An R Framework for the Partitioning of Linkage Disequilibrium between and Within Populations

Patterns of linkage disequilibrium (LD) across the genome result from a myriad of contributing factors including selection and genetic drift. Natural selection can increase LD near individually selected loci, or it can influence LD between epistatically selected groups of loci. Statistics have previ...

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Bibliographic Details
Main Authors: Paul F. Petrowski, Elizabeth G. King, Timothy M. Beissinger
Format: Article
Language:English
Published: Ubiquity Press 2019-04-01
Series:Journal of Open Research Software
Subjects:
Online Access:https://openresearchsoftware.metajnl.com/articles/250
Description
Summary:Patterns of linkage disequilibrium (LD) across the genome result from a myriad of contributing factors including selection and genetic drift. Natural selection can increase LD near individually selected loci, or it can influence LD between epistatically selected groups of loci. Statistics have previously been derived which compare levels of linkage disequilibrium in subpopulations relative to the total population. These statistics may be leveraged to identify loci that may be under selection or epistatic selection. This is a powerful approach, but to date no framework exists to support its use on a genome-wide scale. We present ohtadstats, an R package designed to facilitate the implementation of Ohta’s D statistics in a variety of use cases. Statistics calculated by this package can be used to determine whether a locus is under selection or not, and can provide insight into the nature of the selection that is taking place (hard sweep or epistatic selection). This package is available on the Comprehensive R Archive Network (CRAN).   Funding statement: This research was supported by funding from the USDA Agricultural Research Service. PFP is funded by the University of Missouri Life Sciences Fellowship and a training grant from the National Institute of Health (T32GM008396).
ISSN:2049-9647