The impact of selection in the \Lambda-Wright-Fisher model

Abstract

The purpose of this article is to study some asymptotic properties of the \Lambda-Wright-Fisher process with selection. This process represents the frequency of a disadvantaged allele. The resampling mechanism is governed by a finite measure \Lambda on [0,1] and the selection by a parameter \alpha. When the measure \Lambda verifies \int_0^1-\log(1-x)x^{-2} \Lambda(dx)<\infty, some particular behaviours in the frequency of the allele can occur. The selection coefficient \alpha may be large enough to compensate the random genetic drift. In other words, for certain selection pressure, the disadvantaged allele will vanish asymptotically. This phenomenon cannot occur in the classical Wright-Fisher diffusion. We study the dual process of the \Lambda-Wright-Fisher process with selection and prove this result through martingale arguments.