Nothing
#' Helper function to estimating g2 from really large datasets
#'
#' @param genotypes \code{data.frame} with individuals in rows and loci in columns,
#' containing genotypes coded as 0 (homozygote), 1 (heterozygote) and NA (missing)
#' @param nperm number or permutations for to estimate a p-value
#' @param nboot number of bootstraps to estimate a confidence interval
#' @param boot_over Bootstrap over individuals by specifying "inds" and over loci with "loci". Defaults to "ind".
#' @param CI confidence interval (default to 0.95)
#' @param parallel Default is FALSE. If TRUE, bootstrapping and permutation tests are parallelized
#' @param ncores Specify number of cores to use for parallelization. By default,
#' all available cores are used.
#' @param verbose If FALSE, nothing will be printed to show the status of bootstraps and permutations.
#' @keywords internal
#'
subset_snps <- function(genotypes, nperm = 0, nboot = 0, boot_over = "inds",
CI = 0.95, parallel = FALSE, ncores = NULL, verbose = TRUE, subset_loci = 1000){
g2_subset <- function(genotypes) {
geno_sub <- genotypes[, sample(subset_loci, replace = FALSE)]
g2_out <- g2_snps(geno_sub, nperm = 0, nboot = 0, boot_over, CI, parallel, ncores, verbose)
}
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.