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.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Zhang, Dongni

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-103114-144505

Advisor

• Wu, Zheyang

Year

• 2014

Sponsor

• Genetic Analysis Workshop 19

Date created

• 2014-10-31

Resource type

• Major Qualifying Project

Major

• Mathematical Sciences

Rights statement

• In Copyright