The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Review of processing and analysis methods for DNA methylation array data
Open accessAbstract
The promise of epigenome-wide association studies and cancer-specific somatic DNA methylation 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 and a summary of the advantages of recent approaches proposed for handling those issues, focusing on approaches publicly available in open-source environments such as R and Bioconductor. We hope that the processing tools and analysis flowchart described herein 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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Cites
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“We also aim to counter some of the perceived limitations of these arrays, i.e., that there are too many “false positives” in analyzing micro-array data (Ioannidis, 2007).”
BackgroundGenome-wide methylation profiles reveal quantitative views of human aging rates
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DNA methylation arrays as surrogate measures of cell mixture distribution
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Cited by
Influence of environmental exposure on human epigenetic regulation
Marsit, C. J. (2015) · Journal of Experimental Biology · doi:10.1242/jeb.106971 · Cited by 253
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Self-citationDeepMF: deciphering the latent patterns in omics profiles with a deep learning method
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“…S j , where u i and v j are vectors of size K which encode structures that underlie the data; that is, the predicted element of feature F i on sample S j is calculated as: The predicted matrix ˆ A can be thought of as the product of the feature latent factor matrix U and sample latent factor matrix”
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Metadata
- Authors
- Wilhelm-Benartzi, C. S., Koestler, D. C., Karagas, M. R., Flanagan, J. M., Christensen, B. C., Kelsey, K. T., Marsit, C. J., Houseman, E. A., & Brown, R.
- Venue
- British Journal of Cancer
- Published
- 2013-08-27
- Volume
- 109
- Issue
- 6
- Pages
- 1394-1402
- ISSN
- 0007-0920 (ISSN-L)
- 1532-1827
- OpenAlex
- W2085245717
- Cited by
- 201
- References
- 18
- FWCI
- 6.72
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Wilhelm-Benartzi, C. S., Koestler, D. C., Karagas, M. R., Flanagan, J. M., Christensen, B. C., Kelsey, K. T., Marsit, C. J., Houseman, E. A., & Brown, R. (2013). Review of processing and analysis methods for DNA methylation array data. British Journal of Cancer. https://doi.org/10.1038/bjc.2013.496
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