Document Detail


Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R.
MedLine Citation:
PMID:  18024473     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
SUMMARY: Hierarchical clustering is a widely used method for detecting clusters in genomic data. Clusters are defined by cutting branches off the dendrogram. A common but inflexible method uses a constant height cutoff value; this method exhibits suboptimal performance on complicated dendrograms. We present the Dynamic Tree Cut R package that implements novel dynamic branch cutting methods for detecting clusters in a dendrogram depending on their shape. Compared to the constant height cutoff method, our techniques offer the following advantages: (1) they are capable of identifying nested clusters; (2) they are flexible-cluster shape parameters can be tuned to suit the application at hand; (3) they are suitable for automation; and (4) they can optionally combine the advantages of hierarchical clustering and partitioning around medoids, giving better detection of outliers. We illustrate the use of these methods by applying them to protein-protein interaction network data and to a simulated gene expression data set. AVAILABILITY: The Dynamic Tree Cut method is implemented in an R package available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/BranchCutting.
Authors:
Peter Langfelder; Bin Zhang; Steve Horvath
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural     Date:  2007-11-16
Journal Detail:
Title:  Bioinformatics (Oxford, England)     Volume:  24     ISSN:  1367-4811     ISO Abbreviation:  Bioinformatics     Publication Date:  2008 Mar 
Date Detail:
Created Date:  2008-02-29     Completed Date:  2008-08-08     Revised Date:  2009-11-04    
Medline Journal Info:
Nlm Unique ID:  9808944     Medline TA:  Bioinformatics     Country:  England    
Other Details:
Languages:  eng     Pagination:  719-20     Citation Subset:  IM    
Affiliation:
Department of Human Genetics, University of California at Los Angeles, CA 90095-7088, USA.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Cluster Analysis*
Protein Binding
Proteins / metabolism
Grant Support
ID/Acronym/Agency:
1U19AI063603-01/AI/NIAID NIH HHS; 1U24NS043562-01/NS/NINDS NIH HHS
Chemical
Reg. No./Substance:
0/Proteins

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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