R/simulation_utils.R

In mmollina/MAPPoly: Genetic Linkage Maps in Autopolyploids

#' Simulate mapping population (one parent)
#'
#' This function simulates a polyploid mapping population
#' under random chromosome segregation
#' with one informative parent. This function is not to be
#' directly called by the user
#' @keywords internal
sim_cross_one_informative_parent <- function(ploidy,
                                           n.mrk,
                                           rf.vec,
                                           hom.allele,
                                           n.ind,
                                           seed = NULL,
                                           prob = NULL){
    if(!is.null(seed)) set.seed(seed)
    if(length(rf.vec) == 1) rf.vec <- rep(rf.vec, n.mrk-1)
    res <- matrix(NA,n.ind,n.mrk)
    rf.res <- numeric(n.mrk-1)

    ## Listing all possible bivalent configurations
    a <- perm_tot(1:ploidy)
    bv.conf <- vector("list", nrow(a))
    for(i in 1:nrow(a))
    {
      temp <- apply(matrix(a[i,], 2, ploidy/2), 2, sort)
      bv.conf[[i]] <- temp[,order(temp[1,]), drop = FALSE]
    }
    bv.conf <- unique(bv.conf)
    names(bv.conf) <- sapply(bv.conf, function(x) paste(apply(x, 2,
                                                  function(x)
                                                    paste0("[", paste0(x, collapse = ""), "]", collapse = "")),
                                            collapse = ""))
    if(is.null(prob))
      prob <- rep(1/length(bv.conf), length(bv.conf))

    for(k in 1:n.ind){              #for each individual
        gen.1 <- matrix(1:ploidy,ploidy,n.mrk)  #simulates the chromosomes multiallelic markers in 'n.mrk' positions
        id <- sample(x = 1:length(bv.conf), size = 1, prob = prob) #sampling one bivalent configuration based on given probabilities
        choosed_biv <- bv.conf[[id]]
        choosed_biv <- choosed_biv[,sample(1:(ploidy/2)), drop = FALSE]
        for(i in 1:ncol(choosed_biv))
        {
          choosed_biv[,i] <- sample(choosed_biv[,i])
        }
        pole.1 <- choosed_biv[1,, drop = FALSE]
        pole.2 <- choosed_biv[2,, drop = FALSE]
        set.2 <- gen.1[pole.1,, drop = FALSE]      #allocating the chromosomes on the variables set.1 and set.2, thus (set.1[i], set.2[i]) represents a bivalent
        set.1 <- gen.1[pole.2,, drop = FALSE]
        for(i in 1:(ploidy/2)){         #for each one of the ploidy/2 chromosome pair (bivalents)
            a <- set.1[i,, drop = FALSE]
            b <- set.2[i,, drop = FALSE]
            for(j in 1:(n.mrk-1)){             #for each adjacent interval between.mrkkers
                if(runif(1)  < rf.vec[j]){       #if a random number drawn from the interval [0,1] (according a uniform distribution)
                                        #is less than the recombination fraction for that interval
                    which.swap <- c((j+1):n.mrk)     #the alleles for that interval and bivalent are swapped
                    temp <- a[which.swap]
                    a[which.swap] <- b[which.swap]
                    b[which.swap] <- temp
                }
            }             #this completes the whole bivalent
            set.1[i,] <- a  #attributing the resulting vector to the initial variables
            set.2[i,] <- b
        }               #for all bivalents
        if(sample(0:1,1)) gam <- set.1 #sample one of the meiotic products
        else gam <- set.2
        for(i in 1:(ploidy/2)){ #counting the recombinant chromosomes in their multiallelic form
            for(j in 2:ncol(gam)){
                if(!gam[i,j] == gam[i,j-1])
                    rf.res[j-1] <- rf.res[j-1]+1
            }
        }
        for(i in 1:n.mrk)
            gam[,i] <- as.numeric(!is.na(match(gam[,i], hom.allele[[i]])))
        res[k,] <- apply(gam, 2, sum)
    }
    rf.calc <- rf.res/(n.ind*ploidy/2)  #computing the recombination fraction
    dimnames(res) <- list(paste("Ind",1:n.ind, sep = "_"), paste("M",1:n.mrk, sep = "_"))
    list(data.sim.one.parent = res, cross.count.one.parent = rf.res, rf.calc.one.parent = rf.calc)
}

