@ARTICLE{TreeBASE2Ref18946,
author = {Robert Aaron Makowsky and Christian Cox and Corey Roelke and Paul T. Chippindale},
title = {Analyzing the Relationship between Sequence Divergence and Nodal Support using Bayesian Phylogenetic Analyses},
year = {2010},
keywords = {Divergence, Phylogenetics, Bayesian, Sequence},
doi = {},
url = {http://},
pmid = {},
journal = {Molecular Phylogenetics and Evolution},
volume = {},
number = {},
pages = {},
abstract = {Determining the appropriate gene for phylogeny reconstruction can be a difficult process. Rapidly evolving genes tend to resolve recent relationships, but suffer from alignment issues and increased homoplasy among distantly related species. Conversely, slowly evolving genes generally perform best for deeper relationships, but lack sufficient variation to resolve recent relationships. We determine the relationship between sequence divergence and Bayesian phylogenetic reconstruction ability using both natural and simulated datasets. The natural data is based on 28 well-supported relationships within the subphylum Vertebrata. Sequences of 12 genes were acquired and Bayesian analyses were used to determine phylogenetic support for correct relationships. Simulated datasets were designed to determine whether an optimal range of sequence divergence exists across extreme phylogenetic conditions. Across all genes we found that an optimal range of divergence for resolving the correct relationships does exist, although this level of divergence expectedly depends on the distance metric. Simulated datasets show that an optimal range of sequence divergence exists across diverse topologies and models of evolution. We determine that a simple to measure property of genetic sequences (genetic distance) is related to phylogenic reconstruction ability in Bayesian analyses. This information should be useful for selecting the most informative gene to resolve any relationships, especially those that are difficult to resolve, as well as minimizing both cost and confounding information during project design.}
}
Citation for Study 10500
Citation title:
"Analyzing the Relationship between Sequence Divergence and Nodal Support using Bayesian Phylogenetic Analyses".
Study name:
"Analyzing the Relationship between Sequence Divergence and Nodal Support using Bayesian Phylogenetic Analyses".
This study is part of submission 10490
(Status: Published).
Citation
Makowsky R.A., Cox C., Roelke C., & Chippindale P. 2010. Analyzing the Relationship between Sequence Divergence and Nodal Support using Bayesian Phylogenetic Analyses. Molecular Phylogenetics and Evolution, .
Authors
-
Makowsky R.A.
(submitter)
205-975-9122
-
Cox C.
-
Roelke C.
-
Chippindale P.
Abstract
Determining the appropriate gene for phylogeny reconstruction can be a difficult process. Rapidly evolving genes tend to resolve recent relationships, but suffer from alignment issues and increased homoplasy among distantly related species. Conversely, slowly evolving genes generally perform best for deeper relationships, but lack sufficient variation to resolve recent relationships. We determine the relationship between sequence divergence and Bayesian phylogenetic reconstruction ability using both natural and simulated datasets. The natural data is based on 28 well-supported relationships within the subphylum Vertebrata. Sequences of 12 genes were acquired and Bayesian analyses were used to determine phylogenetic support for correct relationships. Simulated datasets were designed to determine whether an optimal range of sequence divergence exists across extreme phylogenetic conditions. Across all genes we found that an optimal range of divergence for resolving the correct relationships does exist, although this level of divergence expectedly depends on the distance metric. Simulated datasets show that an optimal range of sequence divergence exists across diverse topologies and models of evolution. We determine that a simple to measure property of genetic sequences (genetic distance) is related to phylogenic reconstruction ability in Bayesian analyses. This information should be useful for selecting the most informative gene to resolve any relationships, especially those that are difficult to resolve, as well as minimizing both cost and confounding information during project design.
Keywords
Divergence, Phylogenetics, Bayesian, Sequence
External links
About this resource
- Canonical resource URI:
http://purl.org/phylo/treebase/phylows/study/TB2:S10500
- Other versions:
Nexus
NeXML
- Show BibTeX reference
@ARTICLE{TreeBASE2Ref18946,
author = {Robert Aaron Makowsky and Christian Cox and Corey Roelke and Paul T. Chippindale},
title = {Analyzing the Relationship between Sequence Divergence and Nodal Support using Bayesian Phylogenetic Analyses},
year = {2010},
keywords = {Divergence, Phylogenetics, Bayesian, Sequence},
doi = {},
url = {http://},
pmid = {},
journal = {Molecular Phylogenetics and Evolution},
volume = {},
number = {},
pages = {},
abstract = {Determining the appropriate gene for phylogeny reconstruction can be a difficult process. Rapidly evolving genes tend to resolve recent relationships, but suffer from alignment issues and increased homoplasy among distantly related species. Conversely, slowly evolving genes generally perform best for deeper relationships, but lack sufficient variation to resolve recent relationships. We determine the relationship between sequence divergence and Bayesian phylogenetic reconstruction ability using both natural and simulated datasets. The natural data is based on 28 well-supported relationships within the subphylum Vertebrata. Sequences of 12 genes were acquired and Bayesian analyses were used to determine phylogenetic support for correct relationships. Simulated datasets were designed to determine whether an optimal range of sequence divergence exists across extreme phylogenetic conditions. Across all genes we found that an optimal range of divergence for resolving the correct relationships does exist, although this level of divergence expectedly depends on the distance metric. Simulated datasets show that an optimal range of sequence divergence exists across diverse topologies and models of evolution. We determine that a simple to measure property of genetic sequences (genetic distance) is related to phylogenic reconstruction ability in Bayesian analyses. This information should be useful for selecting the most informative gene to resolve any relationships, especially those that are difficult to resolve, as well as minimizing both cost and confounding information during project design.}
}
- Show RIS reference
TY - JOUR
ID - 18946
AU - Makowsky,Robert Aaron
AU - Cox,Christian
AU - Roelke,Corey
AU - Chippindale,Paul T.
T1 - Analyzing the Relationship between Sequence Divergence and Nodal Support using Bayesian Phylogenetic Analyses
PY - 2010
KW - Divergence
KW - Phylogenetics
KW - Bayesian
KW - Sequence
UR - http://dx.doi.org/
N2 - Determining the appropriate gene for phylogeny reconstruction can be a difficult process. Rapidly evolving genes tend to resolve recent relationships, but suffer from alignment issues and increased homoplasy among distantly related species. Conversely, slowly evolving genes generally perform best for deeper relationships, but lack sufficient variation to resolve recent relationships. We determine the relationship between sequence divergence and Bayesian phylogenetic reconstruction ability using both natural and simulated datasets. The natural data is based on 28 well-supported relationships within the subphylum Vertebrata. Sequences of 12 genes were acquired and Bayesian analyses were used to determine phylogenetic support for correct relationships. Simulated datasets were designed to determine whether an optimal range of sequence divergence exists across extreme phylogenetic conditions. Across all genes we found that an optimal range of divergence for resolving the correct relationships does exist, although this level of divergence expectedly depends on the distance metric. Simulated datasets show that an optimal range of sequence divergence exists across diverse topologies and models of evolution. We determine that a simple to measure property of genetic sequences (genetic distance) is related to phylogenic reconstruction ability in Bayesian analyses. This information should be useful for selecting the most informative gene to resolve any relationships, especially those that are difficult to resolve, as well as minimizing both cost and confounding information during project design.
L3 -
JF - Molecular Phylogenetics and Evolution
VL -
IS -
ER -