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

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-alpha-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.

Automated summary

In this study, the performance of four commonly used DIA software suites (DIA-NN, Spectronaut, MaxDIA, and Skyline) combined with seven different spectral libraries in global proteome analysis was evaluated using benchmark data sets that simulate biological complexity. The study also assessed their performances in analyzing phosphopeptide standards and TNF-alpha-induced phosphoproteome regulation. The results provide practical guidance for constructing a robust data analysis pipeline for different proteomics studies implementing the DIA technique.