A likelihood approach to populations samples of microsatellite alleles.
This paper presents a likelihood approach to population samples of microsatellite alleles. A Markov chain recursion method previously published by GRIFFITHS and TAVARE is applied to estimate the likelihood function under different models of microsatellite evolution. The method presented can be applied to estimate a fundamental population genetics parameter theta as well as parameters of the mutational model. The new likelihood estimator provides a better estimator of theta in terms of the mean square error than previous approaches. Furthermore, it is demonstrated how the method may easily be applied to test models of microsatellite evolution. In particular it is shown how to compare a one-step model of microsatellite evolution to a multi-step model by a likelihood ratio test.
Nielsen
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Department of Integrative Biology, University of California, Berkeley 94720-3140, USA. rasmus@mws4.biol.berkeley.edu
D000483:Alleles; D005828:Genetics, Population; D016013:Likelihood Functions; D008390:Markov Chains; D008433:Mathematics; D018895:Microsatellite Repeats / Q000235:genetics*; D008957:Models, Genetic