Are a set of microarrays independent of each other?
Are a set of microarrays independent of each other?
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DOI：
10.1214/09-aoas236
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发表时间：
2009-01-01
期刊：
影响因子：
--
通讯作者：
Efron B
中科院分区：
文献类型：
--
作者：
Efron B
观察到行可能相关的 m × n 矩阵 X 后，我们希望检验列彼此独立的假设。我们的动机来自微阵列研究，其中 X 行记录 m 个不同基因的表达水平，通常高度相关，而列代表 n 个单独的微阵列，大概是独立获得的。独立性假设是所有熟悉的微阵列分析排列、交叉验证和引导方法的基础，因此了解独立性何时失败非常重要。我们开发非参数和正态理论测试方法。 X 的行和列相关性以一种使测试过程复杂化的方式相互作用，本质上是通过降低相关估计量的准确性。
Having observed an m × n matrix X whose rows are possibly correlated, we wish to test the hypothesis that the columns are independent of each other. Our motivation comes from microarray studies, where the rows of X record expression levels for m different genes, often highly correlated, while the columns represent n individual microarrays, presumably obtained independently. The presumption of independence underlies all the familiar permutation, cross-validation, and bootstrap methods for microarray analysis, so it is important to know when independence fails. We develop nonparametric and normal-theory testing methods. The row and column correlations of X interact with each other in a way that complicates test procedures, essentially by reducing the accuracy of the relevant estimators.