triangulaR: an R package for identifying AIMs and building triangle plots using SNP data from hybrid zones DOI Creative Commons
Ben J. Wiens, Lucas H. DeCicco, Jocelyn P. Colella

и другие.

Heredity, Год журнала: 2025, Номер unknown

Опубликована: Апрель 12, 2025

Abstract Hybridization provides a window into the speciation process and reshuffles parental alleles to produce novel recombinant genotypes. Presence or absence of specific hybrid classes across zone can provide support for various modes reproductive isolation. Early generation be distinguished by their combination index interclass heterozygosity, which estimated with molecular data. Hybrid heterozygosity are routinely calculated studies zones, but available resources next-generation sequencing datasets computationally demanding tools visualizing triangle plots lacking. Here, we resource identifying ancestry-informative markers (AIMs) from single nucleotide polymorphism (SNP) datasets, calculating relationship as plot. Our methods implemented in R package triangulaR . We validate our on an empirical dataset simulations genetic data between two groups at low, medium, high levels divergence. accurate precise estimates sample sizes low five individuals per group, similar error another program estimation, bgchm explore allele frequency difference thresholds AIM identification, how this threshold influences accuracy precision estimates. contextualize interpretation describing theoretical expectations under Hardy-Weinberg Equilibrium recommendations best practices AIMs building plots.

Язык: Английский

triangulaR: an R package for identifying AIMs and building triangle plots using SNP data from hybrid zones DOI Creative Commons
Ben J. Wiens, Lucas H. DeCicco, Jocelyn P. Colella

и другие.

Heredity, Год журнала: 2025, Номер unknown

Опубликована: Апрель 12, 2025

Abstract Hybridization provides a window into the speciation process and reshuffles parental alleles to produce novel recombinant genotypes. Presence or absence of specific hybrid classes across zone can provide support for various modes reproductive isolation. Early generation be distinguished by their combination index interclass heterozygosity, which estimated with molecular data. Hybrid heterozygosity are routinely calculated studies zones, but available resources next-generation sequencing datasets computationally demanding tools visualizing triangle plots lacking. Here, we resource identifying ancestry-informative markers (AIMs) from single nucleotide polymorphism (SNP) datasets, calculating relationship as plot. Our methods implemented in R package triangulaR . We validate our on an empirical dataset simulations genetic data between two groups at low, medium, high levels divergence. accurate precise estimates sample sizes low five individuals per group, similar error another program estimation, bgchm explore allele frequency difference thresholds AIM identification, how this threshold influences accuracy precision estimates. contextualize interpretation describing theoretical expectations under Hardy-Weinberg Equilibrium recommendations best practices AIMs building plots.

Язык: Английский

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