Zheng Yimin, Zheng Zhihang, Rendeiro André F, Cheung Edwin
Cancer Centre, University of Macau, Taipa, Macau SAR.
Centre for Precision Medicine Research and Training, University of Macau, Taipa, Macau SAR.
Genome Biol. 2025 Jan 6;26(1):5. doi: 10.1186/s13059-024-03469-3.
Biological data visualization is challenged by the growing complexity of datasets. Traditional single-data plots or simple juxtapositions often fail to fully capture dataset intricacies and interrelations. To address this, we introduce "cross-layout," a novel visualization paradigm that integrates multiple plot types in a cross-like structure, with a central main plot surrounded by secondary plots for enhanced contextualization and interrelation insights. We also introduce "Marsilea," a Python-based implementation of cross-layout visualizations, available in both programmatic and web-based interfaces to support users of all experience levels. This paradigm and its implementation offer a customizable, intuitive approach to advance biological data visualization.
生物数据可视化面临着数据集日益复杂的挑战。传统的单数据图或简单并列方式往往无法充分捕捉数据集的复杂性和相互关系。为解决这一问题，我们引入了“交叉布局”，这是一种新颖的可视化范式，它以十字形结构集成多种图类型，中央为主图，周围环绕着副图，以增强情境化并深入了解相互关系。我们还引入了“Marsilea”，这是基于Python的交叉布局可视化实现，提供编程接口和基于网络的接口，以支持所有经验水平的用户。这种范式及其实现为推进生物数据可视化提供了一种可定制、直观的方法。
