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使用Voronoi图形与v3c-viz进行染色体构造捕获数据的可视化和数据探索

Alan M Race¹, Alisa Fuchs^2,3, Ho-Ryun Chung^4,5

¹Philipps University Marburg, Institute for Medical Bioinformatics and Biostatistics, Marburg, 35043, Germany.

Scientific reports

|December 12, 2023

概括

我们介绍了v3c-viz,一种使用沃罗诺伊图的新方法,用于可视化染色体构造捕获 (3C) 数据. 这种自适应的组合策略提高了检测高频染色质接触的性能,即使测序深度中等.

科学领域:

基因组学就是基因组学.
计算生物学计算生物学
分子生物学分子生物学

背景情况:

像Hi-C这样的染色体构造捕获 (3C) 测序方法为染色体相互作用提供了洞察力.
当前分析经常在相互作用矩阵中使用固定大小的容器,这可以在较低的测序深度上掩盖特征.

研究的目的:

通过使用沃罗诺伊图来引入3C数据的新可视化方法.
改进显著的染色体相互作用的识别,特别是在中度的测序深度.

主要方法:

在v3c-viz工具中实现3C数据可视化的Voronoi图.
使用一种适应性捆绑策略,适应本地数据密度.

主要成果:

沃罗诺伊图的方法有效地可视化3C数据,通过适应点密度.
这种方法成功地识别了高频染色质接触,包括那些在增强剂和促进剂的规模,与适度的测序数据.

结论:

沃罗诺伊图为3C测序数据提供了强大的密度估计和可视化策略.
v3c-viz通过对染色质接触的改进可视化,可以更好地发现功能性基因组元素,如增强剂和促进剂.

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