Analysis of Microarray Data for Gene Selection

摘要

Microarray technology has a wide range of applications including identification of genes that change their expression in cells due to disease or treatment. Statistical methods for the selection of differentially expressed genes in two experimental conditions is addressed. The significant flexibility of Johnson system of distributions is very useful in characterizing the complicated data sets like microarray data. We propose a method to identify differentially expressed genes, where we consider a common distribution for the summary measure of equally expressed genes. To estimate this common distribution, the Johnson system of distribution is used. We did a comparison study with some of the other popular methods.