Hi, I am wondering if it is possible to calculate a bootstrap summary for pairwise differentiation statistics (e.g. Nei's Gst). The purpose is to generate confidence intervals for each value generated for all (pairwise) combinations of populations in a genind object. After running:
boot10 <- chao_bootstrap(genind_one, nreps = 10)
I attempted to run:
boot10_pw <- summarise_bootstrap(boot10, pairwise_Gst_Nei)
However, I received an error:
"Error in stats["per.locus", ] : no 'dimnames' attribute for array"
Is this analysis possible to do in the mmod package, or can bootstrap summaries only be performed per locus and then summarized over all loci, disregarding the population structure?
Thank you!
Hi, I am wondering if it is possible to calculate a bootstrap summary for pairwise differentiation statistics (e.g. Nei's Gst). The purpose is to generate confidence intervals for each value generated for all (pairwise) combinations of populations in a genind object. After running: boot10 <- chao_bootstrap(genind_one, nreps = 10)
I attempted to run: boot10_pw <- summarise_bootstrap(boot10, pairwise_Gst_Nei)
However, I received an error: "Error in stats["per.locus", ] : no 'dimnames' attribute for array"
Is this analysis possible to do in the mmod package, or can bootstrap summaries only be performed per locus and then summarized over all loci, disregarding the population structure? Thank you!