IEEE Trans Vis Comput Graph. 2019 Mar;25(3):1543-1558. doi: 10.1109/TVCG.2018.2811488. Epub 2018 Mar 6.
The majority of diseases that are a significant challenge for public and individual heath are caused by a combination of hereditary and environmental factors. In this paper we introduce Lineage, a novel visual analysis tool designed to support domain experts who study such multifactorial diseases in the context of genealogies. Incorporating familial relationships between cases with other data can provide insights into shared genomic variants and shared environmental exposures that may be implicated in such diseases. We introduce a data and task abstraction, and argue that the problem of analyzing such diseases based on genealogical, clinical, and genetic data can be mapped to a multivariate graph visualization problem. The main contribution of our design study is a novel visual representation for tree-like, multivariate graphs, which we apply to genealogies and clinical data about the individuals in these families. We introduce data-driven aggregation methods to scale to multiple families. By designing the genealogy graph layout to align with a tabular view, we are able to incorporate extensive, multivariate attributes in the analysis of the genealogy without cluttering the graph. We validate our designs by conducting case studies with our domain collaborators.
大多数对公众和个人健康构成重大挑战的疾病是由遗传和环境因素共同作用引起的。在本文中，我们介绍了 Lineage，这是一种新颖的可视化分析工具，旨在为研究此类多因素疾病的领域专家提供支持，其研究背景是系谱。将病例之间的家族关系与其他数据结合起来，可以深入了解可能与这些疾病相关的共享基因组变异和共同的环境暴露。我们引入了数据和任务抽象，并认为基于系谱、临床和遗传数据分析此类疾病的问题可以映射到多元图可视化问题上。我们的设计研究的主要贡献是一种新颖的树状多元图表示形式，我们将其应用于系谱以及这些家庭中个体的临床数据。我们引入了数据驱动的聚合方法来扩展到多个家庭。通过设计系谱图布局与表格视图对齐，我们能够在不使图混乱的情况下，在系谱分析中纳入大量的多元属性。我们通过与领域合作伙伴进行案例研究来验证我们的设计。
