选择扫描中的多重测试校正,使用身份按下降段
Seth D Temple1, Sharon R Browning2
1Department of Statistics, University of Washington, Seattle, WA, USA; Department of Statistics, University of Michigan, Ann Arbor, MI, USA; Michigan Institute for Data and AI in Society, University of Michigan, Ann Arbor, MI, USA.
American journal of human genetics
|September 27, 2025
概括
纠正基因适应扫描中的多重测试对于避免错误发现至关重要. 这项研究引入了一种有效的方法,使用身份由血统 (IBD) 建模来准确确定全基因组显著性水平,以检测最近的阳性选择.
科学领域:
- 人口遗传学 人口遗传学
- 基因组学就是基因组学.
- 进化生物学 进化生物学
背景情况:
- 选择扫描中的多重测试可以导致遗传适应的错误发现.
- 由于复杂的扫描统计数据,推导全基因组显著性水平和验证家族智能错误率 (FWER) 控制是具有挑战性的.
研究的目的:
- 提出一种计算效率高的方法,用于确定基因组范围的显著水平,以身份为基因 (IBD) 扫描为基础,用于最近的阳性选择.
- 为了应对多次测试纠正在检测遗传适应的挑战.
主要方法:
- 模拟身份按血统 (IBD) 率的自相关性.
- 开发一种方法来确定基于IBD的扫描的全基因组显著性水平.
- 使用全基因组模拟来验证该方法的性能.
主要成果:
- 拟议的方法证明了对家庭智能错误率 (FWER) 的近似控制.
- 该方法适应了整个基因组的测试间隔.
- 扫描实现了超过50%的功率来检测硬扫描,选择系数>=0.01和代基因频率在25-75%之间.
结论:
- 该研究成功地确定了在不同祖先群体 (非洲,欧洲,南亚) 的人类基因中IBD细分数的统计学上显著的过剩.
- 在删除丰富区域中发现了两种共享的IBD过量信号,跨祖先群体,表明潜在的共同适应性事件.
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