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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
Descripción
Sumario: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.