A comparison of phylogenetic network methods using computer simulation.
We present a series of simulation studies that explore the relative performance of several phylogenetic network approaches (statistical parsimony, split decomposition, union of maximum parsimony trees, neighbor-net, simulated history recombination upper bound, median-joining, reduced median joining...
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2008-04-01
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doaj-2b705ddc6d8546278b2902d711744c8d2020-11-24T21:50:02ZengPublic Library of Science (PLoS)PLoS ONE1932-62032008-04-0134e191310.1371/journal.pone.0001913A comparison of phylogenetic network methods using computer simulation.Steven M WoolleyDavid PosadaKeith A CrandallWe present a series of simulation studies that explore the relative performance of several phylogenetic network approaches (statistical parsimony, split decomposition, union of maximum parsimony trees, neighbor-net, simulated history recombination upper bound, median-joining, reduced median joining and minimum spanning network) compared to standard tree approaches, (neighbor-joining and maximum parsimony) in the presence and absence of recombination.In the absence of recombination, all methods recovered the correct topology and branch lengths nearly all of the time when the substitution rate was low, except for minimum spanning networks, which did considerably worse. At a higher substitution rate, maximum parsimony and union of maximum parsimony trees were the most accurate. With recombination, the ability to infer the correct topology was halved for all methods and no method could accurately estimate branch lengths.Our results highlight the need for more accurate phylogenetic network methods and the importance of detecting and accounting for recombination in phylogenetic studies. Furthermore, we provide useful information for choosing a network algorithm and a framework in which to evaluate improvements to existing methods and novel algorithms developed in the future.http://europepmc.org/articles/PMC2275308?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Steven M Woolley David Posada Keith A Crandall |
spellingShingle |
Steven M Woolley David Posada Keith A Crandall A comparison of phylogenetic network methods using computer simulation. PLoS ONE |
author_facet |
Steven M Woolley David Posada Keith A Crandall |
author_sort |
Steven M Woolley |
title |
A comparison of phylogenetic network methods using computer simulation. |
title_short |
A comparison of phylogenetic network methods using computer simulation. |
title_full |
A comparison of phylogenetic network methods using computer simulation. |
title_fullStr |
A comparison of phylogenetic network methods using computer simulation. |
title_full_unstemmed |
A comparison of phylogenetic network methods using computer simulation. |
title_sort |
comparison of phylogenetic network methods using computer simulation. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2008-04-01 |
description |
We present a series of simulation studies that explore the relative performance of several phylogenetic network approaches (statistical parsimony, split decomposition, union of maximum parsimony trees, neighbor-net, simulated history recombination upper bound, median-joining, reduced median joining and minimum spanning network) compared to standard tree approaches, (neighbor-joining and maximum parsimony) in the presence and absence of recombination.In the absence of recombination, all methods recovered the correct topology and branch lengths nearly all of the time when the substitution rate was low, except for minimum spanning networks, which did considerably worse. At a higher substitution rate, maximum parsimony and union of maximum parsimony trees were the most accurate. With recombination, the ability to infer the correct topology was halved for all methods and no method could accurately estimate branch lengths.Our results highlight the need for more accurate phylogenetic network methods and the importance of detecting and accounting for recombination in phylogenetic studies. Furthermore, we provide useful information for choosing a network algorithm and a framework in which to evaluate improvements to existing methods and novel algorithms developed in the future. |
url |
http://europepmc.org/articles/PMC2275308?pdf=render |
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