Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong, China.
School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta GA 30332, USA.
Brief Bioinform. 2022 Jan 17;23(1). doi: 10.1093/bib/bbab452.
The recent advance of single-cell copy number variation (CNV) analysis plays an essential role in addressing intratumor heterogeneity, identifying tumor subgroups and restoring tumor-evolving trajectories at single-cell scale. Informative visualization of copy number analysis results boosts productive scientific exploration, validation and sharing. Several single-cell analysis figures have the effectiveness of visualizations for understanding single-cell genomics in published articles and software packages. However, they almost lack real-time interaction, and it is hard to reproduce them. Moreover, existing tools are time-consuming and memory-intensive when they reach large-scale single-cell throughputs. We present an online visualization platform, single-cell Somatic Variant Analysis Suite (scSVAS), for real-time interactive single-cell genomics data visualization. scSVAS is specifically designed for large-scale single-cell genomic analysis that provides an arsenal of unique functionalities. After uploading the specified input files, scSVAS deploys the online interactive visualization automatically. Users may conduct scientific discoveries, share interactive visualizations and download high-quality publication-ready figures. scSVAS provides versatile utilities for managing, investigating, sharing and publishing single-cell CNV profiles. We envision this online platform will expedite the biological understanding of cancer clonal evolution in single-cell resolution. All visualizations are publicly hosted at https://sc.deepomics.org.
单细胞拷贝数变异 (CNV) 分析的最新进展在解决肿瘤内异质性、鉴定肿瘤亚群以及在单细胞尺度上恢复肿瘤进化轨迹方面发挥着重要作用。拷贝数分析结果的信息可视化促进了富有成效的科学探索、验证和共享。在已发表的文章和软件包中,有一些单细胞分析图具有理解单细胞基因组学的可视化效果。然而,它们几乎缺乏实时交互,并且很难再现。此外,当达到大规模单细胞通量时,现有的工具既耗时又内存密集。我们提出了一个在线可视化平台,单细胞体细胞变异分析套件 (scSVAS),用于实时交互式单细胞基因组学数据可视化。scSVAS 专门针对大规模单细胞基因组分析而设计,提供了一系列独特的功能。上传指定的输入文件后,scSVAS 会自动部署在线交互式可视化。用户可以进行科学发现、共享交互式可视化并下载高质量的出版准备图形。scSVAS 为管理、调查、共享和发布单细胞 CNV 谱提供了通用工具。我们设想这个在线平台将加速单细胞分辨率下癌症克隆进化的生物学理解。所有的可视化都在 https://sc.deepomics.org 上公开托管。