ggpval
allows you to perform statistic tests and add the corresponding
p-values to ggplots automatically. P-values can be presented numerically
or as stars (e.g. *, **). Alternatively, one can also make any text
annotation between groups.
# Install `ggpval` from CRAN:
install.packages("ggpval")
# You can install the lastest ggpval from github with:
# install.packages("devtools")
devtools::install_github("s6juncheng/ggpval")
Simulate data with groups.
library(ggpval)
library(data.table)
library(ggplot2)
A <- rnorm(200, 0, 3)
B <- rnorm(200, 2, 4)
G <- rep(c("G1", "G2"), each = 100)
dt <- data.table(A, B, G)
dt <- melt(dt, id.vars = "G")
theme_set(theme_classic())
Give the group pairs you want to compare in pairs
. By default we use wilcox.test
, you can al well use t.test
and others. The key word arguments for the test function, such as alternative = c("two.sided", "less", "greater")
, paired=
can be directly given. By default, we use the save default arguments as the test function.
plt <- ggplot(dt, aes(variable, value)) +
geom_boxplot() +
geom_jitter()
add_pval(plt, pairs = list(c(1, 2)), test='wilcox.test', alternative='two.sided')
To convert the plot with ggpval
annotation to plotly, add plotly=TRUE
:
plt <- ggplot(dt, aes(variable, value)) +
geom_boxplot() +
geom_jitter()
plt <- add_pval(plt, pairs = list(c(1, 2)), test = "t.test", plotly=TRUE)
plotly::ggplotly(plt)
plt <- ggplot(dt, aes(variable, value)) +
geom_boxplot() +
geom_jitter() +
facet_wrap(~G)
add_pval(plt, pairs = list(c(1, 2)))
ggpval
tries to infer the column which contains the data to do
statistical testing. In case this inference was wrong or not possible
(for instance the raw data column was not mapped in ggplot object), you
can specify the correct column name with response=
.
dt[, mu := mean(value),
by = c("G", "variable")]
dt[, se := sd(value) / .N,
by = c("G", "variable")]
plt_bar <- ggplot(dt, aes(x=variable, y=mu, fill = variable)) +
geom_bar(stat = "identity", position = 'dodge') +
geom_errorbar(aes(ymin=mu-se, ymax=mu+se),
width = .2) +
facet_wrap(~G)
add_pval(plt_bar, pairs = list(c(1, 2)), response = 'value')
Additional arguments for statistical function can also be directly specified. Here we also the conventional "*" format for significance level.
add_pval(plt_bar, pairs = list(c(1, 2)),
test = 't.test',
alternative = "less",
response = 'value',
pval_star = T)
add_pval(plt, pairs = list(c(1, 2)), annotation = "Awesome")
In case you to want give different annotations to each facets, provide your annotation as a list
add_pval(plt, pairs = list(c(1, 2)), annotation = list("Awesome1", "Awesome2"))
Please report bugs and issues on github issue page: https://github.com/s6juncheng/ggpval/issues. Contributions are welcome.
Thanks to Vicente Yépez for testing and helping with improvement of the package.