Add p-values to ggplot objects.

Add p-values to ggplot objects.

add_pval(
  ggplot_obj,
  pairs = NULL,
  test = "wilcox.test",
  heights = NULL,
  barheight = NULL,
  textsize = 5,
  pval_text_adj = NULL,
  annotation = NULL,
  log = FALSE,
  pval_star = FALSE,
  plotly = FALSE,
  fold_change = FALSE,
  parse_text = NULL,
  response = "infer",
  ...
)

Arguments

ggplot_obj	ggplot object
pairs	a list pairs of comparison. Groups indicated by integer numbers counted from left to right. e.g. list(c(1, 2), c(2, 3)) will compare first group with second, second group with third
test	character of statistical testing method. e.g. t.test, wilcox.test. Default wilcox.test
heights	integer or vector of integers. The heights of the p-value/annotation. Default maximum value from the data
barheight	tip bar height of the annotation. Default calculated by range_y / 20
textsize	p-value/annotation text size
pval_text_adj	distance of p-value/annotation from annotation bar. Default barheight/2
annotation	text to annotate. If specified, statistical test will not be done
log	whether y axis is log transformed. Default FALSE
pval_star	whether transform pval numbers to stars
plotly	set to TRUE if wrap the plot with `ggploty`
fold_change	whether also compute and show fold changes. Default FALSE.
parse_text	whether parse the annotation text (NULL, TRUE, FALSE). If NULL, p-values will be parsed, text annotations will not. Default NULL.
response	the column that contains the data for statistical testing. Default infer from ggplot object.
...	additional arguments for statistical testing function (e.g. alternative = "less").

Examples

library(ggplot2)
library(ggpval)
data("PlantGrowth")
plt <- ggplot(PlantGrowth, aes(group, weight)) +
  geom_boxplot()
add_pval(plt, pairs = list(c(1, 3)), test='wilcox.test')