R/cache_twopts.R

In mmollina/MAPpoly: Genetic Linkage Maps in Autopolyploids

#' Frequency of genotypes for two-point recombination fraction estimation
#'
#' Returns the frequency of each genotype for two-point reduction
#' of dimensionality. The frequency is calculated for all pairwise
#' combinations and for all possible linkage phase configurations.
#'
#' @param input.seq an object of class \code{mappoly.sequence}
#'
#' @param cached If \code{TRUE}, access the counts for all
#'     linkage phase configurations in a internal file (default = FALSE)
#'
#' @param cache.prev an object of class \code{cache.info} containing
#'     pre-computed genotype frequencies, obtained with
#'     \code{\link[mappoly]{cache_counts_twopt}} (optional, default = NULL)
#'
#' @param ncpus Number of parallel processes to spawn (default = 1)
#'
#' @param verbose If \code{TRUE} (default), print the linkage phase
#'     configurations. If \code{cached = TRUE}, nothing is
#'     printed, since all linkage phase configurations will be cached.
#'
#' @param joint.prob If \code{FALSE} (default), returns the frequency of
#'     genotypes for transition probabilities (conditional
#'     probabilities). If \code{TRUE} returns the frequency for joint
#'     probabilities. The latter is especially important to compute the 
#'     Fisher's Information for a pair of markers.  
#'
#' @return An object of class \code{cache.info} which contains one (conditional probabilities)
#'     or two (both conditional and joint probabilities) lists. Each list
#'     contains all pairs of dosages between parents for all markers
#'     in the sequence. The names in each list are of the form 'A-B-C-D', where: A
#'     represents the dosage in parent 1, marker k; B represents the dosage in parent
#'     1, marker k+1; C represents the dosage in parent 2, marker k;
#'     and D represents the dosage in parent 2, marker k+1.  For each
#'     list, the frequencies were computed for all possible linkage
#'     phase configurations. The frequencies for each linkage phase
#'     configuration are distributed in matrices whose names
#'     represents the number of homologous chromosomes that share
#'     alleles. The rows on these matrices represents the dosages in markers k
#'     and k+1 for an individual in the offspring. See Table 3 of
#'     S3 Appendix in Mollinari and Garcia (2019) for an example.
#'
#' @examples
#'     all.mrk <- make_seq_mappoly(tetra.solcap, 1:20)
#'     ## local computation
#'     counts <- cache_counts_twopt(all.mrk, ncpus = 1)
#'     ## load from internal file or web-stored counts (especially important for high ploidy levels)
#'     counts.cached <- cache_counts_twopt(all.mrk, cached = TRUE)
#'
#' @author Marcelo Mollinari, \email{mmollin@ncsu.edu} with updates by Gabriel Gesteira, \email{gdesiqu@ncsu.edu}
#'
#' @references
#'     Mollinari, M., and Garcia, A.  A. F. (2019) Linkage
#'     analysis and haplotype phasing in experimental autopolyploid
#'     populations with high ploidy level using hidden Markov
#'     models, _G3: Genes, Genomes, Genetics_. 
#'     \doi{10.1534/g3.119.400378} 
#'     
#' @keywords two-point analysis
#' 
#' @export
#' @import parallel Rcpp RCurl
#' @importFrom stats na.omit
#' @importFrom utils combn read.table
cache_counts_twopt <- function(input.seq, cached = FALSE, cache.prev = NULL, 
                               ncpus = 1L, verbose = TRUE, joint.prob = FALSE) {
  ## checking for correct object
  start <- proc.time()
  if (!inherits(input.seq, "mappoly.sequence")) {
    stop(deparse(substitute(input.seq)), " is not an object of class 'mappoly.sequence'")
  }
  cache.prev = NULL
  # if(input.seq$ploidy == 2)
  # {
  #   cached <- FALSE
  #   if (verbose)
  #       cat("INFO: Computing genotype frequencies ...\n")
  # }
  if (cached){
    if (input.seq$ploidy  ==  2) ploidy = 'diploid'
    else if (input.seq$ploidy  ==  4) ploidy = 'tetraploid'
    else if (input.seq$ploidy  ==  6) ploidy = 'hexaploid'
    else return(get_cache_two_pts_from_web(input.seq$ploidy, verbose = verbose))
    return(structure(full_counts[[ploidy]], class = "cache.info"))
  }
  temp.count <- NULL
  if (joint.prob) {
    temp.count <- cache_counts_twopt(input.seq, cached = FALSE, cache.prev = cache.prev, 
                                     ncpus = ncpus, verbose = verbose, joint.prob = FALSE)$cond
  }
  if (verbose && input.seq$ploidy >= 8)
    message("\nploidy level ", input.seq$ploidy, ": this operation could take a very long time.
                 \ntry to use the option 'cached' instead.\n")
  dose.names <- sort(unique(apply(rbind(combn(input.seq$seq.dose.p1, 2), combn(input.seq$seq.dose.p2, 2)), 2, paste, collapse = "-")))
  if (!is.null(cache.prev)) {
    if (!inherits(cache.prev, "cache.info")) {
      stop(deparse(substitute(cache.prev)), " is not an object of class 'cache.info'")
    }
    ## Number of distinct genotypic combinations for different ploidy levels
    x <- c(3, 6, 10, 15, 21, 28, 36)
    names(x) <- c("2", "4", "6", "8", "10", "12", "14")
    pl.class <- choose(1 + input.seq$ploidy/2, 2) + 1 + input.seq$ploidy/2
    first.na <- sapply(unlist(cache.prev, recursive = FALSE), function(x) !all(is.na(x)))
    
