Testing for over-representation of Gene Ontology (GO) biologic process categories (Harris et al., 2004; Ashburner et al., 2000) was performed using the Bioconductor package GOstats (Gentleman, 2004). Briefly, for each gene set tested, a list of unique Entrez-Gene identifiers was constructed. This list was then compared to the list of all known Entrez-Gene identifiers that are represented on the Affymetrix chipset Rat Genome 230 2.0. Identification of over-represented GO categories was then accomplished within GOstats using the hypergeometric distribution. To filter out uninteresting categories, only those categories with greater than 9 and less than 300 genes represented on the chipset were included in the analysis. GO categories were called significant at p < 0.05. In addition, network analyses were conducted with Ingenuity® Pathway Analysis (Ingenuity® Systems, www.Ingenuity.com). Briefly, a data set containing gene identifiers and corresponding fold-changes was uploaded into the application. Each gene identifier was mapped to its corresponding gene object in the Ingenuity® Pathways Knowledge Base. An FDR cutoff of 0.15 was set to identify genes with expression levels that were significantly altered. These genes, called focus genes,
