R/RcppExports.R

In LDAandLDAS: Linkage Disequilibrium of Ancestry (LDA) and LDA Score (LDAS)

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

#' @title LDA of a pair of SNPs
#' @description Computation of the pairwise Linkage Disequilibrium of Ancestry (LDA) between a pair of single nucleotide polymorphisms (SNPs).
#' @param data_resample a data frame of the first SNP's ancestry probabilities after resampling.
#' Different ancestry probabilities are in different columns.
#' @param data_base a data frame of the first SNP's ancestry probabilities.
#' Different ancestry probabilities are in different columns.
#' @param data_experiment a data frame of the second SNP's ancestry probabilities.
#' Different ancestry probabilities are in different columns.
#' @param n_ancestry a positive integer representing the number of different ancestries.
#' @return a numeric number representing the pairwise LDA of the two SNPs.
#' @details This function computes the LDA between two SNPs.
#' Resampling of one of the SNPs' painting data is required prior to implementing this function.
#' To compute pairwise LDA between multiple pairs of SNPs, please use \code{\link{LDA}}.
#' @references Barrie, W., Yang, Y., Irving-Pease, E.K. et al. Elevated genetic risk for multiple sclerosis emerged in steppe pastoralist populations. Nature 625, 321–328 (2024).
#' @examples
#' \donttest{
#' # compute the LDA between the 50th SNP and the 55th SNP
#' # painting data for the 50th SNP (2 ancestries)
#' data_base <- cbind(LDAandLDAS::example_painting_p1[,50],
#'                    LDAandLDAS::example_painting_p2[,50])
#'
#' # painting data for the 55th SNP (2 ancestries)
#' data_experiment <- cbind(LDAandLDAS::example_painting_p1[,55],
#'                          LDAandLDAS::example_painting_p2[,55])
#'
#' # resample painting data for the 50th SNP
#' data_resample <- data_base[sample(1:nrow(data_base)),]
#'
#' #compute their pairwise LDA
#' LDA_value <- cal_lda(data_resample,data_base,data_experiment,2)
#' }
#' @export
cal_lda <- function(data_resample, data_base, data_experiment, n_ancestry) {
    .Call(`_LDAandLDAS_cal`, data_resample, data_base, data_experiment, n_ancestry)
}