Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

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 ...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Stefano Moretti, Danitsja van Leeuwen, Hans Gmuender, Stefano Bonassi, Joost van Delft, Jos Kleinjans, Fioravante Patrone, Domenico Franco Merlo
• Keywords: BMCBI 2008, CASh, Gene Expression, Gene Expression Analysis