Abstract
As recombination plays an important role in evolution, its estimation, as well as, the identification of hotspot positions is of considerable interest. We propose a novel approach for estimating historical recombination along a chromosome that involves a sequential multiscale change point estimator. Our method also permits to take demography into account. It uses a composite likelihood estimate and other summary statistics within a regression model fitted on suitable scenarios. Our proposed method is accurate, computationally fast, and provides a parsimonious solution by ensuring a type I error control against too many changes in the recombination rate. An application to human genome data suggests a good congruence between our estimated and experimentally identified hotspots. Our method is implemented in the R-package LDJump, which is freely available from https://github.com/PhHermann/LDJump.