Bootstrap-based Support of HGT Inferred by Maximum Parsimony

<p>Abstract</p> <p>Background</p> <p>Maximum parsimony is one of the most commonly used criteria for reconstructing phylogenetic trees. Recently, Nakhleh and co-workers extended this criterion to enable reconstruction of <it>phylogenetic networks</it>, and d...

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Main Authors: Nakhleh Luay, Jin Guohua, Park Hyun
Format: Article
Language:English
Published: BMC 2010-05-01
Series:BMC Evolutionary Biology
Online Access:http://www.biomedcentral.com/1471-2148/10/131
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spelling doaj-e76e3903aae84ef4becbb380ab6293a42021-09-02T04:30:11ZengBMCBMC Evolutionary Biology1471-21482010-05-0110113110.1186/1471-2148-10-131Bootstrap-based Support of HGT Inferred by Maximum ParsimonyNakhleh LuayJin GuohuaPark Hyun<p>Abstract</p> <p>Background</p> <p>Maximum parsimony is one of the most commonly used criteria for reconstructing phylogenetic trees. Recently, Nakhleh and co-workers extended this criterion to enable reconstruction of <it>phylogenetic networks</it>, and demonstrated its application to detecting reticulate evolutionary relationships. However, one of the major problems with this extension has been that it favors more complex evolutionary relationships over simpler ones, thus having the potential for overestimating the amount of reticulation in the data. An <it>ad hoc </it>solution to this problem that has been used entails inspecting the improvement in the parsimony length as more reticulation events are added to the model, and stopping when the improvement is below a certain threshold.</p> <p>Results</p> <p>In this paper, we address this problem in a more systematic way, by proposing a nonparametric bootstrap-based measure of support of inferred reticulation events, and using it to determine the number of those events, as well as their placements. A number of samples is generated from the given sequence alignment, and reticulation events are inferred based on each sample. Finally, the support of each reticulation event is quantified based on the inferences made over all samples.</p> <p>Conclusions</p> <p>We have implemented our method in the NEPAL software tool (available publicly at <url>http://bioinfo.cs.rice.edu/</url>), and studied its performance on both biological and simulated data sets. While our studies show very promising results, they also highlight issues that are inherently challenging when applying the maximum parsimony criterion to detect reticulate evolution.</p> http://www.biomedcentral.com/1471-2148/10/131
collection DOAJ
language English
format Article
sources DOAJ
author Nakhleh Luay
Jin Guohua
Park Hyun
spellingShingle Nakhleh Luay
Jin Guohua
Park Hyun
Bootstrap-based Support of HGT Inferred by Maximum Parsimony
BMC Evolutionary Biology
author_facet Nakhleh Luay
Jin Guohua
Park Hyun
author_sort Nakhleh Luay
title Bootstrap-based Support of HGT Inferred by Maximum Parsimony
title_short Bootstrap-based Support of HGT Inferred by Maximum Parsimony
title_full Bootstrap-based Support of HGT Inferred by Maximum Parsimony
title_fullStr Bootstrap-based Support of HGT Inferred by Maximum Parsimony
title_full_unstemmed Bootstrap-based Support of HGT Inferred by Maximum Parsimony
title_sort bootstrap-based support of hgt inferred by maximum parsimony
publisher BMC
series BMC Evolutionary Biology
issn 1471-2148
publishDate 2010-05-01
description <p>Abstract</p> <p>Background</p> <p>Maximum parsimony is one of the most commonly used criteria for reconstructing phylogenetic trees. Recently, Nakhleh and co-workers extended this criterion to enable reconstruction of <it>phylogenetic networks</it>, and demonstrated its application to detecting reticulate evolutionary relationships. However, one of the major problems with this extension has been that it favors more complex evolutionary relationships over simpler ones, thus having the potential for overestimating the amount of reticulation in the data. An <it>ad hoc </it>solution to this problem that has been used entails inspecting the improvement in the parsimony length as more reticulation events are added to the model, and stopping when the improvement is below a certain threshold.</p> <p>Results</p> <p>In this paper, we address this problem in a more systematic way, by proposing a nonparametric bootstrap-based measure of support of inferred reticulation events, and using it to determine the number of those events, as well as their placements. A number of samples is generated from the given sequence alignment, and reticulation events are inferred based on each sample. Finally, the support of each reticulation event is quantified based on the inferences made over all samples.</p> <p>Conclusions</p> <p>We have implemented our method in the NEPAL software tool (available publicly at <url>http://bioinfo.cs.rice.edu/</url>), and studied its performance on both biological and simulated data sets. While our studies show very promising results, they also highlight issues that are inherently challenging when applying the maximum parsimony criterion to detect reticulate evolution.</p>
url http://www.biomedcentral.com/1471-2148/10/131
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