เปรียบเทียบวิธี

	การเรียกหาตำแหน่งสูงสุด (peak calling) สำหรับข้อมูล ChIP-seq แบบอนุกรมเวลา	การวิเคราะห์ ATAC-seq
สาขาวิชา	ชีวสารสนเทศศาสตร์	พันธุศาสตร์
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	2008–2012 (ChIP-seq); time-series extensions ~2015–2020	2013
ผู้ริเริ่ม	ENCODE Consortium; extended by Haiminen et al. and broader epigenomics community	Jason Buenrostro, Paul Giresi & William Greenleaf
ประเภท	Computational epigenomics pipeline	Chromatin profiling method
แหล่งต้นตำรับ	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.	Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013). Transposition of native chromatin for fast and sensitive epigenomic profiling of cell populations and tissues. Nature Methods, 10(12), 1213–1218.
ชื่อเรียกอื่น	longitudinal ChIP-seq analysis, dynamic ChIP-seq peak calling, time-course ChIP-seq, temporal chromatin profiling	Chromatin accessibility, Open chromatin, Accessible chromatin analysis
ที่เกี่ยวข้อง	5	2
สรุป	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.	ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) is a method for profiling the landscape of chromatin accessibility genome-wide. Developed by Buenrostro and colleagues in 2013, ATAC-seq uses hyperactive transposase to tag open, accessible chromatin regions, enabling rapid and sensitive identification of regulatory DNA elements. ATAC-seq has become a standard technique for characterizing gene regulatory landscapes, discovering cell-type-specific regulatory elements, and inferring gene regulatory networks.