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Epigenome-Wide Association Studies pp 25–47Cite as

Accurate Measurement of DNA Methylation: Challenges and Bias Correction

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 2432))

Abstract

DNA methylation is a key epigenetic modification involved in gene regulation whose contribution to disease susceptibility is still not fully understood. As the cost of genome sequencing technologies continues to drop, it will soon become commonplace to perform genome-wide quantification of DNA methylation at a single base-pair resolution. However, the demand for its accurate quantification might vary across studies. When the scope of the analysis is to detect regions of the genome with different methylation patterns between two or more conditions, e.g., case vs control; treatments vs placebo, accuracy is not crucial. This is the case in epigenome-wide association studies used as genome-wide screening of methylation changes to detect new candidate genes and regions associated with a specific disease or condition. If the aim of the analysis is to use DNA methylation measurements as a biomarker for diseases diagnosis and treatment (Laird, Nat Rev Cancer 3:253–266, 2003; Bock, Epigenomics 1:99–110, 2009), it is instead recommended to produce accurate methylation measurements. Furthermore, if the objective is the detection of DNA methylation in subclonal tumor cell populations or in circulating tumor DNA or in any case of mosaicism, the importance of accuracy becomes critical. The aim of this chapter is to describe the factors that could affect the precise measurement of methylation levels and a recent Bayesian statistical method called MethylCal and its extension that have been proposed to minimize this problem.

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Acknowledgments

Alan Turing Institute under the Engineering and Physical Sciences Research Council [EP/N510129/1 to L.B.]. The authors thank Jose Ramon Bilbao for providing the celiac data as well as Nora Fernandez-Jimenez and Eamonn Maher for useful discussion regarding the results of the celiac data and mosaic Beckwith–Wiedemann syndrome.

Conflict of Interest

The views expressed are those of the authors and not necessarily those of the NHS or Department of Health.

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Authors and Affiliations

  1. Department of Medical Genetics, University of Cambridge, Cambridge, UK

    Eguzkine Ochoa & Leonardo Bottolo

  2. Cambridge NIHR Biomedical Research Centre, Cambridge, UK

    Eguzkine Ochoa

  3. Department of Epidemiology and Biostatistics, Imperial College London, London, UK

    Verena Zuber

  4. MRC Biostatistics Unit, University of Cambridge, Cambridge, UK

    Verena Zuber & Leonardo Bottolo

  5. The Alan Turing Institute, London, UK

    Leonardo Bottolo

Authors
  1. Eguzkine Ochoa
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  2. Verena Zuber
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  3. Leonardo Bottolo
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Correspondence to Leonardo Bottolo .

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Editors and Affiliations

  1. University of Minnesota, Minneapolis, MN, USA

    Weihua Guan

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Ochoa, E., Zuber, V., Bottolo, L. (2022). Accurate Measurement of DNA Methylation: Challenges and Bias Correction. In: Guan, W. (eds) Epigenome-Wide Association Studies. Methods in Molecular Biology, vol 2432. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1994-0_3

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  • DOI: https://doi.org/10.1007/978-1-0716-1994-0_3

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  • Publisher Name: Humana, New York, NY

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