Comparative Analysis of Gene Sets in the Gene Ontology Space under the Multiple Hypothesis Testing Framework

The Gene Ontology (GO) resource can be used as a powerful tool to uncover the properties shared among, and specific to, a list of genes produced by high-throughput functional genomics studies, such as microarray studies. In the comparative analysis of several gene lists, researchers maybe interested in knowing which GO terms are enriched in one list of genes but relatively depleted in another. Statistical tests such as Fisher's exact test or Chi-square test can be performed to search for such GO terms. However, because multiple GO terms are tested simultaneously, individual p-values from individual tests do not serve as good indicators for picking GO terms. Furthermore, these multiple tests are highly correlated, usual multiple testing procedures that work under an independence assumption are not applicable. In this paper we introduce a procedure, based on False Discovery Rate (FDR), to treat this correlated multiple testing problem. This procedure calculates a moderately conserv...

• Type: Conference
• Year: 2004
• Where: CSB
• Authors: Sheng Zhong, Lu Tian, Cheng Li, Kai-Florian Storch, Wing Hung Wong
• Keywords: Bioinformatics, CSB 2004, GO Terms, Multiple Go Terms, Significant Go Terms