Large amounts of microarray experimental data are available in public repositories. Although a variety of tools have been developed to make use of these data, the number of tools that detect marker genes is limited. Identification of marker genes associated with a specific tissue/cell type is a fundamental challenge in genetic and genomic research. In addition to other genes, marker genes are of great importance for understanding the gene function, the molecular mechanisms underlying complex diseases, and may lead to the development of new drug targets. We have previously developed a Bioconductor R package (MGFM) for marker gene detection from microarray data. The tool is freely available from the Bioconductor web site (https://www.bioconductor.org/packages/release/bioc/html/MGFM.html), and it is also provided as an online application integrated into the CellFinder platform (http://cellfinder.org/analysis/marker). In this work, we applied our tool to a public microarray data set from the NCBI’s Gene Expression Omnibus public repository encompassing samples for 12 human tissues. We compared the set of predicted marker genes to a set of tissue-specific genes obtained from the Tissue-specific Gene Expression and Regulation (TiGER) database. Furthermore, we tested the performance of the tool using two normalization methods, RMA and YuGene. YuGene performed slightly better than RMA. Our tool identified 38,4 % or 37,9 % of the TiGER derived tissue-specific genes using YuGene or RMA, respectively.