title: Analytical error reduction using single point calibration for accurate and precise metabolomic phenotyping.
abstract: Analytical errors caused by suboptimal performance of the chosen platform for a number of metabolites and instrumental drift are a major issue in large-scale metabolomics studies. Especially for MS-based methods, which are gaining common ground within metabolomics, it is difficult to control the analytical data quality without the availability of suitable labeled internal standards and calibration standards even within one laboratory. In this paper, we suggest a workflow for significant reduction of the analytical error using pooled calibration samples and multiple internal standard strategy. Between and within batch calibration techniques are applied and the analytical error is reduced significantly (increase of 25% of peaks with RSD lower than 20%) and does not hamper or interfere with statistical analysis of the final data.
authors.affiliation: TNO Quality of Life, P.O. Box 360, 3700 AJ Zeist, The Netherlands.
authors.forename: Frans M
authors.initials: FM
authors.lastname: van der Kloet
authors.forename: Ivana
authors.initials: I
authors.lastname: Bobeldijk
authors.forename: Elwin R
authors.initials: ER
authors.lastname: Verheij
authors.forename: Renger H
authors.initials: RH
authors.lastname: Jellema
mesh_terms: D000465:Algorithms; D002138:Calibration / Q000592:standards; D013058:Mass Spectrometry / Q000379:methods; D055432:Metabolomics / Q000379:methods / Q000592:standards; D010641:Phenotype; D011786:Quality Control; D015203:Reproducibility of Results