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Mass Spectrometry in Metabolomics pp 333–353Cite as

Statistical Analysis and Modeling of Mass Spectrometry-Based Metabolomics Data

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1198))

Abstract

Multivariate statistical techniques are used extensively in metabolomics studies, ranging from biomarker selection to model building and validation. Two model independent variable selection techniques, principal component analysis and two sample t-tests are discussed in this chapter, as well as classification and regression models and model related variable selection techniques, including partial least squares, logistic regression, support vector machine, and random forest. Model evaluation and validation methods, such as leave-one-out cross-validation, Monte Carlo cross-validation, and receiver operating characteristic analysis, are introduced with an emphasis to avoid over-fitting the data. The advantages and the limitations of the statistical techniques are also discussed in this chapter.

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Acknowledgments

This article was written while one of the authors, Bowei Xi, was on sabbatical leave at the Statistical and Applied Mathematical Sciences Institute (SAMSI, Research Triangle Park, NC). This work is partially funded by NSF DMS-1228348, ARO W911NF-12-1-0558, DoD MURI W911NF-08-1-0238 (BX) and NIH R01GM085291 (DR).

Author information

Authors and Affiliations

  1. Department of Statistics, Purdue University, 250 North University Street, West Lafayette, IN, 47907, USA

    Bowei Xi

  2. Department of Anesthesiology & Pain Medicine, Northwest Metabolomics Research Center, University of Washington, Seattle, WA, 98109, USA

    Haiwei Gu & Daniel Raftery

  3. Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China Institute of Technology, Nanchang, Jiangxi, China

    Haiwei Gu

  4. Department of Chemistry, Purdue University, West Lafayette, IN, USA

    Hamid Baniasadi

  5. Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    Daniel Raftery

Authors
  1. Bowei Xi
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  2. Haiwei Gu
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  3. Hamid Baniasadi
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  4. Daniel Raftery
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Corresponding author

Correspondence to Bowei Xi .

Editor information

Editors and Affiliations

  1. University of Washington Fred Hutchinson Cancer Rsrch Ctr, Seattle, Washington, USA

    Daniel Raftery

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Xi, B., Gu, H., Baniasadi, H., Raftery, D. (2014). Statistical Analysis and Modeling of Mass Spectrometry-Based Metabolomics Data. In: Raftery, D. (eds) Mass Spectrometry in Metabolomics. Methods in Molecular Biology, vol 1198. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1258-2_22

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  • DOI: https://doi.org/10.1007/978-1-4939-1258-2_22

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-1257-5

  • Online ISBN: 978-1-4939-1258-2

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