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	エピゲノムワイド関連解析（EWAS）	ChIP-seqピークコーリング
分野	バイオインフォマティクス	バイオインフォマティクス
系統	Process / pipeline	Process / pipeline
提唱年	2008–2011 (term and framework established c. 2011)	2007–2008
提唱者	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)
種類	Population-scale epigenomic association study	Computational genomics pipeline
原典	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.
別名	EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study	ChIP-seq analysis, peak detection, MACS peak calling, ChIP peak identification
関連	5	6
概要	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.