title: Significance analysis and statistical dissection of variably methylated regions.
abstract: It has recently been proposed that variation in DNA methylation at specific genomic locations may play an important role in the development of complex diseases such as cancer. Here, we develop 1- and 2-group multiple testing procedures for identifying and quantifying regions of DNA methylation variability. Our method is the first genome-wide statistical significance calculation for increased or differential variability, as opposed to the traditional approach of testing for mean changes. We apply these procedures to genome-wide methylation data obtained from biological and technical replicates and provide the first statistical proof that variably methylated regions exist and are due to interindividual variation. We also show that differentially variable regions in colon tumor and normal tissue show enrichment of genes regulating gene expression, cell morphogenesis, and development, supporting a biological role for DNA methylation variability in cancer.
authors.affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
authors.forename: Andrew E
authors.initials: AE
authors.lastname: Jaffe
authors.forename: Andrew P
authors.initials: AP
authors.lastname: Feinberg
authors.forename: Rafael A
authors.initials: RA
authors.lastname: Irizarry
authors.forename: Jeffrey T
authors.initials: JT
authors.lastname: Leek
mesh_terms: D000704:Analysis of Variance; D056808:Biostatistics; D019175:DNA Methylation; D004273:DNA, Neoplasm / Q000737:chemistry / Q000235:genetics; D003627:Data Interpretation, Statistical; D030561:Databases, Nucleic Acid / Q000706:statistics & numerical data; D015894:Genome, Human; D006801:Humans; D009369:Neoplasms / Q000235:genetics
chemical_list: D004273:DNA, Neoplasm