一种从共定位数据确定拓扑域的鲁棒算法
Towards a robust algorithm to determine topological domains from colocalization data
摘要：
理解基因组的复杂空间组织的最重要的任务之一在于从现有的实验数据，特别是从基因组共定位（Hi-C）矩阵中提取关于这种空间组织、染色质拓扑结构域的功能和结构的信息。在这里，我们提出了一个算法，允许揭示底层的层次结构域结构的聚合物构象分析的模块化共定位矩阵。我们还测试了几个模型的聚合物结构：平衡球，随机分形球和规则的分形（皮亚诺）构象的算法。我们定义了我们所谓的簇边界的光谱，并表明，这些光谱的行为显着不同的平衡和分形构象，使我们能够提出一个额外的标准来识别分形聚合物构象。
英文摘要：
One of the most important tasks in understanding the complex spatial organization of the genome consists in extracting information about this spatial organization, the function and structure of chromatin topological domains from existing experimental data, in particular, from genome colocalization (Hi-C) matrices. Here we present an algorithm allowing to reveal the underlying hierarchical domain structure of a polymer conformation from analyzing the modularity of colocalization matrices. We also test this algorithm on several model polymer structures: equilibrium globules, random fractal globules and regular fractal (Peano) conformations. We define what we call a spectrum of cluster borders, and show that these spectra behave strikingly differently for equilibrium and fractal conformations, allowing us to suggest an additional criterion to identify fractal polymer conformations.
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