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

Abstract

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.

Keywords:

• RNA-seq
• Youden Index
• Kolmogorov–Smirnov test
• The best cutoff

Additional information

Funding

We thank the anonymous reviewers for their comments and suggestions that helped improve and clarify the manuscript. SY and ZF are supported in part by the grant U54 GM104940 from the National Institute of General Medical Sciences of the National Institutes of Health which funds the Louisiana Clinical and Translational Science Center. KZ is supported by the grants NIH 5U54MD007595 and 5P20GM103424.