Reconstructing networks of pathways via significance analysis of their intersections

Background: Significance analysis at single gene level may suffer from the limited number of samples and experimental noise that can severely limit the power of the chosen statistical test. This problem is typically approached by applying post hoc corrections to control the false discovery rate, without taking into account prior biological knowledge. Pathway or gene ontology analysis can provide an alternative way to relax the significance threshold applied to single genes and may lead to a better biological interpretation. Results: Here we propose a new analysis method based on the study of networks of pathways. These networks are reconstructed considering both the significance of single pathways (network nodes) and the intersection between them (links). We apply this method for the reconstruction of networks of pathways to two gene expression datasets: the first one obtained from a c-Myc rat fibroblast cell line expressing a conditional Mycestrogen receptor oncoprotein; the second o...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Mirko Francesconi, Daniel Remondini, Nicola Neretti, John M. Sedivy, Leon N. Cooper, Ettore Verondini, Luciano Milanesi, Gastone C. Castellani
• Keywords: BMCBI 2008, Chosen Statistical Test, Significance Analysis, Single Gene Level