Computational Analysis of Transcriptional Profiling in Dysmorphic Syndrome

Abstract

In this paper we present comparative expression, functional and pathway analysis of transcriptional profiling of a dysmorphic patient and its matched control using whole blood and fibroblast cells in an attempt to identify genetic changes in dysmorphic disorders and developmental genes at large. Normalization was done by first finding an invariant set whose expression levels do not change significantly among the chips and then using this set to normalize raw probe values with a smoothing spline invariant set normalization method. Genes with significant change in expression were identified using the lower confidence bound of fold change and these genes were used to perform functional analyses within the context of Gene Ontology categories and biological pathways. Our results indicate that genes with altered expression levels are cell-type specific, activated biological categories are mostly developmental related such as skeletal and muscular system and genes dysregulated in both cell types effect cAMP dependent PKA pathway and consequently the CREB cycle.