Differential Gene Expression Analysis on Microarray Data of Breast Cancer Based on Subgroup Statistic Methods

Abstract

Tomlins et al. (2005) found that the differential expressed genes might only exist in a subset of the cancer group, rather than in all samples of the group. From then on, lots of methods have been proposed by considering this point. In this paper, we first surveyed the recent research progress of detection methods for differential gene expression (DGE) in micro array data of cancer subgroup, and then applied six commonly used methods to simulated data and database provided by West. Through analyzing experimental results, we compared the performance of the six detection methods. This paper performs a comprehensive comparison study of currently popular detection methods of differential gene expression for micro array data analysis with regard to over-expressed cancer subgroup. The obtained results are helpful for dealing with micro array data using detection methods.