Background: Associations between haplotypes and quantitative traits provide valuable information about the\ngenetic basis of complex human diseases. Haplotypes also provide an effective way to deal with untyped SNPs. Two\nmajor challenges arise in haplotype-based association analysis of family data. First, haplotypes may not be inferred\nwith certainty from genotype data. Second, the trait values within a family tend to be correlated because of common\ngenetic and environmental factors.\nResults: To address these challenges, we present an efficient likelihood-based approach to analyzing associations of\nquantitative traits with haplotypes or untyped SNPs. This approach properly accounts for within-family trait\ncorrelations and can handle general pedigrees with arbitrary patterns of missing genotypes. We characterize the\ngenetic effects on the quantitative trait by a linear regression model with random effects and develop efficient\nlikelihood-based inference procedures. Extensive simulation studies are conducted to examine the performance of\nthe proposed methods. An application to family data from the Childhood Asthma Management Program Ancillary\nGenetic Study is provided. A computer program is freely available.\nConclusions: Results from extensive simulation studies show that the proposed methods for testing the haplotype\neffects on quantitative traits have correct type I error rates and are more powerful than some existing methods.
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