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#' @name gl.edit.recode.ind
#' @title Creates or edits individual (=specimen) names, creates a recode_ind
#' file and applies the changes to a genlight object
#' @description
#' A script to edit individual names in a genlight object, or to create a
#' reassignment table taking the individual labels from a genlight object, or to
#' edit existing individual labels in an existing recode_ind file.
#' @details
#' Renaming individuals may be required when there have been errors in labelling
#' arising in the process from sample to DArT files. There may be occasions
#' where renaming individuals is required for preparation of figures. Caution
#' needs to be exercised because of the potential for breaking the 'chain of
#' evidence' between the samples themselves and the analyses. Recoding
#' individuals can also be done with a recode table (csv).
#'
#' This script will input an existing recode table for editing and optionally
#' save it as a new table, or if the name of an input table is not supplied,
#' will generate a table using the individual labels in the parent genlight
#' object.
#'
#' The script, having deleted individuals, optionally identifies resultant
#' monomorphic loci or loci with all values missing and deletes them (using
#' gl.filter.monomorphs.r). The script also optionally recalculates statistics
#' made redundant by the deletion of individuals from the dataset.
#'
#' Use outpath=getwd() or outpath='.' when calling this function to direct
#' output files to your working directory.
#'
#' The script returns a genlight object with the new individual labels and the
#' recalculated locus metadata.
#'
#' @param x Name of the genlight object for which individuals are to be
#' relabelled [required].
#' @param out.recode.file Name of the file to output the new individual labels
#' [optional].
#' @param outpath Path where to save the output file
#' [default tempdir(), mandated by CRAN].
#' @param recalc Recalculate the locus metadata statistics [default TRUE].
#' @param mono.rm Remove monomorphic loci [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 or as specified using gl.set.verbosity].
#' @return An object of class ('genlight') with the revised individual labels.
#' @import utils
#' @export
#' @author Custodian: Arthur Georges -- Post to
#' \url{https://groups.google.com/d/forum/dartr}
#' @seealso \code{\link{gl.recode.ind}}, \code{\link{gl.drop.ind}},
#' \code{\link{gl.keep.ind}}
#' @examples
#' \dontrun{
#' gl <- gl.edit.recode.ind(testset.gl)
#' gl <- gl.edit.recode.ind(testset.gl, out.recode.file='ind.recode.table.csv')
#' }
gl.edit.recode.ind <- function(x,
out.recode.file = NULL,
outpath = tempdir(),
recalc = FALSE,
mono.rm = FALSE,
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)
outfilespec <- file.path(outpath, out.recode.file)
# DO THE JOB
# Store variables
hold <- x
# Take assignments from x
if (verbose >= 2) {
cat(report(
" Extracting current individual labels from the x object\n"
))
}
recode.table <- cbind(indNames(x), indNames(x))
# Create recode table for editting, and bring up the editor
new <- as.matrix(edit(recode.table))
# new <- new[,1:2]
# Write out the recode table, if requested
if (is.null(out.recode.file)) {
if (verbose >= 2) {
cat(
warn(
" Warning: No output table specified, recode table not written to disk\n"
)
)
}
} else {
if (verbose >= 2) {
cat(report(
paste(
" Writing individual recode table to: ",
out.recode.file,
"\n"
)
))
}
write.table(
new,
file = out.recode.file,
sep = ",",
row.names = FALSE,
col.names = FALSE
)
}
# Apply the new assignments
ind.list <- as.character(indNames(x))
ntr <- length(new[, 1])
for (i in 1:nInd(x)) {
for (j in 1:ntr) {
if (ind.list[i] == new[j, 1]) {
ind.list[i] <- new[j, 2]
}
}
}
# Assigning new populations to x
if (verbose >= 2) {
cat(report(" Assigning new individual (=specimen) names\n"))
}
indNames(x) <- ind.list
# If there are populations to be deleted, then recalculate relevant locus metadata and remove monomorphic loci
if ("delete" %in% indNames(x) | "Delete" %in% indNames(x)) {
# Remove populations flagged for deletion
if (verbose >= 2) {
cat(
report(
" Deleting individuals/samples flagged for deletion (Flagged 'Delete' or 'delete')\n"
)
)
}
x <-
gl.drop.ind(x,
ind.list = c("Delete", "delete"),
verbose = 0)
}
# Remove monomorphic loci
if (mono.rm) {
if (verbose >= 2) {
cat(report(" Deleting monomorphic loc\n"))
}
x <- gl.filter.monomorphs(x, verbose = 0)
}
# Check monomorphs have been removed
if (x@other$loc.metrics.flags$monomorphs == FALSE) {
if (verbose >= 2) {
cat(warn(
" Warning: Resultant dataset may contain monomorphic loci\n"
))
}
}
# Recalculate statistics
if (recalc) {
x <- gl.recalc.metrics(x, verbose = 0)
if (verbose >= 2) {
cat(report(" Recalculating locus metrics\n"))
}
} else {
if (verbose >= 2) {
cat(warn(" Locus metrics not recalculated\n"))
x <- utils.reset.flags(x, verbose = 0)
}
}
# REPORT A SUMMARY
if (verbose >= 2) {
cat(" Summary of recoded dataset\n")
# cat(paste(' Original No. of loci:',hold.nLoc,'\n')) cat(paste(' New No. of loci:',nLoc(x),'\n'))
cat(paste(" Original No. of individuals:", nInd(hold), "\n"))
cat(paste(" New No. of individuals:", nInd(x), "\n"))
# cat(paste(' Original No. of populations:', hold.nPop,'\n')) cat(paste(' New No. of populations:', nPop(x),'\n'))
if (!recalc) {
cat(report(" Note: Locus metrics not recalculated\n"))
}
if (!mono.rm) {
cat(report(" Note: Resultant monomorphic loci not deleted\n"))
}
}
# ADD TO HISTORY
nh <- length(x@other$history)
x@other$history[[nh + 1]] <- match.call()
# FLAG SCRIPT END
if (verbose > 0) {
cat(report("Completed:", funname, "\n"))
}
return(x)
}
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