Comparison of various statistical methods for identifying differential gene expression in replicated microarray data.
DNA microarray is a new tool in biotechnology, which allows the simultaneous monitoring of thousands of gene expression in cells. The goal of differential gene expression analysis is to identify those genes whose expression levels change significantly by the experimental conditions. Although various statistical methods have been suggested to confirm differential gene expression, only a few studies compared the performance of the statistical tests. In our study, we extensively compared three types of parametric methods such as T-test, B-statistic and Bayes T-test and three types of non-parametric methods such as samroc, significance analysis of microarray and a modified mixture model using both the simulated datasets and the three real microarray experiments.
Kim
Seo Young
SY
Research Institute for Basic Science, Chonnam National University, Gwangju, Korea.
Lee
Jae Won
JW
Sohn
In Suk
IS
D015870:Gene Expression / Q000235:genetics*; D006801:Humans; D007723:Korea; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis