An Efficient Functional Analysis Method for Micro-array Data Using Gene Ontology

: Microarray data includes tens of thousands of gene expressions simultaneously, so it can be effectively used in identifying the phenotypes of diseases. However, the retrieval of functional information from a large corpus of gene expression data is still a time-consuming task. In this paper, we propose an efficient method for identifying functional categories of differentially expressed genes from a micro-array experiment by using Gene Ontology (GO). Our method is as follows: (1) The expression data set is first filtered to include only genes with mean expression values that differ by at least 3-fold between the two groups. (2) The genes are then ranked based on the t-statistics. The 100 most highly ranked genes are selected as informative genes. (3) The t-value of each informative gene is imposed as a score on the associated GO terms. High-scoring GO terms are then listed with their associated genes and represent the functional category information of the micro-array experiment. A sy...

• Type: Journal
• Year: 2007
• Where: JIPS
• Authors: Dong-wan Hong, Jong-keun Lee, Sung-soo Park, Sang-kyoon Hong, Jee-hee Yoon
• Keywords: Expression Data, Gene Expression, JIPS 2007, Microarray Data