title: An Efficient Approach to Screening Epigenome-Wide Data.
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.
authors.affiliation: Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Zach Curlin Street, Memphis, TN 38152, USA.
authors.forename: Meredith A
authors.identifier: 0000-0001-5312-3774
authors.initials: MA
authors.lastname: Ray
authors.affiliation: Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 915 Green Street, Columbia, SC 29208, USA.
authors.forename: Xin
authors.initials: X
authors.lastname: Tong
authors.affiliation: Human Development and Health, Faculty of Medicine, University of Southampton, 801 South Academic Block Tremona Road, Southampton SO16 6YD, UK.
authors.forename: Gabrielle A
authors.initials: GA
authors.lastname: Lockett
authors.affiliation: Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Zach Curlin Street, Memphis, TN 38152, USA.
authors.forename: Hongmei
authors.identifier: 0000-0003-3557-0364
authors.initials: H
authors.lastname: Zhang
authors.affiliation: Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Zach Curlin Street, Memphis, TN 38152, USA.
authors.forename: Wilfried J J
authors.initials: WJ
authors.lastname: Karmaus
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D018899:CpG Islands / Q000235:genetics*; D019175:DNA Methylation / Q000235:genetics*; D057890:Epigenomics / Q000706:statistics & numerical data*; D015894:Genome, Human; D006801:Humans; D016014:Linear Models; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D012307:Risk Factors