plot_sint: QTLs with respective support interval plots

In guilherme-pereira/QTLpoly: Random-effect multiple QTL mapping in autopolyploids

Description

Creates a plot where colored bars represent the support intervals for QTL peaks (black dots).

Usage

plot_sint(data, model, pheno.col = NULL, main = NULL, drop = FALSE)

Arguments

data	an object of class qtlpoly.data.
model	an object of class qtlpoly.profile or qtlpoly.remim.
pheno.col	a numeric vector with the phenotype column numbers to be plotted; if NULL, all phenotypes from 'data' will be included.
main	a character string with the main title; if NULL, no title will be shown.
drop	if TRUE, phenotypes with no QTL will be dropped; if FALSE (default), all phenotypes will be shown.

Value

A ggplot2 with QTL bars for each linkage group.

Author(s)

Guilherme da Silva Pereira, [e-mail]

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. http://doi.org/10.1534/genetics.120.303080.

See Also

read_data, remim, profile_qtl

Examples

  ## 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)

  # perform remim
  remim.mod <- remim(data = data, w.size = 15, sig.fwd = 0.01, sig.bwd = 0.0001,
    d.sint = 1.5, n.clusters = 4, plot = "remim")

  # plot support intervals
  plot_sint(data = data, model = remim.mod)
  
## End(Not run)

guilherme-pereira/QTLpoly documentation built on Oct. 10, 2021, 10:22 p.m.