Bayesian hybrid index and genomic cline estimation with the R package gghybrid

Admixture, the interbreeding of individuals from differentiated source populations, is now known to be a widespread phenomenon. Genomic studies of natural hybridisation can help to answer many questions on the impacts of admixture on adaptive evolution, reproductive isolation, and speciation. When a large variety of admixture proportions between two source populations exist, both geographic and genomic cline analysis are suitable methods for inferring biased, restricted or excessive gene flow at individual loci into the foreign genomic background, providing evidence for reproductive isolation, selection across an environmental transition, balancing selection, and adaptive introgression. Genomic cline analysis replaces geographic location with genome-wide hybrid index and is therefore useable in circumstances that violate geographic cline assumptions. Here, I introduce gghybrid, an R package for simple and flexible Bayesian estimation of Buerkle's hybrid index and Fitzpatrick's logit-logistic genomic clines using bi-allelic data, suitable for both small and large datasets. gghybrid allows any ploidy and uses Structure input file format. It has separate functions for hybrid index and cline estimation, treating each individual and locus respectively as an independent analysis, making it highly parallelisable. Admixture proportions from other software can alternatively be used in cline analysis, alongside parental allele frequencies. Parameters can be fixed and samples pooled for statistical model comparison with AIC or waic. Here, I describe the functions, pipeline, and statistical properties of gghybrid. Simulations reveal that model comparison with waic is preferred, and use of Bayesian posterior distributions and p values to select candidate non-null loci is problematic and should be avoided.