GENEasso:来自GWAS总结统计数据的复杂疾病中可靠的疾病基因关联的精选资源
Tao Jiang1, Mengting Shao1, Junjie Wang2
1Jiangsu Key Laboratory for Biomedical Electromagnetic Precision Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
Nucleic acids research
|October 30, 2025
概括
基因asso集成了多种基于基因的方法来识别来自全基因组关联研究 (GWAS) 的疾病相关基因. 这个平台增强了复杂疾病研究的生物解释性和可重现性.
科学领域:
- 遗传学和生物信息学 遗传学和生物信息学
- 复杂疾病研究 复杂疾病研究
背景情况:
- 全基因组关联研究 (GWAS) 确定与疾病相关的遗传变异.
- 基于基因的关联分析通过聚合变异级信号来提高生物解释性.
- 现有的方法,如全转录组关联研究 (TWAS),专注于表达介导的效应,限制了全面的基因水平分析.
研究的目的:
- 开发一个全面的平台,GENEasso,整合多个基因水平的统计框架,用于强大的疾病基因关联探索.
- 为分析不同种群和组织的复杂疾病关联提供资源.
- 让用户上传自己的GWAS数据进行分析和比较.
主要方法:
- 整合了七种代表性的基因相关联方法.
- 对8226个精选的GWAS总结统计数据的系统应用.
- 开发一个Web服务器来分析用户提交的数据,并与参考数据库进行比较.
主要成果:
- 产生了716122个高度可靠的疾病基因关联.
- 支持跨方法共识评分,组织特异性丰富和祖先分层分析.
- 通过曼哈顿地图和基于本体学的导航来交互探索结果.
结论:
- 通过交叉方法一致性,GENEasso提高了疾病基因关联的可信性和可重复性.
- 该平台为复杂疾病提供了用户定义的基因优先级工作流.
- GENEasso是一个开放式访问资源,促进基因关联的更广泛研究.
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