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Metabolomics: From Fundamentals to Clinical Applications

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Attention for Chapter 7: Chemometrics Methods and Strategies in Metabolomics
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Chapter title
Chemometrics Methods and Strategies in Metabolomics
Chapter number 7
Book title
Metabolomics: From Fundamentals to Clinical Applications
Published in
Advances in experimental medicine and biology, January 2017
DOI 10.1007/978-3-319-47656-8_7
Pubmed ID
Book ISBNs
978-3-31-947655-1, 978-3-31-947656-8
Authors

Rui Climaco Pinto

Editors

Alessandra Sussulini

Abstract

Chemometrics has been a fundamental discipline for the development of metabolomics, while symbiotically growing with it. From design of experiments, through data processing, to data analysis, chemometrics tools are used to design, process, visualize, explore and analyse metabolomics data.In this chapter, the most commonly used chemometrics methods for data analysis and interpretation of metabolomics experiments will be presented, with focus on multivariate analysis. These are projection-based linear methods, like principal component analysis (PCA) and orthogonal projection to latent structures (OPLS), which facilitate interpretation of the causes behind the observed sample trends, correlation with outcomes or group discrimination analysis. Validation procedures for multivariate methods will be presented and discussed.Univariate analysis is briefly discussed in the context of correlation-based linear regression methods to find associations to outcomes or in analysis of variance-based and logistic regression methods for class discrimination. These methods rely on frequentist statistics, with the determination of p-values and corresponding multiple correction procedures.Several strategies of design-analysis of metabolomics experiments will be discussed, in order to guide the reader through different setups, adopted to better address some experimental issues and to better test the scientific hypotheses.

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 9 18%
Student > Ph. D. Student 7 14%
Researcher 7 14%
Student > Master 5 10%
Student > Bachelor 3 6%
Other 5 10%
Unknown 15 29%
Readers by discipline Count As %
Chemistry 12 24%
Biochemistry, Genetics and Molecular Biology 6 12%
Agricultural and Biological Sciences 5 10%
Medicine and Dentistry 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Other 4 8%
Unknown 20 39%