Molecular Ecology ResourcesBioinformaticsPeer-reviewed journal article
LDJump: Estimating Variable Recombination Rates from Population Genetic Data
Philipp HermanniD, Angelika LahnsteineriD, Irene Tiemann‐BoegeiD, Andreas FutschikiD
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.
- organism: human
- assay: whole-genome sequencing
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 23
- FWCI
- 2.10
- Field percentile
- top 13%
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