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Bioinformatics Advance Access published online on April 27, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm144
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

GAzer: Gene Set Analyzer

Sang-Bae Kim 1,*, Sungjin Yang 1, Seon-Kyu Kim 1, Sang Cheol Kim 2, Hyun Goo Woo 1, David J Volsky 3, Seon-Young Kim 4 and In-Sun Chu 1

1Korean BioInformation Center, KRIBB, Daejeon 305-806, Korea
2Department of Applied Statistics, Yonsei University, Seoul, 120-749, Korea
3Molecular Virology Division, St. Luke’s-Roosevelt Hospital Center, 432 West 58th Street, Antenucci Building, Room 709, New York, NY 10019, USA
4Human Genomics Laboratory, Genome Research Center, KRIBB, Daejeon 305-806, Korea

*To whom correspondence should be addressed. Sang-Bae Kim, E-mail: sbkim{at}kribb.re.kr


  Abstract

Summary: Gene Set Analyzer (GAzer) is a web-based integrated gene set analysis tool covering previously reported parametric and non-parametric models. Based on a simulation test for the reported algorithms, we classified and implemented three main statistical methods consisting of the z-statistic, gene permutation, and sample permutation for ten gene set categories including Gene Ontology (GO) for human, mouse, rat, and yeast. This tool identifies significantly altered gene sets scored by z-statistics and p-values from the z-test or permutation test and provides q-values and Bonferroni p-values to correct multiple hypothesis testing. GAzer allows users to observe changes in expression of each gene in a gene set or to see the significance of the gene sets containing a gene(s) of interest, thus allowing interactive data analysis both at the gene and gene set level. Moreover, GAzer offers extensive annotation for each gene.

Availability: The GAzer gene set analyzer is freely available at http://integromics.kobic.re.kr/GAzer/

Supplementary information: This can be found on the web page (http://integromics.kobic.re.kr/GAzer/supplement.jsp).

Keywords: Microarray data, gene set analysis, Gene Ontology, functional analysis.

Associate Editor: Prof. Alfonso Valencia

Received on November 23, 2006; revised on April 1, 2007; accepted on April 6, 2007

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