plot.statRes {pmartR}R Documentation

Plot statRes Object

Description

Produces plots that summarize the results contained in a 'statRes' object.

Usage

## S3 method for class 'statRes'
plot(
  x,
  plot_type = "bar",
  fc_threshold = NULL,
  fc_colors = c("red", "black", "green"),
  stacked = TRUE,
  show_sig = TRUE,
  color_low = NULL,
  color_high = NULL,
  plotly_layout = NULL,
  interactive = FALSE,
  x_lab = NULL,
  x_lab_size = 11,
  x_lab_angle = NULL,
  y_lab = NULL,
  y_lab_size = 11,
  title_lab = NULL,
  title_lab_size = 14,
  legend_lab = NULL,
  legend_position = "right",
  text_size = 3,
  bw_theme = TRUE,
  display_count = TRUE,
  custom_theme = NULL,
  cluster = FALSE,
  free_y_axis = FALSE,
  ...
)

Arguments

x

'statRes' object to be plotted, usually the result of 'imd_anova'

plot_type

defines which plots to be produced, options are "bar", "volcano", "gheatmap", "fcheatmap"; defaults to "bar". See details for plot descriptions.

fc_threshold

optional threshold value for fold change estimates. Modifies the volcano plot as follows: Vertical lines are added at (+/-)fc_threshold and all observations that have absolute fold change less than abs(fc_threshold) are colored as 'non-significant' (as specified by fc_colors).

fc_colors

vector of length three with character color values interpretable by ggplot. i.e. c("orange", "black", "blue") with the values being used to color negative, non-significant, and positive fold changes respectively

stacked

TRUE/FALSE for whether to stack positive and negative fold change sections in the barplot, defaults to TRUE

show_sig

This input is used when plot_type = "gheatmap". A logical value. If TRUE a visual indicator that a certain bin combination is significant by the g-test is shown.

color_low

This input is used when plot_type = "gheatmap". A character string specifying the color of the gradient for low count values.

color_high

This input is used when plot_type = "gheatmap". A character string specifying the color of the gradient for high count values.

plotly_layout

This input is used when plot_type = "gheatmap". A list of arguments, not including the plot, to be passed to plotly::layout if interactive = TRUE.

interactive

TRUE/FALSE for whether to create an interactive plot using plotly. Not valid for all plots.

x_lab

character string specifying the x-axis label.

x_lab_size

integer value indicating the font size for the x-axis. The default is 11.

x_lab_angle

integer value indicating the angle of x-axis labels.

y_lab

character string specifying the y-axis label.

y_lab_size

integer value indicating the font size for the y-axis. The default is 11.

title_lab

character string specifying the plot title.

title_lab_size

integer value indicating the font size of the plot title. The default is 14.

legend_lab

character string specifying the legend title.

legend_position

character string specifying the position of the legend. Can be one of "right", "left", "top", "bottom", or "none". The default is "none".

text_size

integer specifying the size of the text (number of non-missing values) within the plot. The default is 3.

bw_theme

logical value. If TRUE uses the ggplot2 black and white theme.

display_count

logical value. Indicates whether the non-missing counts will be displayed on the bar plot. The default is TRUE.

custom_theme

a ggplot 'theme' object to be applied to non-interactive plots, or those converted by plotly::ggplotly().

cluster

logical for heatmaps; TRUE will cluster biomolecules on X axis. defaults to TRUE for seqData statistics and FALSE for all others.

free_y_axis

Logical. If TRUE the y axis for each bar plot can have its own range. The default is FALSE.

...

further arguments passed to or from other methods.

Details

Plot types:

Value

ggplot2 plot object if interactive is FALSE, or plotly plot object if interactive is TRUE

Examples


library(pmartRdata)
# Group the data by condition
mypro <- group_designation(
  omicsData = pro_object,
  main_effects = c("Phenotype")
)

# Apply the IMD ANOVA filter
imdanova_Filt <- imdanova_filter(omicsData = mypro)
mypro <- applyFilt(
  filter_object = imdanova_Filt,
  omicsData = mypro,
  min_nonmiss_anova = 2
)

# Implement the IMD ANOVA method and compuate all pairwise comparisons
# (i.e. leave the `comparisons` argument NULL)
anova_res <- imd_anova(omicsData = mypro, test_method = 'anova')
plot(anova_res)
plot(anova_res, plot_type = "volcano")

imd_res <- imd_anova(omicsData = mypro, test_method = 'gtest')
plot(imd_res)

imd_anova_res <- imd_anova(
  omicsData = mypro,
  test_method = 'comb',
  pval_adjust_a_multcomp = 'bon',
  pval_adjust_g_multcomp = 'bon'
)
plot(imd_anova_res, bw_theme = TRUE)
plot(imd_anova_res, plot_type = "volcano", bw_theme = TRUE)


[Package pmartR version 2.4.5 Index]