Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity

Open access
Date
2018Type
- Journal Article
Citations
Cited 51 times in
Web of Science
Cited 55 times in
Scopus
ETH Bibliography
yes
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Abstract
Background
Large sequence datasets are difficult to visualize and handle. Additionally, they often do not represent a random subset of the natural diversity, but the result of uncoordinated and convenience sampling. Consequently, they can suffer from redundancy and sampling biases.
Results
Here we present Treemmer, a simple tool to evaluate the redundancy of phylogenetic trees and reduce their complexity by eliminating leaves that contribute the least to the tree diversity.
Conclusions
Treemmer can reduce the size of datasets with different phylogenetic structures and levels of redundancy while maintaining a sub-sample that is representative of the original diversity. Additionally, it is possible to fine-tune the behavior of Treemmer including any kind of meta-information, making Treemmer particularly useful for empirical studies. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000265156Publication status
publishedExternal links
Journal / series
BMC BioinformaticsVolume
Pages / Article No.
Publisher
BioMed CentralSubject
Representative sample; Large phylogenetic trees; Redundancy reduction; Size reduction; Sampling bias; Clone elimination; Biogeography; Tuberculosis; InfluenzaMore
Show all metadata
Citations
Cited 51 times in
Web of Science
Cited 55 times in
Scopus
ETH Bibliography
yes
Altmetrics