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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/7264
Ver los metadatos del registro completo
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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 |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
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 |
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CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
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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13.22299 |