LDJump: Estimating variable recombination rates from population genetic data

Mol Ecol Resour. 2019 May;19(3):623-638. doi: 10.1111/1755-0998.12994. Epub 2019 Apr 4.

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.

Keywords: R-package; bioinformatics; change-point estimation; population recombination rate; regression.

MeSH terms

  • Computational Biology / methods*
  • Genetics, Population / methods*
  • Genotyping Techniques / methods
  • Humans
  • Recombination, Genetic*
  • Sequence Analysis, DNA / methods

Associated data

  • GENBANK/rs10622653
  • GENBANK/rs2299784