A Comparative Study of Tests for Homogeneity of Variances with Application to DNA Methylation Data |
| |
| Authors: | Xuan Li Weiliang Qiu Jarrett Morrow Dawn L DeMeo Scott T Weiss Yuejiao Fu Xiaogang Wang |
| |
| Institution: | 1. Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada.; 2. Channing Division of Network Medicine, Brigham and Women''s Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, United States of America.; CEA - Institut de Genomique, FRANCE, |
| |
| Abstract: | Variable DNA methylation has been associated with cancers and complex diseases. Researchers have identified many DNA methylation markers that have different mean methylation levels between diseased subjects and normal subjects. Recently, researchers found that DNA methylation markers with different variabilities between subject groups could also have biological meaning. In this article, we aimed to help researchers choose the right test of equal variance in DNA methylation data analysis. We performed systematic simulation studies and a real data analysis to compare the performances of 7 equal-variance tests, including 2 tests recently proposed in the DNA methylation analysis literature. Our results showed that the Brown-Forsythe test and trimmed-mean-based Levene''s test had good performance in testing for equality of variance in our simulation studies and real data analyses. Our results also showed that outlier profiles could be biologically very important. |
| |
| Keywords: | |
|
|
