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Mol Ecol Resour. 2015 Jan;15(1):87-98. doi: 10.1111/1755-0998.12280. Epub 2014 Jun 11.

WFABC: a Wright-Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled data.

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School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Station 15, CH-1015, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.


With novel developments in sequencing technologies, time-sampled data are becoming more available and accessible. Naturally, there have been efforts in parallel to infer population genetic parameters from these data sets. Here, we compare and analyse four recent approaches based on the Wright-Fisher model for inferring selection coefficients (s) given effective population size (N(e)), with simulated temporal data sets. Furthermore, we demonstrate the advantage of a recently proposed approximate Bayesian computation (ABC)-based method that is able to correctly infer genomewide average N(e) from time-serial data, which is then set as a prior for inferring per-site selection coefficients accurately and precisely. We implement this ABC method in a new software and apply it to a classical time-serial data set of the medionigra genotype in the moth Panaxia dominula. We show that a recessive lethal model is the best explanation for the observed variation in allele frequency by implementing an estimator of the dominance ratio (h).


approximate Bayesian computation; effective population size; genetic drift; natural selection; population genetics; time-sampled data

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