Multivariate techniques and their application in nutrition: a metabolomics case study

Kemsley, E Katherine ORCID:, Le Gall, Gwénaëlle ORCID:, Dainty, Jack R ORCID:, Watson, Andrew D, Harvey, Linda J, Tapp, Henri S and Colquhoun, Ian J (2007) Multivariate techniques and their application in nutrition: a metabolomics case study. British Journal of Nutrition, 98 (1). pp. 1-14. ISSN 1475-2662

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The post-genomic technologies are generating vast quantities of data but many nutritional scientists are not trained or equipped to analyse it. In high-resolution NMR spectra of urine, for example, the number and complexity of spectral features mean that computational techniques are required to interrogate and display the data in a manner intelligible to the researcher. In addition, there are often multiple underlying biological factors influencing the data and it is difficult to pinpoint which are having the most significant effect. This is especially true in nutritional studies, where small variations in diet can trigger multiple changes in gene expression and metabolite concentration. One class of computational tools that are useful for analysing this highly multivariate data include the well-known ‘whole spectrum’ methods of principal component analysis and partial least squares. In this work, we present a nutritional case study in which NMR data generated from a human dietary Cu intervention study is analysed using multivariate methods and the advantages and disadvantages of each technique are discussed. It is concluded that an alternative approach, called feature subset selection, will be important in this type of work; here we have used a genetic algorithm to identify the small peaks (arising from metabolites of low concentration) that have been altered significantly following a dietary intervention.

Item Type: Article
Uncontrolled Keywords: adult,algorithms,genetics,methods,administration & dosage,diet,humans,least-squares analysis,methods,male,middle aged,multivariate analysis,methods
Faculty \ School: Faculty of Science > School of Chemistry
Faculty of Science > School of Pharmacy
Faculty of Medicine and Health Sciences > Norwich Medical School

Faculty of Science > School of Biological Sciences
UEA Research Groups: Faculty of Medicine and Health Sciences > Research Centres > Lifespan Health
Depositing User: EPrints Services
Date Deposited: 25 Nov 2010 11:10
Last Modified: 19 Oct 2023 00:48
DOI: 10.1017/S0007114507685365

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