On parametric empirical Bayes methods for comparing multiple groups using replicated gene expression profiles
On parametric empirical Bayes methods for comparing multiple groups using replicated gene expression profiles
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DOI：
10.1002/sim.1548
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发表时间：
2003-12-30
影响因子：
2
通讯作者：
Gould, MN
中科院分区：
文献类型：
--
作者：
Kendziorski, CM;Newton, MA;Gould, MN
DNA微阵列提供了前所未有的大规模基因表达的观点，因此，已经成为研究不同生物系统的基本测量工具。统计问题比比皆是，但许多传统的数据分析方法并不适用，这在很大程度上是因为成千上万的个体基因被测量，而相对较少的复制。经验贝叶斯方法为微阵列数据分析提供了一种自然的方法，因为它们可以显着降低推理问题的维度，同时通过使用整个阵列的信息来补偿相对较少的重复。我们提出了一个通用的经验贝叶斯建模方法，允许在多种条件下复制表达谱。分层混合模型考虑了基因之间平均表达水平的差异、细胞类型之间给定基因的差异表达以及测量波动。两个不同的参数化被认为是：一个基于伽马分布的测量模型和一个基于对数正态分布的测量。错误发现率和相关的操作特性的方法进行了评估，在模拟研究。我们还展示了如何在一个版本的模型中的差分表达的后验几率与两个样本均值的算术平均数与几何平均数的比率有关。该方法用于大鼠乳腺癌的研究，其中可能有四种不同的表达模式。版权所有（C）2003约翰威利父子有限公司。
DNA microarrays provide for unprecedented large-scale views of gene expression and, as a result, have emerged as a fundamental measurement tool in the study of diverse biological systems. Statistical questions abound, but many traditional data analytic approaches do not apply, in large part because thousands of individual genes are measured with relatively little replication. Empirical Bayes methods provide a natural approach to microarray data analysis because they can significantly reduce the dimensionality of an inference problem while compensating for relatively few replicates by using information across the array. We propose a general empirical Bayes modelling approach which allows for replicate expression profiles in multiple conditions. The hierarchical mixture model accounts for differences among genes in their average expression levels, differential expression for a given gene among cell types, and measurement fluctuations. Two distinct parameterizations are considered: a model based on Gamma distributed measurements and one based on log-normally distributed measurements. False discovery rate and related operating characteristics of the methodology are assessed in a simulation study. We also show how the posterior odds of differential expression in one version of the model is related to the ratio of the arithmetic mean to the geometric mean of the two sample means. The methodology is used in a study of mammary cancer in the rat, where four distinct patterns of expression are possible. Copyright (C) 2003 John Wiley Sons, Ltd.