Q-Q plot

Creates a normal quantile-quantile (Q-Q) plot for a set of effects (e.g., phenotypes, genetic values, or plot errors).

Usage

qq_plot(df, effect, labels = FALSE, dim.names = NULL)

Arguments

df

A data frame or vector with the effects to be plotted.

effect

A character defining the effects to be plotted. Ignored when 'df' is a vector.

labels

When TRUE (default is FALSE), column and row labels are displayed. This requires additional columns in the data frame, as specified by dim.names.

dim.names

An optional vector defining the column and row dimensions ('col' and 'row' by default).

Value

A Q-Q plot with x- and y-axes displaying the theoretical and sample quantiles of the effects, respectively.

Examples

# Q-Q plot of the simulated plot errors in the example data frame 'error_df_bivar'
# for Trait 1 in Environment 1.

error_df <- error_df_bivar[error_df_bivar$env == 1, ]

qq <- qq_plot(
  df = error_df,
  effect = "e.Trait1",
  labels = TRUE
)

# Q-Q plot
qq


# Extract the data frame with the theoretical and sample quantiles of the
# user-defined effects.
qq_df <- qq$data