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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 neste...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4808532/ https://www.ncbi.nlm.nih.gov/pubmed/27034928 http://dx.doi.org/10.1155/2016/2615348 |
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author | Ray, Meredith A. Tong, Xin Lockett, Gabrielle A. Zhang, Hongmei Karmaus, Wilfried J. J. |
author_facet | Ray, Meredith A. Tong, Xin Lockett, Gabrielle A. Zhang, Hongmei Karmaus, Wilfried J. J. |
author_sort | Ray, Meredith A. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4808532 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-48085322016-03-31 An Efficient Approach to Screening Epigenome-Wide Data Ray, Meredith A. Tong, Xin Lockett, Gabrielle A. Zhang, Hongmei Karmaus, Wilfried J. J. Biomed Res Int Research Article 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. Hindawi Publishing Corporation 2016 2016-03-13 /pmc/articles/PMC4808532/ /pubmed/27034928 http://dx.doi.org/10.1155/2016/2615348 Text en Copyright © 2016 Meredith A. Ray et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ray, Meredith A. Tong, Xin Lockett, Gabrielle A. Zhang, Hongmei Karmaus, Wilfried J. J. An Efficient Approach to Screening Epigenome-Wide Data |
title | An Efficient Approach to Screening Epigenome-Wide Data |
title_full | An Efficient Approach to Screening Epigenome-Wide Data |
title_fullStr | An Efficient Approach to Screening Epigenome-Wide Data |
title_full_unstemmed | An Efficient Approach to Screening Epigenome-Wide Data |
title_short | An Efficient Approach to Screening Epigenome-Wide Data |
title_sort | efficient approach to screening epigenome-wide data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4808532/ https://www.ncbi.nlm.nih.gov/pubmed/27034928 http://dx.doi.org/10.1155/2016/2615348 |
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