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MS1Connect: a mass spectrometry run similarity measure
MOTIVATION: Interpretation of newly acquired mass spectrometry data can be improved by identifying, from an online repository, previous mass spectrometry runs that resemble the new data. However, this retrieval task requires computing the similarity between an arbitrary pair of mass spectrometry run...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913042/ https://www.ncbi.nlm.nih.gov/pubmed/36702456 http://dx.doi.org/10.1093/bioinformatics/btad058 |
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author | Lin, Andy Deatherage Kaiser, Brooke L Hutchison, Janine R Bilmes, Jeffrey A Noble, William Stafford |
author_facet | Lin, Andy Deatherage Kaiser, Brooke L Hutchison, Janine R Bilmes, Jeffrey A Noble, William Stafford |
author_sort | Lin, Andy |
collection | PubMed |
description | MOTIVATION: Interpretation of newly acquired mass spectrometry data can be improved by identifying, from an online repository, previous mass spectrometry runs that resemble the new data. However, this retrieval task requires computing the similarity between an arbitrary pair of mass spectrometry runs. This is particularly challenging for runs acquired using different experimental protocols. RESULTS: We propose a method, MS1Connect, that calculates the similarity between a pair of runs by examining only the intact peptide (MS1) scans, and we show evidence that the MS1Connect score is accurate. Specifically, we show that MS1Connect outperforms several baseline methods on the task of predicting the species from which a given proteomics sample originated. In addition, we show that MS1Connect scores are highly correlated with similarities computed from fragment (MS2) scans, even though these data are not used by MS1Connect. AVAILABILITY AND IMPLEMENTATION: The MS1Connect software is available at https://github.com/bmx8177/MS1Connect. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-9913042 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-99130422023-02-13 MS1Connect: a mass spectrometry run similarity measure Lin, Andy Deatherage Kaiser, Brooke L Hutchison, Janine R Bilmes, Jeffrey A Noble, William Stafford Bioinformatics Original Paper MOTIVATION: Interpretation of newly acquired mass spectrometry data can be improved by identifying, from an online repository, previous mass spectrometry runs that resemble the new data. However, this retrieval task requires computing the similarity between an arbitrary pair of mass spectrometry runs. This is particularly challenging for runs acquired using different experimental protocols. RESULTS: We propose a method, MS1Connect, that calculates the similarity between a pair of runs by examining only the intact peptide (MS1) scans, and we show evidence that the MS1Connect score is accurate. Specifically, we show that MS1Connect outperforms several baseline methods on the task of predicting the species from which a given proteomics sample originated. In addition, we show that MS1Connect scores are highly correlated with similarities computed from fragment (MS2) scans, even though these data are not used by MS1Connect. AVAILABILITY AND IMPLEMENTATION: The MS1Connect software is available at https://github.com/bmx8177/MS1Connect. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2023-01-25 /pmc/articles/PMC9913042/ /pubmed/36702456 http://dx.doi.org/10.1093/bioinformatics/btad058 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Paper Lin, Andy Deatherage Kaiser, Brooke L Hutchison, Janine R Bilmes, Jeffrey A Noble, William Stafford MS1Connect: a mass spectrometry run similarity measure |
title | MS1Connect: a mass spectrometry run similarity measure |
title_full | MS1Connect: a mass spectrometry run similarity measure |
title_fullStr | MS1Connect: a mass spectrometry run similarity measure |
title_full_unstemmed | MS1Connect: a mass spectrometry run similarity measure |
title_short | MS1Connect: a mass spectrometry run similarity measure |
title_sort | ms1connect: a mass spectrometry run similarity measure |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913042/ https://www.ncbi.nlm.nih.gov/pubmed/36702456 http://dx.doi.org/10.1093/bioinformatics/btad058 |
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