OptM: estimating the optimal number of migration edges on population trees using Treemix

Abstract The software Treemix has become extensively used to estimate the number of migration events, or edges (m), on population trees from genome-wide allele frequency data. However, the appropriate number of edges to include remains unclear. Here, I show that an optimal value of m can be inferred...

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Veröffentlicht in:Biology methods and protocols Jg. 6; H. 1; S. bpab017
1. Verfasser: Fitak, Robert R
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Oxford University Press 2021
Schlagworte:
Bioinformatics
Biology
Datasets
Domestic animals
Gene frequency
Genomes
Genomics
Innovations
Migration
Population
Population genetics
Simulation
Software packages
Trees
population genomics
SNPs
likelihood
structure
ISSN:2396-8923, 2396-8923
Online-Zugang:Volltext
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Zusammenfassung:Abstract The software Treemix has become extensively used to estimate the number of migration events, or edges (m), on population trees from genome-wide allele frequency data. However, the appropriate number of edges to include remains unclear. Here, I show that an optimal value of m can be inferred from the second-order rate of change in likelihood (Δm) across incremental values of m. Repurposed from its original use to estimate the number of population clusters in the software Structure (ΔK), I show using simulated populations that Δm performs equally as well as current recommendations for Treemix. A demonstration of an empirical dataset from domestic dogs indicates that this method may be preferable in large, complex population histories and can prioritize migration events for subsequent investigation. The method has been implemented in a freely available R package called “OptM” and as a web application (https://rfitak.shinyapps.io/OptM/) to interface directly with the output files of Treemix.
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ISSN:2396-8923
2396-8923
DOI:10.1093/biomethods/bpab017