GppFst: genomic posterior predictive simulations of FST and dXY for identifying outlier loci from population genomic data

Richard H Adams; Drew R Schield; Daren C Card; Heath Blackmon; Todd A Castoe

doi:10.1093/bioinformatics/btw795

GppFst: genomic posterior predictive simulations of FST and dXY for identifying outlier loci from population genomic data

Bioinformatics. 2017 May 1;33(9):1414-1415. doi: 10.1093/bioinformatics/btw795.

Authors

Richard H Adams¹, Drew R Schield¹, Daren C Card¹, Heath Blackmon², Todd A Castoe¹

Affiliations

¹ Department of Biology, The University of Texas at Arlington, Arlington, TX 76019, USA.
² Department of Ecology, Evolution & Behavior, University of Minnesota, Saint Paul, MN 55108, USA.

PMID: 28453670
DOI: 10.1093/bioinformatics/btw795

Abstract

Summary: We introduce GppFst, an open source R package that generates posterior predictive distributions of FST and dx under a neutral coalescent model to identify putative targets of selection from genomic data.

Availability and implementation: GppFst is available at ( https://github.com/radamsRHA/GppFst ).

Contact: todd.castoe@uta.edu.

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

Algorithms
Animals
Crotalus / genetics
Genetic Loci*
Genetics, Population / methods*
Genome
Genomics / methods
Models, Genetic*
Polymorphism, Single Nucleotide*
Software*