Guidance for DNA methylation studies: statistical insights from the Illumina EPIC array
Georgina Mansell; T.J. Gorrie-Stone; Yanchun Bao; Meena Kumari; Leonard C. Schalkwyk; Jonathan Mill; Eilís Hannon · 2019 · BMC Genomics
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
There has been a steady increase in the number of studies aiming to identify DNA methylation differences associated with complex phenotypes. Many of the challenges of epigenetic epidemiology regarding study design and interpretation have been discussed in detail, however there are analytical concerns that are outstanding and require further exploration. In this study we seek to address three analytical issues. First, we quantify the multiple testing burden and propose a standard statistical significance threshold for identifying DNA methylation sites that are associated with an outcome. Second
Abstract by Georgina Mansell; T.J. Gorrie-Stone; Yanchun Bao; Meena Kumari; Leonard C. Schalkwyk; Jonathan Mill; Eilís Hannon, BMC Genomics (2019) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.1186/s12864-019-5761-7