방법 비교

	복사본 수 변이 분석	전장 후성유전체 연관 분석 (EWAS)
분야	생물정보학	생물정보학
계열	Process / pipeline	Process / pipeline
기원 연도	1998–2006	2008–2011 (term and framework established c. 2011)
창시자	Pinkel et al. (array CGH); Redon et al. (genome-wide CNV map)	Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application
유형	Genomic structural variant detection pipeline	Population-scale epigenomic association study
원전	Redon, R., Ishikawa, S., Fitch, K. R., et al. (2006). Global variation in copy number in the human genome. Nature, 444(7118), 444–454.	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	CNV analysis, copy number variant detection, CNV calling, somatic copy number alteration analysis	EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study
관련	6	5
요약	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.	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.