เปรียบเทียบวิธี

	การวิเคราะห์ ATAC-seq	การวิเคราะห์ Hi-C	RNA Velocity
สาขาวิชา	พันธุศาสตร์	พันธุศาสตร์	พันธุศาสตร์
ตระกูล	Process / pipeline	Process / pipeline	Process / pipeline
ปีกำเนิด	2013	2009	2018
ผู้ริเริ่ม	Jason Buenrostro, Paul Giresi & William Greenleaf	Erez Lieberman-Aiden & Job Dekker	Gioele La Manno & Pavel Soldatov
ประเภท	Chromatin profiling method	Chromatin interaction method	Trajectory inference method
แหล่งต้นตำรับ	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.	Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., & Dekker, J. (2009). Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science, 326(5950), 289–293.	La Manno, G., Soldatov, R., Zeisel, A., Braun, E., Hochgerner, H., Petukhov, V., & Merad, M. (2018). RNA velocity of single cells. Nature, 560(7737), 494–498.
ชื่อเรียกอื่น	Chromatin accessibility, Open chromatin, Accessible chromatin analysis	Chromosome conformation capture, 3D genome, Chromatin contact mapping	Velocity analysis, Transcriptomic velocity, Cell fate prediction
ที่เกี่ยวข้อง	2	2	2
สรุป	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.	Hi-C (High-Chromosome Conformation Capture) is a technique and associated computational methods for mapping the 3D architecture of the genome within cells. Developed by Lieberman-Aiden and Dekker in 2009, Hi-C identifies physical interactions between genomic regions that may be distant in linear sequence but spatially proximal in 3D nuclear space. Hi-C analysis has revealed fundamental principles of genome organization, including the existence of topologically associating domains (TADs), and provides insights into how 3D structure regulates gene expression and DNA replication.	RNA velocity is a computational method that infers the future developmental state of individual cells from single-cell RNA-sequencing data. Developed by La Manno and colleagues in 2018, RNA velocity analysis measures the direction and pace of cell state transitions by analyzing the ratio of unspliced to spliced mRNA transcripts within individual cells. This enables prediction of cell trajectories and differentiation pathways without requiring temporal sampling or manipulation, providing unique insights into cell fate decisions during development and disease.