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Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules
In metabolomics studies using high-resolution mass spectrometry (MS), a set of product ion spectra is comprehensively acquired from observed ions using the data-dependent acquisition (DDA) mode of various tandem MS. However, especially for low-intensity signals, it is sometimes difficult to distingu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Mass Spectrometry Society of Japan
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9853114/ https://www.ncbi.nlm.nih.gov/pubmed/36713802 http://dx.doi.org/10.5702/massspectrometry.A0106 |
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author | Matsuda, Fumio Komori, Shuka Yamada, Yuki Hara, Daiki Okahashi, Nobuyuki |
author_facet | Matsuda, Fumio Komori, Shuka Yamada, Yuki Hara, Daiki Okahashi, Nobuyuki |
author_sort | Matsuda, Fumio |
collection | PubMed |
description | In metabolomics studies using high-resolution mass spectrometry (MS), a set of product ion spectra is comprehensively acquired from observed ions using the data-dependent acquisition (DDA) mode of various tandem MS. However, especially for low-intensity signals, it is sometimes difficult to distinguish artifact signals from true fragment ions derived from a precursor ion. Inadequate precision in the measured m/z value is also one of the bottlenecks to narrowing down the candidate compositional formula. In this study, we report that averaging multiple product ion spectra can improve m/z precision as well as the reliability of fragment ions that are observed in such spectra. A graph-based method was applied to cluster a set of similar spectra from multiple DDA data files resulting in creating an averaged product-ion spectrum. The error levels for the m/z values declined following the central limit theorem, which allowed us to reduce the number of candidate compositional formulas. The improved reliability and precision of the averaged spectra will contribute to a more efficient annotation of product ion spectral data. |
format | Online Article Text |
id | pubmed-9853114 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Mass Spectrometry Society of Japan |
record_format | MEDLINE/PubMed |
spelling | pubmed-98531142023-01-26 Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules Matsuda, Fumio Komori, Shuka Yamada, Yuki Hara, Daiki Okahashi, Nobuyuki Mass Spectrom (Tokyo) Original Article In metabolomics studies using high-resolution mass spectrometry (MS), a set of product ion spectra is comprehensively acquired from observed ions using the data-dependent acquisition (DDA) mode of various tandem MS. However, especially for low-intensity signals, it is sometimes difficult to distinguish artifact signals from true fragment ions derived from a precursor ion. Inadequate precision in the measured m/z value is also one of the bottlenecks to narrowing down the candidate compositional formula. In this study, we report that averaging multiple product ion spectra can improve m/z precision as well as the reliability of fragment ions that are observed in such spectra. A graph-based method was applied to cluster a set of similar spectra from multiple DDA data files resulting in creating an averaged product-ion spectrum. The error levels for the m/z values declined following the central limit theorem, which allowed us to reduce the number of candidate compositional formulas. The improved reliability and precision of the averaged spectra will contribute to a more efficient annotation of product ion spectral data. The Mass Spectrometry Society of Japan 2022 2022-12-15 /pmc/articles/PMC9853114/ /pubmed/36713802 http://dx.doi.org/10.5702/massspectrometry.A0106 Text en Copyright © 2022 Fumio Matsuda, Shuka Komori, Yuki Yamada, Daiki Hara, and Nobuyuki Okahashi. https://creativecommons.org/licenses/by/2.5/This is an open-access article distributed under the terms of Creative Commons Attribution Non-Commercial 4.0 International License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Original Article Matsuda, Fumio Komori, Shuka Yamada, Yuki Hara, Daiki Okahashi, Nobuyuki Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules |
title | Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules |
title_full | Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules |
title_fullStr | Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules |
title_full_unstemmed | Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules |
title_short | Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules |
title_sort | data processing of product ion spectra: quality improvement by averaging multiple similar spectra of small molecules |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9853114/ https://www.ncbi.nlm.nih.gov/pubmed/36713802 http://dx.doi.org/10.5702/massspectrometry.A0106 |
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