Detecting differential gene expression with a semiparametric hierarchical mixture method.

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Significance analysis of functional categories in gene expression studies: a structured permutation approach (2005, methodology): “An appropriate test statistic is calculated for each gene and used to assign a parametric or permutation-based p-value (Tusher et al., 2001; Dudoit et al., 2002b; Newton et al., 2004).”
Microarray data analysis: from disarray to consolidation and consensus (2006, background): “FDR is equivalent or related to several other metrics that quantify the confidence we can have that any particular gene is differentially expresse”
A general framework for multiple testing dependence (2008, methodology): “Variations on this approach have been suggested, such as estimating a q-value for each test (19) or a posterior error probability (20).”
Use of within-array replicate spots for assessing differential expression in microarray experiments (2005, background): “…each individual gene can be made more reliable by making use of information generated from the whole ensemble of genes (Newton et al., 2001; Tusher et al., 2001; Efron et al., 2001; Efron and Tibshirani, 2002; L¨onnstedt and Speed, 2002; Kendziorski et al., 2003; Newton et al., 2004; Smyth, 2004).”
Harnessing naturally randomized transcription to infer regulatory relationships among genes (2007, neutral): “[17,65].”