Faculty Advisor

Wu, Zheyang

Abstract

Statistical association studies have contributed significantly in the detection of novel genetic factors associated with complex diseases. Incorporation of biological information that reflects the complex mechanism of disease development is likely to increase the power of association tests for detecting novel disease genes. In this study, we develop a statistical framework for association studies that integrates the information of the functional effect of SNPs to the disease related protein-protein interactions. The method is applied to GAW19 exome sequencing data of uncorrelated individuals for detecting novel genes associated to hypotension. Based on both real and simulated phenotypes of hypertension, the method is compared with multiple well-known association tests for sequencing data.

Publisher

Worcester Polytechnic Institute

Date Accepted

October 2014

Major

Mathematical Sciences

Project Type

Major Qualifying Project

Accessibility

Unrestricted

Advisor Department

Mathematical Sciences

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