[基于空间密度聚类的染色质拓扑关联域识别方法]。

Haiyan Gong, Sichen Zhang, Xiaotong Zhang
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引用次数: 0

摘要

高通量染色质构象捕获(Hi-C)技术的快速发展为染色质结构分析提供了丰富的染色体位点间基因组相互作用数据。然而,现有的基于 Hi-C 数据的拓扑关联结构域(TADs)识别方法存在准确率低、对参数敏感性差等问题。在此背景下,本文设计并实现了一种基于空间密度聚类的 TAD 识别方法。该方法对原始 Hi-C 数据进行预处理,得到归一化的 Hi-C 接触矩阵数据。然后,计算地点之间的距离矩阵,根据地点的核心距离和可达性距离生成可达性图,并提取聚类簇。最后,根据聚类结果提取 TAD 边界。该方法能识别一致性更高的 TAD 结构,并且 TAD 边界富含更多的 ChIP-seq 因子。实验结果表明,我们的方法在 TAD 识别方面具有更高的准确性和实际意义。
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[An identification method of chromatin topological associated domains based on spatial density clustering].

The rapid development of high-throughput chromatin conformation capture (Hi-C) technology provides rich genomic interaction data between chromosomal loci for chromatin structure analysis. However, existing methods for identifying topologically associated domains (TADs) based on Hi-C data suffer from low accuracy and sensitivity to parameters. In this context, a TAD identification method based on spatial density clustering was designed and implemented in this paper. The method preprocessed the raw Hi-C data to obtain normalized Hi-C contact matrix data. Then, it computed the distance matrix between loci, generated a reachability graph based on the core distance and reachability distance of loci, and extracted clustering clusters. Finally, it extracted TAD boundaries based on clustering results. This method could identify TAD structures with higher coherence, and TAD boundaries were enriched with more ChIP-seq factors. Experimental results demonstrate that our method has advantages such as higher accuracy and practical significance in TAD identification.

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来源期刊
生物医学工程学杂志
生物医学工程学杂志 Medicine-Medicine (all)
CiteScore
0.80
自引率
0.00%
发文量
4868
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