Mixed directional false discovery rate control in multiple pairwise comparisons using weighted p-values
Mixed directional false discovery rate control in multiple pairwise comparisons using weighted p-values
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DOI：
10.1002/bimj.201300242
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发表时间：
2015-01-01
影响因子：
1.7
通讯作者：
Cui，Xinping
中科院分区：
文献类型：
--
作者：
Zhao，Haibing;Peddada，Shyamal D.;Cui，Xinping
在许多应用中，研究人员有兴趣根据结果变量在 k 个测试组之间进行成对比较。通常情况下，尺寸很大。例如，这种情况出现在涉及多个实验组的基因表达微阵列研究中。研究人员通常不仅对识别给定的一对实验组之间差异表达的基因感兴趣，而且对做出定向推论感兴趣，例如一个基因相对于另一个治疗组在一个治疗组中是否上调或下调。在这种情况下，除了误报（I 类错误）和漏报（II 类错误）等常见错误外，还可能会出现方向性错误（III 类错误）。例如，在剂量反应微阵列研究中，与低剂量组相比，高剂量组中的基因可能被宣称上调，但实际上并非如此。在本文中，我们引入了一种混合方向错误发现率（mdFDR）控制程序，使用加权p值来选择不同方向上的正值。权重定义为正面或负面发现比例两倍的倒数。所提出的程序已被数学证明可以将 mdFDR 控制在 α 水平，并且比郭等人提出的 GSP10 程序具有更大的功效（定义为非真零假设的预期比例）。 （2010）。还进行了模拟研究和实际数据分析，以表明所提出的程序比 GSP10 程序的性能更好。
In many applications, researchers are interested in makingqpairwise comparisons amongktest groups on the basis ofmoutcome variables. Often,mis very large. For example, such situations arise in gene expression microarray studies involving several experimental groups. Researchers are often not only interested in identifying differentially expressed genes between a given pair of experimental groups, but are also interested in making directional inferences such as whether a gene is up‐ or downregulated in one treatment group relative to another. In such situations, in addition to the usual errors such as false positive (Type I error) and false negative (Type II error), one may commit directional error (Type III error). For example, in a dose response microarray study, a gene may be declared to be upregulated in the high dose group compared to the low dose group when it is not. In this paper, we introduce a mixed directional false discovery rate (mdFDR) controlling procedure using weightedp‐values to select positives in different directions. The weights are defined as the inverse of two times the proportion of either positive or negative discoveries. The proposed procedure has been proved mathematically to control the mdFDR at level α and to have a larger power (which is defined as the expected proportion of nontrue null hypotheses) than the GSP10 procedure proposed by Guo et al. (2010). Simulation studies and real data analysis are also conducted to show the outperformance of the proposed procedure than the GSP10 procedure.