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Correcting systematic bias and instrument measurement drift with mzRefinery

Motivation: Systematic bias in mass measurement adversely affects data quality and negates the advantages of high precision instruments. Results: We introduce the mzRefinery tool for calibration of mass spectrometry data files. Using confident peptide spectrum matches, three different calibration me...

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Detalles Bibliográficos
Autores principales: Gibbons, Bryson C., Chambers, Matthew C., Monroe, Matthew E., Tabb, David L., Payne, Samuel H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4653383/
https://www.ncbi.nlm.nih.gov/pubmed/26243018
http://dx.doi.org/10.1093/bioinformatics/btv437
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author Gibbons, Bryson C.
Chambers, Matthew C.
Monroe, Matthew E.
Tabb, David L.
Payne, Samuel H.
author_facet Gibbons, Bryson C.
Chambers, Matthew C.
Monroe, Matthew E.
Tabb, David L.
Payne, Samuel H.
author_sort Gibbons, Bryson C.
collection PubMed
description Motivation: Systematic bias in mass measurement adversely affects data quality and negates the advantages of high precision instruments. Results: We introduce the mzRefinery tool for calibration of mass spectrometry data files. Using confident peptide spectrum matches, three different calibration methods are explored and the optimal transform function is chosen. After calibration, systematic bias is removed and the mass measurement errors are centered at 0 ppm. Because it is part of the ProteoWizard package, mzRefinery can read and write a wide variety of file formats. Availability and implementation: The mzRefinery tool is part of msConvert, available with the ProteoWizard open source package at http://proteowizard.sourceforge.net/ Contact: samuel.payne@pnnl.gov Supplementary information: Supplementary data are available at Bioinformatics online.
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spelling pubmed-46533832015-11-20 Correcting systematic bias and instrument measurement drift with mzRefinery Gibbons, Bryson C. Chambers, Matthew C. Monroe, Matthew E. Tabb, David L. Payne, Samuel H. Bioinformatics Applications Notes Motivation: Systematic bias in mass measurement adversely affects data quality and negates the advantages of high precision instruments. Results: We introduce the mzRefinery tool for calibration of mass spectrometry data files. Using confident peptide spectrum matches, three different calibration methods are explored and the optimal transform function is chosen. After calibration, systematic bias is removed and the mass measurement errors are centered at 0 ppm. Because it is part of the ProteoWizard package, mzRefinery can read and write a wide variety of file formats. Availability and implementation: The mzRefinery tool is part of msConvert, available with the ProteoWizard open source package at http://proteowizard.sourceforge.net/ Contact: samuel.payne@pnnl.gov Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2015-12-01 2015-08-04 /pmc/articles/PMC4653383/ /pubmed/26243018 http://dx.doi.org/10.1093/bioinformatics/btv437 Text en © The Author 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Gibbons, Bryson C.
Chambers, Matthew C.
Monroe, Matthew E.
Tabb, David L.
Payne, Samuel H.
Correcting systematic bias and instrument measurement drift with mzRefinery
title Correcting systematic bias and instrument measurement drift with mzRefinery
title_full Correcting systematic bias and instrument measurement drift with mzRefinery
title_fullStr Correcting systematic bias and instrument measurement drift with mzRefinery
title_full_unstemmed Correcting systematic bias and instrument measurement drift with mzRefinery
title_short Correcting systematic bias and instrument measurement drift with mzRefinery
title_sort correcting systematic bias and instrument measurement drift with mzrefinery
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4653383/
https://www.ncbi.nlm.nih.gov/pubmed/26243018
http://dx.doi.org/10.1093/bioinformatics/btv437
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