In genome-wide association analysis of discontinuous traits, when complex population stratification exists in genomic data, the generalized linear model needs to consider hundreds of covariables at the same time, which slows the calculation speed and presents abnormal solutions. This study aimed to transform the effect value and heritability scale of significant loci in simple linear regression results into interpretable generalized linear regression results. First, the eigenvectors solved by spectral decomposition of the kinship matrix were considered as the principal components (PCs) to correct the population stratification in the discontinuous traits dataset. Then, a new covariate was formed through the sum of the multiplications of each covariate, and its regression coefficient of the principal component was computed using a linear regression model. The new covariate was used as the covariable of simple regression to carry out correlation tests for markers one by one. Finally, the generalized linear model was used for regression analysis of candidate quantitative trait nucleotides (QTNs), and the effects and variance were transformed into the generalized linear regression model scale. The genome-wide association analysis of sex reversal traits in half-smooth tongue sole (Cynoglossus semilaevis) was conducted using the new method and the generalized linear regression model with direct consideration of principal components: The results show that the QTN detection efficiency of this method is higher, a total of 6 QTNs were detected, including 5 QTNs on Z chromosome and 1 QTN on W chromosome. In addition, in terms of genome control, the genome control value of the method in this study is the same as that of the generalized linear regression model which directly considers PC, which is at an optimal level of 1.01. Therefore, the simple regression scaling transformation method based on principal component analysis improved the detection power for QTN detection, while retaining the accuracy of results, with fast and robust genome-wide association analysis of discontinuous traits. In addition, the QTNs detected by the new method proposed in this study can provide theoretical guidance for the study of sex reversal traits in half-smooth tongue soles.