<![CDATA[Genes or regions on chromosome underlying a quantitative trait are called quantitative trait loci (QTL). Characterizing genes controlling quantitative trait on their position in chromosome and their effect on trait is through a process called QTL mapping. In estimating the QTL position and its effect, QTL mapping utilizes the association between QTL and DNA makers. However, many important traits are obtained in categorical scale, such as resistance from certain disease. From a theoritical point of view, QTL mapping method assuming continuous trait could not be applied to categorical trait. This research was facusing on the assessment of the performance of maximum likehood (ML) and regression (REG) approach employed in QTL mapping for binary trait by means of simulation study. The simulation study to evaluate the performance of ML and REG approach was conducted by taking into accounte several factors that may affecting the performance of both approaches. The factors are (1) maker density, (2) QTL effect, (3) sample size, and (4) shape of phenotypic distribution. Form simulation study, it was obtained that the two approaches showing comparable performance. Hence, QTL analysis could be performed using these two approaches due to their similar performance.]]>
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