Exploring power and parameter estimation of the BiSSE method for analyzing species diversification

<p>Abstract</p> <p>Background</p> <p>There has been a considerable increase in studies investigating rates of diversification and character evolution, with one of the promising techniques being the BiSSE method (binary state speciation and extinction). This study uses s...

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Main Authors: Davis Matthew P, Midford Peter E, Maddison Wayne
Format: Article
Language:English
Published: BMC 2013-02-01
Series:BMC Evolutionary Biology
Subjects:
Online Access:http://www.biomedcentral.com/1471-2148/13/38
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spelling doaj-df519e7851914f068834bccb465391742021-09-02T10:43:04ZengBMCBMC Evolutionary Biology1471-21482013-02-011313810.1186/1471-2148-13-38Exploring power and parameter estimation of the BiSSE method for analyzing species diversificationDavis Matthew PMidford Peter EMaddison Wayne<p>Abstract</p> <p>Background</p> <p>There has been a considerable increase in studies investigating rates of diversification and character evolution, with one of the promising techniques being the BiSSE method (binary state speciation and extinction). This study uses simulations under a variety of different sample sizes (number of tips) and asymmetries of rate (speciation, extinction, character change) to determine BiSSE’s ability to test hypotheses, and investigate whether the method is susceptible to confounding effects.</p> <p>Results</p> <p>We found that the power of the BiSSE method is severely affected by both sample size and high tip ratio bias (one character state dominates among observed tips). Sample size and high tip ratio bias also reduced accuracy and precision of parameter estimation, and resulted in the inability to infer which rate asymmetry caused the excess of a character state. In low tip ratio bias scenarios with appropriate tip sample size, BiSSE accurately estimated the rate asymmetry causing character state excess, avoiding the issue of confounding effects.</p> <p>Conclusions</p> <p>Based on our findings, we recommend that future studies utilizing BiSSE that have fewer than 300 terminals and/or have datasets where high tip ratio bias is observed (i.e., fewer than 10% of species are of one character state) should be extremely cautious with the interpretation of hypothesis testing results.</p> http://www.biomedcentral.com/1471-2148/13/38Key innovationsCharacter evolutionSystematics
collection DOAJ
language English
format Article
sources DOAJ
author Davis Matthew P
Midford Peter E
Maddison Wayne
spellingShingle Davis Matthew P
Midford Peter E
Maddison Wayne
Exploring power and parameter estimation of the BiSSE method for analyzing species diversification
BMC Evolutionary Biology
Key innovations
Character evolution
Systematics
author_facet Davis Matthew P
Midford Peter E
Maddison Wayne
author_sort Davis Matthew P
title Exploring power and parameter estimation of the BiSSE method for analyzing species diversification
title_short Exploring power and parameter estimation of the BiSSE method for analyzing species diversification
title_full Exploring power and parameter estimation of the BiSSE method for analyzing species diversification
title_fullStr Exploring power and parameter estimation of the BiSSE method for analyzing species diversification
title_full_unstemmed Exploring power and parameter estimation of the BiSSE method for analyzing species diversification
title_sort exploring power and parameter estimation of the bisse method for analyzing species diversification
publisher BMC
series BMC Evolutionary Biology
issn 1471-2148
publishDate 2013-02-01
description <p>Abstract</p> <p>Background</p> <p>There has been a considerable increase in studies investigating rates of diversification and character evolution, with one of the promising techniques being the BiSSE method (binary state speciation and extinction). This study uses simulations under a variety of different sample sizes (number of tips) and asymmetries of rate (speciation, extinction, character change) to determine BiSSE’s ability to test hypotheses, and investigate whether the method is susceptible to confounding effects.</p> <p>Results</p> <p>We found that the power of the BiSSE method is severely affected by both sample size and high tip ratio bias (one character state dominates among observed tips). Sample size and high tip ratio bias also reduced accuracy and precision of parameter estimation, and resulted in the inability to infer which rate asymmetry caused the excess of a character state. In low tip ratio bias scenarios with appropriate tip sample size, BiSSE accurately estimated the rate asymmetry causing character state excess, avoiding the issue of confounding effects.</p> <p>Conclusions</p> <p>Based on our findings, we recommend that future studies utilizing BiSSE that have fewer than 300 terminals and/or have datasets where high tip ratio bias is observed (i.e., fewer than 10% of species are of one character state) should be extremely cautious with the interpretation of hypothesis testing results.</p>
topic Key innovations
Character evolution
Systematics
url http://www.biomedcentral.com/1471-2148/13/38
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