Statistical methods for detecting genes associated with sperm competition in natural populations of Drosophila, using blocks of tightly linked single nucleotide polymorphisms : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Statistics at Massey University, Albany, New Zealand

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dc.contributor.authorWerner, Lillian Li
dc.date.accessioned2018-09-10T21:46:57Z
dc.date.available2018-09-10T21:46:57Z
dc.date.issued2007
dc.description.abstractThe purpose of the project is to develop statistical methods for detecting genes associated with sperm competition in natural populations of Drosophila (fruit flies). The flies' genotype information given by Fiumera et al. (2004) is used as the starting point of the analysis. This dataset utilizes blocks of tightly linked single nucleotide polymorphisms within genes suspected to affect sperm competition. The sperm competition detection process is completed in three different stages: maternal and offspring haplotypes reconstruction; paternal genotype and offspring fraction estimation; and preferred genotype detection. Software programs HAPLORE and PHASE 2.0 were implemented for maternal and offspring haplotype reconstruction. The software Parentage is applied on the reconstructed haplotypes for estimating paternal genotypes and the amount of offspring they produced. Lastly, the Kruskal Wallis and permutation tests were conducted to detect differences in offspring produced between groups of males with different genotypes.en_US
dc.identifier.urihttp://hdl.handle.net/10179/13774
dc.language.isoenen_US
dc.publisherMassey Universityen_US
dc.rightsThe Authoren_US
dc.subjectGeneticsen_US
dc.subjectStatistical methodsen_US
dc.titleStatistical methods for detecting genes associated with sperm competition in natural populations of Drosophila, using blocks of tightly linked single nucleotide polymorphisms : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Statistics at Massey University, Albany, New Zealanden_US
dc.typeThesisen_US
massey.contributor.authorWerner, Lillian Li
thesis.degree.disciplineStatisticsen_US
thesis.degree.grantorMassey Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Science (M. Sc.)en_US
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