Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R
Abstract
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.
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Hierarchical clustering on the network structure allows uncovering functional modules of genes whose expression profiles are tightly intertwined, which typically correspond to specific biological processes and disease states.
“Hierarchical clustering on the network structure allows us to uncover functional modules of genes whose expression profiles are tightly intertwined,3,4 which typically correspond to specific biological processes and disease states.”
From hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data (2023) · cites this paper as [3]
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- Authors
- Langfelder, P., Zhang, B., & Horvath, S.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Horvath, Steve
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-11-16
- Volume
- 24
- Issue
- 5
- Pages
- 719-720
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2156247618
- Cited by
- 1,892
- References
- 2
- Citations by year
- 2026: 82 · 2025: 108 · 2024: 117 · 2023: 136 · 2022: 155 · 2021: 221 · 2020: 171 · 2019: 140 · 2018: 137 · 2017: 118 · 2016: 117 · 2015: 97 · 2014: 81 · 2013: 64 · 2012: 48
- FWCI
- 23.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (1u24ns043562-01)
- National Institute of Allergy and Infectious Diseases (U19AI063603)
- National Institute of Neurological Disorders and Stroke (1U24NS043562-01)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Clustering Algorithms Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- hierarchical clustering, cluster detection, partitioning around medoids, outlier detection, protein-protein interaction network, gene expression data, co-expression network
- MeSH terms
- Algorithms, Protein Binding, Proteins, Cluster Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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