ScholarGate
Асистент

Порівняння методів

Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.

Байєсівське епігеном-широке асоціативне дослідження (Bayesian EWAS)×Мультиоміксне епігеном-широке асоціативне дослідження×
ГалузьБіоінформатикаБіоінформатика
РодинаProcess / pipelineProcess / pipeline
Рік появи2010s (framework developed ~2013–2016)2011 (EWAS foundation); multi-omics integration ~2015–2020
Автор методуMultiple groups; Bayesian EWAS framework advanced by S. Richardson, P.-C. Tsai, J. T. Bell and colleaguesRakyan, Down, Balding & Beck (EWAS framework); multi-omics integration extended by multiple groups (~2015–2020)
ТипStatistical association analysisIntegrative association study
Основоположне джерелоRichardson, 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 ↗Rakyan, V. K., Down, T. A., Balding, D. J., & Beck, S. (2011). Epigenome-wide association studies for common human diseases. Nature Reviews Genetics, 12(8), 529–541. DOI ↗
Інші назвиBayesian EWAS, B-EWAS, Bayesian methylation-wide association study, Bayesian epigenetic association analysismulti-omics EWAS, integrative EWAS, multi-layer epigenome-wide association, multi-omics epigenomic integration
Пов'язані44
ПідсумокA 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.A multi-omics epigenome-wide association study (multi-omics EWAS) systematically scans the entire epigenome — typically DNA methylation at CpG sites — for associations with a phenotype of interest, then integrates findings across additional omics layers such as transcriptomics, genomics, proteomics, or metabolomics. By linking epigenetic variation to molecular changes at multiple biological levels simultaneously, this approach identifies regulatory mechanisms and biomarkers that single-omics EWAS cannot resolve.
ScholarGateНабір даних
  1. v1
  2. 2 Джерела
  3. PUBLISHED
  1. v1
  2. 2 Джерела
  3. PUBLISHED

Перейти до пошуку Завантажити слайди

ScholarGateПорівняння методів: Bayesian epigenome-wide association study · Multi-omics epigenome-wide association study. Отримано 2026-06-19 з https://scholargate.app/uk/compare