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HiCORE:高分辨率核心染色质环区识别的 Hi-C 分析。

HiCORE: Hi-C Analysis for Identification of Core Chromatin Looping Regions with Higher Resolution.

机构信息

Department of Chemistry, Seoul National University, Seoul 08826, Korea.

Plant Genomics and Breeding Institute, Seoul National University, Seoul 08826, Korea.

出版信息

Mol Cells. 2021 Dec 31;44(12):883-892. doi: 10.14348/molcells.2021.0014.

Abstract

Genome-wide chromosome conformation capture (3C)- based high-throughput sequencing (Hi-C) has enabled identification of genome-wide chromatin loops. Because the Hi-C map with restriction fragment resolution is intrinsically associated with sparsity and stochastic noise, Hi-C data are usually binned at particular intervals; however, the binning method has limited reliability, especially at high resolution. Here, we describe a new method called HiCORE, which provides simple pipelines and algorithms to overcome the limitations of single-layered binning and predict core chromatin regions with three-dimensional physical interactions. In this approach, multiple layers of binning with slightly shifted genome coverage are generated, and interacting bins at each layer are integrated to infer narrower regions of chromatin interactions. HiCORE predicts chromatin looping regions with higher resolution, both in human and genomes, and contributes to the identification of the precise positions of potential genomic elements in an unbiased manner.

摘要

全基因组染色体构象捕获(3C)高通量测序(Hi-C)技术能够识别全基因组染色质环。由于具有限制片段分辨率的 Hi-C 图谱本质上与稀疏性和随机噪声相关,因此 Hi-C 数据通常在特定间隔进行分箱;然而,分箱方法的可靠性有限,尤其是在高分辨率下。在这里,我们描述了一种新的方法,称为 HiCORE,它提供了简单的流程和算法来克服单层分箱的局限性,并预测具有三维物理相互作用的核心染色质区域。在这种方法中,生成了具有轻微基因组覆盖偏移的多层分箱,并且整合了各层的相互作用分箱以推断染色质相互作用的更窄区域。HiCORE 以更高的分辨率预测染色质环区域,无论是在人类还是 基因组中,并且有助于以无偏倚的方式识别潜在基因组元件的精确位置。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/966e/8718365/f74415307f20/molce-44-12-883-f1.jpg

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