Pathway analysis comparison using Crohn's disease genome wide association studies

• Main Authors: Cho Judy, Abraham Clara, Ballard David, Zhao Hongyu
• Format: Article
• Language: English
• Published: BMC 2010-06-01
• Series: BMC Medical Genomics
• Online Access: http://www.biomedcentral.com/1755-8794/3/25

<p>Abstract</p> <p>Background</p> <p>The use of biological annotation such as genes and pathways in the analysis of gene expression data has aided the identification of genes for follow-up studies and suggested functional information to uncharacterized genes. Several studies have applied similar methods to genome wide association studies and identified a number of disease related pathways. However, many questions remain on how to best approach this problem, such as whether there is a need to obtain a score to summarize association evidence at the gene level, and whether a pathway, dominated by just a few highly significant genes, is of interest.</p> <p>Methods</p> <p>We evaluated the performance of two pathway-based methods (Random Set, and Binomial approximation to the hypergeometric test) based on their applications to three data sets of Crohn's disease. We consider both the disease status as a phenotype as well as the residuals after conditioning on IL23R, a known Crohn's related gene, as a phenotype.</p> <p>Results</p> <p>Our results show that Random Set method has the most power to identify disease related pathways. We confirm previously reported disease related pathways and provide evidence for IL-2 Receptor Beta Chain in T cell Activation and IL-9 signaling as Crohn's disease associated pathways.</p> <p>Conclusions</p> <p>Our results highlight the need to apply powerful gene score methods prior to pathway enrichment tests, and that controlling for genes that attain genome wide significance enable further biological insight.</p>