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Visualization of GC/TOF-MS-Based Metabolomics Data for Identification of Biochemically Interesting Compounds Using OPLS Class Models

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Department of Chemistry, Umeå University, SE 901 87 Umeå, Sweden, Umetrics, Tvistevägen 48, P.O. Box 7960, SE 90719, Umeå, Sweden, Umeå Plant Science Center, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, SE-901 87 Umeå, Sweden, and AstraZeneca R&D, SE 43183 Mölndal, Sweden
Cite this: Anal. Chem. 2008, 80, 1, 115–122
Publication Date (Web):November 21, 2007
https://doi.org/10.1021/ac0713510
Copyright © 2008 American Chemical Society
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    Abstract

    Metabolomics studies generate increasingly complex data tables, which are hard to summarize and visualize without appropriate tools. The use of chemometrics tools, e.g., principal component analysis (PCA), partial least-squares to latent structures (PLS), and orthogonal PLS (OPLS), is therefore of great importance as these include efficient, validated, and robust methods for modeling information-rich chemical and biological data. Here the S-plot is proposed as a tool for visualization and interpretation of multivariate classification models, e.g., OPLS discriminate analysis, having two or more classes. The S-plot visualizes both the covariance and correlation between the metabolites and the modeled class designation. Thereby the S-plot helps identifying statistically significant and potentially biochemically significant metabolites, based both on contributions to the model and their reliability. An extension of the S-plot, the SUS-plot (shared and unique structure), is applied to compare the outcome of multiple classification models compared to a common reference, e.g., control. The used example is a gas chromatography coupled mass spectroscopy based metabolomics study in plant biology where two different transgenic poplar lines are compared to wild type. By using OPLS, an improved visualization and discrimination of interesting metabolites could be demonstrated.

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    †

     Umeå University.

    ‡

     Umetrics.

    §

     Swedish University of Agricultural Sciences.

    ‖

     Visiting fellow:  Department of Biochemistry, University of Cambridge, Cambridge, UK.

    ⊥

     AstraZeneca R&D.

    *

     To whom correspondence should be addressed. Phone:+46907866917. Fax:  +4690138885. E-mail:  [email protected].

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