HOW TO ADD P-VALUES TO GGPLOT FACETS

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
stat.test <- df %>%
  group_by(dose) %>%
  t_test(len ~ supp) %>%
  adjust_pvalue(method = "bonferroni") %>%
  add_significance()
# Create a box plot
bxp <- ggboxplot(
  df, x = "supp", y = "len", fill = "#00AFBB", 
  facet.by = "dose"
)

# Make facet and add p-values
stat.test <- stat.test %>% add_xy_position(x = "supp")
bxp + stat_pvalue_manual(stat.test)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
stat.test <- df %>%
  group_by(dose) %>%
  t_test(len ~ supp) %>%
  adjust_pvalue(method = "bonferroni") %>%
  add_significance()
# Create a box plot
bxp <- ggboxplot(
  df, x = "supp", y = "len", fill = "#00AFBB", 
  facet.by = "dose"
)

# Make facet and add p-values
stat.test <- stat.test %>% add_xy_position(x = "supp")
bxp + stat_pvalue_manual(stat.test)
# Make the facet scale free and add jitter points
# Move down the bracket using `bracket.nudge.y`
# Hide ns (non-significant)
# Show adjusted p-values and significance levels
# Add 10% spaces between the p-value labels and the plot border
bxp <- ggboxplot(
  df, x = "supp", y = "len", fill = "#00AFBB", 
  facet.by = "dose", scales = "free", add = "jitter"
)
bxp +  
  stat_pvalue_manual(
    stat.test, bracket.nudge.y = -2, hide.ns = TRUE,
    label = "{p.adj}{p.adj.signif}"
  ) +
  scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = "mean_sd", 
  fill = "#00AFBB", facet.by = "dose"
)

# Add p-values onto the bar plots
stat.test <- stat.test %>% add_xy_position(fun = "mean_sd", x = "supp")
bp + stat_pvalue_manual(stat.test)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)

# Add p-values onto the bar plots
stat.test <- stat.test %>% add_xy_position(fun = "max", x = "supp")
bp + stat_pvalue_manual(stat.test)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
  group_by(group, dose) %>%
  t_test(len ~ supp) %>%
  adjust_pvalue(method = "bonferroni") %>%
  add_significance()
# Create box plots with significance levels
# Hide ns (non-significant)
stat.test <- stat.test %>% add_xy_position(x = "supp")
ggboxplot(
  df, x = "supp", y = "len", fill = "#E7B800",
  facet = c("group", "dose")
) +
  stat_pvalue_manual(stat.test, hide.ns = TRUE)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
  group_by(group, dose) %>%
  t_test(len ~ supp) %>%
  adjust_pvalue(method = "bonferroni") %>%
  add_significance()
# Create bar plots with significance levels
# Hide ns (non-significant)
stat.test <- stat.test %>% add_xy_position(x = "supp", fun = "mean_sd")
ggbarplot(
  df, x = "supp", y = "len", fill = "#E7B800",
  add = c("mean_sd", "jitter"), facet = c("group", "dose")
) +
  stat_pvalue_manual(stat.test, hide.ns = TRUE)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
  group_by(supp) %>%
  t_test(len ~ dose)
# Box plots with p-values
stat.test <- stat.test %>% add_y_position()
ggboxplot(df, x = "dose", y = "len", fill = "#FC4E07", facet.by = "supp") +
  stat_pvalue_manual(stat.test, label = "p.adj.signif", tip.length = 0.01) +
  scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
# Bar plot with p-values
# Add 10% space on the y-axis above the box plots
stat.test <- stat.test %>% add_y_position(fun = "mean_sd")
ggbarplot(
  df, x = "dose", y = "len", fill = "#FC4E07",
  add = "mean_sd", facet.by = "supp"
) + 
  stat_pvalue_manual(stat.test,  label = "p.adj.signif", tip.length = 0.01) +
  scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
  group_by(supp) %>%
  t_test(len ~ dose, ref.group = "0.5")
# Box plots with p-values
stat.test <- stat.test %>% add_y_position()
ggboxplot(df, x = "dose", y = "len", fill = "#FC4E07", facet.by = "supp") +
  stat_pvalue_manual(stat.test, label = "p.adj.signif", tip.length = 0.01) +
  scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
# Show only significance levels at x = group2
# Move down significance symbols using vjust
stat.test <- stat.test %>% add_y_position()
ggboxplot(df, x = "dose", y = "len", fill = "#FC4E07", facet.by = "supp") +
  stat_pvalue_manual(stat.test, label = "p.adj.signif", x = "group2", vjust = 2)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
# Bar plot with p-values
# Add 10% space on the y-axis above the box plots
stat.test <- stat.test %>% add_y_position(fun = "mean_sd")
ggbarplot(
  df, x = "dose", y = "len", fill = "#FC4E07",
  add = c("mean_sd", "jitter"), facet.by = "supp"
) + 
  stat_pvalue_manual(stat.test,  label = "p.adj.signif", tip.length = 0.01) +
  scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
# Create box plots with significance levels
# Hide ns (non-significant)
# Add 15% space between labels and the plot top border
stat.test <- stat.test %>% add_xy_position(x = "dose")
ggboxplot(
  df, x = "dose", y = "len", fill = "#FC4E07",
  facet = c("group", "supp"),
 )
stat_pvalue_manual(stat.test, hide.ns = TRUE)
scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
# Create bar plots with significance levels
# Hide ns (non-significant)
# Add 15% space between labels and the plot top border
stat.test <- stat.test %>% add_xy_position(x = "dose", fun = "mean_sd")
ggbarplot(
  df, x = "dose", y = "len", fill = "#FC4E07",
  add = c("mean_sd", "jitter"), facet = c("group", "supp")
) 
  stat_pvalue_manual(stat.test, hide.ns = TRUE) 
  scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
# Box plots
bxp <- ggboxplot(
  df, x = "supp", y = "len", color = "dose", 
  palette = "jco", facet.by = "group"
)
bxp 

