ArticlePloS one2019
TreeCluster: Clustering biological sequences using phylogenetic trees.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 118 papers.
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Who cites it
118 citing papers in PubMed.
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- Discovering New Orthologous Groups with P-COGs.Biochemical genetics · 2026Article
- PhyloNaP: a user-friendly database of phylogeny for natural product-producing enzymes.Bioinformatics (Oxford, England) · 2026Article
- Host adaptation drives genome evolution and virulence diversification in a bacterial zoonotic pathogen.bioRxiv : the preprint server for biology · 2026Article
- Chromid-like secondary replicons as predicted key sites of biosynthetic gene clusters inmSystems · 2026Article
- A Bacillales-specific tubular scaffold essential for NADH dehydrogenase activity.Nature communications · 2026Article
- Species identification and genotyping ofMicrobiology spectrum · 2026Article
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- Comparison ofbioRxiv : the preprint server for biology · 2026Article
- Pathological convergence of a bacterial plant pathogen is associated with the horizontal transfer of an effector-containing mobile element.BMC genomics · 2026Article
- Molecular clock dating using complex mixture models: applied to ancient symbionts.Molecular biology and evolution · 2026Article
- Tmn blocks phage spread via plasmolysis and triggers synergistic defence responses.bioRxiv : the preprint server for biology · 2026Article
- Evolution and diversity of oxidoreductases involved in redox balance and energy conservation.Nature ecology & evolution · 2026Article
- Environmental and Phylogenetic Investigations of Aspergillus flavus Outbreak Linked to Contaminated Building Materials, Denmark, 2025.Emerging infectious diseases · 2026Article
58 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors.
Funding
Abstract
Clustering homologous sequences based on their similarity is a problem that appears in many bioinformatics applications. The fact that sequences cluster is ultimately the result of their phylogenetic relationships. Despite this observation and the natural ways in which a tree can define clusters, most applications of sequence clustering do not use a phylogenetic tree and instead operate on pairwise sequence distances. Due to advances in large-scale phylogenetic inference, we argue that tree-based clustering is under-utilized. We define a family of optimization problems that, given an arbitrary tree, return the minimum number of clusters such that all clusters adhere to constraints on their heterogeneity. We study three specific constraints, limiting (1) the diameter of each cluster, (2) the sum of its branch lengths, or (3) chains of pairwise distances. These three problems can be solved in time that increases linearly with the size of the tree, and for two of the three criteria, the algorithms have been known in the theoretical computer scientist literature. We implement these algorithms in a tool called TreeCluster, which we test on three applications: OTU clustering for microbiome data, HIV transmission clustering, and divide-and-conquer multiple sequence alignment. We show that, by using tree-based distances, TreeCluster generates more internally consistent clusters than alternatives and improves the effectiveness of downstream applications. TreeCluster is available at https://github.com/niemasd/TreeCluster.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.