caa a22 4500 37892575X CHVBK 20180305123617.0 cr unu---uuuuu 161128e20040212xx s 000 0 eng 10.2202/1544-6115.1027 doi (NATIONALLICENCE)gruyter-10.2202/1544-6115.1027 Smyth Gordon K. Walter and Eliza Hall Institute Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments [Elektronische Daten] [Gordon K Smyth] The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior odds of differential expression in a replicated two-color experiment using a simple hierarchical parametric model. The purpose of this paper is to develop the hierarchical model of Lonnstedt and Speed (2002) into a practical approach for general microarray experiments with arbitrary numbers of treatments and RNA samples. The model is reset in the context of general linear models with arbitrary coefficients and contrasts of interest. The approach applies equally well to both single channel and two color microarray experiments. Consistent, closed form estimators are derived for the hyperparameters in the model. The estimators proposed have robust behavior even for small numbers of arrays and allow for incomplete data arising from spot filtering or spot quality weights. The posterior odds statistic is reformulated in terms of a moderated t-statistic in which posterior residual standard deviations are used in place of ordinary standard deviations. The empirical Bayes approach is equivalent to shrinkage of the estimated sample variances towards a pooled estimate, resulting in far more stable inference when the number of arrays is small. The use of moderated t-statistics has the advantage over the posterior odds that the number of hyperparameters which need to estimated is reduced; in particular, knowledge of the non-null prior for the fold changes are not required. The moderated t-statistic is shown to follow a t-distribution with augmented degrees of freedom. The moderated t inferential approach extends to accommodate tests of composite null hypotheses through the use of moderated F-statistics. The performance of the methods is demonstrated in a simulation study. Results are presented for two publicly available data sets. ©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston Microarrays nationallicence Statistical Theory and Methods nationallicence microarrays nationallicence empirical Bayes nationallicence linear models nationallicence hyperparameters nationallicence differential expression nationallicence Statistical Applications in Genetics and Molecular Biology De Gruyter 3/1(2004-02-12), 1-25 3:1<1 2004 3 sagmb https://doi.org/10.2202/1544-6115.1027 text/html Onlinezugriff via DOI 1 research article jats NATIONALLICENCE 856 40 https://doi.org/10.2202/1544-6115.1027 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Smyth Gordon K. Walter and Eliza Hall Institute NATIONALLICENCE 773 0- Statistical Applications in Genetics and Molecular Biology De Gruyter 3/1(2004-02-12), 1-25 3:1<1 2004 3 sagmb CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-gruyter