Exploring the Genomic Landscape of Cancer Patient Cohorts with GenVisR.
Exploring the Genomic Landscape of Cancer Patient Cohorts with GenVisR.
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DOI：
10.1002/cpz1.252
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发表时间：
2021-09
期刊：
影响因子：
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通讯作者：
Griffith OL
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文献类型：
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作者：
Skidmore ZL;Campbell KM;Cotto KC;Griffith M;Griffith OL
创建可视化来解释基因组学数据仍然是计算生物学中数据科学的一个重要方面。GenVisR bioconductor软件包的创建是为了降低出版质量图形的入口点，并且仍然是该领域内的一套流行工具。GenVisR支持涵盖广泛主题的可视化，包括生成拷贝数改变、体细胞变异、序列质量指标等的可视化摘要的功能。最近，GenVisR软件包进行了重大更新，以提高性能和功能。为了证明GenVisR的实用性，我们提出了一种使用更新的Waterfall（）函数来创建肿瘤队列突变景观的可定制oncoprint风格图的方案。我们解释了安装、数据导入、配置、绘图、临床注释和自定义的基础知识。介绍GenVisR库、Waterfall（）函数和其他基因组可视化工具的在线研讨会可在genviz.org上获得。
The creation of visualizations to interpret genomics data remains an important aspect of data science within computational biology. The GenVisR bioconductor package was created to lower the entry point for publication quality graphics and has remained a popular suite of tools within this domain. GenVisR supports visualizations covering a breadth of topics including functions to produce visual summaries of copy number alterations, somatic variants, sequence quality metrics, and more. Recently the GenVisR package has undergone significant updates to increase performance and functionality. To demonstrate the utility of GenVisR we present a protocol for use of the updated Waterfall() function to create a customizable oncoprint style plot of the mutational landscape of a tumor cohort. We explain the basics of installation, data import, configuration, plotting, clinical annotation and customization. A companion online workshop describing the GenVisR library, Waterfall() function, and other genomic visualization tools is available at genviz.org.