Microarray experiments examine the change in transcript levels of tens of thousands of genes simultaneously. To derive meaningful data, biologists investigate the response of genes within specific pathways. Pathways are comprised of genes that interact to carry out a particular biological function. Existing methods for analyzing pathways focus on detecting changes in the mean or over-representation of the number of differentially expressed genes relative to the total of genes within the pathway. The issue of how to incorporate the influence of correlation among the genes is not generally addressed.
['Mayer Alvo', 'Zhongzhu Liu', 'Andrew Williams', 'Carole L. Yauk']
Testing for mean and correlation changes in microarray experiments: an application for pathway analysis