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. 2007 Mar;80(3):567-76.
doi: 10.1086/512727. Epub 2007 Jan 30.

Efficient Association Mapping of Quantitative Trait Loci With Selective Genotyping

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Free PMC article

Efficient Association Mapping of Quantitative Trait Loci With Selective Genotyping

B E Huang et al. Am J Hum Genet. .
Free PMC article

Abstract

Selective genotyping (i.e., genotyping only those individuals with extreme phenotypes) can greatly improve the power to detect and map quantitative trait loci in genetic association studies. Because selection depends on the phenotype, the resulting data cannot be properly analyzed by standard statistical methods. We provide appropriate likelihoods for assessing the effects of genotypes and haplotypes on quantitative traits under selective-genotyping designs. We demonstrate that the likelihood-based methods are highly effective in identifying causal variants and are substantially more powerful than existing methods.

Figures

Figure  1.
Figure 1.
Empirical power for detecting causal haplotype 11 at the nominal significance level of .05 under 2-SNP models with MAFs of .3 and .4 and with (cL,cU)=(-2,1) as a function of the LD. The solid and dotted red curves correspond to the conditional and prospective likelihoods, respectively, under the dominant model with β=.2, whereas the solid and dotted blue curves correspond to the conditional and prospective likelihoods, respectively, under the recessive model with β=.3.
Figure  2.
Figure 2.
Empirical type I error for testing null haplotype 10 at the nominal significance level of .05 under 2-SNP additive models with MAFs of .3 and .4 and D′ of .75 as a function of the effect size of causal haplotype 11. The solid and dotted red curves correspond to the conditional and prospective likelihoods, respectively, under (cL,cU)=(-2,1), whereas the solid and dotted blue curves correspond to the conditional and prospective likelihoods, respectively, under (cL,cU)=(-1,1). A solid black reference line is drawn at the nominal significance level of .05.

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