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迪斯科P-ad:以距离相关性为基础的-价值调整增强了代谢学多重测试校正

Debmalya Nandy^1,2, Debashis Ghosh¹, Katerina Kechris^1,2

¹Department of Biostatistics & Informatics, Colorado School of Public Heath, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.

|January 24, 2025

概括

我们引入了一种新的方法,基于距离相关的p值调整 (DisCo P-ad),以改善omics研究中的多重测试校正. 这种方法提高了统计能力,减少了代谢学和其他高维数据分析中的错误发现.

科学领域:

生物统计学生物统计学
生物信息学是一种生物信息学.
基因组学就是基因组学.
代谢学代谢学代谢学

背景情况:

高通量omics研究产生了大量数据集与众多噪音变量.
在统计分析中,多次测试校正至关重要,以尽量减少错误或错过的发现.
现有的多重测试纠正方法在奥米克学,特别是代谢学,可能过于保守,宽容,或在他们的假设有限.

研究的目的:

建议对高维欧米数据的p值调整程序进行新的修改.
增强现有的基于自身分析的多重测试校正方法.
提高统计能力,减少代谢全组关联研究 (MWAS) 中的错误阳性.

主要方法:

通过对应矩阵的自身分析估计独立测试的有效数.
根据距离相关性提出修改,这是一个更一般的关联度量.
评估拟议方法在不同研究设计的代谢学数据上的性能.

主要成果:

基于距离相关性的p值调整 (DisCo P-ad) 与现有方法相比显示出更高的性能.
这项研究评估了常见的全基因组关联研究 (GWAS) 的p值调整程序和为MWAS量身定制的程序.
距离相关性在各种样本大小与特征比率,反应类型和代谢物分组中显示出更好的结果.

结论:

迪斯科P-ad为基于自身分析的多重测试校正提供了一种新的增强.
该方法可以增加统计能力,并减少omics研究中的假阳性.
DisCo P-ad适用于代谢学和其他高维的数据分析.

关键词:

相关的测试相关的测试.有效数量测试的测试.自己的分析.代谢组范围的关联研究.多次测试多次测试多次测试一个点向错误率的点向错误率.

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