Add manually p-values to a ggplot, such as box blots, dot plots and stripcharts. Frequently asked questions are available on Datanovia ggpubr FAQ page, for example:
stat_pvalue_manual(
data,
label = NULL,
y.position = "y.position",
xmin = "group1",
xmax = "group2",
x = NULL,
size = 3.88,
label.size = size,
bracket.size = 0.3,
bracket.nudge.y = 0,
bracket.shorten = 0,
color = "black",
linetype = 1,
tip.length = 0.03,
remove.bracket = FALSE,
step.increase = 0,
step.group.by = NULL,
hide.ns = FALSE,
vjust = 0,
coord.flip = FALSE,
position = "identity",
...
)
a data frame containing statitistical test results. The expected
default format should contain the following columns: group1 | group2 |
p | y.position | etc
. group1
and group2
are the groups that
have been compared. p
is the resulting p-value. y.position
is
the y coordinates of the p-values in the plot.
the column containing the label (e.g.: label = "p" or label =
"p.adj"), where p
is the p-value. Can be also an expression that can
be formatted by the glue()
package. For example, when
specifying label = "t-test, p = {p}", the expression {p} will be
replaced by its value.
column containing the coordinates (in data units) to be used for absolute positioning of the label. Default value is "y.position". Can be also a numeric vector.
column containing the position of the left sides of the brackets. Default value is "group1".
(optional) column containing the position of the right sides of the brackets. Default value is "group2". If NULL, the p-values are plotted as a simple text.
x position of the p-value. Should be used only when you want plot the p-value as text (without brackets).
size of label text.
Width of the lines of the bracket.
Vertical adjustment to nudge brackets by. Useful to move up or move down the bracket. If positive value, brackets will be moved up; if negative value, brackets are moved down.
a small numeric value in [0-1] for shortening the with of bracket.
text and line color. Can be variable name in the data for coloring by groups.
linetype. Can be variable name in the data for changing linetype by groups.
numeric vector with the fraction of total height that the bar goes down to indicate the precise column. Default is 0.03.
logical, if TRUE
, brackets are removed from the
plot. Considered only in the situation, where comparisons are performed
against reference group or against "all".
numeric vector with the increase in fraction of total height for every additional comparison to minimize overlap.
a variable name for grouping brackets before adding step.increase. Useful to group bracket by facet panel.
can be logical value or a character vector.
Case when logical value. If TRUE, hide ns symbol when displaying
significance levels. Filter is done by checking the column
p.adj.signif
, p.signif
, p.adj
and p
.
Case when character value. Possible values are "p" or "p.adj", for filtering out non significant.
move the text up or down relative to the bracket. Can be also a column name available in the data.
logical. If TRUE
, flip x and y coordinates so that
horizontal becomes vertical, and vertical, horizontal. When adding the
p-values to a horizontal ggplot (generated using
coord_flip()
), you need to specify the option
coord.flip = TRUE
.
position adjustment, either as a string, or the result of a call to a position adjustment function.
other arguments passed to the function geom_bracket()
or
geom_text()
# T-test
stat.test <- compare_means(
len ~ dose, data = ToothGrowth,
method = "t.test"
)
stat.test
#> # A tibble: 3 × 8
#> .y. group1 group2 p p.adj p.format p.signif method
#> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 len 0.5 1 1.27e- 7 2.5e- 7 1.3e-07 **** T-test
#> 2 len 0.5 2 4.40e-14 1.3e-13 4.4e-14 **** T-test
#> 3 len 1 2 1.91e- 5 1.9e- 5 1.9e-05 **** T-test
# Create a simple box plot
p <- ggboxplot(ToothGrowth, x = "dose", y = "len")
p
# Perform a t-test between groups
stat.test <- compare_means(
len ~ dose, data = ToothGrowth,
method = "t.test"
)
stat.test
#> # A tibble: 3 × 8
#> .y. group1 group2 p p.adj p.format p.signif method
#> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 len 0.5 1 1.27e- 7 2.5e- 7 1.3e-07 **** T-test
#> 2 len 0.5 2 4.40e-14 1.3e-13 4.4e-14 **** T-test
#> 3 len 1 2 1.91e- 5 1.9e- 5 1.9e-05 **** T-test
# Add manually p-values from stat.test data
# First specify the y.position of each comparison
stat.test <- stat.test %>%
mutate(y.position = c(29, 35, 39))
p + stat_pvalue_manual(stat.test, label = "p.adj")
# Customize the label with glue expression
# (https://github.com/tidyverse/glue)
p + stat_pvalue_manual(stat.test, label = "p = {p.adj}")
# Grouped bar plots
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
ToothGrowth$dose <- as.factor(ToothGrowth$dose)
# Comparisons against reference
stat.test <- compare_means(
len ~ dose, data = ToothGrowth, group.by = "supp",
method = "t.test", ref.group = "0.5"
)
stat.test
#> # A tibble: 4 × 9
#> supp .y. group1 group2 p p.adj p.format p.signif method
#> <fct> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 VC len 0.5 1 0.000000681 0.000002 6.8e-07 **** T-test
#> 2 VC len 0.5 2 0.0000000468 0.00000019 4.7e-08 **** T-test
#> 3 OJ len 0.5 1 0.0000878 0.000088 8.8e-05 **** T-test
#> 4 OJ len 0.5 2 0.00000132 0.0000026 1.3e-06 **** T-test
# Plot
bp <- ggbarplot(ToothGrowth, x = "supp", y = "len",
fill = "dose", palette = "jco",
add = "mean_sd", add.params = list(group = "dose"),
position = position_dodge(0.8))
bp + stat_pvalue_manual(
stat.test, x = "supp", y.position = 33,
label = "p.signif",
position = position_dodge(0.8)
)