Genotype-Phenotype Association Using High Throughput Sequencing Data

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Publication Type dissertation
School or College School of Medicine
Department Human Genetics
Author Kronenberg, Zev Nachman
Title Genotype-Phenotype Association Using High Throughput Sequencing Data
Date 2015-08
Description 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
Type Text
Publisher University of Utah
Subject MESH Genotype; Phenotype; Chromosome Breakpoints; Epistasis, Genetic; Genetic Variation; Sequence Alignment; Sequence Analysis, DNA; Computational Biology; Mutation Rate; SOXE Transcription Factors; Whole Genome Sequencing; Software; Algorithms; Columbidae
Dissertation Institution University of Utah
Dissertation Name Doctor of Philosophy
Language eng
Relation is Version of Digital version of Genotype-Phenotype Association Using High Throughput Sequencing Data
Rights Management Copyright © Zev Nachman Kronenberg 2015
Format Medium aaplication/pdf
Format Extent 49,997,383 bytes
Source Original in Marriott Library Special Collections
ARK ark:/87278/s6dg18z9
Setname ir_etd
Date Created 2019-07-30
Date Modified 2021-05-06
ID 1432976
Reference URL