Microarray Data Analysis

-Mainly on a Functional Analysis using DAVID-

Abstract

Microarray technique is one of methods for analyzing gene expression. In modern life science of post-genome era, extraction of biologically meaningful information from microarray data is one of the most important problems. Cluster analysis is a traditional way of analyzing microarray data and can classify genes showing similar expression pattern into one group. However, this method cannot clarify the biological properties of each gene group, and the meaning of gene expression changes of the sample, even though common regulatory mechanism of gene expression is implied. Recently, a new analyzing method, which combines microarray data with Gene Ontology information, has developed. This method classifies genes into groups according to accumulated functional information and selects statistically important groups. Using this method, we can obtain clues to find out biologically important gene groups. In this review, theory and the practical procedure of microarray data analysis using DAVID will be mainly discussed.