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University of Southern California Dissertations and Theses
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Plant genome wide association studies and improvement of the linear mixed model by applying the weighted relationship matrix
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Plant genome wide association studies and improvement of the linear mixed model by applying the weighted relationship matrix
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Abstract (if available)
Abstract
Genome-Wide Association Studies (GWAS) have become a powerful tool to delve into causal loci of important traits. Their application is not confined to human studies, but they are also widely used in plant studies. In the sense that improving modern cultivated plants is important considering rapidly changing climate environment, utilizing GWAS is essential for the modern agricultural. I introduce GWAS performed on two plant species: oil palm and chickpea. The results can be used for future breeding systems and the methodologies used for the studies can be applied to other association studies as well. The last chapter introduces a simulation study which was performed aiming at improving the linear mixed model. With the simple idea of weighting the relationship matrix, the performance of the model could be improved in the context of population stratification. In GWAS, it is still an open question what types of modified relationship matrix are optimal for specific biological scenarios, and I anticipate that the simulation study can open up a new revenue of advanced linear mixed models.
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University of Southern California Dissertations and Theses
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Asset Metadata
Creator
Shin, Min-Gyoung
(author)
Core Title
Plant genome wide association studies and improvement of the linear mixed model by applying the weighted relationship matrix
School
College of Letters, Arts and Sciences
Degree
Doctor of Philosophy
Degree Program
Computational Biology and Bioinformatics
Publication Date
08/01/2019
Defense Date
05/23/2019
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
chickpea,GWAS,linear mixed model,nested association mapping,OAI-PMH Harvest,oil palm
Format
application/pdf
(imt)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Nuzhdin, Sergey (
committee chair
), Chen, Liang (
committee member
), Marjoram, Paul (
committee member
), Millstein, Joshua (
committee member
)
Creator Email
mingyous@usc.edu,mushrumrum@gmail.com
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-c89-206289
Unique identifier
UC11663161
Identifier
etd-ShinMinGyo-7712.pdf (filename),usctheses-c89-206289 (legacy record id)
Legacy Identifier
etd-ShinMinGyo-7712.pdf
Dmrecord
206289
Document Type
Dissertation
Format
application/pdf (imt)
Rights
Shin, Min-Gyoung
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA
Tags
chickpea
GWAS
linear mixed model
nested association mapping