A modified revisited Haseman-Elston method to further improve power.
The original and revisited Haseman-Elston methods are simple robust methods to detect linkage, but neither is uniformly optimal in terms of power. In this report, we propose a simple modification of the revisited Haseman-Elston method that retains the simplicity and robustness properties, but increases its power. We demonstrate theoretically that the modification can be more powerful than the optimally weighted Haseman-Elston method when the sibship mean can be correctly specified. We then examine the properties of this modification by simulation when the sibship mean is replaced by its best linear unbiased predictor. The simulation results indicate that this modification maintains good control over type I error, even in the case of larger sibships, and that the empirical power of this modification is similar to that of the optimally weighted Haseman-Elston method in most cases.
Wang
Tao
T
Department of Epidemiology and Biostatistics, Wolstein Research Building, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106-7281, USA.
Elston
Robert C
RC
D000704:Analysis of Variance; D003627:Data Interpretation, Statistical; D008040:Genetic Linkage; D006801:Humans; D008957:Models, Genetic; D011336:Probability; D019655:Quantitative Trait, Heritable