plot_profile: Logarithm of _P_-value (LOP) profile plots

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

Description

Plots profiled logarithm of score-based P-values (LOP) from individual or combined traits.

Usage

plot_profile(
  data = data,
  model = model,
  pheno.col = NULL,
  sup.int = FALSE,
  main = NULL,
  legend = "bottom",
  ylim = NULL,
  grid = 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.
sup.int	if TRUE, support interval are shown as shaded areas; if FALSE (default), no support interval is show.
main	a character string with the main title; if NULL, no title is shown.
legend	legend position (either "bottom", "top", "left" or "right"); if NULL, no legend is shown.
ylim	a numeric value pair supplying the limits of y-axis, e.g. c(0,10); if NULL (default), limits will be provided automatically.
grid	if TRUE, profiles will be organized in rows (one per trait); if FALSE (default), profiles will appear superimposed. Only effective when plotting profiles from more than one trait.

Value

A ggplot2 with the LOP profiles for each trait.

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

profile_qtl, remim

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 profiles
  for (p in remim.mod$pheno.col) { 
    plot_profile(data = data, model = remim.mod, pheno.col = p, ylim = c(0, 10))
  } # separate plots
    
  plot_profile(data = data, model = remim.mod, grid = FALSE) # combined plots
  
## End(Not run)

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