Canonical correlation analysis for gene-based pleiotropy discovery.

ABSTRACT: Genome-wide association studies have identified a wealth of genetic variants involved in complex traits and multifactorial diseases. There is now considerable interest in testing variants for association with multiple phenotypes (pleiotropy) and for testing multiple variants for association with a single phenotype (gene-based association tests). Such approaches can increase statistical power by combining evidence for association over multiple phenotypes or genetic variants respectively. Canonical Correlation Analysis (CCA) measures the correlation between two sets of multidimensional variables, and thus offers the potential to combine these two approaches. To apply CCA, we must restrict the number of attributes relative to the number of samples. Hence we consider modules of genetic variati

SUBMITTER: Seoane JA 

PROVIDER: S-EPMC4199483 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature