Recently developed, the biotechnology denominated Microarrays permits a simultaneous monitoring of the gene expression values of hundred thousands of genes; fact that introduces a new interpretation of the results obtained in researches developed in many distinct areas including, for example, Pharmacology and Medicine, once the obtained results are read according to the molecular level.However, despite the fact that much technology is used in the Microarrays technique, its application still causes some implications, for example, the countless sources of existing variance, the scale of answers or the natural difficulty in analyzing a large number of genetic fragments measured by few experimental units.Facing such complications, a lot of methodologies were suggested in order to reduce or eliminate the problems caused by the Microarrays technique and also foster the obtainment of more reliable results from the gene expression values, yet many challenges still persist.Under this perspective, the present work aimed at exploring two alternative methodologies regarding concepts, despite both were contextualized according to the Microarrays problem and applied with the same objective: enabling the identification of the genes differently expressed under different experimental conditions.The first methodology was composed by the application of Analysis of Variance Models of fixed effects with changes in the test statistics, correction methodologies for multiple tests and volcano plot.The second methodology consisted of the contextualization and application of the Item Response Theory -IRT towards the Microarrays experiments, being this one not much explored in analysis that use this kind of data, but enabling the selection of genes differently expressed from an estimated latent trait for each gene and the construction of a scale for the categories of gene expression answers.The motivation for the present work came from an experiment of Microarrays with congenic mice made available by the Cardiology and Molecular Genetics Laboratory of the Heart Institute (InCor-USP) that aimed at identifying "genes" associated with hypertension.