PennPRS:一个集中式云计算平台,用于精准医学中高效的多基因风险评分培训.
Jin Jin1,2, Bingxuan Li3, Xiyao Wang4
1Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
medRxiv : the preprint server for health sciences
|February 24, 2025
概括
宾夕法尼亚PRS是一个新的云平台,用于在没有个体遗传数据的情况下训练多基因风险得分 (PRS). 该工具提高了PRS模型培训的可访问性,使全球精准医学研究受益.
科学领域:
- 遗传学 是一个遗传学.
- 计算生物学 计算生物学
- 精准医学是一门精准的医学.
背景情况:
- 多基因风险评分 (PRS) 对于疾病风险预测和精准医学中的分层至关重要.
- 由于计算资源的限制,复杂的方法和数据隐私问题,PRS的广泛采用受到阻碍.
研究的目的:
- 推出PennPRS,一个可扩展的云平台,用于在线可访问的多基因风险评分 (PRS) 模型培训.
- 通过新的伪训练算法,使PRS模型培训无需个人级遗传数据.
主要方法:
- 开发用于多种PRS方法和整体方法的伪训练算法.
- 使用广泛的模拟和大规模真实数据分析对超过6000种表型进行验证.
- 实施基于云的平台,以七种方法支持单个和多个祖先的PRS培训.
主要成果:
- 在没有直接访问个体遗传数据的情况下,PennPRS可以实现PRS模型培训.
- 该平台支持用户数据上传和与GWAS目录 (超过27,000个数据集) 的集成.
- 训练有素的PRS模型可以公开访问超过8,000种表型,以及它们的重量.
结论:
- PennPRS提供了一种新的云计算解决方案,以实现PRS应用程序的民主化.
- 该平台解决了计算资源的差异,改善了全球PRS研究社区的可访问性.
- 促进PRS在精准医学研究和临床实践中的更广泛实施.
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