read_data: Read genotypic and phenotypic data
In guilherme-pereira/QTLpoly: Random-effect multiple QTL mapping in autopolyploids

Description Usage Arguments Value Author(s) References See Also Examples

Reads files in specific formats and creates a qtlpoly.data object to be used in subsequent analyses.

read_data(
  ploidy = 6,
  geno.prob = genoprob,
  geno.dose = NULL,
  double.reduction = FALSE,
  pheno = pheno,
  weights = NULL,
  step = 1
)

## S3 method for class 'qtlpoly.data'
print(x, detailed = FALSE)

`ploidy`	a numeric value of ploidy level of the cross.
`geno.prob`	an object of class `mappoly.genoprob` from mappoly.
`geno.dose`	an object of class `mappoly.data` from mappoly.
`double.reduction`	if `TRUE`, double reduction genotypes are taken into account; if `FALSE`, no double reduction genotypes are considered.
`pheno`	a data frame of phenotypes (columns) with individual names (rows) identical to individual names in `geno.prob` and/or `geno.dose` object.
`weights`	a data frame of phenotype weights (columns) with individual names (rows) identical to individual names in `pheno` object.
`step`	a numeric value of step size (in centiMorgans) where tests will be performed, e.g. 1 (default); if `NULL`, tests will be performed at every marker.
`x`	an object of class `qtlpoly.data` to be printed.
`detailed`	if `TRUE`, detailed information on linkage groups and phenotypes in shown; if `FALSE`, no details are printed.

An object of class qtlpoly.data which is a list containing the following components:

`ploidy`	a scalar with ploidy level.
`nlgs`	a scalar with the number of linkage groups.
`nind`	a scalar with the number of individuals.
`nmrk`	a scalar with the number of marker positions.
`nphe`	a scalar with the number of phenotypes.
`lgs.size`	a vector with linkage group sizes.
`cum.size`	a vector with cumulative linkage group sizes.
`lgs.nmrk`	a vector with number of marker positions per linkage group.
`cum.nmrk`	a vector with cumulative number of marker positions per linkage group.
`lgs`	a list with selected marker positions per linkage group.
`lgs.all`	a list with all marker positions per linkage group.
`step`	a scalar with the step size.
`pheno`	a data frame with phenotypes.
`G`	a list of relationship matrices for each marker position.
`Z`	a list of conditional probability matrices for each marker position for genotypes.
`X`	a list of conditional probability matrices for each marker position for alleles.
`Pi`	a matrix of identical-by-descent shared alleles among genotypes.

Guilherme da Silva Pereira, gdasilv@ncsu.edu

Pereira GS, Gemenet DC, Mollinari M, Olukolu BA, Wood JC, Mosquera V, Gruneberg WJ, Khan A, Buell CR, Yencho GC, Zeng ZB (2020) Multiple QTL mapping in autopolyploids: a random-effect model approach with application in a hexaploid sweetpotato full-sib population, Genetics 215 (3): 579-595. http://doi.org/10.1534/genetics.120.303080.

read_data, maps, pheno

  ## Not run: 
  # load raw data
  data(maps)
  data(pheno)

  # estimate conditional probabilities using mappoly package
  library(mappoly)
  genoprob <- lapply(maps, calc_genoprob)

  # prepare data
  data <- read_data(ploidy = 6, geno.prob = genoprob, pheno = pheno, step = 1)
  
## End(Not run)