Performance Analysis of Gene Expression Data Using Mann–Whitney U Test

Abstract

In this article, performance of gene expression data is analyzed using statistical method resembling Mann–Whitney U test. Biological field investigation of gene expression data is one of the budding domains, in which lot of research work is projected. The finding of the most correlated genes into a group is one of the challenging tasks that will be measured using some of the statistical methods like parametric or nonparametric methods. The microarray is taken as input from the gene expression data that is applied into different methods such as two-sample tests, one-way ANOVA, paired t-test, and Mann–Whitney U test. Scientifically evaluating the recital of each scheme based on virtual and natural information beneath conditions the result shows that clearly the Mann–Whitney U test will produce better result of correlated result and form as cluster group.