Bandingkan metode

	Studi Asosiasi Seluruh Epigenom	Analisis Variasi Jumlah Salinan
Bidang	Bioinformatika	Bioinformatika
Keluarga	Process / pipeline	Process / pipeline
Tahun asal	2009–2011	1998–2006
Pencetus	Rakyan, Down, Balding & Beck (2011); Irizarry group for differential methylation methods (~2009–2014)	Pinkel et al. (array CGH); Redon et al. (genome-wide CNV map)
Tipe	Comparative epigenome-wide analysis	Genomic structural variant detection pipeline
Sumber perintis	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.
Alias	Differential EWAS, comparative EWAS, epigenome-wide differential methylation analysis, EWAS differential design	CNV analysis, copy number variant detection, CNV calling, somatic copy number alteration analysis
Terkait	6	6
Ringkasan	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.	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.