ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking.
ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking.
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DOI：
10.1093/bioinformatics/btq170
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发表时间：
2010-06-15
期刊：
影响因子：
--
通讯作者：
Hayes DN
中科院分区：
文献类型：
--
作者：
Wilkerson MD;Hayes DN
总结：无监督类发现是癌症研究中非常有用的技术，其中可能存在但未知的具有生物学特征的固有组。共识聚类（CC）方法提供了定量和可视化的稳定性证据，用于估计数据集中无监督类的数量。CumbersuscapterPlus在R中实现了CC方法，并扩展了新的功能和可视化，包括项目跟踪，项目一致性和集群一致性图。这些新功能为用户提供了详细的信息，使用户能够在无监督的类发现中做出更具体的决策。供货情况：Bioconductor Plus是一个开源软件，使用R语言编写，遵循GPL-2，可通过Bioconductor项目（http：//www.bioconductor. org/）获得。联系方式：mwilkers@med.unc.edu补充信息：补充数据可在生物信息学在线获得。
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: mwilkers@med.unc.edu Supplementary Information: Supplementary data are available at Bioinformatics online.
DOI：
10.1073/pnas.241500798
发表时间：
2001-11-20
影响因子：
11.1
作者：
Garber, ME;Troyanskaya, OG;Petersen, I
通讯作者：
Petersen, I
影响因子：
7.5
作者：
Monti, S;Tamayo, P;Golub, T
通讯作者：
Golub, T