Microarrays and Their Use in a Comparative Experiment

By B. Elton, Robert Tibshirani, Virginia W. Goss, Gilbert Chu. 2000

87 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/686abad29d835044cf97434c3c0fb9f80321c856

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Citations in the corpus

On parametric empirical Bayes methods for comparing multiple groups using replicated gene expression profiles (2003, methodology): “[10, 11] describe empirical Bayesian calculations which relax the parametric assumptions.”
A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments (2002, methodology): “The mixture model approach follows the novel idea of the EB approach of Efron et al. (2000) and of the SAM of Tusher et al. (2001): estimating the null distribution using z j s.”
Multiple Hypothesis Testing in Microarray Experiments (2003, methodology): “In contrast to the earlier version of SAM in Efron et al. (2000), the SAM procedure in Tusher, Tibshirani and Chu (2001) is not entirely based on the permutation distribution of the order statistics and controls the PCER in the strong sense.”
Empirical Bayes Analysis of a Microarray Experiment (2001, methodology): “(Efron et al. (2000) showed that in fact a better “s4v5” can be obtained in the radiation experiment by removing plates U1A and I1A from the dataset (1.1); a processing error appears to have degraded the results from I1A.) Our tactic of choosing the Z mapping to maximize p14Z5 is nearly equivalent t”
Statistical tests for differential expression in cDNA microarray experiments (2003, background): “• The SAM (‘significance analysis of microarrays’) test statistic is S = Rg c + —––— SEg , where the constant c can be taken to be the 90th percentile SEg value [47].”
A Survey on Filter Techniques for Feature Selection in Gene Expression Microarray Analysis (2012, methodology): “According to [40] there are two strategies to obtain p1: a bayesian and a frequentist approach.”