plotBoxplot: Plot numeric distribution and statistical tests
In kueckelj/SPATA2: A Toolbox for Spatial Gene Expression Analysis

plotBoxplot

R Documentation

Plot numeric distribution and statistical tests

Description

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.

Usage

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_bcsp = 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,
  of_sample = NA,
  ...
)

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,
  of_sample = NA,
  ...
)

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,
  of_sample = NA,
  ...
)

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,
  of_sample = NA,
  ...
)

Arguments

`object`	An object of class `spata2`.
`variables`	Character vector. The variables of interest: Gene sets: Must be in `getGeneSets()` Genes: Must be in `getGenes()` Features: Must be numeric ones of `getFeatureNames()`
`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.
`n_bcsp`	Numeric value. Specifies the sample size of barcode-spots and can be set to prevent overplotting.
`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 set to TRUE informative messages regarding the computational progress will be printed. (Warning messages will always be printed.)
`of_sample`	This argument is currently inactive. It might be reactivated when spata-objects can store more than one sample.
`...`	Additional arguments given to the respective `ggplot2::geom_<plot_type>()` function. E.g. `plotViolinplot()` relies on `ggplot2::geom_violin()`.