方法对比

	表观基因组关联研究 (EWAS)	ChIP-seq Peak Calling
领域	生物信息学	生物信息学
方法族	Process / pipeline	Process / pipeline
起源年份	2008–2011 (term and framework established c. 2011)	2007–2008
提出者	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)
类型	Population-scale epigenomic association study	Computational genomics pipeline
开创性文献	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.
别名	EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study	ChIP-seq analysis, peak detection, MACS peak calling, ChIP peak identification
相关	5	6
摘要	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.