Significance analysis and statistical dissection of variably methylated regions
Open Access
- 17 June 2011
- journal article
- research article
- Published by Oxford University Press (OUP) in Biostatistics
- Vol. 13 (1), 166-178
- https://doi.org/10.1093/biostatistics/kxr013
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.Keywords
This publication has 24 references indexed in Scilit:
- Personalized Epigenomic Signatures That Are Stable Over Time and Covary with Body Mass IndexScience Translational Medicine, 2010
- Asymptotic Conditional Singular Value Decomposition for High-Dimensional Genomic DataBiometrics, 2010
- Stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and diseaseProceedings of the National Academy of Sciences, 2010
- A general framework for multiple testing dependenceProceedings of the National Academy of Sciences, 2008
- An integrated software system for analyzing ChIP-chip and ChIP-seq dataNature Biotechnology, 2008
- Comprehensive high-throughput arrays for relative methylation (CHARM)Genome Research, 2008
- Model-based analysis of tiling-arrays for ChIP-chipProceedings of the National Academy of Sciences, 2006
- The history of cancer epigeneticsNature Reviews Cancer, 2004
- Statistical significance for genomewide studiesProceedings of the National Academy of Sciences, 2003
- A Direct Approach to False Discovery RatesJournal of the Royal Statistical Society Series B: Statistical Methodology, 2002