格拉佩文 - - 图形分析管道开发环境用于传染病
John-Stuart Brittain1,2, Joseph Tsui2,3, Rhys Inward2,3
1Oxford Research Software Engineering Group, University of Oxford, Oxford, England, UK.
Wellcome open research
|June 30, 2025
概括
通过模块化管道,GRAPEVNE简化了传染病数据分析,提供实时公共卫生洞察力和流行病准备. 这个平台增强了数据驱动的发现和研究中的可重复性.
科学领域:
- 计算生物学 计算生物学
- 流行病学 流行病学
- 生物信息学是一种生物信息学.
背景情况:
- 传染病数据量和多样性的增加为实时公共卫生决策提供了机会.
- 全球数据利用受到预处理,数据科学能力和资源获取差异的阻碍.
研究的目的:
- 开发一个平台,以促进地方一级的大规模传染病数据分析,而无需跨境数据共享.
- 简化复杂,重复的数据分析工作流程的创建,执行和共享.
主要方法:
- 开发了GRAPEVNE (图形分析管道开发环境),一个使用Snakemake工作流管理系统的平台.
- 实施了模块化管道方法,每个模块都是一个独立的Snakemake工作流.
- 通过每个模块内的配置,脚本和元数据来确保互操作性.
主要成果:
- GRAPEVNE支持多种应用,包括基因组分析,流行病学建模和大规模数据处理.
- 该平台简化了复杂的工作流程,促进了数据驱动的发现,并提高了研究可重复性.
- 证明了端到端自动化与登革热病毒管道用于遗传学分析和遗传学推断.
结论:
- 通过简化传染病数据分析,GRAPEVNE赋予研究人员和公共卫生机构权力.
- 该开源的模块化平台增强了实时疫情监测,预测和流行病学数据处理.
- 通过用户驱动的生态系统,促进生物医学和流行病学研究的持续创新.
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