Benchmarking commonly used software suites and analysis workflows for DIA proteomics and phosphoproteomics

Ronghui Lou, Ye Cao, Shanshan Li, Xiaoyu Lang, Yunxia Li, Yaoyang Zhang () and Wenqing Shui ()
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Ronghui Lou: ShanghaiTech University
Ye Cao: University of Chinese Academy of Sciences
Shanshan Li: ShanghaiTech University
Xiaoyu Lang: ShanghaiTech University
Yunxia Li: Chinese Academy of Sciences
Yaoyang Zhang: Chinese Academy of Sciences
Wenqing Shui: ShanghaiTech University

Nature Communications, 2023, vol. 14, issue 1, 1-17

Abstract: Abstract A plethora of software suites and multiple classes of spectral libraries have been developed to enhance the depth and robustness of data-independent acquisition (DIA) data processing. However, how the combination of a DIA software tool and a spectral library impacts the outcome of DIA proteomics and phosphoproteomics data analysis has been rarely investigated using benchmark data that mimics biological complexity. In this study, we create DIA benchmark data sets simulating the regulation of thousands of proteins in a complex background, which are collected on both an Orbitrap and a timsTOF instruments. We evaluate four commonly used software suites (DIA-NN, Spectronaut, MaxDIA and Skyline) combined with seven different spectral libraries in global proteome analysis. Moreover, we assess their performances in analyzing phosphopeptide standards and TNF-α-induced phosphoproteome regulation. Our study provides a practical guidance on how to construct a robust data analysis pipeline for different proteomics studies implementing the DIA technique.

Date: 2023
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DOI: 10.1038/s41467-022-35740-1

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