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BMC Proc. 2011 Nov 29;5 Suppl 9:S29. doi: 10.1186/1753-6561-5-S9-S29.

Use of principal components to aggregate rare variants in case-control and family-based association studies in the presence of multiple covariates.

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  • 1Department 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.


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.

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