Bias in tree searches and its consequences for measuring groups supports

Autores
Goloboff, Pablo Augusto; Simmons, Mark P.
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
When doing a bootstrap analysis with a single tree saved per pseudoreplicate, biased search algorithms may influence support values more than actual properties of the data set. Two methods commonly used for finding phylogenetic trees consist of randomizing the input order of species in multiple addition sequences followed by branch swapping, or using random trees as the starting point for branch swapping. The randomness inherent to such methods is assumed to eliminate
any consistent preferences for some trees or unsupported groups of taxa, but both methods can be significantly biased. In the case of trees created by sequentially adding taxa, a bias may occur even if every addition sequence is equiprobable, and if one of the equally optimal positions for each terminal to add to the tree is selected equiprobably. In the case of branch swapping, the bias can happen even when branch swapping equiprobably selects any of the trees of better score in the
subtree-pruning-regrafting-neighborhood or tree-bisection-reconnection-neighborhood. Consequently, when the data set is ambiguous, both random-addition sequences and branch swapping from random trees may (i) find some of the optimal trees much more frequently than others and (ii) find some groups with a frequency that differs from their frequency among all optimal trees. When the data set defines a single optimal tree, the groups present in that tree may have a different probability of being found by a search, even if supported by equal amounts of evidence. This may happen in both parsimony and maximum-likelihood analyses, and even in small data sets without incongruence.
Fil: Goloboff, Pablo Augusto. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; Argentina
Fil: Simmons, Mark P.. State University Of Colorado - Fort Collins; Estados Unidos
Materia
Phylogeny
Tree.Searches
Supports
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/7264

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spelling Bias in tree searches and its consequences for measuring groups supportsGoloboff, Pablo AugustoSimmons, Mark P.PhylogenyTree.SearchesSupportshttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1When doing a bootstrap analysis with a single tree saved per pseudoreplicate, biased search algorithms may influence support values more than actual properties of the data set. Two methods commonly used for finding phylogenetic trees consist of randomizing the input order of species in multiple addition sequences followed by branch swapping, or using random trees as the starting point for branch swapping. The randomness inherent to such methods is assumed to eliminate<br />any consistent preferences for some trees or unsupported groups of taxa, but both methods can be significantly biased. In the case of trees created by sequentially adding taxa, a bias may occur even if every addition sequence is equiprobable, and if one of the equally optimal positions for each terminal to add to the tree is selected equiprobably. In the case of branch swapping, the bias can happen even when branch swapping equiprobably selects any of the trees of better score in the<br />subtree-pruning-regrafting-neighborhood or tree-bisection-reconnection-neighborhood. Consequently, when the data set is ambiguous, both random-addition sequences and branch swapping from random trees may (i) find some of the optimal trees much more frequently than others and (ii) find some groups with a frequency that differs from their frequency among all optimal trees. When the data set defines a single optimal tree, the groups present in that tree may have a different probability of being found by a search, even if supported by equal amounts of evidence. This may happen in both parsimony and maximum-likelihood analyses, and even in small data sets without incongruence.Fil: Goloboff, Pablo Augusto. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; ArgentinaFil: Simmons, Mark P.. State University Of Colorado - Fort Collins; Estados UnidosOxford University Press2014-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/7264Goloboff, Pablo Augusto; Simmons, Mark P.; Bias in tree searches and its consequences for measuring groups supports; Oxford University Press; Systematic Biology; 63; 6; 9-2014; 851-8611063-5157enginfo:eu-repo/semantics/altIdentifier/url/http://sysbio.oxfordjournals.org/content/63/6/851.longinfo:eu-repo/semantics/altIdentifier/doi/info:eu-repo/semantics/altIdentifier/doi/10.1093/sysbio/syu051info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:21:03Zoai:ri.conicet.gov.ar:11336/7264instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:21:03.426CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Bias in tree searches and its consequences for measuring groups supports
title Bias in tree searches and its consequences for measuring groups supports
spellingShingle Bias in tree searches and its consequences for measuring groups supports
Goloboff, Pablo Augusto
Phylogeny
Tree.Searches
Supports
title_short Bias in tree searches and its consequences for measuring groups supports
title_full Bias in tree searches and its consequences for measuring groups supports
title_fullStr Bias in tree searches and its consequences for measuring groups supports
title_full_unstemmed Bias in tree searches and its consequences for measuring groups supports
title_sort Bias in tree searches and its consequences for measuring groups supports
dc.creator.none.fl_str_mv Goloboff, Pablo Augusto
Simmons, Mark P.
