Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity
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Author / Producer
Date
2018
Publication Type
Journal Article
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.
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Publication status
published
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Book title
Journal / series
Volume
19
Pages / Article No.
164
Publisher
BioMed Central
Event
Edition / version
Methods
Software
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Date collected
Date created
Subject
Representative sample; Large phylogenetic trees; Redundancy reduction; Size reduction; Sampling bias; Clone elimination; Biogeography; Tuberculosis; Influenza