article Open AccessTop 1% cited
Guidance for DNA methylation studies: statistical insights from the Illumina EPIC array
BMC Genomics · 2019 · Vol. 20(1) · pp. 366–366
Georgina Mansell✉(University of Exeter)T.J. Gorrie-Stone(University of Essex)Yanchun Bao(University of Essex)Meena Kumari(University of Essex)Leonard C. Schalkwyk(University of Essex)Jonathan Mill(University of Exeter)Eilís Hannon(University of Exeter)
Abstract
We propose that a significance threshold of P < 9 × 10<sup>- 8</sup> adequately controls the false positive rate for EPIC array DNA methylation studies. Moreover, our results indicate that linear regression is a valid statistical methodology for DNA methylation studies, despite the fact that the data do not always satisfy the assumptions of this test. These findings have implications for epidemiological-based studies of DNA methylation and provide a framework for the interpretation of findings from current and future studies.
Epigenetics and DNA MethylationRNA modifications and cancerGenomics and Chromatin DynamicsBiologyDNA methylationDNA microarrayEPICComputational biologyGeneticsMethylationDNABioinformaticsGene
MeSH terms
HumansLinear ModelsCpG IslandsDNA MethylationOligonucleotide Array Sequence AnalysisEpigenesis, GeneticGenome-Wide Association StudyEpigenomics
Funding
- University of Essex
- Directorate for Biological Sciences
- Medical Research Council
- Economic and Social Research Council
Citations
383
FWCI
15.50
field-weighted impact
References
55
Percentile
99%
vs. same field & year
Citations per year
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