read_data function

Read genotypic and phenotypic data

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

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

Returns

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.

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)

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

Author(s)

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