方法对比
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| 时间序列ChIP-seq峰值调用× | ATAC-seq 分析× | |
|---|---|---|
| 领域≠ | 生物信息学 | 遗传学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 2008–2012 (ChIP-seq); time-series extensions ~2015–2020 | 2013 |
| 提出者≠ | ENCODE Consortium; extended by Haiminen et al. and broader epigenomics community | Jason Buenrostro, Paul Giresi & William Greenleaf |
| 类型≠ | Computational epigenomics pipeline | Chromatin profiling method |
| 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. DOI ↗ | 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. link ↗ |
| 别名≠ | longitudinal ChIP-seq analysis, dynamic ChIP-seq peak calling, time-course ChIP-seq, temporal chromatin profiling | Chromatin accessibility, Open chromatin, Accessible chromatin analysis |
| 相关≠ | 5 | 2 |
| 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. | 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. |
| ScholarGate数据集 ↗ |
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