Further investigation on the regression method of mapping quantitative trait loci

Abstract

The simple regression method of mapping quantitative trait loci (QTL) is further investigated in comparison with the mixture model maximum likelihood method under high heritabilities, dominant and missing markers. No significant difference between the two methods is detected in terms of errors of parameter estimation and statistical powers, with the exception that the estimation of residual variance provided by the regression method is confounded with part of the QTL variance. The test statistic profiles show some difference between the two methods, but the difference is only detectable at the micro level. An alternative method, referred to as iteratively reweighted least squares, is proposed, which can correct the deficiency of parameter confounding in the regression method yet retains the properties of simplicity and rapidity of the ordinary regression method. Like the existing regression method, the weighted least squares method can be useful in QTL mapping in conjunction with the permutation tests and construction of confidence intervals by bootstrapping.