Incorporating the empirical null hypothesis into the Benjamini-Hochberg procedure.
Incorporating the empirical null hypothesis into the Benjamini-Hochberg procedure.
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DOI：
10.1515/1544-6115.1735
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发表时间：
2012-07-26
影响因子：
0.9
通讯作者：
Ghosh, Debashis
中科院分区：
文献类型：
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作者：
Ghosh, Debashis
针对多重测试问题，benjamin - hochberg （B-H）法已成为应用中非常流行的一种方法。我们展示了如何将B-H过程解释为基于与p值分布对应的间隔的检验。这种解释导致了经验零假设的结合，这是Efron（2004）创造的一个术语。我们为B-H过程的经验零假设开发了一种混合建模方法，并证明了关于有限样本和错误发现率渐近控制的一些理论结果。通过对两个高通量数据集以及模拟数据的应用说明了该方法。
For the problem of multiple testing, the Benjamini-Hochberg (B-H) procedure has become a very popular method in applications. We show how the B-H procedure can be interpreted as a test based on the spacings corresponding to the p-value distributions. This interpretation leads to the incorporation of the empirical null hypothesis, a term coined by Efron (2004). We develop a mixture modelling approach for the empirical null hypothesis for the B-H procedure and demonstrate some theoretical results regarding both finite-sample as well as asymptotic control of the false discovery rate. The methodology is illustrated with application to two high-throughput datasets as well as to simulated data.