WOMBAT-P: Benchmarking Label-Free Proteomics Data Analysis Workflows.

The inherent diversity of approaches in proteomics research has led to a wide range of software solutions for data analysis. These software solutions encompass multiple tools, each employing different algorithms for various tasks such as peptide-spectrum matching, protein inference, quantification, statistical analysis, and visualization. To enable an unbiased comparison of commonly used bottom-up label-free proteomics workflows, we introduce WOMBAT-P, a versatile platform designed for automated benchmarking and comparison. WOMBAT-P simplifies the processing of public data by utilizing the sample and data relationship format for proteomics (SDRF-Proteomics) as input. This feature streamlines the analysis of annotated local or public ProteomeXchange data sets, promoting efficient comparisons among diverse outputs. Through an evaluation using experimental ground truth data and a realistic biological data set, we uncover significant disparities and a limited overlap in the quantified proteins. WOMBAT-P not only enables rapid execution and seamless comparison of workflows but also provides valuable insights into the capabilities of different software solutions. These benchmarking metrics are a valuable resource for researchers in selecting the most suitable workflow for their specific data sets. The modular architecture of WOMBAT-P promotes extensibility and customization. The software is available at https://github.com/wombat-p/WOMBAT-Pipelines.

Citation

David Bouyssié, Pınar Altıner, Salvador Capella-Gutierrez, José M Fernández, Yanick Paco Hagemeijer, Peter Horvatovich, Martin Hubálek, Fredrik Levander, Pierluigi Mauri, Magnus Palmblad, Wolfgang Raffelsberger, Laura Rodríguez-Navas, Dario Di Silvestre, Balázs Tibor Kunkli, Julian Uszkoreit, Yves Vandenbrouck, Juan Antonio Vizcaíno, Dirk Winkelhardt, Veit Schwämmle. WOMBAT-P: Benchmarking Label-Free Proteomics Data Analysis Workflows. Journal of proteome research. 2024 Jan 05;23(1):418-429

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PMID: 38038272

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