research-article

ConsensusClusterPlus

Authors:

Matthew D. Wilkerson,

D. Neil HayesAuthors Info & Claims

Bioinformatics, Volume 26, Issue 12

Pages 1572 - 1573

https://doi.org/10.1093/bioinformatics/btq170

Published: 01 June 2010 Publication History

Abstract

Summary: Unsupervised class discovery is a highly useful technique in cancer research, where intrinsic groups sharing biological characteristics may exist but are unknown. The consensus clustering (CC) method provides quantitative and visual stability evidence for estimating the number of unsupervised classes in a dataset. ConsensusClusterPlus implements the CC method in R and extends it with new functionality and visualizations including item tracking, item-consensus and cluster-consensus plots. These new features provide users with detailed information that enable more specific decisions in unsupervised class discovery.

Availability: ConsensusClusterPlus is open source software, written in R, under GPL-2, and available through the Bioconductor project ( http://www.bioconductor.org/).

Contact: [email protected]

Supplementary Information: Supplementary data are available at Bioinformatics online.

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Published In

Bioinformatics Volume 26, Issue 12

June 2010

105 pages

ISSN:1367-4803

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Publisher

Oxford University Press, Inc.

United States

Publication History

Published: 01 June 2010

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