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Research article - Peer-reviewed, 2012

Strategy for Optimizing LC-MS Data Processing in Metabolomics: A Design of Experiments Approach

Eliasson, Mattias; Rannar, Stefan; Madsen, Rasmus; Donten, Magdalena A.; Marsden-Edwards, Emma; Moritz, Thomas; Shockcor, JP; Johansson, Erik; Trygg, Johan


A strategy for optimizing LC-MS metabolomics data processing is proposed. We applied this strategy on the XCMS open source package written in R on both human and plant biology data. The strategy is a sequential design of experiments (DoE) based on a dilution series from a pooled sample and a measure of correlation between diluted concentrations and integrated peak areas. The reliability index metric, used to define peak quality, simultaneously favors reliable peaks and disfavors unreliable peaks using a weighted ratio between peaks with high and low response linearity. DoE optimization resulted in the case studies in more than 57% improvement in the reliability index compared to the use of the default settings. The proposed strategy can be applied to any other data processing software involving parameters to be tuned, e.g., MZmine 2. It can also be fully automated and used as a module in a complete metabolomics data processing pipeline.

Published in

Analytical Chemistry
2012, volume: 84, number: 15, pages: 6869-6876

Authors' information

Eliasson, Mattias
Umeå University
Rannar, Stefan
Umeå University
Madsen, Rasmus
Umeå University
Donten, Magdalena A. (Donten, Magdalena A.)
Umeå University
Marsden-Edwards, Emma
Waters Corp, Milford
Swedish University of Agricultural Sciences, Department of Forest Genetics and Plant Physiology
Shockcor, JP
Johansson, Erik
Trygg, Johan

UKÄ Subject classification

Analytical Chemistry

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