Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 17 of 17 for “"statistical genetics"”.
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Multivariate linear mixed models for statistical genetics
… traits, including diseases. However, the statistical analysis of genotype-phenotype associations remains challenging due to multiple factors. First, many traits have polygenic architectures, which means that they are controlled by a large number of variants with small individual effects. …
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Statistical genetics tools for empowered data-driven decisions
… requires the strategic implementation of statistical genetics tools. This shift necessitates data-driven decision-making, placing professionals proficient in this toolkit at a significant advantage for addressing both traditional and emerging challenges. This thesis serves as a practical …
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Bayesian Kernel Models for Statistical Genetics and Cancer Genomics
… component models for solving complex problems in statistical genetics and molecular biology. Many of these types of statistical methods have been developed specifically to be applied to solve similar biological problems. For example, kernel regression models have a long history in statistics, …
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A Contribution to the Statistical Genetics of the Production of Milk and Its Proximate Constituents by Purebred and Crossbred Dairy Cattle
Made available in DSpace on 2014-12-09T14:29:04Z (GMT). No. of bitstreams: 1 6915270.pdf: 1930915 bytes, checksum: d0ac110293806dacb91037015169f7ba (MD5) Previous issue date: 1969
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Kernel-based association measures
… have been widely used for describing the statistical relationships between two sets of variables. Traditional association measures tend to focus on specialized settings (specific types of variables or association patterns). Based on an in-depth summary of existing measures, we propose a …
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Host and pathogen genetics associated with pneumococcal meningitis
… contribution of variation in host and pathogen genetics to pneumococcal meningitis is unknown. In this thesis I develop and apply statistical genetics techniques to identify genomic variation associated with the various stages of pneumococcal meningitis, including colonisation, invasion and …
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Bayesian Linear Modeling in High Dimensions: Advances in Hierarchical Modeling, Inference, and Evaluation
… from increasingly large datasets. In statistical genetics, for example, we observe up to millions of genetic variations in each of thousands of individuals, and wish to associate these variations with the development of disease. For ‘high dimensional’ problems like this, the languages …
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Understanding the Genetic Basis of Sex Differences in Human Height
… Despite this, the field of population genetics has rarely considered the special role of sex-linked loci and sex-biased genetic effectors in establishing sex-dependent trait variation. In this thesis, I integrate existing tools in statistical genetics for the repurposed goal of …
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Statistical methods to improve understanding of the genetic basis of complex diseases
Robust statistical methods, utilising the vast amounts of genetic data that is now available, are required to resolve the genetic aetiology of complex human diseases including immune-mediated diseases. Essential to this process is firstly the use of genome-wide association studies (GWAS) to …
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Common variants in antibody deficiencies
The inborn errors of immunity (IEIs) comprise a group of almost 500 diseases charac- terised by immune dysfunction of genetic origin. Many of these disorders represent canoni- cal examples of Mendelian disease and study of their genetic aetiology is largely conducted within a rare-variant, …
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Pathogenicity and selective constraint in the non-coding genome
… a function related to alternative splicing. - Statistical modelling of the distribution of variants in developmental disorder patients suggests that a small fraction of bases (maximum likelihood estimate of 3%) within a disease-associated non-coding element are likely pathogenic with high …
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Exploring nonlinear regression methods, with application to association studies
The field of nonlinear regression is a long way from reaching a consensus. Once a method decides to explore nonlinear combinations of predictors, a number of questions are raised, such as what nonlinear combinations to permit and how best to search the resulting model space. Genetic Association …
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Using single-cell RNA-seq to assess the effect of common genetic variants on gene expression during development
Over the last fifteen years, genome-wide association studies (GWAS) have been used to identify thousands of DNA variants associated with complex traits and diseases, by exploiting naturally occurring genetic variation in large populations of individuals. More recently, similar approaches have been …
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Modelling human complex traits with regression and neural-network based methods
… the large-scale population cohorts with adequate statistical power were available up until recently. With the advent of graphics processing unit computing farms and neural-network based methods, together with large biobank-scale data sets, such as the UK Biobank which offers a sample size of …
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Biological and Aetiological Inference from the Statistical Genetic Analyses of Blood Cell Traits
Blood cells are crucial to human physiology, with functions in oxygen transport, infection control, and wound healing. Molecular mechanisms endogenous to blood cells have been implicated in the aetiologies of cancer, infection and inflammatory and immune disorders. The genetic determinants of blood …
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Causal inference in integrative genomics: exploring de novo mutations and unravelling causal mechanisms via gene regulatory networks in developmental process
… influencing DNMs have been hindered by limited statistical power, primarily due to the challenge of obtaining an adequate number of parent-offspring trios. However, leveraging the rare disease cohort from the UK's 100,000 Genomes Project (100kGP), which comprises over 10,000 trios, provided an …
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Development of An In Silico Kir Genotyping Algorithm and Its Application to Population and Cancer Immunogenetic Analyses
<p>Gene content determination and variant calling in the complex KIR genomic region are useful for immune system function analysis, pathogenesis and disease risk factor elucidation, immunotherapy development, evolutionary investigations, and human migration modeling. Sequence-specific …