方法对比

	时间序列ChIP-seq峰值调用	表观基因组关联研究 (EWAS)
领域	生物信息学	生物信息学
方法族	Process / pipeline	Process / pipeline
起源年份	2008–2012 (ChIP-seq); time-series extensions ~2015–2020	2008–2011 (term and framework established c. 2011)
提出者	ENCODE Consortium; extended by Haiminen et al. and broader epigenomics community	Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application
类型	Computational epigenomics pipeline	Population-scale epigenomic association study
开创性文献	Landt, S. G., Marinov, G. K., Kundaje, A., Kheradpour, P., Pauli, F., Batzoglou, S., ... & Snyder, M. (2012). ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Research, 22(9), 1813–1831.	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.
别名	longitudinal ChIP-seq analysis, dynamic ChIP-seq peak calling, time-course ChIP-seq, temporal chromatin profiling	EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study
相关	5	5
摘要	Time-series ChIP-seq peak calling extends standard chromatin immunoprecipitation sequencing analysis to samples collected at multiple time points. By identifying and comparing protein-DNA binding peaks across a temporal dimension, the method reveals how transcription factor occupancy, histone modifications, or chromatin remodeler binding evolve during biological processes such as differentiation, circadian cycles, or stimulus response.	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.