© 2015

Computational and Statistical Epigenomics

  • Andrew E. Teschendorff

Part of the Translational Bioinformatics book series (TRBIO, volume 7)

Table of contents

  1. Front Matter
    Pages i-v
  2. Normalization and Analysis Methods for DNA Methylation and ChIP-Seq Data

    1. Front Matter
      Pages 1-1
    2. Francesco Marabita, Jesper Tegnér, David Gomez-Cabrero
      Pages 3-34
    3. E. Andrés Houseman
      Pages 35-50
    4. Devin C. Koestler, E. Andrés Houseman
      Pages 91-123
  3. Integrative and Medical Epigenomics

    1. Front Matter
      Pages 125-125
    2. Ming Su, Xiaoyang Dou, Hao Cheng, Jing-Dong J. Han
      Pages 127-139
    3. Jens Przybilla, Thimo Rohlf, Joerg Galle
      Pages 141-160
    4. Andrew E. Teschendorff
      Pages 161-185
    5. Jesus Mendez-Gonzalez, Juan Sandoval
      Pages 187-217

About this book


This book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike.

Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK.


Bioinformatics Biostatistics Complex Diseases DNA methylation Epigenomics

Editors and affiliations

  • Andrew E. Teschendorff
    • 1
  1. 1.CAS Key Laboratory of Computational BiologyChinese Academy of Sciences and Max-Planck Gesellschaft Partner, Institute for Computational BiologyShanghaiChina

Bibliographic information

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“This volume in the Translational Bioinformatics series introduces modern computational and statistical tools for translational epigenomic research with a special focus on DNA methylation. … This is a valuable resource for students, clinicians, and researchers who wish to understand the basics of modern computational and statistical tools for translational epigenomics research. The analytical, storage-related, and interpretive methods discussed in this book hold great promise in helping improve prediction, early diagnosis, severity monitoring, therapeutic effect, and prognosis of human diseases.” (Pooja Sethi, Doody’s Book Reviews, July, 2015)