Abstract Details
Activity Number:
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71
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Type:
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Contributed
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Date/Time:
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Sunday, August 3, 2014 : 4:00 PM to 5:50 PM
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Sponsor:
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Biometrics Section
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Abstract #313414
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View Presentation
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Title:
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Robustness to Divergence Time Estimation When Inferring Species Trees from Estimated Gene Trees
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Author(s):
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James Degnan*+ and Michael DeGiorgio
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Companies:
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University of New Mexico and Penn State
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Keywords:
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coalescence ;
method of moments ;
phylogenetics ;
maximum likelihood ;
population genetics
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Abstract:
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When a species diverges, separate genetic lineages within the population remain distinct. Assuming there is no gene flow between populations after speciation, the time to the most recent genetic ancestor (called the coalescence time) for two copies of the same gene has a shifted exponential distribution, where the shift parameter is the (unknown) time of speciation. The maximum likelihood estimate of the speciation time is the minimum coalescence time taken over a set of independent genetic loci if the coalescence times are known, and is an efficient estimator. In practice, however, coalescence times must be estimated from data and have a high degree of uncertainty. This talk explores how in this setting, estimating the speciation time in terms of the method of moments estimator, using the average coalescence time, can show better performance, and in fact the naive maximum likelihood estimator (ignoring errors in observed coalescence time) is statistically inconsistent for the speciation divergence time.
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Authors who are presenting talks have a * after their name.
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