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ConsensusClusterPlus: a Class Discovery Tool with Confidence Assessments and Item Tracking

Overview
Journal Bioinformatics
Publisher Oxford University Press
Specialty Biology
Date 2010 Apr 30
PMID 20427518
Citations 2961
Authors
Matthew D Wilkerson
D Neil Hayes
Affiliations
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Abstract

Unlabelled: 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/).

Supplementary Information: Supplementary data are available at Bioinformatics online.

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