R/read.cross.gary.R

In mQTL.NMR: Metabolomic Quantitative Trait Locus Mapping for 1H NMR data

read.cross.gary <-
function (dir, genfile, mnamesfile, chridfile, phefile, pnamesfile, mapfile, estimate.map, na.strings) 
{
    if (missing(genfile)) genfile <- "geno.dat"
    if (missing(mnamesfile)) mnamesfile <- "mnames.txt"
    if (missing(chridfile)) chridfile <- "chrid.dat"
    if (missing(phefile)) phefile <- "pheno.dat"
    if (missing(pnamesfile)) pnamesfile <- "pnames.txt"
            if (missing(mapfile)) mapfile <- "markerpos.txt"
    if (!missing(dir) && dir != "") {
              genfile <- file.path(dir, genfile)
              mnamesfile <- file.path(dir, mnamesfile)
      chridfile <- file.path(dir, chridfile)
              if (!is.null(mapfile)) mapfile <- file.path(dir, mapfile)
          }
          allgeno <- as.matrix(read.table(genfile, na.strings = "9")) + 1
            pheno <- phefile
          chr <- scan(chridfile, what = character(), quiet = TRUE)
          mnames <- scan(mnamesfile, what = character(), quiet = TRUE)
          if (!is.null(mapfile)) {
     map <- read.table(mapfile, row.names = 1)
     map <- map[mnames, 1]
     map.included <- TRUE
  }else{
     map <- seq(0, by = 5, len = length(mnames))
             map.included <- FALSE
          }
          if (!is.null(pnamesfile)) pnames <- pnamesfile
    else pnames <- paste("pheno", 1:ncol(pheno), sep = "")
          uchr <- unique(chr)
          n.chr <- length(uchr)
  geno <- vector("list", n.chr)
  names(geno) <- uchr
  min.mar <- 1
  for (i in 1:n.chr) {
     temp.map <- map[chr == uchr[i]]
     if (any(is.na(temp.map))) {
        o <- (seq(along = temp.map))[is.na(temp.map)]
        for (j in o) {
           if (j == 1 || all(is.na(temp.map[1:(j - 1)]))) {
               z <- min((seq(along = temp.map))[-o])
               temp.map[j] <- min(temp.map, na.rm = TRUE) - (z - j + 1)
           } else if (j == length(temp.map) || all(is.na(temp.map[-(1:j)]))) {
               z <- max((seq(along = temp.map))[-o])
               temp.map[j] <- max(temp.map, na.rm = TRUE) + (j - z + 1)
                  } else {
       temp.map[j] <- (min(temp.map[-(1:j)], na.rm = TRUE) + max(temp.map[1:(j - 1)], na.rm = TRUE))/2
                          }
}
    }
    names(temp.map) <- mnames[chr == uchr[i]]
            data <- allgeno[, min.mar:(length(temp.map) + min.mar - 1), drop = FALSE]
                    min.mar <- min.mar + length(temp.map)
                    colnames(data) <- names(temp.map)
    geno[[i]] <- list(data = data, map = temp.map)
    if (uchr[i] == "X" || uchr[i] == "x") class(geno[[i]]) <- "X" else class(geno[[i]]) <- "A"
            }
    colnames(pheno) <- pnames
            sw2numeric <- function(x) {
      pattern <- "^[ \t]*-*[0-9]*[.]*[0-9]*[ \t]*$"
              n <- sum(!is.na(x))
              if (length(grep(pattern, as.character(x[!is.na(x)]))) == n) return(as.numeric(as.character(x)))
                else return(x)
            }
    pheno <- data.frame(lapply(as.data.frame(pheno), sw2numeric))
    n.mar1 <- sapply(geno, function(a) ncol(a$data)) 
    n.mar2 <- sapply(geno, function(a) length(a$map))
    n.phe <- ncol(pheno)
    n.ind1 <- nrow(pheno)
    n.ind2 <- sapply(geno, function(a) nrow(a$data))
    if (any(n.ind1 != n.ind2)) {
      print(c(n.ind1, n.ind2)) 
      stop("Number of individuals in genotypes and phenotypes do not match.")
    }
            if (any(n.mar1 != n.mar2)) {
        print(c(n.mar1, n.mar2))
      stop("Numbers of markers in genotypes and marker names files do not match.")
    }
    cat(" --Read the following data:\n") 
    cat("\t", n.ind1, " individuals\n") 
    cat("\t", sum(n.mar1), " markers\n") 
    cat("\t", n.phe, " phenotypes\n")
    if (max(allgeno[!is.na(allgeno)]) <= 2) type <- "bc" else type <- "f2" 
    cross <- list(geno = geno, pheno = pheno)
    class(cross) <- c(type, "cross")
    cross.type <- class(cross)[1] 
    if (cross.type == "f2") max.gen <- 5 else max.gen <- 2 
    u <- unique(allgeno) 
    if (any(!is.na(u) & (u > max.gen | u < 1))) { 
      err <- paste("There are stange values in the genotype data :", paste(sort(u), collapse = ":"), ".")
      stop(err)
    }
    cross$pheno <- as.data.frame(cross$pheno)
    if (!map.included) {
        for (i in 1:nchr(cross)) cross$geno[[i]]$map <- cross$geno[[i]]$map - min(cross$geno[[i]]$map)
            }
    list(cross, (!map.included && estimate.map))
}