plot_sint: QTLs with respective support interval plots

In 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. doi: 10.1534/genetics.120.303080.

See Also

read_data, remim, profile_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)

  # Plot support intervals
  plot_sint(data = data, model = remim.mod)
  

qtlpoly documentation built on Jan. 12, 2022, 5:06 p.m.