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spread.gl:在高性能浏览器应用程序中可视化病原体的传播

Yimin Li^1,2, Nena Bollen^1,2, Samuel L Hong¹

¹Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven 3000, Belgium.

Bioinformatics (Oxford, England)

|December 3, 2024

概括

我们开发了Spread.gl,这是一个开源应用程序,用于可视化病原体传播历史. 该工具有助于研究人员了解时空传播模式,并探索影响疾病传播的环境因素.

科学领域:

流行病学流行病学
计算生物学计算生物学
生物信息学是一种生物信息学.

背景情况:

贝叶斯哲学地理分析对于了解病原体传播历史至关重要.
解释复杂的植物地理数据需要先进的可视化工具.

研究的目的:

开发一个直观和功能丰富的可视化工具,用于植物地理重建.
为了能够探索影响病原体传播的环境因素.

主要方法:

开发Spread.gl,一个开源的,基于浏览器的应用程序.
对离散和连续的植物地理推理的可视化.
病原体通过时间的地理分散的动画.
植物遗传数据与环境数据层的整合.

主要成果:

斯普雷德.格尔 (Spread.gl) 提供了对植物地理数据的平滑和直观可视化.
该应用程序支持动画病原体随时间的传播.
使用大规模的SARS-CoV-2基因组数据集 (>17000个序列) 证明了实用性.

结论:

Spread.gl增强了复杂的植物地理分析的解释.
有助于探索病原体传播的环境驱动因素.
为流行病学研究和公共卫生提供了宝贵的资源.

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