Genetic studies of both common and rare genetic variation have been extremely successful in identifying genes and variants associated to schizophrenia, autism and other psychiatric disorders. Nevertheless, for most psychiatric disorders, the vast majority of genetic effects are as yet undetected.
Our specific aims are to 1) quantify the heritability explained by rare and functional classes of variation; 2) boost association power via leveraging related traits; and 3) infer biological mechanisms via local fine-mapping and genome- wide causal inference. We will guide our research using >800,000 samples from genome-wide association, exome sequencing and genome sequencing studies of psychiatric disease. The methods we propose to develop will be implemented in software packages that we will make widely available to the community.
We will develop new statistical methods for the analysis of common and rare variant genetic data, in order to boost power to detect association and interpret the biological consequences of genetic variation. We will apply these methods across massive genetic datasets of psychiatric disease including genome-wide association, whole exome sequencing and whole genome sequencing. We will make these methods freely available in open source tools such as Hail.
