A Study on the Multivariate Permutation Test to Detect the Minimal Fold Changes of Gene Expression Levels

The traditional hypothesis for identification of differentially expressed genes fails to take the biological meaning fold changes into consideration. However, a gene is differentially expressed if its fold change exceeds a threshold value in biological field. Compared with the traditional hypothesis of equality, the two one-sided tests procedure based on interval hypothesis（Liu, et al, 2007）not only consider the minimal biologically meaningful expression but truly identify the differentially expressed genes. To continue the research, we will apply multivariate permutation test to the interval hypothesis. Based on this proposed method, we conduct a simulation study to investigate its power, overall type I error and average type I error when the normal assumption of expression levels is in doubt.
The simulation results indicate that because of lower overall type I error and average type I error and higher average power, the interval hypothesis works better than the traditional hypothesis of equality when there are enough replicates in array. And the multivariate permutation test which is a non-parametric approach could improve the ability of identifying gene expression with interval hypothesis.