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Thesis - University Access Only
Master of Science (MS)
Association mapping has been widely used to detect desirable genetic markers associated with traits of interest for plant improvement. Missing marker data are a common and yet challenging issue in many association mapping studies, especially as the number of markers used for these studies is large. On the other hand, selection of several sets of DNA markers with potential epistasis associated with target traits will greatly help plant improvement via a marker assisted selection approach. In this study, we first proposed a linkage-based imputation method for missing marker data given available linkage information and then integrated a MDR (multifactor dimensionality reduction) method with a forward variable selection approach. The simulation studies showed that both the proposed linkage-based imputation method and MDR-based forward selection method performed well. We also applied these methods to determine SNP (single nucleotide polymorphism) markers with potential epistasis associated with agronomic traits in two crops: barley and wheat.
Library of Congress Subject Headings
Includes bibliographical references (pages 118-136)
Number of Pages
South Dakota State University
In Copyright - Non-Commercial Use Permitted
Xu, Yi, "Genetic Association Mapping : Missing Markers, Epistatic Effects, and Applications" (2014). Electronic Theses and Dissertations. 1592.