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Quantitative trait loci, Gaussian mixture distribution, LOD scores, Likelihood ratio test, Method of maximum B-likelihood, Robustness.

Genes controlling a certain trait of organism is known as quantitative trait loci (QTL). The standard Interval mapping (Lander and Botstein, 1989) is a popular way to scan the whole genome for the evidence of QTLs. It searches a QTL within each interval between two adjacent markers by performing likelihood ratio test (LRT). However, the standard Interval mapping (SIM) approach is not robust against outliers. An attempt is made to robustify SIM for QTL analysis by maximizing $eta$-likelihood function using the EM like algorithm. We investigate the robustness performance of the proposed method in a comparison of SIM algorithm using synthetic datasets. Experimental results show that the proposed method significantly improves the performance over the SIM approach for QTL mapping in presence of outliers; otherwise, it keeps equal performance.