Ausin, A. C.Gómez Villegas, Miguel ÁngelGonzález Pérez, BeatrizRodríguez Bernal, María TeresaSalazar Mendoza, IsabelSanz San Miguel, Luis2023-06-202023-06-202011Ausín, M. C., Gómez Villegas, M. Á., González Pérez, B. et al. «Bayesian Analysis of Multiple Hypothesis Testing with Applications to Microarray Experiments». Communications in Statistics - Theory and Methods, vol. 40, n.o 13, abril de 2011, pp. 2276-91. DOI.org (Crossref), https://doi.org/10.1080/03610921003778183.0361-092610.1080/03610921003778183https://hdl.handle.net/20.500.14352/42207Recently, the field of multiple hypothesis testing has experienced a great expansion, basically because of the new methods developed in the field of genomics. These new methods allow scientists to simultaneously process thousands of hypothesis tests. The frequentist approach to this problem is made by using different testing error measures that allow to control the Type I error rate at a certain desired level. Alternatively, in this article, a Bayesian hierarchical model based on mixture distributions and an empirical Bayes approach are proposed in order to produce a list of rejected hypotheses that will be declared significant and interesting for a more detailed posterior analysis. In particular, we develop a straightforward implementation of a Gibbs sampling scheme where all the conditional posterior distributions are explicit. The results are compared with the frequentist False Discovery Rate (FDR) methodology. Simulation examples show that our model improves the FDR procedure in the sense that it diminishes the percentage of false negatives keeping an acceptable percentage of false positives.engBayesian Analysis of Multiple Hypothesis Testing with Applications to Microarray Experimentsjournal articlehttps//doi.org/10.1080/03610921003778183https://www.tandfonline.com/doi/full/10.1080/03610921003778183restricted access519.22Empirical Bayes methodsFalse discovery rateGibbs samplerMixture modelsMultiple hypothesis testingFalse Discovery RateGene-ExpressionEmpirical BayesModelStatistics & ProbabilityEstadística matemática (Matemáticas)1209 Estadística