Significance analysis and statistical dissection of variably methylated regions

被引:71
作者
Jaffe, Andrew E. [3 ]
Feinberg, Andrew P. [2 ]
Irizarry, Rafael A. [1 ]
Leek, Jeffrey T. [1 ]
机构
[1] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Biostat, Baltimore, MD 21205 USA
[2] Johns Hopkins Univ, Ctr Epigenet, Baltimore, MD 21205 USA
[3] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol & Biostat, Baltimore, MD 21205 USA
基金
美国国家卫生研究院;
关键词
Bump finding; Functional data analysis; Multiple testing; Preprocessing; Variably methylation regions (VMRs); MODEL-BASED ANALYSIS; ARRAYS; CHIP;
D O I
10.1093/biostatistics/kxr013
中图分类号
Q [生物科学];
学科分类号
090105 [作物生产系统与生态工程];
摘要
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.
引用
收藏
页码:166 / 178
页数:13
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