This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Haseman and Elston (H-E) proposed a robust test to detect linkage between a quantitative trait and a genetic marker. In their method the squared sib-pair trait difference is regressed on the estimated proportion of alleles at a locus shared identical by descent by sib pairs. This method was recently improved by changing the dependent variable to a weighted average of minus half the squared sib-pair difference and half the squared mean-corrected sib-pair sum. We have shown that under the assumption of normality this is equivalent to taking the dependent variable to be a mean-corrected cross-product in which the chosen mean leads to optimal power. We have now extended this method to larger pedigrees, to multiple traits, to include covariates at both the individual and pedigree level, and to use phase permutation to produce a generally valid test of linkage. Furthermore, we have shown that population stratification, if not accounted for, biases the method; that the misuse of 'uninformative' families can lead to increased Type I error; and that one can select individuals who have been used for such a linkage analysis in a way that increases the power of a subsequent association analysis. In all, four theoretical publications have resulted from this research in the past year.
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