MRanalysis:一个全面的在线平台,用于集成,多方法的门德尔随机化和相关的后GWAS分析
Abao Xing1, Tiantian Cai2, Haofan Du3
1Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macao, 999078, Macao SR.
GigaScience
|October 22, 2025
概括
MRanalysis和GWASkit简化了门德尔随机化 (MR) 和全基因组关联研究 (GWAS) 数据分析. 这些工具提高了遗传流行病学研究的可访问性,可靠性和效率.
科学领域:
- 流行病学 流行病学
- 遗传流行病学遗传流行病学
- 生物信息学是一种生物信息学.
背景情况:
- 门德尔随机化 (MR) 使用全基因组关联研究 (GWAS) 数据推断因果关系.
- 数据格式不一致,工作流标准化问题以及编程技能要求阻碍了MR的采用.
- 为了解决这些局限性,MR分析和GWASkit被开发出来.
研究的目的:
- 开发用于集成MR分析和GWAS数据预处理的用户友好工具.
- 降低MR分析的进入障碍,使其更容易获得和更有效.
- 加速遗传流行病学方面的发现,并为公共卫生战略提供信息.
主要方法:
- MRanalysis提供了一个无代码的,基于Web的平台,用于全面的MR分析.
- GWASkit为快速的GWAS数据预处理提供了一个独立的工具,包括rs ID转换和格式标准化.
- 这两种工具都有直观的界面,并显示出高精度和效率.
主要成果:
- MRanalysis支持单变量,多变量和调度MR分析,具有综合质量评估,功率估计和可视化.
- 与现有的工具相比,GWASkit显著提高了GWAS数据预处理的准确性和效率.
- 案例研究证实了MR分析和GWASkit的实际实用性和效率.
结论:
- MRanalysis和GWASkit使MR分析民主化,提高了其可访问性,可靠性和效率.
- 这些工具可以加速遗传发现,支持公共卫生倡议,并指导有针对性的干预.
- 核磁共振分析和GWASkit在理解基因-环境-健康结果关系方面取得了重大进展.
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