v.0.0.22
Launch
Produce new hierarchical clusters from existing ones based on a new tree cutoff parameter.
This App produces new hierarchical clusters (also referred to as a dendrogram or cluster tree) from existing ones by applying a new cutoff value for cutting the branches and then reconstructing the set of clusters.
NOTE: This App expects a cluster set generated by the hierarchical clustering algorithm and will not run successfully on clusters generated by any other approach, such as K-means or WGCNA.
This method is based on the cutree method from the R stats package.
Team members who developed & deployed algorithm in KBase: Paramvir Dehal, Roman Sutormin, Michael Sneddon, Srividya Ramakrishnan, Pavel Novichkov, Keith Keller. For questions, please contact us.
Related Publications
- Arkin AP, Cottingham RW, Henry CS, Harris NL, Stevens RL, Maslov S, et al. KBase: The United States Department of Energy Systems Biology Knowledgebase. Nature Biotechnology. 2018;36: 566. doi: 10.1038/nbt.4163 , https://www.nature.com/articles/nbt.4163
App Specification:
https://github.com/kbaseapps/FeatureValues/tree/6cdc50905a08883a53333c073abe1e1df7b3f97f/ui/narrative/methods/expression_toolkit_clusters_from_dendrogramModule Commit: 6cdc50905a08883a53333c073abe1e1df7b3f97f