交互式数据共享,用于基于多个问卷的暴露组全相关性研究和个性化环境和基因研究中的暴露组相关性
Dillon Lloyd1, John S House1, Farida S Akhtari1
1Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
Exposome
|March 1, 2024
概括
了解暴露组,或所有生命暴露,是健康的关键. PEGS Explorer可视化暴露相关性,有助于暴露全组关联研究 (ExWAS) 和疾病研究.
科学领域:
- 环境健康 环境健康
- 计算生物学是一种计算生物学.
- 基因组学就是基因组学.
背景情况:
- 暴露组包括整个生命中的所有个体暴露,对于理解共发生和健康影响至关重要.
- 全暴露组关联研究 (ExWAS) 正在出现,将暴露组与疾病联系起来,类似于全基因组关联研究 (GWAS).
- 有限的工具和数据共享阻碍了全面的暴露研究和对暴露与疾病关系的理解.
研究的目的:
- 开发一个Web应用程序,PEGS Explorer,用于探索各种环境和生活方式暴露之间的相关性.
- 为了解决缺乏可访问的数据和结果共享在exposome科学.
- 为了促进假设生成和在其他队伍中复制发现.
主要方法:
- 开发了PEGS Explorer网络应用程序,使用来自个性化环境和基因研究 (PEGS) 的数据.
- 严格计算暴露相关性,考虑各种数据类型.
- 整合了以前发表的ExWAS结果,并利用地球可视化来进行数据探索.
主要成果:
- PEGS Explorer允许可视化各种暴露 (环境,饮食,生活方式等) 之间的相关性. 与复杂疾病相关的.
- 该应用程序提供了一个集中资源,用于探索暴露组数据和以前发布的ExWAS发现.
- 促进了暴露组-疾病关联研究的上下文化,假设生成和复制.
结论:
- PEGS Explorer提高了对暴露组数据和ExWAS结果的可访问性,解决了该领域的关键差距.
- 该工具支持研究人员了解复杂的暴露关系及其对健康的影响.
- 未来的更新将确保PEGS Explorer仍然是暴露组科学的一个动态和有价值的资源.
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