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在控制错误发现率的同时进行样本量的快速计算及其在微阵列分析中的应用。

Quick calculation for sample size while controlling false discovery rate with application to microarray analysis.

作者信息

Liu Peng, Hwang J T Gene

机构信息

Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA.

出版信息

Bioinformatics. 2007 Mar 15;23(6):739-46. doi: 10.1093/bioinformatics/btl664. Epub 2007 Jan 19.

Abstract

MOTIVATION

Sample size calculation is important in experimental design and is even more so in microarray or proteomic experiments since only a few repetitions can be afforded. In the multiple testing problems involving these experiments, it is more powerful and more reasonable to control false discovery rate (FDR) or positive FDR (pFDR) instead of type I error, e.g. family-wise error rate (FWER). When controlling FDR, the traditional approach of estimating sample size by controlling type I error is no longer applicable.

RESULTS

Our proposed method applies to controlling FDR. The sample size calculation is straightforward and requires minimal computation, as illustrated with two sample t-tests and F-tests. Based on simulation with the resultant sample size, the power is shown to be achievable by the q-value procedure.

AVAILABILITY

A Matlab code implementing the described methods is available upon request.

摘要

动机

样本量计算在实验设计中很重要,在微阵列或蛋白质组学实验中更是如此,因为只能进行少量重复实验。在涉及这些实验的多重检验问题中,控制错误发现率(FDR)或正错误发现率(pFDR)比控制I型错误(例如家族性错误率(FWER))更有效且更合理。在控制FDR时,通过控制I型错误来估计样本量的传统方法不再适用。

结果

我们提出的方法适用于控制FDR。样本量计算很简单,所需计算量最小,如两个样本t检验和F检验所示。基于使用所得样本量进行的模拟,通过q值程序显示出该功效是可以实现的。

可用性

可根据要求提供实现所述方法的Matlab代码。

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