Process / pipelineBioinformatics / omics

Bayesian Epigenome-Wide Association Study (Bayesian EWAS)

A Bayesian EWAS is a genome-scale association analysis that links epigenetic marks — most commonly CpG-site DNA methylation — to a phenotype or trait of interest, replacing or supplementing the classical frequentist p-value framework with a Bayesian probabilistic model. It yields posterior probabilities of association and credible intervals for each CpG site, allowing formal incorporation of prior biological knowledge and more principled handling of the multiple-testing burden intrinsic to testing hundreds of thousands of sites simultaneously.

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Sources

  1. Richardson, S., Tsai, P. C., Bell, J. T., & Timpson, N. J. (2016). Bayesian approaches to studying associations between epigenetic marks and phenotypes. International Journal of Epidemiology, 45(3), 694–705. link
  2. Johansson, A., Enroth, S., & Gyllensten, U. (2013). Continuous aging of the human DNA methylome throughout the human lifespan. PLoS ONE, 8(6), e67378. link

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Referenced by

ScholarGateBayesian epigenome-wide association study (Bayesian Epigenome-Wide Association Study). Retrieved 2026-06-04 from https://scholargate.app/en/bioinformatics/bayesian-epigenome-wide-association-study