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Statistical properties of the site-frequency spectrum associated with lambda-coalescents.


ABSTRACT: Statistical properties of the site-frequency spectrum associated with ?-coalescents are our objects of study. In particular, we derive recursions for the expected value, variance, and covariance of the spectrum, extending earlier results of Fu (1995) for the classical Kingman coalescent. Estimating coalescent parameters introduced by certain ?-coalescents for data sets too large for full-likelihood methods is our focus. The recursions for the expected values we obtain can be used to find the parameter values that give the best fit to the observed frequency spectrum. The expected values are also used to approximate the probability a (derived) mutation arises on a branch subtending a given number of leaves (DNA sequences), allowing us to apply a pseudolikelihood inference to estimate coalescence parameters associated with certain subclasses of ?-coalescents. The properties of the pseudolikelihood approach are investigated on simulated as well as real mtDNA data sets for the high-fecundity Atlantic cod (Gadus morhua). Our results for two subclasses of ?-coalescents show that one can distinguish these subclasses from the Kingman coalescent, as well as between the ?-subclasses, even for a moderate (maybe a few hundred) sample size.

SUBMITTER: Birkner M 

PROVIDER: S-EPMC3813835 | biostudies-other | 2013 Nov

REPOSITORIES: biostudies-other

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Statistical properties of the site-frequency spectrum associated with lambda-coalescents.

Birkner Matthias M   Blath Jochen J   Eldon Bjarki B  

Genetics 20130911 3


Statistical properties of the site-frequency spectrum associated with Λ-coalescents are our objects of study. In particular, we derive recursions for the expected value, variance, and covariance of the spectrum, extending earlier results of Fu (1995) for the classical Kingman coalescent. Estimating coalescent parameters introduced by certain Λ-coalescents for data sets too large for full-likelihood methods is our focus. The recursions for the expected values we obtain can be used to find the par  ...[more]

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