Includes abstract. / Includes bibliographical references. / In this project, we review some existing pathway-based approaches for GWA study analyses, by exploring different implemented methods for combining effects of multiple modest genetic variants at gene and pathway levels. We then propose a graph-based method, ancGWAS, that incorporates the signal from GWA study, and the locus-specific ancestry into the human protein-protein interaction (PPI) network to identify significant sub-networks or pathways associated with the trait of interest. This network-based method applies centrality measures within linkage disequilibrium (LD) on the network to search for pathways and applies a scoring summary statistic on the resulting pathways to identify the most enriched pathways associated with complex diseases.
|Publisher||University of Cape Town, Faculty of Science, Department of Molecular and Cell Biology|
|Source Sets||South African National ETD Portal|
|Type||Master Thesis, Masters, MSc|
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