GeneCluster 2.0: an advanced toolset for bioarray analysis (original) (raw)

Journal Article

M. Reich ,

The Eli and Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02141, USA

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K. Ohm ,

The Eli and Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02141, USA

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M. Angelo ,

The Eli and Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02141, USA

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P. Tamayo ,

The Eli and Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02141, USA

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J. P. Mesirov

The Eli and Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02141, USA

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Received:

03 September 2003

Accepted:

03 December 2003

Published:

26 February 2004

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M. Reich, K. Ohm, M. Angelo, P. Tamayo, J. P. Mesirov, GeneCluster 2.0: an advanced toolset for bioarray analysis, Bioinformatics, Volume 20, Issue 11, July 2004, Pages 1797–1798, https://doi.org/10.1093/bioinformatics/bth138
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Abstract

Summary: GeneCluster 2.0 is a software package for analyzing gene expression and other bioarray data, giving users a variety of methods to build and evaluate class predictors, visualize marker lists, cluster data and validate results. GeneCluster 2.0 greatly expands the data analysis capabilities of GeneCluster 1.0 by adding classification, class discovery and permutation test methods. It includes algorithms for building and testing supervised models using weighted voting and _k_-nearest neighbor algorithms, a module for systematically finding and evaluating clustering via self-organizing maps, and modules for marker gene selection and heat map visualization that allow users to view and sort samples and genes by many criteria. GeneCluster 2.0 is a standalone Java application and runs on any platform that supports the Java Runtime Environment version 1.3.1 or greater.

Availability: http://www.broad.mit.edu/cancer/software

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Present address: Google, Mountain View, CA 94043, USA

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Bioinformatics 20(11) © Oxford University Press 2004; all rights reserved.