An Efficient Approach to Screening Epigenome-Wide Data. (13th March 2016)

• Record Type: Journal Article
• Authors: Ray, Meredith A.; Tong, Xin; Lockett, Gabrielle A.; Zhang, Hongmei; Karmaus, Wilfried J. J.
• Other Names: Zhai Weiwei Academic Editor.
• Is Part Of: BioMed research international. Volume 2016(2016)
• Publication Date: 2016-03-13
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2016/2615348
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : Screening cytosine-phosphate-guanine dinucleotide (CpG) DNA methylation sites in association with some covariate(s) is desired due to high dimensionality. We incorporate surrogate variable analyses (SVAs) into (ordinary or robust) linear regressions and utilize training and testing samples for nested validation to screen CpG sites. SVA is to account for variations in the methylation not explained by the specified covariate(s) and adjust for confounding effects. To make it easier to users, this screening method is built into a user-friendly R package, ttScreening, with efficient algorithms implemented. Various simulations were implemented to examine the robustness and sensitivity of the method compared to the classical approaches controlling for multiple testing: the false discovery rates-based (FDR-based) and the Bonferroni-based methods. The proposed approach in general performs better and has the potential to control both types I and II errors. We applied ttScreening to 383, 998 CpG sites in association with maternal smoking, one of the leading factors for cancer risk.