read_data: Read genotypic and phenotypic data
In qtlpoly: Random-Effect Multiple QTL Mapping in Autopolyploids

read_data

R Documentation

Read genotypic and phenotypic data

Description

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

Usage

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

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

Arguments

`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.
`verbose`	if `TRUE` (default), current progress is shown; if `FALSE`, no output is produced.
`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.
`...`	currently ignored

Value

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.

Author(s)

Guilherme da Silva Pereira, gdasilv@ncsu.edu, with minor updates by Gabriel de Siqueira Gesteira, gdesiqu@ncsu.edu

References

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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1534/genetics.120.303080")}.

Examples

  
  # Estimate conditional probabilities using mappoly package
  library(mappoly)
  library(qtlpoly)
  genoprob4x = lapply(maps4x[c(5)], calc_genoprob)
  data = read_data(ploidy = 4, geno.prob = genoprob4x, pheno = pheno4x, step = 1)

qtlpoly documentation built on May 29, 2024, 2:14 a.m.