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Plot QTL effects along chromosome

Source: R/ggplot_coef.R
ggplot_coef.Rd

Plot estimated QTL effects along a chromosomes.

Usage

ggplot_coef(
  object,
  map,
  columns = NULL,
  col = NULL,
  scan1_output = NULL,
  gap = 25,
  ylim = NULL,
  bgcolor = "gray90",
  altbgcolor = "gray85",
  ylab = "QTL effects",
  xlim = NULL,
  ...
)

ggplot_coefCC(object, map, colors = qtl2::CCcolors, ...)

# S3 method for class 'scan1coef'
autoplot(object, ...)

Arguments

object

Estimated QTL effects ("coefficients") as obtained from scan1coef.

map

A list of vectors of marker positions, as produced by insert_pseudomarkers.

columns

Vector of columns to plot

col

Vector of colors, same length as columns. If NULL, some default choices are made.

scan1_output

If provided, we make a two-panel plot with coefficients on top and LOD scores below. Should have just one LOD score column; if multiple, only the first is used.

gap

Gap between chromosomes.

ylim

y-axis limits. If NULL, we use the range of the plotted coefficients.

bgcolor

Background color for the plot.

altbgcolor

Background color for alternate chromosomes.

ylab

y-axis label

xlim

x-axis limits. If NULL, we use the range of the plotted coefficients.

...

Additional graphics parameters.

colors

Colors to use for plotting.

Value

object of class ggplot.

Details

ggplot_coefCC() is the same as ggplot_coef(), but forcing columns=1:8 and using the Collaborative Cross colors, CCcolors.

See also

ggplot_scan1, ggplot_snpasso

Examples

# read data
iron <- qtl2::read_cross2(system.file("extdata", "iron.zip", package="qtl2"))

# insert pseudomarkers into map
map <- qtl2::insert_pseudomarkers(iron$gmap, step=1)

# calculate genotype probabilities
probs <- qtl2::calc_genoprob(iron, map, error_prob=0.002)

# grab phenotypes and covariates; ensure that covariates have names attribute
pheno <- iron$pheno[,1]
covar <- match(iron$covar$sex, c("f", "m")) # make numeric
names(covar) <- rownames(iron$covar)

# calculate coefficients for chromosome 7
coef <- qtl2::scan1coef(probs[,7], pheno, addcovar=covar)

# plot QTL effects
ggplot2::autoplot(coef, map[7], columns=1:3)