Statistical Inferences About the Genetic Architecture of Disease
Hujoel, Margaux L.A.
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CitationHujoel, Margaux L.A. 2020. Statistical Inferences About the Genetic Architecture of Disease. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences.
AbstractThis dissertation consists of the use or development of three distinct methods to better understand the genetic architecture of disease. The first chapter focuses on using existing methods to better understand the role of regulatory elements in disease. The main conclusion is that disease heritability enrichment is concentrated in putative enhancers and promoters with ancient sequence age and conserved function across species, as well as promoters of loss-of-function intolerant genes. The second chapter proposes an approach to adjust mutation prevalence estimates for ascertainment bias. We outline a general approach for conducting a meta-analysis in complex settings (a variety of study designs and ascertainment mechanisms) by incorporating study-specific ascertainment mechanisms into a joint likelihood function. The third chapter develops novel methodology to integrate family history of disease to increase association power. LT-FH, the novel association method, greatly increases association power in case-control association studies when family history of disease is available.
Citable link to this pagehttps://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37365748
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