#' Simulate mapping population (tow parents)
#' @keywords internal
sim_cross_two_informative_parents <- function(ploidy,
                                           n.mrk,
                                           rf.vec,
                                           n.ind,
                                           hom.allele.p,
                                           hom.allele.q,
                                           prob.P = NULL,
                                           prob.Q = NULL,
                                           seed = NULL){
    if(!is.null(seed)) set.seed(seed)
    dose.p <- unlist(lapply(hom.allele.p, function(x) sum(as.logical(x))))
    dose.q <- unlist(lapply(hom.allele.q, function(x) sum(as.logical(x))))
    if(any(apply(rbind(dose.p,dose.q),2,sum) == 0)) stop("Found zero doses in both parents at the same marker")
    if(!is.null(seed)) set.seed(seed)
    ##Parent 1
    data.P <- sim_cross_one_informative_parent(ploidy = ploidy, n.mrk = n.mrk, rf.vec = rf.vec,
                           hom.allele = hom.allele.p, n.ind = n.ind, prob = prob.P)
    ##Parent 2
    data.Q <- sim_cross_one_informative_parent(ploidy = ploidy, n.mrk = n.mrk, rf.vec = rf.vec,
                           hom.allele = hom.allele.q, n.ind = n.ind, prob = prob.Q)
    rf.calc <- (data.P$cross.count.one.parent + data.Q$cross.count.one.parent)/(n.ind*ploidy)
    data.sim.two.parents <- data.P$data.sim.one.parent + data.Q$data.sim.one.parent
    list(data.sim.two.parents = data.sim.two.parents, rf.calc = rf.calc)
}

#' Draw simple parental linkage phase configurations
#'
#' This function draws the parental map (including the linkage
#' phase configuration) in a pdf output. This function is not to
#' be directly called by the user
#' @importFrom grDevices pdf dev.off
#' @keywords internal
draw_cross <- function(ploidy,
                       dist.vec = NULL,
                       hom.allele.p,
                       hom.allele.q, 
                       file = NULL, 
                       width = 12, 
                       height = 6){
    if(!is.null(file))
        pdf(file, width = width, height = height)
    oldpar <- par(xaxt = "n")
    on.exit(par(oldpar))
    plot(c(0,22), c(0,-(ploidy+12)), type = "n", 
         axes = FALSE, xlab = "Partental homology groups", 
         main = paste("Ploidy: ", ploidy), ylab = "")
    for(i in -(1:ploidy)){
        lines(c(0,10), c(i,i))
        lines(c(12,22), c(i,i))
    }
    pos.p <- dist.vec/max(dist.vec)*10
    for(i in 1:length(hom.allele.p)){
        abline(v = pos.p[i], lty = 2, lwd = .5)
        text(pos.p[i], 0, i, cex = .7)
        if(any(hom.allele.p[[i]] != 0))
            points(x = rep(pos.p[i],length(hom.allele.p[[i]])), y = -hom.allele.p[[i]], col = 2, pch = 20, cex = 2)
        points(pos.p[i] , -(ploidy+10), pch = "|")
        text(pos.p[i], -(ploidy+10)-.8, labels = round(dist.vec,1)[i], srt = 90)
    }
    pos.q <- pos.p+12
    for(i in 1:length(hom.allele.q)){
        abline(v = pos.q[i], lty = 2, lwd = .5)
        text(pos.q[i], 0, i, cex = .7)
        if(any(hom.allele.q[[i]] != 0))
            points(x = rep(pos.q[i],length(hom.allele.q[[i]])), y = -hom.allele.q[[i]], col = 2, pch = 20, cex = 2)
        points(pos.q[i] , -(ploidy+10), pch = "|")
        text(pos.q[i], -(ploidy+10)-.8, labels = round(dist.vec,1)[i], srt = 90)
    }
    text(x = 11,y = -(ploidy+1)/2,labels = "X", cex = 2)
    lines(c(0,10), c(-(ploidy+10),-(ploidy+10)))
    lines(c(12,22), c(-(ploidy+10),-(ploidy+10)))
    if(!is.null(file)) dev.off()
}