เปรียบเทียบวิธี

	Epigenome-Wide Association Study (EWAS)	การวิเคราะห์ความแปรผันของจำนวนสำเนา
สาขาวิชา	ชีวสารสนเทศศาสตร์	ชีวสารสนเทศศาสตร์
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	2008–2011 (term and framework established c. 2011)	1998–2006
ผู้ริเริ่ม	Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application	Pinkel et al. (array CGH); Redon et al. (genome-wide CNV map)
ประเภท	Population-scale epigenomic association study	Genomic structural variant detection pipeline
แหล่งต้นตำรับ	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.	Redon, R., Ishikawa, S., Fitch, K. R., et al. (2006). Global variation in copy number in the human genome. Nature, 444(7118), 444–454.
ชื่อเรียกอื่น	EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study	CNV analysis, copy number variant detection, CNV calling, somatic copy number alteration analysis
ที่เกี่ยวข้อง	5	6
สรุป	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.	Copy number variation (CNV) analysis is a genomic pipeline for detecting regions where individuals carry fewer or more copies of a DNA segment than the reference genome. CNVs span kilobases to megabases and are a major class of structural variation implicated in cancer, neurodevelopmental disorders, and population diversity. The pipeline typically processes SNP array intensities or read-depth signals from whole-genome sequencing, applies segmentation algorithms, calls gain and loss events, and annotates them against gene and clinical databases.