A method for computing the overall statistical significance of a treatment effect among a group of genes

Background: In studies that use DNA arrays to assess changes in gene expression, our goal is to evaluate the statistical significance of treatments on sets of genes. Genes can be grouped by a molecular function, a biological process, or a cellular component, e.g., gene ontology (GO) terms. The meaning of an affected GO group is often clearer than interpretations arising from a list of the statistically significant genes. Results: Computer simulations demonstrated that correlations among genes invalidate many statistical methods that are commonly used to assign significance to GO terms. Ignoring these correlations overstates the statistical significance. Meta-analysis methods for combining p-values were modified to adjust for correlation. One of these methods is elaborated in the context of a comparison between two treatments. The form of the correlation adjustment depends upon the alternative hypothesis. Conclusion: Reliable corrections for the effect of correlations among genes on th...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Robert R. Delongchamp, Taewon Lee, Cruz Velasco
• Keywords: Affected Go Group, BMCBI 2006, Go Term, Statistical Significance