Correcting systematic bias and instrument measurement drift with mzRefinery

Journal Article · Tue Aug 04 00:00:00 EDT 2015 · Bioinformatics

DOI: https://doi.org/10.1093/bioinformatics/btv437 · OSTI ID:1241083

Gibbons, Bryson C. ^[1]; Chambers, Matthew C. ^[2]; Monroe, Matthew E. ^[1]; Tabb, David L. ^[2]; Payne, Samuel H. ^[1]

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1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Biological Sciences Division
2. Vanderbilt Univ., Nashville, TN (United States). Dept. of Biomedical Informatics

Systematic bias in mass measurement adversely affects data quality and negates the advantages of high precision instruments. We introduce the mzRefinery tool into the ProteoWizard package 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 zero ppm. Because it is part of the ProteoWizard package, mzRefinery can read and write a wide variety of file formats. In conclusion, we report on availability; the mzRefinery tool is part of msConvert, available with the ProteoWizard open source package at http://proteowizard.sourceforge.net/

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States). Environmental Molecular Sciences Laboratory (EMSL)
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Inst. of Health (NIH)
• Grant/Contract Number: AC05-76RL01830
• OSTI ID: 1241083
• Report Number(s): PNNL-SA--108198; 48680; KP1601010
• Journal Information: Bioinformatics, Journal Name: Bioinformatics Journal Issue: 23 Vol. 31; ISSN 1367-4803
• Publisher: Oxford University PressCopyright Statement
• Country of Publication: United States
• Language: English