Moving toward System Genetics through Multiple Trait Analysis in Genome-Wide Association Studies

Abstract

Association studies are a staple of genotype-phenotype mapping studies, whether they are based on single markers, haplotypes, candidate genes, genome-wide genotypes, or whole genome sequences. Although genetic epidemiological studies typically contain data collected on multiple traits which themselves are often correlated, most analyses have been performed on single traits. Here, I review several methods that have been developed to perform multiple trait analysis. These methods range from traditional multivariate models for systems of equations to recently developed graphical approaches based on network theory. The application of network theory to genetics is termed systems genetics and has the potential to address long-standing questions in genetics about complex processes such as coordinate regulation, homeostasis, and pleiotropy.

Keywords: multivariate analysis; pleiotropy; systems genetics.

Figure 1

(A) A Bayesian network consisting of a marker M, traits D directly associated with M, traits I indirectly associated with M, and traits U unassociated with M. Edges represent conditional dependencies, with the arrow pointing from the parent node to the child node. (B) The adjacency matrix corresponding to the graph in (A). (C) A dynamic Bayesian network for a cycle using an underlying Bayesian network that is acyclic.