Statistical Inferences About the Genetic Architecture of Disease

genetic architecture;GWAS;ascertainment bias

Hujoel, Margaux L.A. ; Price, Alkes

University:Havard University

Department:Biostatistics

关键词: genetic architecture;    GWAS;    ascertainment bias;   

Others  :  https://dash.harvard.edu/bitstream/handle/1/37365748/HUJOEL-DISSERTATION-2020.pdf?sequence=1&isAllowed=y

美国|英语

来源: Digital Access to Scholarship at Harvard

【 摘 要 】

This 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.