Abstract
Data processing forms a crucial step in metabolomics studies, impacting upon data output quality, analysis potential and subsequent biological interpretation. This chapter provides an overview of data processing and analysis of GC-MS- and LC-MS-based metabolomics data. Data preprocessing steps are described, including the different software available for dealing with such complex datasets. Multivariate techniques for the subsequent analysis of metabolomics data, including principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA), are described with illustrations. Steps for the identification of potential biomarkers and the use of metabolite databases are also outlined.
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Acknowledgements
The authors would like to acknowledge Dr. Timothy Ebbels for valuable discussions during the preparation of this chapter. EW would like to acknowledge Waters Corporation for funding. Perrine Masson would like to acknowledge Servier Laboratories Ltd. for funding.
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Want, E., Masson, P. (2011). Processing and Analysis of GC/LC-MS-Based Metabolomics Data. In: Metz, T. (eds) Metabolic Profiling. Methods in Molecular Biology, vol 708. Humana Press. https://doi.org/10.1007/978-1-61737-985-7_17
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DOI: https://doi.org/10.1007/978-1-61737-985-7_17
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