    ## check if the ploidy levels match
    if (ncol(cache.prev[[min(which(first.na))]][[1]]) != pl.class) {
      warning(deparse(substitute(cache.prev)), " contains counts for ploidy level ", names(which(x  ==  ncol(cache.prev[[1]][[1]]))), "\n  Obtaining new counts for ploidy ",
              input.seq$ploidy)
      return(cache_counts_twopt(input.seq = input.seq, cache.prev = NULL, ncpus = ncpus, verbose = verbose, joint.prob = joint.prob))
    }
    remaining <- which(is.na(pmatch(dose.names, names(cache.prev))))
    if (length(remaining)  ==  0) {
        if (verbose)
            cat("\n Nothing to add to 'cache.prev'. Returning original 'cache prev'.\n")
      return(cache.prev)
    }
    dose.names <- dose.names[remaining]
  }
  aux.mat <- matrix(unlist(lapply(strsplit(dose.names, split = "-"), as.numeric)), ncol = 4, byrow = TRUE)
  dimnames(aux.mat) <- list(paste("Conf.", 1:nrow(aux.mat), sep = ""), c("P.k", "P.k+1", "Q.k", "Q.k+1"))
  if (verbose) {
    cat("\n   Caching the following dosage combination: \n")
    print(aux.mat)
  }
  if (ncpus > 1) {
    if (verbose)
      cat("INFO: Using ", ncpus, " CPU's for calculation.\n")
    cl <- makeCluster(ncpus)
    on.exit(stopCluster(cl))
    y <- parApply(cl, aux.mat, 1, get_counts_all_phases, ploidy = input.seq$ploidy, joint.prob = joint.prob)
    end <- proc.time()
  } else {
    if (verbose)
      cat("INFO: Going singlemode. Using one Core/CPU/PC for calculation.\n")
    y <- apply(aux.mat, 1, get_counts_all_phases, input.seq$ploidy, joint.prob = joint.prob)
    end <- proc.time()
  }
  if (verbose) {
    cat("INFO: Done with", nrow(aux.mat), "phase configurations\n")
    cat("INFO: Calculation took:", round((end - start)[3], digits = 3), "seconds\n")
  }
  names(y) <- dose.names
  w <- c(cache.prev, y)
  joint <- NULL
  cond <- temp.count
  if (joint.prob)
    joint <- w else cond <- w
  all.dose.names <- apply(expand.grid(0:input.seq$ploidy, 0:input.seq$ploidy, 0:input.seq$ploidy, 0:input.seq$ploidy), 1, paste, collapse = "-")
  z1 <- z2 <- vector("list", length(all.dose.names))
  names(z1) <- names(z2) <- all.dose.names
  z1[names(cond)] <- cond
  if (joint.prob)
    z2[names(joint)] <- joint
  structure(list(cond = z1, joint = z2), class = "cache.info")
}

#' @export
print.cache.info <- function(x, ...) {
  x$cond[sapply(x$cond, is.null)] <- NA
  NonNAindex <- which(!is.na(x$cond))
  firstNonNA <- min(NonNAindex)
  y <- c(3, 6, 10, 15, 21, 28, 36)
  names(y) <- c("2", "4", "6", "8", "10", "12", "14")
  cat("  This is an object of class 'cache.info'")
  cat("\n  -----------------------------------------------------")
  ## printing summary
  cat("\n  Ploidy level:                               ", names(which(ncol(x$cond[[firstNonNA]][[1]]) == y)), "\n")
  cat("  No. marker combinations:                    ", length(x$cond), "\n")
  cat("  -----------------------------------------------------\n")
}