These functions display the distribution of numeric variables for the whole sample or in a comparative manner if argument across is specified. plotViolinplot() and plotBoxplot() allow for statistical tests such as t-test or ANOVA.

plotBoxplot(
  object,
  variables,
  across = NULL,
  across_subset = NULL,
  relevel = NULL,
  clrp = NULL,
  clrp_adjust = NULL,
  test_groupwise = NULL,
  test_pairwise = NULL,
  ref_group = NULL,
  step_increase = 0.01,
  vjust = 0,
  display_facets = NULL,
  scales = "free",
  nrow = NULL,
  ncol = NULL,
  display_points = FALSE,
  n_bcs = NULL,
  pt_alpha = NULL,
  pt_clr = NULL,
  pt_size = NULL,
  pt_shape = NULL,
  method_gs = NULL,
  normalize = NULL,
  verbose = NULL,
  of_sample = NA,
  ...
)

plotDensityplot(
  object,
  variables,
  across = NULL,
  across_subset = NULL,
  relevel = NULL,
  clrp = NULL,
  clrp_adjust = NULL,
  display_facets = NULL,
  scales = "free_x",
  nrow = NULL,
  ncol = NULL,
  method_gs = NULL,
  normalize = NULL,
  verbose = NULL,
  ...
)

plotHistogram(
  object,
  variables,
  across = NULL,
  across_subset = NULL,
  relevel = NULL,
  clrp = NULL,
  clrp_adjust = NULL,
  scales = "free_x",
  nrow = NULL,
  ncol = NULL,
  method_gs = NULL,
  normalize = NULL,
  verbose = NULL,
  ...
)

plotRidgeplot(
  object,
  variables,
  across = NULL,
  across_subset = NULL,
  relevel = NULL,
  alpha = 0.8,
  clrp = NULL,
  clrp_adjust = NULL,
  display_facets = NULL,
  scales = "free",
  nrow = NULL,
  ncol = NULL,
  method_gs = NULL,
  normalize = NULL,
  verbose = NULL,
  ...
)

plotVioBoxplot(
  object,
  variables,
  across = NULL,
  across_subset = NULL,
  relevel = NULL,
  clrp = NULL,
  clrp_adjust = NULL,
  test_groupwise = NULL,
  test_pairwise = NULL,
  ref_group = NULL,
  step_increase = 0.01,
  display_facets = NULL,
  vjust = 0,
  scales = "free",
  nrow = NULL,
  ncol = NULL,
  display_points = FALSE,
  n_bcsp = NULL,
  pt_alpha = NULL,
  pt_clr = NULL,
  pt_size = NULL,
  pt_shape = NULL,
  method_gs = NULL,
  normalize = NULL,
  verbose = NULL,
  ...
)

plotViolinplot(
  object,
  variables,
  across = NULL,
  across_subset = NULL,
  relevel = NULL,
  clrp = NULL,
  clrp_adjust = NULL,
  test_groupwise = NULL,
  test_pairwise = NULL,
  ref_group = NULL,
  step_increase = 0.01,
  display_facets = NULL,
  vjust = 0,
  scales = "free",
  nrow = NULL,
  ncol = NULL,
  display_points = FALSE,
  n_bcsp = NULL,
  pt_alpha = NULL,
  pt_clr = NULL,
  pt_size = NULL,
  pt_shape = NULL,
  method_gs = NULL,
  normalize = NULL,
  verbose = NULL,
  ...
)

Arguments

object

An object of class SPATA2 or, in case of S4 generics, objects of classes for which a method has been defined.

variables

Character vector. The names of the data variables of interest.

across

Character value or NULL. Specifies the grouping variable of interest.

Use getGroupingOptions() to obtain all variable names that group the barcode spots of your object in a certain manner.

across_subset

Character vector or NULL. Specifies the particular groups of interest the grouping variable specified in argument across contains.

If set to NULL all of them are chosen. You can prefix groups you are NOT interested in with a '-'. (Saves writing if there are more groups you are interested in than groups you are not interested in.)

Use getGroupNames() to obtain all valid input options.

relevel

Logical value. If set to TRUE the input order of across_subset determines the order in which the groups of interest are displayed. Groups that are not included are dropped which affects the colors with which they are displayed.

clrp

Character value. Specifies the color palette to be used to represent groups of discrete variables. Run validColorPalettes() to obtain valid input options.

clrp_adjust

Named character vector or NULL. If character, it adjusts the color palette that is used to represent the groups. Names of the input vector must refer to the group and the respective named element denotes the color with which to represent the group.

test_groupwise

Character value or NULL. Specifies the groupwise statistical test to be conducted. If character, one of 'anova', 'kruskal.test'. If set to NULL the testing is skipped.

test_pairwise

Character value or NULL. Specifies the pairwise statistical test to be conducted. If character, one of 't.test', 'wilcox.test'. If set to NULL the testing is skipped.

ref_group

Character value or NULL. Specifies the reference group against which all other groups are compared in the test denoted in test_groupwise is conducted. If set to NULL the first group found is taken.

step_increase

Numeric value. Denotes the increase in fraction of total height for every additional comparison to minimize overlap.

vjust

Numeric value. Denotes the relative, vertical position of the results of the test denoted in test.groupwise. Negative input highers, positive input lowers the position.

display_facets

Logical value. If set to TRUE the plot is split via ggplot2::facet_wrap() such that each variable gets it's own subplot.

nrow, ncol

Numeric values or NULL. Used to arrange multiple plots.

display_points

Logical value. If set to TRUE points are used additionally to display the results.

pt_alpha

Numeric value. Specifies the degree of transparency of all points.

pt_clr

Character value. Specifies the color of all points.

pt_size

Numeric value. Specifies the size of all points.

method_gs

Character value. The method according to which gene sets will be handled specified as a character of length one. This can be either 'mean or one of 'gsva', 'ssgsea', 'zscore', or 'plage'. The latter four will be given to gsva::GSVA().

normalize

Logical. If set to TRUE values will be scaled to 0-1.

Hint: Variables that are uniformly expressed can not be scaled and are discarded.

verbose

Logical. If TRUE, informative messages regarding the computational progress will be printed.

(Warning messages will always be printed.)

...

Additional arguments given to the respective ggplot2::geom_<plot_type>() function. E.g. plotViolinplot() relies on ggplot2::geom_violin().

n_bcsp

Numeric value. Specifies the sample size of barcode-spots and can be set to prevent overplotting.

Value

Returns a ggplot that can be additionally customized according to the rules of the ggplot2 framework.

Examples


library(SPATA2)
library(tidyverse)

data("example_data")

object <- example_data$object_UKF275T_diet

plotBoxplot(object, variables = c("METRN", "MBP", "CA11"))
plotBoxplot(object, variables = c("METRN", "MBP", "CA11"), across = "bayes_space")

plotViolinplot(object, variables = c("METRN", "MBP", "CA11"))
plotViolinplot(object, variables = c("METRN", "MBP", "CA11"), across = "bayes_space")

# works the same for all functions....

plotBoxplot(
   object = object,
   variables = "METRN",
   across = "bayes_space",
   across_subset = c("2", "3"),
   test_pairwise = "t.test"
   )