A methodology for multivariate phenotype-based genome-wide association studies to mine pleiotropic genes.

ABSTRACT:

Background

Current Genome-Wide Association Studies (GWAS) are performed in a single trait framework without considering genetic correlations between important disease traits. Hence, the GWAS have limitations in discovering genetic risk factors affecting pleiotropic effects.

Results

This work reports a novel data mining approach to discover patterns of multiple phenotypic associations over 52 anthropometric and biochemical traits in KARE and a new analytical scheme for GWAS of multivariate phenotypes defined by the discovered patterns. This methodology applied to the GWAS for multivariate phenotype highLDLhighTG derived from the predicted patterns of the phenotypic associations. The patterns of the phenotypic associations were informative to draw relations between plasma lipi

SUBMITTER: Park SH 

PROVIDER: S-EPMC3287479 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature