network analysis of allelic association data
Wednesday 14 April 2010
Network and pathway analysis tools are traditionally used to interrogate gene expression data in order to understand the biological processes affected by a particular manipulation or disease/condition of interest.
A systems-level understanding of the biological processes affected in particular disease states can allow one to identify candidates not only for pharmaceutical intervention but also for potential prognostic and diagnostic markers for the disease.
However, network and pathway analyses are currently underutilized in the interpretation of large-scale genetic association study results.
While simple monogenic, overtly Mendelian diseases are easily understood in the context of a single genetic aberration, the vast majority of diseases follow more complex patterns of inheritance and are influenced by a large number of genes and environmental stimuli.
Genetic association studies investigating complex diseases that exploit network and pathway analysis tools can shed light on the genetic networks affected by particular genetic variations and sequence polymorphisms, just as gene expression studies can reveal genes dysregulated in a particular disease state.
Pathway and network analysis with high-density allelic association data. Torkamani A, Schork NJ. Methods Mol Biol. 2009;563:289-301. PMID: #19597792#
Pathway analysis of seven common diseases assessed by genome-wide association. Torkamani A, Topol EJ, Schork NJ. Genomics. 2008 Nov;92(5):265-72. PMID: #18722519#