방법 비교

	전장 후성유전체 연관 분석 (EWAS)	ChIP-seq Peak Calling
분야	생물정보학	생물정보학
계열	Process / pipeline	Process / pipeline
기원 연도	2008–2011 (term and framework established c. 2011)	2007–2008
창시자	Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application	Johnson et al. (ChIP-seq concept, 2007); Zhang et al. (MACS algorithm, 2008)
유형	Population-scale epigenomic association study	Computational genomics pipeline
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.	Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., & Liu, X. S. (2008). Model-based analysis of ChIP-seq (MACS). Genome Biology, 9(9), R137.
별칭	EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study	ChIP-seq analysis, peak detection, MACS peak calling, ChIP peak identification
관련	5	6
요약	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.	ChIP-seq peak calling is a computational pipeline that identifies genomic regions where a protein of interest — a transcription factor or histone modification — is enriched, based on sequencing reads from chromatin immunoprecipitation experiments. It converts raw sequencing data into a set of high-confidence binding or modification sites across the genome, enabling downstream analysis of gene regulation, chromatin state, and epigenetic mechanisms.