Estimating effective population size from temporally spaced samples with a novel, efficient maximum-likelihood algorithm.
The effective population size [Formula: see text] is a key parameter in population genetics and evolutionary biology, as it quantifies the expected distribution of changes in allele frequency due to genetic drift. Several methods of estimating [Formula: see text] have been described, the most direct of which uses allele frequencies measured at two or more time points. A new likelihood-based estimator [Formula: see text] for contemporary effective population size using temporal data is developed in this article. The existing likelihood methods are computationally intensive and unable to handle the case when the underlying [Formula: see text] is large. This article tries to work around this problem by using a hidden Markov algorithm and applying continuous approximations to allele frequencies and transition probabilities. Extensive simulations are run to evaluate the performance of the proposed estimator [Formula: see text], and the results show that it is more accurate and has lower variance than previous methods. The new estimator also reduces the computational time by at least 1000-fold and relaxes the upper bound of [Formula: see text] to several million, hence allowing the estimation of larger [Formula: see text]. Finally, we demonstrate how this algorithm can cope with nonconstant [Formula: see text] scenarios and be used as a likelihood-ratio test to test for the equality of [Formula: see text] throughout the sampling horizon. An R package "NB" is now available for download to implement the method described in this article.
Department of Life Sciences, Silwood Park Campus, Imperial College London, Ascot, Berkshire SL5 7PY, United Kingdom tin-yu.hui11@imperial.ac.uk.
Tin-Yu J
http://orcid.org/0000-0002-1702-803X
TY
Hui
Department of Life Sciences, Silwood Park Campus, Imperial College London, Ascot, Berkshire SL5 7PY, United Kingdom.
Austin
A
Burt
D000465:Algorithms; D005828:Genetics, Population / Q000379:methods*; D016013:Likelihood Functions; D008957:Models, Genetic; D011153:Population / Q000235:genetics; D018401:Sample Size; D013995:Time
effective population size; genetic drift; maximum-likelihood estimation