PDF(Pubmed)
Abstract：
Phylogeographic analyses are able to exploit the location data associated with sampled molecular sequences to reconstruct the spatio-temporal dispersal history of a pathogen. Visualisation software is commonly used to facilitate the interpretation of the accompanying estimation results, as these are not always easily interpretable. spread.gl is a powerful, open-source and feature-rich browser application that enables smooth, intuitive and user-friendly visualisation of both discrete and continuous phylogeographic inference results, enabling the animation of pathogen geographic dispersal through time. spread.gl can render and combine the visualisation of several data layers, including a geographic layer (e.g., a world map), multiple layers that contain information extracted from the input phylogeny, and different types of layers that represent environmental data. As such, users can explore which environmental data may have shaped pathogen dispersal patterns, that can subsequently be formally tested through more principled statistical analyses. We showcase the visualisation features of spread.gl on several representative pathogen dispersal examples, including the smooth animation of a phylogeny encompassing over 17,000 genomic sequences resulting from a large-scale SARS-CoV-2 analysis.
摘要：
系统地理学分析能够利用与采样的分子序列相关的位置数据来重建病原体的时空扩散历史。可视化软件通常用于帮助解释附带的估计结果，因为这些并不总是容易解释的。spread.gl是一个强大的，开源和功能丰富的浏览器应用程序，使流畅，离散和连续系统地理推断结果的直观和用户友好的可视化，通过时间实现病原体地理传播的动画。spread.gl可以渲染和组合几个数据层的可视化，包括地理层(例如，世界地图)，包含从输入系统发育中提取的信息的多个层，以及表示环境数据的不同类型的层。因此，用户可以探索哪些环境数据可能塑造了病原体扩散模式，随后可以通过更有原则的统计分析进行正式测试。我们展示了传播的可视化功能。关于几个代表性病原体传播实例的GL，包括由大规模SARS-CoV-2分析产生的包含17,000多个基因组序列的系统发育的平滑动画。
