Date of Graduation

Spring 2011

Degree

Master of Science in Mathematics

Department

Mathematics

Committee Chair

George Mathew

Abstract

Genes play an important role in the study of hereditary diseases. The human genome contains thousands of genes. Therefore, finding a specific gene or genes responsible for any human disease is a very difficult procedure. A first step in searching for disease genes is by using methods of linkage analysis. Some genes on the same chromosome tend to be inherited together and these are said to be linked. Some of the statistical inference procedures of whether two genes are likely to lie near each other on a chromosome, and therefore are likely to be inherited together, are by the estimation of recombination fraction and by the LOD score (logarithm of odds score) based on likelihood functions. In this thesis, these procedures are applied to some complex pedigree structures. Difficulties and limitations of these procedures are discussed to help define which method is best in a given situation. In addition, sibship analysis and associated non-parametric methods of linkage analysis are shown for analyzing genetic data. The advantage of these methods is linked lies in the difficulties of estimating nuisance parameters that exist in parametric methods.

Keywords

genes, alleles, genetic epidemiology, recombination fraction, likelihood function, LOD score, pedigree, statistical tests

Subject Categories

Mathematics

Copyright

© Aaron Nathaniel Baker

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