Robust RNA-seq data analysis using an integrated method of ROC curve and Kolmogorov-Smirnov test

It is a common approach to dichotomize a continuous biomarker in clinical setting for the convenience of application. Analytically, results from using a dichotomized biomarker are often more reliable and resistant to outliers, bi-modal and other unknown distributions. There are two commonly used methods for selecting the best cutoff value for dichotomization of a continuous biomarker, using either maximally selected chi-square statistic or a ROC curve, specifically the Youden Index. In this paper, we explained that in many situations, it is inappropriate to use the former. By using the Maximum Absolute Youden Index (MAYI), we demonstrated that the integration of a MAYI and the Kolmogorov-Smirnov test is not only a robust non-parametric method, but also provides more meaningful p value for selecting the cutoff value than using a Mann-Whitney test. In addition, our method can be applied directly in clinical settings.

Automated summary

Dichotomizing a continuous biomarker is a common approach in clinical settings. This paper compares two commonly used methods for selecting the cutoff value and introduces a new method that combines the Maximum Absolute Youden Index (MAYI) and the Kolmogorov-Smirnov test, providing more reliable and meaningful results in clinical applications.