Linganisha mbinu

	Wito wa Kilele cha ChIP-seq	Uchambuzi wa ATAC-seq
Nyanja	Bioinformatiki	Jenetiki
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	2007–2008	2013
Mwanzilishi	Johnson et al. (ChIP-seq concept, 2007); Zhang et al. (MACS algorithm, 2008)	Jason Buenrostro, Paul Giresi & William Greenleaf
Aina	Computational genomics pipeline	Chromatin profiling method
Chanzo asilia	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.	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.
Majina mbadala	ChIP-seq analysis, peak detection, MACS peak calling, ChIP peak identification	Chromatin accessibility, Open chromatin, Accessible chromatin analysis
Zinazohusiana	6	2
Muhtasari	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.	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.