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    Fouad Zakharia.
    The central theme of this work revolves around the genetics of admixed individuals---individuals who derive their ancestry from two or more different ancestral populations.The genomes of admixed individuals exhibit unique properties that make them both fascinating and challenging to study using existing statistical methods. Their uniqueness lies in their block-like structure, a feature that is the direct result of generations of recombination events. An important advance in the field of admixture genetics has been the development of algorithms capable of determining the ancestry of different regions in the admixed genome. As we will illustrate in this work, local ancestry information can readily be harnessed towards the investigation of subcontinental structure, by which we attempt to determine the specific ancestral populations that gave rise to the admixed genomes under study, and whether differences exist in the ancestral makeup of these admixed samples. The latter line of investigation is of particular relevance to genome-wide association studies, which are prone to confounding if structure in a population has not been explicitly corrected for. This work is thus divided into three parts. We first apply some straightforward multivariate statistical methods such as PCA to gain insights into the African ancestry of African Americans. To this end, we introduce a novel method for the study of specific components of admixture in admixed individuals. We then expand on this work to introduce more sophisticated algorithms for the study of admixed genomics. These methods entail the development of an improved method for local ancestry deconvolution, and the implementation of a PCA approach designed to handle large amounts of missing data. We illustrate the power of using these methods in conjunction with one another with the study of two Latino populations. Finally, we describe a novel phasing algorithm designed to incorporate sequencing information into the process of haplotype reconstruction---an important upstream step for many of the analyses described here.
    Digital Access   2012