This article is part of the supplement: Genetic Analysis Workshop 17: Unraveling Human Exome Data
Use of principal components to aggregate rare variants in case-control and family-based association studies in the presence of multiple covariates
- Equal contributors
Department of Epidemiology and Biostatistics and Institute for Human Genetics, University of California San Francisco, 1450 Third Street, Box 3110, San Francisco, CA 94148-3110, USA
BMC Proceedings 2011, 5(Suppl 9):S29 doi:10.1186/1753-6561-5-S9-S29Published: 29 November 2011
Rare variants may help to explain some of the missing heritability of complex diseases. Technological advances in next-generation sequencing give us the opportunity to test this hypothesis. We propose two new methods (one for case-control studies and one for family-based studies) that combine aggregated rare variants and common variants located within a region through principal components analysis and allow for covariate adjustment. We analyzed 200 replicates consisting of 209 case subjects and 488 control subjects and compared the results to weight-based and step-up aggregation methods. The principal components and collapsing method showed an association between the gene FLT1 and the quantitative trait Q1 (P<10−30) in a fraction of the computation time of the other methods. The proposed family-based test has inconclusive results. The two methods provide a fast way to analyze simultaneously rare and common variants at the gene level while adjusting for covariates. However, further evaluation of the statistical efficiency of this approach is warranted.