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For genetic association studies with related individuals, standard linear mixed-effect model is the most popular approach. The model treats a complex trait (phenotype) as the response variable while a genetic variant (genotype) as a covariate. An alternative approach is to reverse the roles of phenotype and genotype. This class of tests includes quasi-likelihood based score tests. In this work, after reviewing these existing methods, we propose a general, unifying 'reverse' regression framework. We then show that the proposed method can also explicitly adjust for potential departure from Hardy-Weinberg equilibrium. Lastly, we demonstrate the additional flexibility of the proposed model on allele frequency estimation, as well as its connection with earlier work of best linear unbiased allele-frequency estimator. We conclude the paper with supporting evidence from simulation and application studies.

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