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How to make DNA methylome wide association studies more powerful

How to make DNA methylome wide association studies more powerful
How to make DNA methylome wide association studies more powerful
Genome-wide association studies had a troublesome adolescence, while researchers increased statistical power, in part by increasing subject numbers. Interrogating the interaction of genetic and environmental influences raised new challenges of statistical power, which were not easily bested by the addition of subjects. Screening the DNA methylome offers an attractive alternative as methylation can be thought of as a proxy for the combined influences of genetics and environment. There are statistical challenges unique to DNA methylome data and also multiple features, which can be exploited to increase power. We anticipate the development of DNA methylome association study designs and new analytical methods, together with integration of data from other molecular species and other studies, which will boost statistical power and tackle causality. In this way, the molecular trajectories that underlie disease development will be uncovered.
1750-1911
1-13
Lin, Xinyi
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Barton, Sheila
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Holbrook, Joanna
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Lin, Xinyi
0ab1cdb3-022b-4ac2-982f-bed3a2c44107
Barton, Sheila
4f674382-ca0b-44ad-9670-e71a0b134ef0
Holbrook, Joanna
69989b79-2710-4f12-946e-c6214e1b6513

Lin, Xinyi, Barton, Sheila and Holbrook, Joanna (2016) How to make DNA methylome wide association studies more powerful. Epigenomics, 1-13. (doi:10.2217/epi-2016-0017). (PMID:27052998)

Record type: Article

Abstract

Genome-wide association studies had a troublesome adolescence, while researchers increased statistical power, in part by increasing subject numbers. Interrogating the interaction of genetic and environmental influences raised new challenges of statistical power, which were not easily bested by the addition of subjects. Screening the DNA methylome offers an attractive alternative as methylation can be thought of as a proxy for the combined influences of genetics and environment. There are statistical challenges unique to DNA methylome data and also multiple features, which can be exploited to increase power. We anticipate the development of DNA methylome association study designs and new analytical methods, together with integration of data from other molecular species and other studies, which will boost statistical power and tackle causality. In this way, the molecular trajectories that underlie disease development will be uncovered.

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Accepted/In Press date: 23 March 2016
e-pub ahead of print date: 7 April 2016
Organisations: Faculty of Medicine

Identifiers

Local EPrints ID: 393103
URI: http://eprints.soton.ac.uk/id/eprint/393103
ISSN: 1750-1911
PURE UUID: 1d67b109-96dc-4c6f-89c5-69cba1d41409
ORCID for Sheila Barton: ORCID iD orcid.org/0000-0003-4963-4242
ORCID for Joanna Holbrook: ORCID iD orcid.org/0000-0003-1791-6894

Catalogue record

Date deposited: 21 Apr 2016 08:17
Last modified: 17 Dec 2019 06:51

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Contributors

Author: Xinyi Lin
Author: Sheila Barton ORCID iD
Author: Joanna Holbrook ORCID iD

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