Quantile Normalization Approach for Liquid Chromatography-Mass Spectrometry-based Metabolomic Data from Healthy Human Volunteers

Title
Quantile Normalization Approach for Liquid Chromatography-Mass Spectrometry-based Metabolomic Data from Healthy Human Volunteers
Author(s)
임미선이주미[이주미]박정현[박정현]성숙진[성숙진]서정주[서정주]박성민[박성민]이혜원[이혜원]윤영란[윤영란]
Keywords
CDNA MICROARRAY DATA; LEVOFLOXACIN; BIASES
Issue Date
201208
Publisher
JAPAN SOC ANALYTICAL CHEMISTRY
Citation
ANALYTICAL SCIENCES, v.28, no.8, pp.801 - 805
Abstract
In metabolomic research, it is important to reduce systematic error in experimental conditions. To ensure that metabolomic data from different studies are comparable, it is necessary to remove unwanted systematic factors by data normalization. Several normalization methods are used for metabolomic data, but the best method has not yet been identified. In this study, to reduce variation from non-biological systematic errors, we applied 1-norm, 2-norm, and quantile normalization methods to liquid chromatography-mass spectrometry (LC-MS)-based metabolomic data from human urine samples after oral administration of cyclosporine (high- and low-dose) in healthy volunteers and compared the effectiveness of the three methods. The principal component analysis (PCA) score plot showed more obvious groupings according to the cyclosporine dose after quantile normalization than after the other two methods and prior to normalization. Quantile normalization is a simple and effective method to reduce non-biological systematic variation from human LC-MS-based metabolomic data, revealing the biological variance.
URI
http://hdl.handle.net/YU.REPOSITORY/27512
ISSN
0910-6340
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약학대학 > 약학부 > Articles
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