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Estimation of a significance threshold for epigenome‐wide association studies
Epigenome‐wide association studies (EWAS) are designed to characterise population‐level epigenetic differences across the genome and link them to disease. Most commonly, they assess DNA‐methylation status at cytosine‐guanine dinucleotide (CpG) sites, using platforms such as the Illumina 450k array t...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5813244/ https://www.ncbi.nlm.nih.gov/pubmed/29034560 http://dx.doi.org/10.1002/gepi.22086 |
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author | Saffari, Ayden Silver, Matt J. Zavattari, Patrizia Moi, Loredana Columbano, Amedeo Meaburn, Emma L. Dudbridge, Frank |
author_facet | Saffari, Ayden Silver, Matt J. Zavattari, Patrizia Moi, Loredana Columbano, Amedeo Meaburn, Emma L. Dudbridge, Frank |
author_sort | Saffari, Ayden |
collection | PubMed |
description | Epigenome‐wide association studies (EWAS) are designed to characterise population‐level epigenetic differences across the genome and link them to disease. Most commonly, they assess DNA‐methylation status at cytosine‐guanine dinucleotide (CpG) sites, using platforms such as the Illumina 450k array that profile a subset of CpGs genome wide. An important challenge in the context of EWAS is determining a significance threshold for declaring a CpG site as differentially methylated, taking multiple testing into account. We used a permutation method to estimate a significance threshold specifically for the 450k array and a simulation extrapolation approach to estimate a genome‐wide threshold. These methods were applied to five different EWAS datasets derived from a variety of populations and tissue types. We obtained an estimate of [Formula: see text] for the 450k array, and a genome‐wide estimate of [Formula: see text]. We further demonstrate the importance of these results by showing that previously recommended sample sizes for EWAS should be adjusted upwards, requiring samples between ∼10% and ∼20% larger in order to maintain type‐1 errors at the desired level. |
format | Online Article Text |
id | pubmed-5813244 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-58132442018-02-21 Estimation of a significance threshold for epigenome‐wide association studies Saffari, Ayden Silver, Matt J. Zavattari, Patrizia Moi, Loredana Columbano, Amedeo Meaburn, Emma L. Dudbridge, Frank Genet Epidemiol Research Articles Epigenome‐wide association studies (EWAS) are designed to characterise population‐level epigenetic differences across the genome and link them to disease. Most commonly, they assess DNA‐methylation status at cytosine‐guanine dinucleotide (CpG) sites, using platforms such as the Illumina 450k array that profile a subset of CpGs genome wide. An important challenge in the context of EWAS is determining a significance threshold for declaring a CpG site as differentially methylated, taking multiple testing into account. We used a permutation method to estimate a significance threshold specifically for the 450k array and a simulation extrapolation approach to estimate a genome‐wide threshold. These methods were applied to five different EWAS datasets derived from a variety of populations and tissue types. We obtained an estimate of [Formula: see text] for the 450k array, and a genome‐wide estimate of [Formula: see text]. We further demonstrate the importance of these results by showing that previously recommended sample sizes for EWAS should be adjusted upwards, requiring samples between ∼10% and ∼20% larger in order to maintain type‐1 errors at the desired level. John Wiley and Sons Inc. 2017-10-15 2018-02 /pmc/articles/PMC5813244/ /pubmed/29034560 http://dx.doi.org/10.1002/gepi.22086 Text en © 2017 The Authors Genetic Epidemiology Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Saffari, Ayden Silver, Matt J. Zavattari, Patrizia Moi, Loredana Columbano, Amedeo Meaburn, Emma L. Dudbridge, Frank Estimation of a significance threshold for epigenome‐wide association studies |
title | Estimation of a significance threshold for epigenome‐wide association studies |
title_full | Estimation of a significance threshold for epigenome‐wide association studies |
title_fullStr | Estimation of a significance threshold for epigenome‐wide association studies |
title_full_unstemmed | Estimation of a significance threshold for epigenome‐wide association studies |
title_short | Estimation of a significance threshold for epigenome‐wide association studies |
title_sort | estimation of a significance threshold for epigenome‐wide association studies |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5813244/ https://www.ncbi.nlm.nih.gov/pubmed/29034560 http://dx.doi.org/10.1002/gepi.22086 |
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