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One of the main objectives in the analysis of microarray experiments is the identification of genes that are differentially expressed under two experimental conditions. Many analysis methods for identifying differentially expressed (DE) genes were developed. Here we compared three analysis methods which are the significance analysis of microarrays (SAM), the t-based meta-analysis (TB) and the rank product meta-analysis (RP). We found out strengths and weaknesses of the three analysis methods with respected to three measures, which we referred to as efficiency, stringency, and ability to handle heterogeneity. The TB is more efficient than the SAM and the RP. In addition, the RP is the best analysis method of the three with other two measures. We concluded that meta-analysis is a powerful tool for identifying differentially expressed genes.