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