most suitable workflow for their specific datasets.
- The modular design of WOMBAT-P allows for extensibility and customization.
