iHuman Institute, ShanghaiTech University, Shanghai, 201210, China.
School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
Nat Commun. 2023 Jan 6;14(1):94. doi: 10.1038/s41467-022-35740-1.
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.
已经开发出了大量的软件套件和多种类的光谱库，以增强数据非依赖性采集（DIA）数据处理的深度和稳健性。然而，使用模拟生物复杂性的基准数据很少研究 DIA 软件工具和光谱库的组合如何影响 DIA 蛋白质组学和磷酸化蛋白质组学数据分析的结果。在这项研究中，我们创建了 DIA 基准数据集，模拟了在复杂背景下数千种蛋白质的调控，这些数据集是在 Orbitrap 和 timsTOF 仪器上收集的。我们评估了四种常用的软件套件（DIA-NN、Spectronaut、MaxDIA 和 Skyline）与七种不同的光谱库相结合在全蛋白质组分析中的性能。此外，我们评估了它们在分析磷酸肽标准品和 TNF-α 诱导的磷酸化蛋白质组调控中的性能。我们的研究为不同的蛋白质组学研究实施 DIA 技术提供了一个关于如何构建稳健的数据分析管道的实用指南。
