Population genetics inference for longitudinally-sampled mutants under strong selection.

ABSTRACT: Longitudinal allele frequency data are becoming increasingly prevalent. Such samples permit statistical inference of the population genetics parameters that influence the fate of mutant variants. To infer these parameters by maximum likelihood, the mutant frequency is often assumed to evolve according to the Wright-Fisher model. For computational reasons, this discrete model is commonly approximated by a diffusion process that requires the assumption that the forces of natural selection and mutation are weak. This assumption is not always appropriate. For example, mutations that impart drug resistance in pathogens may evolve under strong selective pressure. Here, we present an alternative approximation to the mutant-frequency distribution that does not make any assumptions about the magnit

SUBMITTER: Lacerda M 

PROVIDER: S-EPMC4224163 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature