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After his study of food science at the Rheinische Friedrich-Wilhelms University of Bonn, Tobias J Demetrowitsch obtained his doctoral degree in the research field of metabolomics at the Christian-Albrechts-University of Kiel. The present paper is part of his doctoral thesis and describes an extended strategy to evaluate and verify complex or large-scale experiments and data sets. Large-scale studies result in high sample numbers, requiring the analysis of samples in different batches. So far, the verification of such LC-MS-based metabolomics studies is difficult. Common approaches have not provided a reliable validation procedure to date. This article shows a novel verification process for a large-scale human urine study (analyzed by a LC/QToF-MS system) using a two-step validation procedure. The first step comprises a targeted approach that aims to examine and exclude statistical outliers. The second step consists of a principle component analysis, with the aim of a tight cluster of all quality controls and a second for all volunteer samples. The applied study design provides a reliable two-step validation procedure for large-scale studies and additionally contains an inhouse verification procedure.

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