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

Open Access Proceedings

A weighted accumulation test for associating rare genetic variation with quantitative phenotypes

Chuanhua Xing12, Glen A Satten3 and Andrew S Allen12*

Author affiliations

1 Department of Biostatistics and Bioinformatics, Duke University, 2424 Erwin Road, Suite 1102 Hock Plaza, Box 2721, Durham, NC 27710, USA

2 Duke Clinical Research Institute, Duke University, 2400 Pratt Street, Durham, NC 27705-3976, USA

3 Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, GA 30333, USA

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Citation and License

BMC Proceedings 2011, 5(Suppl 9):S6  doi:10.1186/1753-6561-5-S9-S6

Published: 29 November 2011

Abstract

Currently there is a great deal of interest in developing methods for testing the role that rare variation plays in disease development. Here we propose a weighted association test that accumulates genetic variation across a signaling pathway. We evaluate our approach by analyzing simulated phenotype data from an exome sequencing study of 697 unrelated individuals from the Genetic Analysis Workshop 17 (GAW17) data set. Although our weighted approach identifies several interesting pathways associated with phenotype Q1, so does an alternative unweighted accumulation approach. Such a result is not unexpected because there is no systematic relationship between the allele frequency of a variant and its effect on phenotype in the GAW17 simulation model.