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Pathway Analysis for Targeted and Untargeted Metabolomics

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Computational Methods and Data Analysis for Metabolomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2104))

Abstract

Recent advances in analytical techniques, particularly LC-MS, generate increasingly large and complex metabolomics datasets. Pathway analysis tools help place the experimental observations into relevant biological or disease context. This chapter provides an overview of the general concepts and common tools for pathway analysis, including Mummichog for untargeted metabolomics. Examples of pathway mapping, MetScape, and Mummichog are explained. This serves as both a practical tutorial and a timely survey of pathway analysis for label-free metabolomics data.

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Acknowledgments

This work has been funded in part by the US national Institutes of Health via grants U01CA235487 (Karnovsky, Michailidis), U19 AI090023 (Pulendran), U2C ES026560 (Marsit), and U01 CA235493 (Li, Xia, Siuzdak).

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Authors and Affiliations

  1. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA

    Alla Karnovsky

  2. Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA

    Shuzhao Li

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  1. Alla Karnovsky
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  2. Shuzhao Li
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Correspondence to Shuzhao Li .

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Editors and Affiliations

  1. Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA

    Shuzhao Li

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Karnovsky, A., Li, S. (2020). Pathway Analysis for Targeted and Untargeted Metabolomics. In: Li, S. (eds) Computational Methods and Data Analysis for Metabolomics. Methods in Molecular Biology, vol 2104. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0239-3_19

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  • DOI: https://doi.org/10.1007/978-1-0716-0239-3_19

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0238-6

  • Online ISBN: 978-1-0716-0239-3

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