Benchmarking commonly used software suites and analysis workflows for DIA proteomics and phosphoproteomics.
Ronghui LouYe CaoShanshan LiXiaoyu LangYunxia LiYao-Yang ZhangWenqing ShuiPublished in: Nature communications (2023)
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.
Keyphrases
- data analysis
- mass spectrometry
- optical coherence tomography
- electronic health record
- magnetic resonance imaging
- rheumatoid arthritis
- high resolution
- magnetic resonance
- oxidative stress
- quality improvement
- machine learning
- high glucose
- big data
- label free
- liquid chromatography
- endothelial cells
- single molecule
- stress induced
- contrast enhanced
- atomic force microscopy