fit_model2 function

Fits multiple QTL models

Fits alternative multiple QTL models by performing variance component estimation using REML.

fit_model2(
  data,
  model,
  probs = "joint",
  polygenes = "none",
  keep = TRUE,
  verbose = TRUE,
  pheno.col = NULL
)

Arguments

• data: an object of class qtlpoly.data.
• model: an object of class qtlpoly.profile or qtlpoly.remim.
• probs: a character string indicating if either "joint" (genotypes) or "marginal" (parental gametes) conditional probabilities should be used.
• polygenes: a character string indicating if either "none", "most" or "all" QTL should be used as polygenes.
• keep: if TRUE (default), stores all matrices and estimates from fitted model; if FALSE, nothing is stored.
• verbose: if TRUE (default), current progress is shown; if FALSE, no output is produced.
• pheno.col: a numeric vector with the phenotype column numbers to be summarized; if NULL (default), all phenotypes from 'data' will be included.

Returns

An object of class qtlpoly.fitted which contains a list of results for each trait with the following components:

• pheno.col: a phenotype column number.

• fitted: a sommer object of class mmer.

• qtls: a data frame with information from the mapped QTL.

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)

  # Search for QTL
  remim.mod = remim(data = data, pheno.col = 1, w.size = 15, sig.fwd = 0.0011493379,
sig.bwd = 0.0002284465, d.sint = 1.5, n.clusters = 1)

  # Fit model
  fitted.mod = fit_model(data=data, model=remim.mod, probs="joint", polygenes="none")

References

Covarrubias-Pazaran G (2016) Genome-assisted prediction of quantitative traits using the R package sommer. PLoS ONE 11 (6): 1–15. tools:::Rd_expr_doi("10.1371/journal.pone.0156744") .

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

read_data, remim

Author(s)

Guilherme da Silva Pereira, gdasilv@ncsu.edu