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微阵列实验中固定样本量下功效评估及错误发现率的实用指南。

Practical guidelines for assessing power and false discovery rate for a fixed sample size in microarray experiments.

作者信息

Tong Tiejun, Zhao Hongyu

机构信息

Department of Applied Mathematics, University of Colorado, Boulder, CO 80309, U.S.A.

出版信息

Stat Med. 2008 May 20;27(11):1960-72. doi: 10.1002/sim.3237.

Abstract

One major goal in microarray studies is to identify genes having different expression levels across different classes/conditions. In order to achieve this goal, a study needs to have an adequate sample size to ensure the desired power. Owing to the importance of this topic, a number of approaches to sample size calculation have been developed. However, due to the cost and/or experimental difficulties in obtaining sufficient biological materials, it might be difficult to attain the required sample size. In this article, we address more practical questions for assessing power and false discovery rate (FDR) for a fixed sample size. The relationships between power, sample size and FDR are explored. We also conduct simulations and a real data study to evaluate the proposed findings.

摘要

微阵列研究的一个主要目标是识别在不同类别/条件下具有不同表达水平的基因。为了实现这一目标,一项研究需要有足够的样本量以确保所需的检验效能。由于这个主题的重要性,已经开发了许多样本量计算方法。然而,由于获取足够生物材料的成本和/或实验困难,可能难以达到所需的样本量。在本文中,我们针对固定样本量评估检验效能和错误发现率(FDR)提出了更实际的问题。探讨了检验效能、样本量和错误发现率之间的关系。我们还进行了模拟和实际数据研究以评估所提出的结果。

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