DNA methylation data analysis and its application to cancer research

Xiaotu Ma, Yi Wei Wang, Michael Q. Zhang, Adi F. Gazdar

Research output: Contribution to journalArticle

54 Scopus citations

Abstract

With the rapid development of genome-wide high-throughput technologies, including expression arrays, SNP arrays and next-generation sequencing platforms, enormous amounts of molecular data have been generated and deposited in the public domain. The application of computational approaches is required to yield biological insights from this enormous, ever-growing resource. A particularly interesting subset of these resources is related to epigenetic regulation, with DNA methylation being the most abundant data type. In this paper, we will focus on the analysis of DNA methylation data and its application to cancer studies. We first briefly review the molecular techniques that generate such data, much of which has been obtained with the use of the most recent version of Infinium HumanMethylation450 BeadChip® technology (Illumina, CA, USA). We describe the coverage of the methylome by this technique. Several examples of data mining are provided. However, it should be understood that reliance on a single aspect of epigenetics has its limitations. In the not too distant future, these defects may be rectified, providing scientists with previously unavailable opportunities to explore in detail the role of epigenetics in cancer and other disease states.

Original languageEnglish (US)
Pages (from-to)301-316
Number of pages16
JournalEpigenomics
Volume5
Issue number3
DOIs
Publication statusPublished - Jun 2013

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Keywords

  • cancer/testis antigen
  • computational biology
  • data analysis
  • DNA methylation
  • Encyclopedia of DNA Elements Consortium
  • gene expression
  • imprinted gene
  • Infinium HumanMethylation450 BeadChip
  • NIH Roadmap Epigenomics Mapping Consortium
  • The Cancer Genome Atlas

ASJC Scopus subject areas

  • Genetics
  • Cancer Research

Cite this

Ma, X., Wang, Y. W., Zhang, M. Q., & Gazdar, A. F. (2013). DNA methylation data analysis and its application to cancer research. Epigenomics, 5(3), 301-316. https://doi.org/10.2217/epi.13.26