Statistical and integrative system-level analysis of DNA methylation data

Andrew Teschendorff, Caroline Relton

Research output: Contribution to journalArticle (Academic Journal)peer-review

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Abstract

Epigenetics plays a key role in cellular development and function. Alterations to the epigenome are thought to capture and mediate the effects of genetic and environmental risk factors on complex disease. Currently, DNA methylation is the only epigenetic mark that can be measured reliably and genome-wide in large numbers of samples. This review discusses some of the key statistical challenges and algorithms associated with drawing inferences from DNA methylation data, including cell-type heterogeneity, feature selection, reverse causation and system-level analyses that require integration with other data types such as gene expression, genotype, transcription factor binding and other epigenetic information.
Original languageEnglish
Number of pages19
JournalNature Reviews Genetics
Early online date13 Nov 2017
DOIs
Publication statusE-pub ahead of print - 13 Nov 2017

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