A new statistic for the analysis of association between trait and polymorphic marker loci

Inference for detecting the existence of an association between a diallelic marker and a trait locus is based on the chi-squared statistic with one degree of freedom. For polymorphic markers with m alleles (m>2), three approaches are mainly used in practice. First, one may use Pearsonʹs chi-squared statistic with m−1 degrees of freedom (d.f.) but this leads to a loss in test power. Second, one can select an allele to be the most associated and then collapse the other allele categories into a single class. This reduces in a biased way, the locus to a diallelic system. Third, one may use the Terwilliger [J.D. Terwilliger, Am. J. Hum. Genet. 56 (1995) 777] likelihood ratio statistic which has a non-standard unknown limiting probability distribution. In this paper, we propose a new statistic, LD, based on the second testing approach. We derive the asymptotic probability distribution of LD in an easy way. Simulation studies show that LD is more powerful than Pearsonʹs chi-squared statistic with m−1 d.f.