The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	Analysis of gene expression data using Expressionist 3.1 and GeneSpring 4.2
Author:	Shrivastava, Indu
View Online:	njit-etd2003-014 (xi, 87 pages ~ 9.2 MB pdf)
Department:	Federated Biological Sciences Department of NJIT and Rutgers-Newark
Degree:	Master of Science
Program:	Computational Biology
Document Type:	Thesis
Advisory Committee:	Recce, Michael (Committee co-chair) Liebman, Jeffrey M. (Committee co-chair) Tolias, Peter P. (Committee member)
Date:	2003-01
Keywords:	Gene expression analysis Data mining
Availability:	Unrestricted
Abstract:	The purpose of this study was to determine the differences in the gene expression analysis methods of two data mining tools, ExpressionisticTM 3.1 and GeneSpringTM 4.2 with focus on basic statistical analysis and clustering algorithms. The data for this analysis was derived from the hybridization of Rattus norvegicus RNA to the Affymetrix RG34A GeneChip. This analysis was derived from experiments designed to identify changes in gene expression patterns that were induced in vivo by an experimental treatment. The tools were found to be comparable with respect to the list of statistically significant genes that were up-regulated by more than two fold. Approximately 78% of this gene list was present in both tools. ExpressionistTm 3.1 was capable of representing the different linkage methods of hierarchical clustering as average, complete and single, whereas in GeneSpringTM 4.2, the user could manipulate the separation ratio and minimum distance of the hierarchical tree.