Journal Article

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

Gygli, Sebastian M., Loiseau, Chloé, Menardo, Fabrizio, Borrell, Sonia, Rutaihwa, Liliana K., Beisel, Christian, Brites, Daniela, Gagneux, Sebastien, Trauner, Andrej, Coscolla, Mireia

2018

Overview

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.

• Publisher: BioMed Central,BioMed Central Ltd,BMC
• Subject: Algorithms / Biogeography / Bioinformatics / Biomedical and Life Sciences / Clone elimination / Computational Biology - methods / Computational Biology/Bioinformatics / Computer Appl. in Life Sciences / Control / Databases, Genetic / DNA sequencing / Humans / Influenza A virus - genetics / Information Storage and Retrieval / Large phylogenetic trees / Life Sciences / Microarrays / Mycobacterium tuberculosis - genetics / Nucleotide sequencing / Phylogenetic trees / Phylogeny / Redundancy reduction / Representative sample / Sampling bias / Selection bias / Sequence analysis (applications) / Size reduction / Software