title: Quantile normalization approach for liquid chromatography-mass spectrometry-based metabolomic data from healthy human volunteers.
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.
authors.affiliation: Department of Biomedical Science and Clinical Trial Center, Kyungpook National University Graduate School and Hospital, Daegu, Korea.
authors.forename: Joomi
authors.initials: J
authors.lastname: Lee
authors.forename: Jeonghyeon
authors.initials: J
authors.lastname: Park
authors.forename: Mi-sun
authors.initials: MS
authors.lastname: Lim
authors.forename: Sook Jin
authors.initials: SJ
authors.lastname: Seong
authors.forename: Jeong Ju
authors.initials: JJ
authors.lastname: Seo
authors.forename: Sung Min
authors.initials: SM
authors.lastname: Park
authors.forename: Hae Won
authors.initials: HW
authors.lastname: Lee
authors.forename: Young-Ran
authors.initials: YR
authors.lastname: Yoon
mesh_terms: D000284:Administration, Oral; D002853:Chromatography, Liquid; D018592:Cross-Over Studies; D016572:Cyclosporine / Q000008:administration & dosage / Q000652:urine*; D016208:Databases, Factual; D064368:Healthy Volunteers; D006801:Humans; D013058:Mass Spectrometry; D055432:Metabolomics / Q000379:methods*; D016011:Normal Distribution; D025341:Principal Component Analysis
chemical_list: D016572:Cyclosporine