qtlpoly (version 0.2.4)

read_data2: 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_data2(
  ploidy = 6,
  geno.prob,
  geno.dose = NULL,
  double.reduction = FALSE,
  pheno,
  weights = NULL,
  step = 1,
  verbose = TRUE
)

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.

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.

Author

Guilherme da Silva Pereira, , Gabriel de Siqueira Gesteira,

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. tools:::Rd_expr_doi("10.1534/genetics.120.303080").

See Also

maps6x, pheno6x

Examples

  # \donttest{
  # 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)
  # }