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ABSTRACT: Motivation
DNA methylation is an intensely studied epigenetic mark implicated in many biological processes of direct clinical relevance. Although sequencing-based technologies are increasingly allowing high-resolution measurements of DNA methylation, statistical modelling of such data is still challenging. In particular, statistical identification of differentially methylated regions across different conditions poses unresolved challenges in accounting for spatial correlations within the statistical testing procedure.Results
We propose a non-parametric, kernel-based method, M(3)D, to detect higher order changes in methylation profiles, such as shape, across pre-defined regions. The test statistic explicitly accounts for differences in coverage levels between samples, thus h
SUBMITTER: Mayo TR
PROVIDER: S-EPMC4380032 | biostudies-literature | 2015 Mar
REPOSITORIES: biostudies-literature