Interdisciplinary Sciences: Computational Life Sciences ( IF 3.9 ) Pub Date : 2021-06-23 , DOI: 10.1007/s12539-021-00453-4 Chunlin Long 1 , Yinjing Liao 2 , Yizhou Li 3 , Jianrong Yan 1 , Min Zhu 1 , Menglong Li 2
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The development of Hi-C technology has generated terabytes of chromatin interaction data, which bring possibilities for insight study of chromatin structure. Several studies revealed that mammalian chromosomes are folded into topological associated domains (TADs), which are conserved across cell types. Accurate detection of topological associated domains is now a vital process for revealing the relationship between the structure and function of genome organization. Unfortunately, the current TAD detection methods require massive computing resources, careful parameter adjustment and/or encounter inconsistent results. In this paper, we propose a novel method, Spectral-Based TAD Detector (SBTD), and evaluate its performance with a set of widely accepted statistical methods. We treat the chromatin interaction matrix as a graph and first introduce cosine similarity as a measure of the interaction patterns between bins. The results show that SBTD identifies higher quality TADs than the popular methods (DomainCaller, TopDom and SpectralTAD) and the internal bins of TADs identified by SBTD have higher correlation. Besides, The TADs identified by SBTD show a highly similar histone modification signal enrichment pattern at the boundary as reported in the previous literature. Finally, the motif enrichment analysis shows that compared with the background region, the DNA motifs of known insulator proteins are significantly enriched in the TAD boundary region identified by our method, which proves the high performance of our proposed method. Overall, SBTD is much more effective than existing methods with only one easy-to-adjust parameter, cluster number, for which we provide optimization guidelines.
Graphic abstract
中文翻译：
SBTD：一种从 Hi-C 数据中检测拓扑相关域的新方法
Hi-C技术的发展产生了数TB的染色质相互作用数据，为深入研究染色质结构带来了可能。几项研究表明，哺乳动物染色体被折叠成拓扑相关域 (TAD)，这些域在细胞类型中是保守的。准确检测拓扑相关域现在是揭示基因组组织结构和功能之间关系的重要过程。不幸的是，当前的 TAD 检测方法需要大量的计算资源、仔细的参数调整和/或遇到不一致的结果。在本文中，我们提出了一种新方法，即基于光谱的 TAD 检测器 (SBTD)，并使用一组广泛接受的统计方法评估其性能。我们将染色质相互作用矩阵视为一个图形，并首先引入余弦相似度作为 bin 之间相互作用模式的度量。结果表明，SBTD 比流行的方法（DomainCaller、TopDom 和 SpectralTAD）识别出更高质量的 TAD，并且 SBTD 识别的 TAD 的内部 bin 具有更高的相关性。此外，SBTD 鉴定的 TAD 在边界处显示出高度相似的组蛋白修饰信号富集模式，如先前文献中报道的那样。最后，基序富集分析表明，与背景区域相比，已知绝缘子蛋白的 DNA 基序在我们的方法识别的 TAD 边界区域中显着富集，这证明了我们提出的方法的高性能。总体，
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