高度参数化的多基因分数倾向于通过随机效应过度适应人口分层
Alan J Aw1,2,3, Jeremy McRae3, Elior Rahmani4
1Department of Statistics, University of California, Berkeley.
bioRxiv : the preprint server for biology
|February 14, 2024
概括
高度参数化的多基因分数 (PGSs) 可能包括随机遗传变异效应,而不是因果效应,由于人口结构. 这种随机性解释了为什么PGS在特定群体中表现良好,但概括不好,突出了随机性测试的必要性.
科学领域:
- 遗传学 遗传学 是一个
- 生物信息学是一种生物信息学.
- 统计遗传学 统计遗传学
背景情况:
- 多基因分数 (PGS) 越来越多地被用于临床遗传学,通常包含数千种遗传变异.
- 在高度参数化的PGS中包含的许多变体没有达到全基因组的意义,这引发了关于它们因果贡献的疑问.
结论:
- 非显著变异的随机性解释了队列特异性表现和高度参数化的PGSs的概括性之间的差异.
- 变异随机性测试对于可靠的PGS评估和临床应用至关重要.
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