Controlling the quality of metabolomics data: new strategies to get the best out of the QC sample

Godzien, J., Alonso-Herranz, V., Barbas, C. and Armitage, E. G. (2015) Controlling the quality of metabolomics data: new strategies to get the best out of the QC sample. Metabolomics, 11(3), pp. 518-528. (doi: 10.1007/s11306-014-0712-4)

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Abstract

The type and use of quality control (QC) samples is a ‘hot topic’ in metabolomics. QCs are not novel in analytical chemistry; however since the evolution of using QCs to control the quality of data in large scale metabolomics studies (first described in 2011), the need for detailed knowledge of how to use QCs and the effects they can have on data treatment is growing. A controlled experiment has been designed to illustrate the most advantageous uses of QCs in metabolomics experiments. For this, samples were formed from a pool of plasma whereby different metabolites were spiked into two groups in order to simulate biological biomarkers. Three different QCs were compared: QCs pooled from all samples, QCs pooled from each experimental group of samples separately and QCs provided by an external source (QC surrogate). On the experimentation of different data treatment strategies, it was revealed that QCs collected separately for groups offers the closest matrix to the samples and improves the statistical outcome, especially for biomarkers unique to one group. A novel quality assurance plus procedure has also been proposed that builds on previously published methods and has the ability to improve statistical results for QC pool. For this dataset, the best option to work with QC surrogate was to filter data based only on group presence. Finally, a novel use of recursive analysis is portrayed that allows the improvement of statistical analyses with respect to the ratio between true and false positives.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Armitage, Dr Emily Grace
Authors: Godzien, J., Alonso-Herranz, V., Barbas, C., and Armitage, E. G.
College/School:College of Medical Veterinary and Life Sciences > School of Infection & Immunity
Journal Name:Metabolomics
Publisher:Springer
ISSN:1573-3882
ISSN (Online):1573-3890
Published Online:27 July 2014

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