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Estimation of a significance threshold for epigenome‐wide association studies
Author(s) -
Saffari Ayden,
Silver Matt J.,
Zavattari Patrizia,
Moi Loredana,
Columbano Amedeo,
Meaburn Emma L.,
Dudbridge Frank
Publication year - 2018
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.22086
Subject(s) - epigenome , cpg site , biology , computational biology , genome , genetics , context (archaeology) , dna methylation , genome wide association study , single nucleotide polymorphism , gene , genotype , gene expression , paleontology
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 α = 2.4 × 10 − 7for the 450k array, and a genome‐wide estimate of α = 3.6 × 10 − 8. 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.