Structural variants integration and visualization: A comprehensive R package for integration of somatic structural variations from multiple callers and visualization

Tumor discovery Pub Date : 2023-07-20 DOI:10.36922/td.0894
Lei Yu, Le Zhang, Lili Wang, Zhenyu Jia
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引用次数: 0

Abstract

Whole genome sequencing (WGS) emerges as a powerful tool for detecting structural variations (SVs) in genomes. However, different SV callers can produce variable results due to the distinct rationale and sensitivity of pipelines, highlighting the need for effective tools to compare and merge results from multiple callers. Here, we developed an R package, structural variants integration and visualization, to facilitate the integration, classification, and visualization of SV results from multiple callers, allowing for accurate identification of the most reliable SVs. Our package relies on a complex translocation projection and clustering method, enabling the projection of each translation to a point in a Cartesian coordinate system and visualization of SVs at both whole-genome and individual chromosome levels. Thus, our approach provides a valuable framework for analyzing SVs from WGS data, improving the accuracy and efficiency of SV detection, and enhancing the potential of WGS for clinical and research applications.
结构变体集成和可视化:一个全面的R包,用于集成来自多个调用者的体细胞结构变体和可视化
全基因组测序(WGS)是检测基因组结构变异(SVs)的有力工具。然而,由于管道的原理和敏感性不同,不同的SV调用程序可能产生不同的结果,这就突出了对有效工具的需求,以比较和合并来自多个调用程序的结果。在这里,我们开发了一个R包,结构变量集成和可视化,以促进来自多个调用者的SV结果的集成,分类和可视化,从而允许准确识别最可靠的SV。我们的软件包依赖于复杂的易位投影和聚类方法,能够将每个翻译投影到笛卡尔坐标系中的一个点,并在全基因组和单个染色体水平上可视化sv。因此,我们的方法为从WGS数据中分析SV,提高SV检测的准确性和效率,增强WGS在临床和研究中的应用潜力提供了一个有价值的框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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