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

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...

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Autores principales: Menardo, Fabrizio, Loiseau, Chloé, Brites, Daniela, Coscolla, Mireia, Gygli, Sebastian M., Rutaihwa, Liliana K., Trauner, Andrej, Beisel, Christian, Borrell, Sonia, Gagneux, Sebastien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5930393/
https://www.ncbi.nlm.nih.gov/pubmed/29716518
http://dx.doi.org/10.1186/s12859-018-2164-8
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author Menardo, Fabrizio
Loiseau, Chloé
Brites, Daniela
Coscolla, Mireia
Gygli, Sebastian M.
Rutaihwa, Liliana K.
Trauner, Andrej
Beisel, Christian
Borrell, Sonia
Gagneux, Sebastien
author_facet Menardo, Fabrizio
Loiseau, Chloé
Brites, Daniela
Coscolla, Mireia
Gygli, Sebastian M.
Rutaihwa, Liliana K.
Trauner, Andrej
Beisel, Christian
Borrell, Sonia
Gagneux, Sebastien
author_sort Menardo, Fabrizio
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2164-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-59303932018-05-09 Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity Menardo, Fabrizio Loiseau, Chloé Brites, Daniela Coscolla, Mireia Gygli, Sebastian M. Rutaihwa, Liliana K. Trauner, Andrej Beisel, Christian Borrell, Sonia Gagneux, Sebastien BMC Bioinformatics Software 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2164-8) contains supplementary material, which is available to authorized users. BioMed Central 2018-05-02 /pmc/articles/PMC5930393/ /pubmed/29716518 http://dx.doi.org/10.1186/s12859-018-2164-8 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Menardo, Fabrizio
Loiseau, Chloé
Brites, Daniela
Coscolla, Mireia
Gygli, Sebastian M.
Rutaihwa, Liliana K.
Trauner, Andrej
Beisel, Christian
Borrell, Sonia
Gagneux, Sebastien
Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity
title Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity
title_full Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity
title_fullStr Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity
title_full_unstemmed Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity
title_short Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity
title_sort treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5930393/
https://www.ncbi.nlm.nih.gov/pubmed/29716518
http://dx.doi.org/10.1186/s12859-018-2164-8
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