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Stem Cell Transcriptional Networks pp 109–131Cite as

Detection of Epigenetic Field Defects Using a Weighted Epigenetic Distance-Based Method

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 2117))

Abstract

Identifying epigenetic field defects, notably early DNA methylation alterations, is important for early cancer detection. Research has suggested these early methylation alterations are infrequent across samples and identifiable as outlier samples. Here we developed a weighted epigenetic distance-based method characterizing (dis)similarity in methylation measures at multiple CpGs in a gene or a genetic region between pairwise samples, with weights to up-weight signal CpGs and down-weight noise CpGs. Using distance-based approaches, weak signals that might be filtered out in a CpG site-level analysis could be accumulated and therefore boost the overall study power. In constructing epigenetic distances, we considered both differential methylation (DM) and differential variability (DV) signals. We demonstrated the superior performance of the proposed weighted epigenetic distance-based method over nonweighted versions and site-level EWAS (epigenome-wide association studies) methods in simulation studies. Application to breast cancer methylation data from Gene Expression Omnibus (GEO) comparing normal-adjacent tissue to tumor of breast cancer patients and normal tissue of independent age-matched cancer-free women identified novel epigenetic field defects that were missed by EWAS methods, when majority were previously reported to be associated with breast cancer and were confirmed the progression to breast cancer. We further replicated some of the identified epigenetic field defects.

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Authors and Affiliations

  1. Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA

    Ya Wang, Min Qian & Shuang Wang

  2. Department of Biostatistics, George Washington University, Washington, DC, USA

    Peifeng Ruan

  3. CAS Key Lab of Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Beijing, China

    Andrew E. Teschendorff

  4. Statistical Cancer Genomics, UCL Cancer Institute, University College London, London, UK

    Andrew E. Teschendorff

Authors
  1. Ya Wang
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  2. Min Qian
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  3. Peifeng Ruan
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  4. Andrew E. Teschendorff
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  5. Shuang Wang
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Corresponding author

Correspondence to Shuang Wang .

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Editors and Affiliations

  1. Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI, USA

    Benjamin L. Kidder

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Wang, Y., Qian, M., Ruan, P., Teschendorff, A.E., Wang, S. (2020). Detection of Epigenetic Field Defects Using a Weighted Epigenetic Distance-Based Method. In: Kidder, B. (eds) Stem Cell Transcriptional Networks. Methods in Molecular Biology, vol 2117. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0301-7_6

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  • DOI: https://doi.org/10.1007/978-1-0716-0301-7_6

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0300-0

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