An efficient approach to screening epigenome-wide data
An efficient approach to screening epigenome-wide data
Screening cytosine-phosphate-guanine dinucleotide (CpG) DNA methylation sites in association with some covariate(s) is desired due to high dimensionality. We incorporate surrogate variable analyses (SVAs) into (ordinary or robust) linear regressions and utilize training and testing samples for nested validation to screen CpG sites. SVA is to account for variations in the methylation not explained by the specified covariate(s) and adjust for confounding effects. To make it easier to users, this screening method is built into a user-friendly R package, ttScreening, with efficient algorithms implemented. Various simulations were implemented to examine the robustness and sensitivity of the method compared to the classical approaches controlling for multiple testing: the false discovery rates-based (FDR-based) and the Bonferroni-based methods. The proposed approach in general performs better and has the potential to control both types I and II errors. We applied ttScreening to 383,998 CpG sites in association with maternal smoking, one of the leading factors for cancer risk.
1-16
Tong, Xin
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Ray, Meredith A.
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Lockett, Gabrielle A
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Zhang, Hongmei
9f774048-54d6-4321-a252-3887b2c76db0
Karmaus, Wilfried J.J.
bdb92f4f-86ee-4097-946f-5217ce4737fb
13 March 2016
Tong, Xin
0e86225e-f4e1-49b5-ac04-4a2a6b9a202b
Ray, Meredith A.
9ad3f4c3-4746-49df-a23a-7549914efa7a
Lockett, Gabrielle A
4d92a28c-f54c-431b-81f6-e82ad9057d7a
Zhang, Hongmei
9f774048-54d6-4321-a252-3887b2c76db0
Karmaus, Wilfried J.J.
bdb92f4f-86ee-4097-946f-5217ce4737fb
Tong, Xin, Ray, Meredith A., Lockett, Gabrielle A, Zhang, Hongmei and Karmaus, Wilfried J.J.
(2016)
An efficient approach to screening epigenome-wide data.
BioMed Research International, 2016 (2615348), .
(doi:10.1155/2016/2615348).
(PMID:27034928)
Abstract
Screening cytosine-phosphate-guanine dinucleotide (CpG) DNA methylation sites in association with some covariate(s) is desired due to high dimensionality. We incorporate surrogate variable analyses (SVAs) into (ordinary or robust) linear regressions and utilize training and testing samples for nested validation to screen CpG sites. SVA is to account for variations in the methylation not explained by the specified covariate(s) and adjust for confounding effects. To make it easier to users, this screening method is built into a user-friendly R package, ttScreening, with efficient algorithms implemented. Various simulations were implemented to examine the robustness and sensitivity of the method compared to the classical approaches controlling for multiple testing: the false discovery rates-based (FDR-based) and the Bonferroni-based methods. The proposed approach in general performs better and has the potential to control both types I and II errors. We applied ttScreening to 383,998 CpG sites in association with maternal smoking, one of the leading factors for cancer risk.
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2615348.pdf
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More information
Accepted/In Press date: 11 February 2016
Published date: 13 March 2016
Organisations:
Human Development & Health
Identifiers
Local EPrints ID: 390698
URI: http://eprints.soton.ac.uk/id/eprint/390698
ISSN: 2314-6133
PURE UUID: 041654ca-a977-4e36-8ae6-a30323c55adc
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Date deposited: 06 Apr 2016 13:36
Last modified: 14 Mar 2024 23:22
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Contributors
Author:
Xin Tong
Author:
Meredith A. Ray
Author:
Gabrielle A Lockett
Author:
Hongmei Zhang
Author:
Wilfried J.J. Karmaus
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