In the past decade, genome-wide association studies (GWAS) have produced rich single-nucleotide polymorphism (SNP) data available to researchers. Among them, the large scale studies including the HapMap project [1] and the 1000 Genomes project [2] have provided publicly accessible databases of reference ancestral populations for imputation and quality control purposes. The idea of GWAS is to conduct fast SNP-based association tests to scan the whole genome using case-control samples. Yet, many complex diseases such as mental health disorders may have multiple phenotypic traits with continuous outcomes [3]. This pleiotropy in complex traits [4] provides several potential advantages to the direct modeling of pleiotropic associations. First, a model search for loci that are simultaneously associated with multiple phenotypes would likely have higher power than a model search that only considers each phenotype individually. Second, more exact modeling may yield more accurate prediction of either or both phenotypes. Third, pleiotropic genes may tend to have a more central role in the relevant functional pathways.
