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This article is part of the supplement: Genetic Analysis Workshop 17: Unraveling Human Exome Data

Open Access Proceedings

Addition of multiple rare SNPs to known common variants improves the association between disease and gene in the Genetic Analysis Workshop 17 data

Jenna Sykes1, Lu Cheng1, Wei Xu12, Ming-Sound Tsao3, Geoffrey Liu24 and Melania Pintilie12*

Author Affiliations

1 Department of Biostatistics, Princess Margaret Hospital, 610 University Avenue, Toronto, ON M5G 2M9, Canada

2 Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON M5T 3M7, Canada

3 Laboratory of Medicine and Pathobiology, Princess Margaret Hospital, 610 University Avenue, Toronto, ON M5G 2M9, Canada

4 Division of Molecular Genomics, Princess Margaret Hospital, 610 University Avenue, Toronto, ON M5G 2M9, Canada

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BMC Proceedings 2011, 5(Suppl 9):S97  doi:10.1186/1753-6561-5-S9-S97

Published: 29 November 2011

Abstract

The upcoming release of new whole-genome genotyping technologies will shed new light on whether there is an associative effect of previously immeasurable rare variants on incidence of disease. For Genetic Analysis Workshop 17, our team focused on a statistical method to detect associations between gene-based multiple rare variants and disease status. We added a combination of rare SNPs to a common variant shown to have an influence on disease status. This method provides us with an enhanced ability to detect the effect of these rare variants, which, modeled alone, would normally be undetectable. Adjusting for significant clinical parameters, several genes were found to have multiple rare variants that were significantly associated with disease outcome.