IEEE Trans Vis Comput Graph. 2018 Jan;24(1):522-531. doi: 10.1109/TVCG.2017.2745978. Epub 2017 Aug 29.
This paper presents an interactive visualization interface-HiPiler-for the exploration and visualization of regions-of-interest in large genome interaction matrices. Genome interaction matrices approximate the physical distance of pairs of regions on the genome to each other and can contain up to 3 million rows and columns with many sparse regions. Regions of interest (ROIs) can be defined, e.g., by sets of adjacent rows and columns, or by specific visual patterns in the matrix. However, traditional matrix aggregation or pan-and-zoom interfaces fail in supporting search, inspection, and comparison of ROIs in such large matrices. In HiPiler, ROIs are first-class objects, represented as thumbnail-like "snippets". Snippets can be interactively explored and grouped or laid out automatically in scatterplots, or through dimension reduction methods. Snippets are linked to the entire navigable genome interaction matrix through brushing and linking. The design of HiPiler is based on a series of semi-structured interviews with 10 domain experts involved in the analysis and interpretation of genome interaction matrices. We describe six exploration tasks that are crucial for analysis of interaction matrices and demonstrate how HiPiler supports these tasks. We report on a user study with a series of data exploration sessions with domain experts to assess the usability of HiPiler as well as to demonstrate respective findings in the data.
本文提出了一个交互式可视化界面-HiPiler-用于探索和可视化大型基因组互作矩阵中的感兴趣区域。基因组互作矩阵近似于基因组上对区域彼此之间的物理距离，可以包含多达 300 万行和列，并且有许多稀疏区域。感兴趣区域 (ROI) 可以通过例如相邻行和列的集合，或者矩阵中的特定视觉模式来定义。然而，传统的矩阵聚合或平移缩放接口在支持搜索、检查和比较此类大型矩阵中的 ROI 方面失败了。在 HiPiler 中，ROI 是第一类对象，用缩略图状的“片段”表示。片段可以通过交互方式进行探索，并通过散点图或降维方法自动进行分组或布局。片段通过刷选和链接与可导航的整个基因组互作矩阵相关联。HiPiler 的设计基于对 10 位参与基因组互作矩阵分析和解释的领域专家进行的一系列半结构化访谈。我们描述了对于分析互作矩阵至关重要的六个探索任务，并展示了 HiPiler 如何支持这些任务。我们报告了一项用户研究，其中包括一系列与领域专家的数据探索会议，以评估 HiPiler 的可用性，并展示数据中的相应发现。
