Functional Analysis: Evaluation of Response Intensities - Tailoring ANOVA for Lists of Expression Subsets

Background: Microarray data is frequently used to characterize the expression profile of a whole genome and to compare the characteristics of that genome under several conditions. Geneset analysis methods have been described previously to analyze the expression values of several genes related by known biological criteria (metabolic pathway, pathology signature, co-regulation by a common factor, etc.) at the same time and the cost of these methods allows for the use of more values to help discover the underlying biological mechanisms. Results: As several methods assume different null hypotheses, we propose to reformulate the main question that biologists seek to answer. To determine which genesets are associated with expression values that differ between two experiments, we focused on three ad hoc criteria: expression levels, the direction of individual gene expression changes (up or down regulation), and correlations between genes. We introduce the FAERI methodology, tailored from a t...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Fabrice Berger, Bertrand De Meulder, Anthoula Gaigneaux, Sophie Depiereux, Eric Bareke, Michael Pierre, Benoît De Hertogh, Mauro Delorenzi, Eric Depiereux
• Keywords: BMCBI 2010, Expression Levels, Expression Profile, Expression Values