The recent development of microarray technology has led statisticians and bioinformaticians to develop new statistical methodologies for comparing different biological samples. The objective is to identify a small number of differentially expressed genes from among thousands. In quantitative proteomics, analysis of protein expression using two-dimensional gel electrophoresis shows some similarities with transcriptomic studies. Thus, the goal of this study was to evaluate different data analysis methodologies widely used in array analysis using different proteomic data sets of hundreds of proteins. Even with few replications, the significance analysis of microarrays method appeared to be more powerful than the Student's t test in truly declaring differentially expressed proteins. This procedure will avoid wasting time due to false positives and losing information with false negatives.
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