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TreeSwift: A massively scalable Python tree package

Phylogenetic trees are essential to evolutionary biology, and numerous methods exist that attempt to extract phylogenetic information applicable to a wide range of disciplines, such as epidemiology and metagenomics. Currently, the three main Python packages for trees are Bio.Phylo, DendroPy, and the...

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Detalles Bibliográficos
Autor principal: Moshiri, N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328415/
https://www.ncbi.nlm.nih.gov/pubmed/35903557
http://dx.doi.org/10.1016/j.softx.2020.100436
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author Moshiri, N.
author_facet Moshiri, N.
author_sort Moshiri, N.
collection PubMed
description Phylogenetic trees are essential to evolutionary biology, and numerous methods exist that attempt to extract phylogenetic information applicable to a wide range of disciplines, such as epidemiology and metagenomics. Currently, the three main Python packages for trees are Bio.Phylo, DendroPy, and the ETE Toolkit, but as dataset sizes grow, parsing and manipulating ultra-large trees becomes impractical for these tools. To address this issue, we present TreeSwift, a user-friendly and massively scalable Python package for traversing and manipulating trees that is ideal for algorithms performed on ultra-large trees.
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spelling pubmed-93284152022-07-27 TreeSwift: A massively scalable Python tree package Moshiri, N. SoftwareX Article Phylogenetic trees are essential to evolutionary biology, and numerous methods exist that attempt to extract phylogenetic information applicable to a wide range of disciplines, such as epidemiology and metagenomics. Currently, the three main Python packages for trees are Bio.Phylo, DendroPy, and the ETE Toolkit, but as dataset sizes grow, parsing and manipulating ultra-large trees becomes impractical for these tools. To address this issue, we present TreeSwift, a user-friendly and massively scalable Python package for traversing and manipulating trees that is ideal for algorithms performed on ultra-large trees. 2020 2020-03-04 /pmc/articles/PMC9328415/ /pubmed/35903557 http://dx.doi.org/10.1016/j.softx.2020.100436 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Moshiri, N.
TreeSwift: A massively scalable Python tree package
title TreeSwift: A massively scalable Python tree package
title_full TreeSwift: A massively scalable Python tree package
title_fullStr TreeSwift: A massively scalable Python tree package
title_full_unstemmed TreeSwift: A massively scalable Python tree package
title_short TreeSwift: A massively scalable Python tree package
title_sort treeswift: a massively scalable python tree package
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328415/
https://www.ncbi.nlm.nih.gov/pubmed/35903557
http://dx.doi.org/10.1016/j.softx.2020.100436
work_keys_str_mv AT moshirin treeswiftamassivelyscalablepythontreepackage