Review of processing and analysis methods for DNA methylation array data Public Deposited

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  • The promise of epigenome-wide association studies (EWAS) and cancer specific somatic changes in improving our understanding of cancer coupled with the decreasing cost and increasing coverage of DNA methylation microarrays, has brought about a surge in the use of these technologies. Here, we aim to provide both a review of issues encountered in the processing and analysis of array-based DNA methylation data, as well as to summarize advantages of recent approaches proposed for handling those issues; focusing on approaches publicly available in open-source environments such as R and Bioconductor. The processing tools and analysis flowchart described we hope will facilitate researchers to effectively use these powerful DNA methylation array-based platforms, thereby advancing our understanding of human health and disease.
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  • Wilhelm-Benartzi, C. S., Koestler, D. C., Karagas, M. R., Flanagan, J. M., Christensen, B. C., Kelsey, K. T., . . . Brown, R. (2013). Review of processing and analysis methods for DNA methylation array data. British Journal of Cancer, 109(6), 1394-1402. doi:10.1038/bjc.2013.496
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  • 109
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  • 6
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  • This work was supported by Cancer Research UK program A6689 (JMF, CWB, and RB). JMF is funded by Breast Cancer Campaign, RB is funded by Ovarian Cancer Action. CJM and EAH are funded by NIMH R01 MH094609. KTK is funded by the U.S. NIH grants (R01 CA121147, R01 CA078609, and R01 CA100679. MRK is funded by P20 ES018175, R01 CA57494 and EPA RD83459901.
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