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Detecting differential expression in microarray data: comparison of optimal procedures
Authors:Elena Perelman  Alexander Ploner  Stefano Calza  Yudi Pawitan
Institution:(1) Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17177 Stockholm, Sweden;(2) Department of Biomedical Sciences and Biotechnologies, , Brescia, Italy
Abstract:

Background  

Many procedures for finding differentially expressed genes in microarray data are based on classical or modified t-statistics. Due to multiple testing considerations, the false discovery rate (FDR) is the key tool for assessing the significance of these test statistics. Two recent papers have generalized two aspects: Storey et al. (2005) have introduced a likelihood ratio test statistic for two-sample situations that has desirable theoretical properties (optimal discovery procedure, ODP), but uses standard FDR assessment; Ploner et al. (2006) have introduced a multivariate local FDR that allows incorporation of standard error information, but uses the standard t-statistic (fdr2d). The relationship and relative performance of these methods in two-sample comparisons is currently unknown.
Keywords:
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