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A Comparative Analysis of Data Analysis Tools for Data-Independent Acquisition Mass Spectrometry
Data-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, D...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Biochemistry and Molecular Biology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458344/ https://www.ncbi.nlm.nih.gov/pubmed/37481071 http://dx.doi.org/10.1016/j.mcpro.2023.100623 |
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author | Zhang, Fangfei Ge, Weigang Huang, Lingling Li, Dan Liu, Lijuan Dong, Zhen Xu, Luang Ding, Xuan Zhang, Cheng Sun, Yingying A, Jun Gao, Jinlong Guo, Tiannan |
author_facet | Zhang, Fangfei Ge, Weigang Huang, Lingling Li, Dan Liu, Lijuan Dong, Zhen Xu, Luang Ding, Xuan Zhang, Cheng Sun, Yingying A, Jun Gao, Jinlong Guo, Tiannan |
author_sort | Zhang, Fangfei |
collection | PubMed |
description | Data-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. |
format | Online Article Text |
id | pubmed-10458344 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Society for Biochemistry and Molecular Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-104583442023-08-27 A Comparative Analysis of Data Analysis Tools for Data-Independent Acquisition Mass Spectrometry Zhang, Fangfei Ge, Weigang Huang, Lingling Li, Dan Liu, Lijuan Dong, Zhen Xu, Luang Ding, Xuan Zhang, Cheng Sun, Yingying A, Jun Gao, Jinlong Guo, Tiannan Mol Cell Proteomics Research Data-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. American Society for Biochemistry and Molecular Biology 2023-07-21 /pmc/articles/PMC10458344/ /pubmed/37481071 http://dx.doi.org/10.1016/j.mcpro.2023.100623 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Zhang, Fangfei Ge, Weigang Huang, Lingling Li, Dan Liu, Lijuan Dong, Zhen Xu, Luang Ding, Xuan Zhang, Cheng Sun, Yingying A, Jun Gao, Jinlong Guo, Tiannan A Comparative Analysis of Data Analysis Tools for Data-Independent Acquisition Mass Spectrometry |
title | A Comparative Analysis of Data Analysis Tools for Data-Independent Acquisition Mass Spectrometry |
title_full | A Comparative Analysis of Data Analysis Tools for Data-Independent Acquisition Mass Spectrometry |
title_fullStr | A Comparative Analysis of Data Analysis Tools for Data-Independent Acquisition Mass Spectrometry |
title_full_unstemmed | A Comparative Analysis of Data Analysis Tools for Data-Independent Acquisition Mass Spectrometry |
title_short | A Comparative Analysis of Data Analysis Tools for Data-Independent Acquisition Mass Spectrometry |
title_sort | comparative analysis of data analysis tools for data-independent acquisition mass spectrometry |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458344/ https://www.ncbi.nlm.nih.gov/pubmed/37481071 http://dx.doi.org/10.1016/j.mcpro.2023.100623 |
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