R/gl2related.r

In dartR: Importing and Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide Restriction Fragment Analysis

#' Converts a genlight object to format suitable to be run with Coancestry
#'
#' The output txt file contains the SNP data and an additional column with the
#' names of the individual. The file then can be used and loaded into coancestry
#' or - if installed - run with the related package. Be aware the related
#' package was crashing in previous versions, but in general is using the same
#' code as coancestry and therefore should have identical results. Also running
#' coancestry with thousands of SNPs via the GUI seems to be not reliable and
#' therefore for comparisons between coancestry and related we suggest to use
#' the command line version of coancestry.
#'
#' @param x Name of the genlight object containing the SNP data [required].
#' @param outfile File name of the output file (including extension)
#' [default 'related.txt'].
#' @param outpath Path where to save the output file [default tempdir()].
#' @param save A switch if you want to save the file or not. This might be
#' useful for someone who wants to use the coancestry function to calculate
#' relatedness and not export to coancestry. See the example below
#' [default TRUE].
#' @param verbose Verbosity: 0, silent or fatal errors; 1, begin and end; 2,
#' progress log; 3, progress and results summary; 5, full report
#' [default 2, unless specified using gl.set.verbosity].
#' @return A data.frame that can be used to run with the related package
#' @export
#' @author Bernd Gruber (bugs? Post to
#' \url{https://groups.google.com/d/forum/dartr})
#' @examples
#' gtd <- gl2related(bandicoot.gl[1:10,1:20], save=FALSE)
#' \dontrun{
#' ##running with the related package
#' #install.packages('related', repos='http://R-Forge.R-project.org')
#' library(related)
#' coan <- coancestry(gtd, wang=1)
#' head(coan$relatedness)
#' ##check ?coancestry for information how to use the function.
#' }
#' @references Jack Pew, Jinliang Wang, Paul Muir and Tim Frasier (2014).
#' related: related: an R package for analyzing pairwise relatedness
#'  data based on codominant molecular markers.
#'  R package version 0.8/r2.
#'   \url{https://R-Forge.R-project.org/projects/related/}

gl2related <- function(x,
                       outfile = "related.txt",
                       outpath = tempdir(),
                       save = TRUE,
                       verbose = NULL) {
    
    # SET VERBOSITY
    verbose <- gl.check.verbosity(verbose)
    
    # FLAG SCRIPT START
    funname <- match.call()[[1]]
    utils.flag.start(func = funname,
                     build = "Jody",
                     verbosity = verbose)
    
    # CHECK DATATYPE
    datatype <- utils.check.datatype(x, verbose = verbose)
    
    # DO THE JOB
    
    gd <- as.matrix(x)
    
    mm <- matrix(NA, nrow = nrow(gd), ncol = ncol(gd) * 2)
    mm[, seq(1, nLoc(x) * 2, 2)] <- gd
    mm <- ifelse(mm == 1, 0, mm)
    
    mm[, seq(2, nLoc(x) * 2, 2)] <- gd
    mm <- ifelse(mm == 1, 2, mm)
    
    mm <- mm + 1
    mm <- ifelse(is.na(mm), 0, mm)
    
    gtd <- data.frame(V1 = as.character(indNames(x)), mm)
    gtd$V1 <- as.character(gtd$V1)
    
    fn <- file.path(outpath, outfile)
    # export as file
    if (save)
        write.table(
            gtd,
            file = fn,
            sep = "\t",
            col.names = F,
            row.names = F
        )
    
    # FLAG SCRIPT END
    
    if (verbose >= 1) {
        cat(report("Completed:", funname, "\n"))
    }
    
    # RETURN
    
    return(gtd)
    
}