Teschendorff, AE;
Relton, CL;
(2018)
Statistical and integrative system-level analysis of DNA methylation data.
Nature Reviews Genetics
, 19
pp. 129-147.
10.1038/nrg.2017.86.
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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.
Type: | Article |
---|---|
Title: | Statistical and integrative system-level analysis of DNA methylation data |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1038/nrg.2017.86 |
Publisher version: | http://dx.doi.org/10.1038/nrg.2017.86 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Bioinformatics, DNA methylation, Epigenetics analysis, Epigenomics, Statistical methods |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences |
URI: | https://discovery.ucl.ac.uk/id/eprint/10043142 |
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