Plot a MOBSTER fit.

Usage

plot.dbpmm(
  x,
  cutoff_assignment = 0,
  beta_colors = RColorBrewer::brewer.pal(n = 9, "Set1"),
  tail_color = "gainsboro",
  na_color = "gray",
  annotation_extras = NULL,
  secondary_axis = NULL,
  ...
)

Arguments

x: An object of class "dbpmm".
cutoff_assignment: Parameters passed to run function Clusters which returns the hard clustering assignments for the histogram plot if one wants to plot only mutations with responsibility above this parameter.
beta_colors: A vector of colors that are used to colour the Beta clusters. Colors are used by order for "C1", "C2", "C3", etc. If too few colours are used the rainbow palette is used instead of beta_colors. In all cases the colour of the tail is set by the other parameter tail_color.
tail_color: The colour of the tail cluster, if any.
annotation_extras: A dataframe that contains a label column, and a VAF value. The labels will be annotated to the corresponding clusters of the VAF values.
secondary_axis: NULL to leave the second axis empty, "SSE" to report the cumulative percentage of SSE error, and "N" to report the cumulative number of mutations.
...

Value

A ggplot object for the plot.

Examples

data(fit_example)
plot(fit_example$best)

plot(fit_example$best, secondary_axis = 'SSE')

plot(fit_example$best, cutoff_assignment = .7)
#> Warning: You did not pass enough input colours, adding a gray colour
#> Available: C1, C2, Tail
#> Missing: NA

plot(fit_example$best, beta_colors = c("indianred3", "orange"))

plot(fit_example$best, tail_color = 'black')