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 10 of 10 for “"association testing"”.
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Principled "convergence" non-coding rare variant association testing in complex disease
… are still unknown. Thus far, genome-wide association studies (GWAS) have only explained a small proportion of disease heritability, indicating that there is a large number of additional loci that contribute to complex diseases like type 2 diabetes (T2D), which is the primary case study in …
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Generalization of kernel machine methods for association testing of multi-omics data
Over the past couple of decades, genome-wide association studies (GWASs) have successfully identified thousands of loci associated with complex traits and diseases in humans. Despite the immense success of these statistical tools, post-GWAS, we are often left underwhelmed by findings that are …
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Genome-Scale Genetics: Lessons from Founder Populations
… posed by these populations for traditional association methods. Population isolates often contain large amounts of direct and cryptic relatedness that confound baseline assumptions of independence among genotypes and phenotypes and require specialized approaches to account for this sample …
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Statistical methods to infer biological interactions
… the effects of related individuals on standard association statistics for genome-wide association studies (GWAS) and introduce a new statistic that corrects for relatedness. Then, we introduce a statistically powerful association testing framework that corrects for confounding from population …
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Bayesian variable selection for linear mixed models when p is much larger than n with applications in genome wide association studies
Genome-wide association studies (GWAS) seek to identify single nucleotide polymorphisms (SNP) causing phenotypic responses in individuals. Commonly, GWAS analyses are done by using single marker association testing (SMA) which investigates the effect of a single SNP at a time and selects a …
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Deep learning of regulatory sequence variation in Pulmonary Arterial Hypertension
… of variants into functional groups for association testing. A convolutional neural network (CNN) has been trained using publicly available data sets to predict epigenetic features from DNA sequences. The model was tested against known enhancer regions and its accurate performance was …
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Understanding Inflammatory Bowel Disease using High-Throughput Sequencing
… when using sequencing to perform case-control association testing at scale, and the methods that can be used to overcome these. I then test for novel IBD associations in a low coverage whole genome sequencing dataset, and uncover a significant burden of rare, damaging missense variation in the …
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Multivariate linear mixed models for statistical genetics
In the last decade, genome-wide association studies have helped to advance our understanding of the genetic architecture of many important traits, including diseases. However, the statistical analysis of genotype-phenotype associations remains challenging due to multiple factors. First, many traits …
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Recessive and rare variant effects on common diseases and the immune cell transcriptome
… and the TOPMed-r2 panel. We then performed association testing with 898 common diseases, identifying 207 loci that reached standard genome-wide significance (p-value 5x10-8) under the recessive model and were more significant than under the additive model. Of these, about 70% demonstrated a …
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Statistical co-analysis of high-dimensional association studies
… definitions. Understanding patterns of association across this range of phenotypes requires co-analysis of high-dimensional association studies in order to characterise shared and distinct elements. In this thesis I address several problems in this area, with a general linking aim of …