One of the main methods to analyze gene expression data is biclustering, a nonsupervised technique, which consists of selection subgroups of genes that co-expressed under subgroups of experimental conditions. A large number of biclustering algorithms have been developed to classify gene expression data. These algorithms can give as output a large number of overlapped biclusters, whose visualization still requires deeper studies. We present VisBicluster, a web-based interactive visualization tool for displaying biclustering results. The developed visualization technique consists of laying out the generated biclusters in a two-dimensional matrix where each bicluster is represented as a column and each overlap between a set of biclusters is represented as a row. A search interface for the user is developed to query the matrix of bicluster intersection and visualize the results matching the queries. Our tool supports many interactive features such as sorting, zooming, and details-on-demand. We proved the usefulness of VisBicluster with biclustering results from real and synthetic datasets. Besides, we performed a user study with 14 participants to illustrate the clarity and simplicity of overlap representation with our tool.

中文翻译：

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VisBicluster：表达数据的基于矩阵的 Bicluster 可视化。

分析基因表达数据的主要方法之一是双聚类，这是一种非监督技术，它由在实验条件亚组下共表达的基因选择亚组组成。已经开发了大量的双聚类算法来对基因表达数据进行分类。这些算法可以给出大量重叠的双簇作为输出，其可视化仍然需要更深入的研究。我们展示了 VisBicluster，一种基于 Web 的交互式可视化工具，用于显示双聚类结果。开发的可视化技术包括在二维矩阵中布置生成的 biclusters，其中每个 bicluster 表示为一列，一组 biclusters 之间的每个重叠表示为一行。为用户开发了一个搜索界面来查询双聚类交集的矩阵并可视化与查询匹配的结果。我们的工具支持许多交互功能，例如排序、缩放和按需详细信息。我们证明了VisBicluster与来自真实和合成数据集的双聚类结果。此外，我们对 14 名参与者进行了用户研究，以说明使用我们的工具重叠表示的清晰性和简单性。