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LDJump: Estimating variable recombination rates from population genetic data.


ABSTRACT: 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.

SUBMITTER: Hermann P 

PROVIDER: S-EPMC6519033 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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LDJump: Estimating variable recombination rates from population genetic data.

Hermann Philipp P   Heissl Angelika A   Tiemann-Boege Irene I   Futschik Andreas A  

Molecular ecology resources 20190404 3


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,  ...[more]

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