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A population-based study of a quantitative trait, e.g. Blood Pressure(BP) maybe seriously compromised when the trait is subject to the effects of atreatment. Without appropriate corrections this can lead to considerablereduction of statistical power. Here we demonestrate this in the scenario ofQTL mapping through Single-Marker Analysis. The data are simulated from anormal mixtrure for different values of allele frequencies, separation betweennormal populations and Linkage Disequilibrium, and several methods ofcorrection are compared to check which can best compensate for the loss ofpower if treatment effects are ignored. In one of these methods, underlying BPsare approximated by subtracting an estimate of mean value of medicine effectfrom obsereved BPs in treated subjects. We domonestrate the efficacy of thismethod throughout different choices of parameters. Finally to account forquantitative traits that follow non-normal distributions, data are simulatedfrom lognormal mixtures similarly and Kruskal-Wallis test is used to obtainestimates of powers for different methods of analysis.

Adjusting for Treatment Effects in Studies of Quantitative Traits