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Transformation, Normalization, and Batch Effect in the Analysis of Mass Spectrometry Data for Omics Studies

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Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry

Part of the book series: Frontiers in Probability and the Statistical Sciences ((FROPROSTAS))

Abstract

Data transformation, normalization, and handling of batch effect are a key part of data analysis for almost all spectrometry-based omics data. This paper reviews and contrasts these three distinct aspects. We present a systematic overview of the key approaches and critically review some common procedures. Much of this paper is inspired by mass spectrometry-based experimentation, but most of our discussion carries over to omics data using distinct spectrometric approaches generally.

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Acknowledgements

This work was supported by funding from the European Community’s Seventh Framework Programme FP7/2011: Marie Curie Initial Training Network MEDIASRES (“Novel Statistical Methodology for Diagnostic/Prognostic and Therapeutic Studies and Systematic Reviews,” www.mediasres-itn.eu) with the Grant Agreement Number 290025 and by funding from the European Union’s Seventh Framework Programme FP7/ Health/F5/2012: MIMOmics (“Methods for Integrated Analysis of Multiple Omics Datasets,” http://www.mimomics.eu) under the Grant Agreement Number 305280.

Thanks to Mar Rodríguez Girondo for critical comments on an early version of this text.

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Authors and Affiliations

  1. Department of Medical Statistics, Leiden University Medical Center, 9600, 2300 RC, Leiden, The Netherlands

    Bart J. A. Mertens

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  1. Bart J. A. Mertens
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Correspondence to Bart J. A. Mertens .

Editor information

Editors and Affiliations

  1. Department of Biostatistics, University of Florida, Gainesville, Florida, USA

    Susmita Datta

  2. Department of Medical Statistics and Bioinformatics, Leiden University Medical Centre, RC Leiden, The Netherlands

    Bart J. A. Mertens

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Mertens, B.J.A. (2017). Transformation, Normalization, and Batch Effect in the Analysis of Mass Spectrometry Data for Omics Studies. In: Datta, S., Mertens, B. (eds) Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry. Frontiers in Probability and the Statistical Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-45809-0_1

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