Automated group assignment in large phylogenetic trees using GRUNT: GRouping, ungrouping, naming tool

Dalevi, Daniel, DeSantis, Todd Z., Fredslund, Jakob, Andersen, Gary L., Markowitz, Victor M. and Hugenholtz, Philip (2007) Automated group assignment in large phylogenetic trees using GRUNT: GRouping, ungrouping, naming tool. BMC Bioinformatics, 8 . doi:10.1186/1471-2105-8-402


Author Dalevi, Daniel
DeSantis, Todd Z.
Fredslund, Jakob
Andersen, Gary L.
Markowitz, Victor M.
Hugenholtz, Philip
Title Automated group assignment in large phylogenetic trees using GRUNT: GRouping, ungrouping, naming tool
Journal name BMC Bioinformatics   Check publisher's open access policy
ISSN 1471-2105
Publication date 2007-10
Sub-type Article (original research)
DOI 10.1186/1471-2105-8-402
Open Access Status DOI
Volume 8
Total pages 6
Place of publication London, United Kindgom
Publisher BioMed Central
Language eng
Formatted abstract
Background: Accurate taxonomy is best maintained if species are arranged as hierarchical groups in phylogenetic trees. This is especially important as trees grow larger as a consequence of a rapidly expanding sequence database. Hierarchical group names are typically manually assigned in trees, an approach that becomes unfeasible for very large topologies.
Results: We have developed an automated iterative procedure for delineating stable (monophyletic) hierarchical groups to large (or small) trees and naming those groups according to a set of sequentially applied rules. In addition, we have created an associated ungrouping tool for removing existing groups that do not meet user-defined criteria (such as monophyly). The procedure is implemented in a program called GRUNT (GRouping, Ungrouping, Naming Tool) and has been applied to the current release of the Greengenes (Hugenholtz) 16S rRNA gene taxonomy comprising more than 130,000 taxa.
Conclusion: GRUNT will facilitate researchers requiring comprehensive hierarchical grouping of large tree topologies in, for example, database curation, microarray design and pangenome assignments. The application is available at the greengenes website
Keyword Mixed models
Bacterial
Arb
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: ERA 2012 Admin Only
School of Chemistry and Molecular Biosciences
 
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