author Goloboff, Pablo Augusto
author_facet Goloboff, Pablo Augusto
Simmons, Mark P.
author_role author
author2 Simmons, Mark P.
author2_role author
dc.subject.none.fl_str_mv Phylogeny
Tree.Searches
Supports
topic Phylogeny
Tree.Searches
Supports
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv When doing a bootstrap analysis with a single tree saved per pseudoreplicate, biased search algorithms may influence support values more than actual properties of the data set. Two methods commonly used for finding phylogenetic trees consist of randomizing the input order of species in multiple addition sequences followed by branch swapping, or using random trees as the starting point for branch swapping. The randomness inherent to such methods is assumed to eliminate<br />any consistent preferences for some trees or unsupported groups of taxa, but both methods can be significantly biased. In the case of trees created by sequentially adding taxa, a bias may occur even if every addition sequence is equiprobable, and if one of the equally optimal positions for each terminal to add to the tree is selected equiprobably. In the case of branch swapping, the bias can happen even when branch swapping equiprobably selects any of the trees of better score in the<br />subtree-pruning-regrafting-neighborhood or tree-bisection-reconnection-neighborhood. Consequently, when the data set is ambiguous, both random-addition sequences and branch swapping from random trees may (i) find some of the optimal trees much more frequently than others and (ii) find some groups with a frequency that differs from their frequency among all optimal trees. When the data set defines a single optimal tree, the groups present in that tree may have a different probability of being found by a search, even if supported by equal amounts of evidence. This may happen in both parsimony and maximum-likelihood analyses, and even in small data sets without incongruence.
Fil: Goloboff, Pablo Augusto. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; Argentina
Fil: Simmons, Mark P.. State University Of Colorado - Fort Collins; Estados Unidos
description When doing a bootstrap analysis with a single tree saved per pseudoreplicate, biased search algorithms may influence support values more than actual properties of the data set. Two methods commonly used for finding phylogenetic trees consist of randomizing the input order of species in multiple addition sequences followed by branch swapping, or using random trees as the starting point for branch swapping. The randomness inherent to such methods is assumed to eliminate<br />any consistent preferences for some trees or unsupported groups of taxa, but both methods can be significantly biased. In the case of trees created by sequentially adding taxa, a bias may occur even if every addition sequence is equiprobable, and if one of the equally optimal positions for each terminal to add to the tree is selected equiprobably. In the case of branch swapping, the bias can happen even when branch swapping equiprobably selects any of the trees of better score in the<br />subtree-pruning-regrafting-neighborhood or tree-bisection-reconnection-neighborhood. Consequently, when the data set is ambiguous, both random-addition sequences and branch swapping from random trees may (i) find some of the optimal trees much more frequently than others and (ii) find some groups with a frequency that differs from their frequency among all optimal trees. When the data set defines a single optimal tree, the groups present in that tree may have a different probability of being found by a search, even if supported by equal amounts of evidence. This may happen in both parsimony and maximum-likelihood analyses, and even in small data sets without incongruence.
publishDate 2014
dc.date.none.fl_str_mv 2014-09
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/7264
Goloboff, Pablo Augusto; Simmons, Mark P.; Bias in tree searches and its consequences for measuring groups supports; Oxford University Press; Systematic Biology; 63; 6; 9-2014; 851-861
1063-5157
url http://hdl.handle.net/11336/7264
identifier_str_mv Goloboff, Pablo Augusto; Simmons, Mark P.; Bias in tree searches and its consequences for measuring groups supports; Oxford University Press; Systematic Biology; 63; 6; 9-2014; 851-861
1063-5157
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://sysbio.oxfordjournals.org/content/63/6/851.long
info:eu-repo/semantics/altIdentifier/doi/
info:eu-repo/semantics/altIdentifier/doi/10.1093/sysbio/syu051
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
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dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
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instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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