방법 비교

	차등 전장 후성유전체 연관 분석	전장 후성유전체 연관 분석 (EWAS)
분야	생물정보학	생물정보학
계열	Process / pipeline	Process / pipeline
기원 연도	2009–2011	2008–2011 (term and framework established c. 2011)
창시자	Rakyan, Down, Balding & Beck (2011); Irizarry group for differential methylation methods (~2009–2014)	Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application
유형	Comparative epigenome-wide analysis	Population-scale epigenomic association study
원전	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.	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.
별칭	Differential EWAS, comparative EWAS, epigenome-wide differential methylation analysis, EWAS differential design	EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study
관련	6	5
요약	A Differential Epigenome-Wide Association Study (Differential EWAS) scans hundreds of thousands of CpG methylation sites across the genome to identify those whose methylation levels differ significantly between two or more comparison groups — such as cases vs. controls, exposed vs. unexposed, or distinct developmental stages. It is the standard epigenomic analogue of a differential expression analysis but operates at the level of DNA methylation marks rather than RNA counts.	An epigenome-wide association study (EWAS) is a hypothesis-free, genome-scale method that systematically tests whether epigenetic marks — predominantly CpG-site DNA methylation — differ between individuals with and without a trait, disease, or exposure. By scanning hundreds of thousands of genomic positions simultaneously, EWAS identifies loci where the epigenome is reproducibly associated with a phenotype, offering a layer of biological regulation that classical GWAS does not capture.