论文标题
药物基因组学研究中不平等样本量的一种修改的最大对比度方法
A modified maximum contrast method for unequal sample sizes in pharmacogenomic studies
论文作者
论文摘要
在药物基因组学研究中，生物医学研究人员通常通过使用Kruskal-Wallis检验或对数转换后的数据来分析基因型和生物反应之间的关联。但是，由于这些方法检测到意外的生物反应模式，因此检测预期模式的功率降低了。以前，我们提出了最大对比方法和在药物基因组学研究中为不等样本量的最大对比度方法的组合。但是，我们注意到，置换的修改后的最大对比统计量的分布取决于滋扰参数$σ^2 $，即种群差异。在本文中，我们提出了一种经过修改的最大对比方法，其统计量不取决于滋扰参数。此外，我们通过模拟研究比较了这些方法的性能。模拟结果表明，修改后的最大对比方法给出了最低的假阳性速率。因此，此方法对于在某些条件下检测真实的响应模式具有强大的功能。此外，它比列出的修改后的最大对比度方法更快，更准确。根据这些结果，我们建议在给定情况下选择适当方法的经验法则。
In pharmacogenomic studies, biomedical researchers commonly analyze the association between genotype and biological response by using the Kruskal--Wallis test or one-way analysis of variance (ANOVA) after logarithmic transformation of the obtained data. However, because these methods detect unexpected biological response patterns, the power for detecting the expected pattern is reduced. Previously, we proposed a combination of the maximum contrast method and the permuted modified maximum contrast method for unequal sample sizes in pharmacogenomic studies. However, we noted that the distribution of the permuted modified maximum contrast statistic depends on a nuisance parameter $σ^2$, which is the population variance. In this paper, we propose a modified maximum contrast method with a statistic that does not depend on the nuisance parameter. Furthermore, we compare the performance of these methods via simulation studies. The simulation results showed that the modified maximum contrast method gave the lowest false-positive rate; therefore, this method is powerful for detecting the true response patterns in some conditions. Further, it is faster and more accurate than the permuted modified maximum contrast method. On the basis of these results, we suggest a rule of thumb to select the appropriate method in a given situation.
