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An Extension to and Application of the Multifactor Dimensionality Reduction Pedigree Disequilibrium Test

As the field of genetics explores beyond mapping single-site disease susceptibility loci, epistasis between genes is being considered in disease models. These hypotheses present new problems for investigators as they search through ever more complex data structures. The dimensionality and size of a search space, the types and strengths of disease associations in data, and the quality of inference allowed given a result are all challenges when testing for putative epistatic disease models.
Method development to analyze family data for epistatic interactions is in a preliminary stage. The multifactor dimensionality reduction pedigree disequilibrium test (MDR-PDT) is one technique for assessing epistatic models in family data. The objective of this proposal is to refine, test, and apply this method to real data.
MDR-PDT is a method that implements the genoPDT statistic within the framework of the MDR algorithm. We hypothesize that at the conclusion of my aims, the MDR-PDT algorithms utility and power will be improved. In the following dissertation we developed a cross validation algorithm for pedigree data, and an omnibus model selection method. We also implemented an extension to MDR-PDT that includes a likelihood ratio test for the statistical significance of an interaction found by the MDR-PDT search using logistic regression. Finally, MDR-PDT was applied to Alzheimers candidate gene datasets and revealed a multilocus model involving several genes that are functional candidates.

Identiferoai:union.ndltd.org:VANDERBILT/oai:VANDERBILTETD:etd-03032008-135056
Date04 March 2008
CreatorsEdwards, Todd L
ContributorsDana Crawford, Eden Martin, Charles Matthews, Jonathan Haines, Marylyn Ritchie
PublisherVANDERBILT
Source SetsVanderbilt University Theses
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.library.vanderbilt.edu//available/etd-03032008-135056/
Rightsunrestricted, I 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 Vanderbilt 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.

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