Fangfei Zhang, Weigang Ge, Lingling Huang, Dan Li, Lijuan Liu, Zhen Dong, Luang Xu, Xuan Ding, Cheng Zhang, Yingying Sun, Jun A, Jinlong Gao, Tiannan Guo
Molecular & cellular proteomics : MCP 2023 SepData-independent acquisition (DIA) mass spectrometry-based proteomics generates reproducible proteome data. The complex processing of the DIA data has led to the development of multiple data analysis tools. In this study, we assessed the performance of five tools (OpenSWATH, EncyclopeDIA, Skyline, DIA-NN, and Spectronaut) using six DIA datasets obtained from TripleTOF, Orbitrap, and TimsTOF Pro instruments. By comparing identification and quantification metrics and examining shared and unique cross-tool identifications, we evaluated both library-based and library-free approaches. Our findings indicate that library-free approaches outperformed library-based methods when the spectral library had limited comprehensiveness. However, our results also suggest that constructing a comprehensive library still offers benefits for most DIA analyses. This study provides comprehensive guidance for DIA data analysis tools, benefiting both experienced and novice users of DIA-mass spectrometry technology. Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.
Fangfei Zhang, Weigang Ge, Lingling Huang, Dan Li, Lijuan Liu, Zhen Dong, Luang Xu, Xuan Ding, Cheng Zhang, Yingying Sun, Jun A, Jinlong Gao, Tiannan Guo. A Comparative Analysis of Data Analysis Tools for Data-Independent Acquisition Mass Spectrometry. Molecular & cellular proteomics : MCP. 2023 Sep;22(9):100623
PMID: 37481071
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