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Exploring power and parameter estimation of the BiSSE method for analyzing species diversification Davis, Matthew P; Midford, Peter E; Maddison, Wayne
Abstract
Background: 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. Results 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. Conclusions 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.
Item Metadata
Title |
Exploring power and parameter estimation of the BiSSE method for analyzing species diversification
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Creator | |
Publisher |
BioMed Central
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Date Issued |
2013-02-11
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Description |
Background:
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.
Results
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.
Conclusions
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.
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Subject | |
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Type | |
Language |
eng
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Date Available |
2015-10-24
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution 4.0 International (CC BY 4.0)
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DOI |
10.14288/1.0132637
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URI | |
Affiliation | |
Citation |
BMC Evolutionary Biology. 2013 Feb 11;13(1):38
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Publisher DOI |
10.1186/1471-2148-13-38
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Peer Review Status |
Reviewed
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Scholarly Level |
Faculty
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Copyright Holder |
Davis et al; licensee BioMed Central Ltd.
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Citations and Data
Rights
Attribution 4.0 International (CC BY 4.0)