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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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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 |
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. |
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