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LDJump : Estimating variable recombination rates from population genetic data
Author(s) -
Hermann Philipp,
Heissl Angelika,
TiemannBoege Irene,
Futschik Andreas
Publication year - 2019
Publication title -
molecular ecology resources
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/1755-0998.12994
Subject(s) - biology , estimator , recombination , statistics , genotyping , population , hotspot (geology) , regression , recombination rate , genetics , mathematics , demography , sociology , geophysics , gene , genotype , geology
As recombination plays an important role in evolution, its estimation and the identification of hotspot positions is of considerable interest. We propose a novel approach for estimating population recombination rates based on genotyping or sequence data that involves a sequential multiscale change point estimator. Our method also permits demography to be taken into account. It uses several 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 at https://github.com/PhHermann/LDJump.