UC San Diego

Searching the genetic basis of human complex traits is an essential tool to illuminating biological processes and predicting risks of diseases. However, with the advance of genotyping technologies, e.g. genome sequencing, and sophistication of phenotypic measurements, e.g. magnetic resonance imaging, two prong challenges have imposed on the endeavor for mapping genotypes to phenotypes. First is the weak genetic signals due to the multifactorial contributions from common genetic variants. The effect sizes of those genetic variants become too small to be detected. The second is the inconsistency of the phenotypic measurements, which the genetically fundamental units, or so called endophenotype, are not apparent. This polygenes-polymeasurements problem become even more prominent in recent surge of large-scale cross-traits genomic studies. This dissertation is a collection of my series studies to develop novel methods to tackle the polygenes-polymeasurement challenges. In particular, I focused on how to extract generalizable signals from diverse genomic databses. The extracted signals can be useful in either predicting disease risks or elucidating biological processes in human brain.