Department of Genetics and Genomics Sciences, Icahn School of Medicine, New York, NY, 10029, USA.
Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Bioinformatics. 2021 Jul 27;37(13):1912-1914. doi: 10.1093/bioinformatics/btaa878.
Despite widespread prevalence of somatic structural variations (SVs) across most tumor types, understanding of their molecular implications often remains poor. SVs are extremely heterogeneous in size and complexity, hindering the interpretation of their pathogenic role. Tools integrating large SV datasets across platforms are required to fully characterize the cancer's somatic landscape.
svpluscnv R package is a swiss army knife for the integration and interpretation of orthogonal datasets including copy number variant segmentation profiles and sequencing-based structural variant calls. The package implements analysis and visualization tools to evaluate chromosomal instability and ploidy, identify genes harboring recurrent SVs and detects complex rearrangements such as chromothripsis and chromoplexia. Further, it allows systematic identification of hot-spot shattered genomic regions, showing reproducibility across alternative detection methods and datasets.
https://github.com/ccbiolab/svpluscnv.
Supplementary data are available at Bioinformatics online.
尽管大多数肿瘤类型中普遍存在体细胞结构变异 (SVs),但对其分子影响的理解往往仍然很差。SVs 在大小和复杂性上非常多样,这阻碍了对其致病作用的解释。需要整合来自不同平台的大型 SV 数据集的工具来全面描述癌症的体细胞景观。
svpluscnv R 包是整合和解释正交数据集的瑞士军刀,包括拷贝数变异分割谱和基于测序的结构变异调用。该软件包实现了分析和可视化工具,用于评估染色体不稳定性和倍性,识别包含反复出现 SVs 的基因,并检测复杂重排,如染色体重排和染色体片段融合。此外,它允许系统地识别热点破碎的基因组区域,在不同的检测方法和数据集之间具有可重复性。
https://github.com/ccbiolab/svpluscnv。
补充数据可在生物信息学在线获得。