R/utils.assignment.r

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

#' @name utils.assignment
#' @title Population assignment probabilities
#' @description
#' This function takes one individual and estimates
#' their probability of coming from individual populations
#' from multilocus genotype frequencies.
#
#' @param x Name of the genlight object containing the SNP data [required].
#' @param unknown Name of the individual to be assigned to a population [required].
# @param inbreeding_par The inbreeding parameter [default 0].
#' @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].
#' @details
#' This function is a re-implementation of the function multilocus_assignment
#'  from package gstudio.
#'  Description of the method used in this function can be found at:
#' https://dyerlab.github.io/applied_population_genetics/population-assignment.html
#' @return A \code{data.frame} consisting of assignment probabilities for each
#'  population.
#' @author Custodian: Luis Mijangos -- Post to
#' \url{https://groups.google.com/d/forum/dartr}
#' @examples
#' require("dartR.data")
#' res <- utils.assignment(platypus.gl,unknown="T27")
#' @export

utils.assignment <- function(x,
                             unknown,
                             # inbreeding_par = 0,
                             verbose = 2) {
  # 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)
  
  if (unknown %in% indNames(x) == FALSE) {
    stop(error(
      paste("  Individual", unknown, "is not in the genlight object\n")
    ))
  }
  
  # DO THE JOB
  
  # filtering loci with all missing data by population
  # x <- gl.filter.allna(x, by.pop = TRUE, verbose = 0)
  unknown_pop <- gl.keep.ind(x, ind.list = unknown, verbose = 0)
  unknown_pop <- data.frame(gl2alleles(unknown_pop))
  
  x <- gl.drop.ind(x, ind.list = unknown, verbose = 0)
  
  pop_names <- popNames(x)
  
  pop_list <- seppop(x)
  gl_alleles <- do.call(rbind, strsplit(x$loc.all, "/"))
  
  frequencies <- lapply(pop_list, function(y) {
    freq_allele <- gl.alf(y)
    freqs_gl <-
      data.frame(
        Allele1 = gl_alleles[, 1],
        Allele2 = gl_alleles[, 2],
        Frequency1 = freq_allele[, 1],
        Frequency2 = freq_allele[, 2]
      )
    return(freqs_gl)
  })
  
  ret <- data.frame(Population = pop_names, Probability = 0)
  
  for (popx in 1:nPop(x)) {
    prob <- 1
    
    if (verbose >= 2) {
      cat(
        report(
          "  Assigning individual",
          unknown,
          "against population",
          pop_names[popx],
          "\n"
        )
      )
    }
    
    popfreq <- frequencies[[popx]]
    
    loc <-
      as.data.frame(do.call(rbind, strsplit(unname(
        unlist(unknown_pop)
      ), ":")))
    colnames(loc) <- c("a1", "a2")
    
    df_assign <- cbind(loc, popfreq)
    df_assign$hom1 <- df_assign$Frequency1 ^ 2
    df_assign$hom2 <- df_assign$Frequency2 ^ 2
    df_assign$het <- 2 * df_assign$Frequency1 * df_assign$Frequency2
    
    df_assign[which(df_assign$a1 == df_assign$a2 &
                      df_assign$a1 == df_assign$Allele1), c("hom2", "het")] <-
      0
    
    df_assign[which(df_assign$a1 == df_assign$a2 &
                      df_assign$a1 == df_assign$Allele2), c("hom1", "het")] <-
      0
    
    df_assign[which(df_assign$a1 != df_assign$a2), c("hom1", "hom2")] <-
      0
    
    df_assign$prob <-
      df_assign$hom1 + df_assign$hom2 + df_assign$het
    
    df_assign[which(is.na(df_assign$a1)), "prob"] <- NA
    
    df_assign[which(df_assign$prob == 0), "prob"] <- -1
    
    df_assign$prob <-    df_assign$prob / nLoc(x)
    
    #   if (inbreeding_par > 0) {
    #     f <- f * (1 - inbreeding_par)
    #     if (all_alleles[1] == all_alleles[2]) {
    #       f <-
    #         f + (popfreq$Frequency[popfreq$Allele == all_alleles[1]] * inbreeding_par)
    #     }
    #   }
    #
    
    # assign probability
    ret[popx, "Probability"] <- sum(df_assign$prob, na.rm = TRUE)
  }
  
  ret <- ret[order(-ret$Probability),]
  ret$Posterior <- ret$Probability / sum(ret$Probability)
  ret$Posterior <- round(ret$Posterior, 5)
  ret$Probability <- round(ret$Probability, 5)
  
  # FLAG SCRIPT END
  
  if (verbose >= 1) {
    cat(report("Completed:", funname, "\n"))
  }
  
  # RETURN
  
  return(invisible(ret))
  
}

gl2alleles <- function (gl) {
  x <- as.matrix(gl[, ])
  homs1 <-
    paste(substr(gl@loc.all, 1, 1), "/", substr(gl@loc.all, 1, 1), sep = "")
  hets <- gl@loc.all
  homs2 <-
    paste(substr(gl@loc.all, 3, 3), "/", substr(gl@loc.all, 3, 3), sep = "")
  xx <- matrix(NA, ncol = ncol(x), nrow = nrow(x))
  for (i in 1:nrow(x)) {
    for (ii in 1:ncol(x)) {
      inp <- x[i, ii]
      if (!is.na(inp)) {
        if (inp == 0)
          xx[i, ii] <- homs1[ii]
        else if (inp == 1)
          xx[i, ii] <- hets[ii]
        else if (inp == 2)
          xx[i, ii] <- homs2[ii]
      } else {
        xx[i, ii] <- NA
      }
    }
  }
  xx <- gsub("/", ":", xx)
  return(xx)
}