Weighting improves the 'new Haseman-Elston'method

WF Forrest - Human Heredity, 2001 - karger.com
WF Forrest
Human Heredity, 2001karger.com
Abstract Elston et al.[Genet Epidemiol, in press] apply the results of Wright [Am J Hum Genet
1997; 60: 740–742] and Drigalenko [Am J Hum Genet 1998; 63: 1242–1245] to extend the
traditional Haseman-Elston regression scheme [Haseman and Elston, Behav Genet 1972; 2:
3–19] to include not only linkage information contained in the sib pair's squared difference,
but also information in their mean-corrected squared sum. The new algorithm detects
linkage to a quantitative trait locus by modelling sib pair trait covariance as a function of …
Abstract
Elston et al. [Genet Epidemiol, in press] apply the results of Wright [Am J Hum Genet 1997;60:740–742] and Drigalenko [Am J Hum Genet 1998;63:1242–1245] to extend the traditional Haseman-Elston regression scheme [Haseman and Elston, Behav Genet 1972;2:3–19] to include not only linkage information contained in the sib pair’s squared difference, but also information in their mean-corrected squared sum. The new algorithm detects linkage to a quantitative trait locus by modelling sib pair trait covariance as a function of identity-by-descent status. We demonstrate why this new estimator is suboptimal and can in some cases be inferior to the original Haseman-Elston method. We also describe a simple approach to estimation which improves on this new Haseman-Elston method by incorporating variance-based weights into the test statistic while staying within the linear modelling framework. In support of our theoretical claim, we conduct both a sib pair simulation and an application to GAW 10 sib pair data showing that our new estimator is superior to both the old and new Haseman-Elston schemes currently implemented in the analysis package S.A.G.E. 4.0.
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