Visualization algorithms have been widely used for intuitive interrogation of genomic data and popularly used tools include MDS, t-SNE, and UMAP. However, these algorithms are not tuned for the visualization of binary data and none of them consider the hubness of observations for the visualization. In order to address these limitations, here we propose hubViz, a novel tool for hub-centric visualization of binary data. We evaluated the performance of hubViz with its application to the gene expression data measured in multiple brain regions of rats exposed to cocaine, the single-cell RNA-seq data of peripheral blood mononuclear cells treated with interferon beta, and the literature mining data to investigate relationships among diseases. We further evaluated the performance of hubViz using simulation studies. We showed that hubViz provides effective visual inspection by locating the hub in the center and the contrasting elements in the opposite sides around the center. We believe that hubViz and its software can be powerful tools that can improve visualizations of various genomic data. The hubViz is implemented as an R package hubviz, which is publicly available at https://dongjunchung.github.io/hubviz/.

中文翻译：

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hubViz：一种用于以中心为中心的可视化的新工具

可视化算法已广泛用于基因组数据的直观查询，常用的工具包括 MDS、t-SNE 和 UMAP。然而，这些算法并未针对二进制数据的可视化进行调整，并且它们都没有考虑可视化观察的中心性。为了解决这些限制，我们在这里提出了 hubViz，这是一种用于以中心为中心的二进制数据可视化的新工具。我们评估了 hubViz 的性能，并将其应用于暴露于可卡因的大鼠的多个大脑区域中测量的基因表达数据、用干扰素 β 处理的外周血单个核细胞的单细胞 RNA-seq 数据以及文献挖掘数据以进行调查疾病之间的关系。我们使用模拟研究进一步评估了 hubViz 的性能。我们展示了 hubViz 通过将中心定位在中心并将对比元素定位在中心周围的相对侧来提供有效的视觉检查。我们相信 hubViz 及其软件可以成为强大的工具，可以改善各种基因组数据的可视化。hubViz 作为 R 包 hubviz 实现，可在 https://dongjunchung.github.io/hubviz/ 公开获得。