Disease Gene Mapping in General Pedigrees

dc.contributor.advisorMichael D. Purugganan, Committee Memberen_US
dc.contributor.advisorBruce S. Weir, Committee Chairen_US
dc.contributor.advisorSharon R. Browning, Committee Memberen_US
dc.contributor.advisorZhao-Bang Zeng, Committee Memberen_US
dc.contributor.advisorMargarate G. Ehm, Committee Memberen_US
dc.contributor.authorLi, Lien_US
dc.date.accessioned2010-04-02T19:08:45Z
dc.date.available2010-04-02T19:08:45Z
dc.date.issued2005-02-28en_US
dc.degree.disciplineBioinformaticsen_US
dc.degree.leveldissertationen_US
dc.degree.namePhDen_US
dc.description.abstractDisease gene mapping is one of the main focuses of genetic epidemiology and statistical genetics. This dissertation explores some methods and algorithms in this area, especially in pedigrees. The first chapter gives an introduction to human genetics and disease gene mapping. Existing linkage and association methods are introduced and compared. Probabilities of genotypic data from multiple linked marker loci on related individuals are used as likelihoods of gene locations for gene-mapping, or as likelihoods of other parameters of interest in human genetics. With the recent development in genetics and molecular biology techniques, large-scale marker data has become available, which requires highly efficient likelihood calculations especially for complex pedigrees. Algorithms for likelihood calculations for pedigree data are reviewed in chapter 2. Besides exact likelihood calculation methods and MCMC, a Sequential Importance Sampling (SIS) approach has been proposed to enable calculations for large pedigrees with large numbers of markers. However, when the system gets large, the variance of the importance sampling weights increases while both efficiency and accuracy of the method decrease. We propose an optimization algorithm for calculating the likelihood of general pedigrees in Chapter 3. We incorporate a resampling strategy into SIS to reduce the variance inflation problem. A successful linkage analysis may identify a linkage region of interest containing hundreds of genes at a magnitude of perhaps ten to thirty centiMorgans. A follow-up association (or so-called linkage disequilibrium) analysis can provide much finer gene-mapping but is subject to greater multiple testing problems. In Chapter 4, we present a method for determining whether an association result is responsible for a non-parametric linkage result for binary traits in general pedigrees. The correlation between family frequency of a variant of interest and family LOD score is used as a measure of whether the association between a given variant at a marker and the disease status can help to explain a significant linkage result seen in the collection of families in the region around the marker.en_US
dc.identifier.otheretd-10212004-142157en_US
dc.identifier.urihttp://www.lib.ncsu.edu/resolver/1840.16/5154
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectgene mappingen_US
dc.subjectdisequilibriumen_US
dc.subjectlinkageen_US
dc.subjectdiseaseen_US
dc.subjectassociationen_US
dc.titleDisease Gene Mapping in General Pedigreesen_US

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