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    Modeling the role of social structures in population genetics : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Statistics at Massey University, Manawatu, New Zealand

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    Abstract
    Building on a theoretical framework, population genetics has been widely applied to diverse organisms, from bacteria to animals. On humans, this has led to the reconstruction of history, the timing of settlements, and migration between populations. Mostly based on the coalescent theory, modern population genetic studies are challenged by human social structures, which are difficult to incorporate into analytically models. The implications of social structure on population genetics are mostly unknown. This work presents new modeling and inference methods to model the role of social structure in poulation genetics. The applications of these new techniques permit to gain better understanding of the history and practices of a number of Indonesian island communities. This thesis comprises three published, organized as sequential chapters. The Introduction describes population genetic models and the statistical tools that are used to make inferences. The second chapter presents the first paper, which measures the change of population size through time on four Indonesian islands structured by history and geography. The third chapter presents SMARTPOP, a new simulation tool to study social structure, including mating systems and genetic diversity. The fourth chapter focuses on Asymmetric Prescriptive Alliance, a famous kinship system linking the migration of women between communities with cousin alliance. The fifth chapter presents a conclusion and future directions. In combination, this body of work shows the importance of including social structure in population genetics and proposes new ways to reconstruct aspects of social history.
    Date
    2015
    Author
    Guillot, Elsa Gratianne
    Rights
    The Author
    Publisher
    Massey University
    Description
    Listed in 2015 Dean's List of Exceptional Theses
    URI
    http://hdl.handle.net/10179/6951
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