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Background: In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions., Results: In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability., Conclusion: CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between coalitional games and statistics that resulted in a selection of genes with a potential impact in the regulation of complex pathways.

Differences in biological responses to exposure to hazardous airborne substances between children and adults have been reported, suggesting children to be more susceptible. Aim of this study was to improve our understanding of differences in susceptibility in cancer risk associated with air pollution by comparing genome-wide gene expression profiles in peripheral blood of children and their parents. Gene expression analysis was performed in blood from children and parents living in two different regions in the Czech Republic with different levels of air pollution. Data were analyzed by two different approaches: one method first selected significantly differentially expressed genes and analyzed these gene lists for overrepresented biological processes, whereas the other applied the T-profiler tool to directly perform pathway analyses on the total gene set without preselection of significantly modulated gene expressions. In addition, gene expressions in both children and adults were investigated for associations with micronuclei frequencies. Both analysis approaches returned considerably more genes or gene groups and pathways that significantly differed between children from both regions than between parents. Very little overlap was observed between children and adults. The two most important biological processes or molecular functions significantly modulated in children, but not in adults, are nucleosome and immune response related. Our study suggests differences between children and adults in relation to air pollution exposure at the transcriptome level. The findings underline the necessity of implementing environmental health policy measures specifically for protecting children's health.