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dc.contributor.advisorFan, Ruzong
dc.creatorJung, Jeesun
dc.date.accessioned2005-11-01T15:49:14Z
dc.date.available2005-11-01T15:49:14Z
dc.date.created2004-08
dc.date.issued2005-11-01
dc.identifier.urihttps://hdl.handle.net/1969.1/2681
dc.description.abstractAs a large number of single nucleotide polymorphisms (SNPs) and microsatellite markers are available, high resolution mapping employing multiple markers or multiple allele markers is an important step to identify quantitative trait locus (QTL) of complex human disease. For many complex diseases, quantitative phenotype values contain more information than dichotomous traits do. Much research has been done on conducting high resolution mapping using information of linkage and linkage disequilibrium. The most commonly employed approaches for mapping QTL are pedigree-based linkage analysis and population-based association analysis. As one of the methods dealing with multiple alleles markers, mixed models are developed to work out family-based association study with the information of transmitted allele and nontransmitted allele from one parent to offspring. For multiple markers, variance component models are proposed to perform association study and linkage analysis simultaneously. Linkage analysis provides suggestive linkage based on a broad chromosome region and is robust to population admixtures. One the other hand, allelic association due to linkage disequilibrium (LD) usually operates over very short genetic distance, but is affected by population stratification. Combining both approaches plays a synergistic role in overcoming their limitations and in increasing the efficiency and effectiveness of gene mapping.en
dc.format.extent867081 bytesen
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherTexas A&M University
dc.subjectLinkageen
dc.subjectLinkage disequilibriumen
dc.subjectAssociation studyen
dc.subjectvariance component modelen
dc.subjectmixed modelen
dc.titleHigh resolution linkage and association study of quantitative trait locien
dc.typeBooken
dc.typeThesisen
thesis.degree.departmentStatisticsen
thesis.degree.disciplineStatisticsen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameDoctor of Philosophyen
thesis.degree.levelDoctoralen
dc.contributor.committeeMemberWang, Naisyin
dc.contributor.committeeMemberDahm, P. Fred
dc.contributor.committeeMemberSze, Sing-Hoi
dc.type.genreElectronic Dissertationen
dc.type.materialtexten
dc.format.digitalOriginborn digitalen


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