Abstract
This chapter covers the genome-wide DNA methylation analysis using microarray platforms, such as Illumina Infinium HumanMethylation27 BeadChips or HumanMethylation450 BeadChips. Using our previously published ovarian cancer dataset (Bauerschlag et al., Oncology 80:12–20, 2011), we introduce the underlying design principles of these methylation array platforms and describe common yet effective bioinformatic strategies for data analysis, including data preprocessing, clustering methods, and differential methylation tests. We also describe the downstream analytic techniques for the results derived from the methylation array, i.e., gene set enrichment analysis and sequence-based motif analysis, which can be utilized for generating biological hypotheses.
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Acknowledgements
This work was supported by the state North Rhine Westphalia within the BioNRW2 project “StemCellFactory” (M.Z., W.W.) and the Stem Cell Network NRW (W.W.). Q.L. and M.Z. were supported by DFG Priority Program SPP1356.
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Lin, Q., Wagner, W., Zenke, M. (2013). Analysis of Genome-Wide DNA Methylation Profiles by BeadChip Technology. In: Malek, A., Tchernitsa, O. (eds) Ovarian Cancer. Methods in Molecular Biology, vol 1049. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-547-7_3
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DOI: https://doi.org/10.1007/978-1-62703-547-7_3
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