Comparison of computational methods for Hi-C data analysis.
Comparison of computational methods for Hi-C data analysis.
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DOI：
10.1038/nmeth.4325
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发表时间：
2017-07
期刊：
影响因子：
48
通讯作者：
Bicciato S
中科院分区：
文献类型：
--
作者：
Forcato M;Nicoletti C;Pal K;Livi CM;Ferrari F;Bicciato S
HI-C是一种全基因组测序技术，用于研究细胞核内的3D染色质构象。研究最多的结构可以从Hi-C-染色质相互作用和拓扑相关结构域(TADS)中识别出来-需要计算方法来分析全基因组接触概率图。我们定量地比较了13种算法对6个具有里程碑意义的研究和模拟的Hi-C数据的分析性能。比较发现，用于识别染色质相互作用的方法在性能上存在明显差异，并且用于TAD检测的算法的结果更具可比性。
Hi-C is a genome-wide sequencing technique to investigate the 3D chromatin conformation inside the nucleus. The most studied structures that can be identified from Hi-C - chromatin interactions and topologically associating domains (TADs) - require computational methods to analyze genome-wide contact probability maps. We quantitatively compared the performances of 13 algorithms for the analysis of Hi-C data from 6 landmark studies and simulations. The comparison revealed clear differences in the performances of methods to identify chromatin interactions and more comparable results of algorithms for TAD detection.