Genotype-Phenotype association using High Throughput Sequencing data

Genotype Phenotype Association (GPA) is a means to identify candidate genes and genetic variants that may contribute to phenotypic variation. Technological advances in DNA sequencing continue to improve the efficiency and accuracy of GPA. Currently, High Throughput Sequencing (HTS) is the preferred method for GPA as it is fast and economical. HTS allows for population-level characterization of genetic variation, required for GPA studies. Despite the potential power of using HTS in GPA studies, there are technical hurdles that must be overcome. For instance, the excessive error rate in HTS data and the sheer size of population-level data can hinder GPA studies. To overcome these challenges, I have written two software programs for the purpose of HTS GPA. The first toolkit, GPAT++, is designed to detect GPA using small genetic variants. Unlike pervious software, GPAT++'s association test models the inherent errors in HTS, preventing many spurious GPA. The second toolkit, Whole Genome Alignment Metrics (WHAM), was designed for GPA using large genetic variants (structural variants). By integrating both structural variant identification and association testing, WHAM can identify shared structural variants associated with a phenotype. Both GPAT++ and WHAM have been successfully applied to real-world GPA studies