Dataset Information
ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking.
Ontology highlight
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.
SUBMITTER: Wilkerson MD
PROVIDER: S-EPMC2881355 | biostudies-literature | 2010 Jun
REPOSITORIES: biostudies-literature
Publications
ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking.
Bioinformatics (Oxford, England) 20100428 12
<h4>Unlabelled</h4>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-conse ...[more]