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
# Bar plots
bp <- ggbarplot(
  df, x = "supp", y = "len", color = "dose",
  palette = "jco", add = "mean_sd",
  position = position_dodge(0.8),
  facet.by = "group"
)
bp

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
  group_by(supp, group) %>%
  t_test(len ~ dose) 
# Box plots with p-values
# Hide ns (non-significant)
stat.test <- stat.test %>%
  add_xy_position(x = "supp", dodge = 0.8)
bxp + 
  stat_pvalue_manual(
    stat.test, label = "p.adj.signif", tip.length = 0.01,
    hide.ns = TRUE
  ) +
  scale_y_continuous(expand = expansion(mult = c(0.01, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
# Bar plots with p-values
stat.test <- stat.test %>%
  add_xy_position(x = "supp", fun = "mean_sd", dodge = 0.8)
bp 
  stat_pvalue_manual(
    stat.test, label = "p.adj.signif", tip.length = 0.01,
    hide.ns = TRUE
  ) 
  scale_y_continuous(expand = expansion(mult = c(0.01, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
  group_by(supp, group) %>%
  t_test(len ~ dose, ref.group = "0.5")
stat.test
# Box plots with p-values
stat.test <- stat.test %>%
  add_xy_position(x = "supp", dodge = 0.8)
bxp + 
  stat_pvalue_manual(
    stat.test, label = "p.adj.signif", tip.length = 0.01
  ) +
  scale_y_continuous(expand = expansion(mult = c(0.01, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
  df, x = "supp", y = "len", add = c("mean_sd", "jitter"), 
  fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
  group_by(supp, group) %>%
  t_test(len ~ dose, ref.group = "0.5")
stat.test
# Bar plots with p-values
stat.test <- stat.test %>%
  add_xy_position(x = "supp", fun = "mean_sd", dodge = 0.8)
bp 
  stat_pvalue_manual(
    stat.test, label = "p.adj.signif", tip.length = 0.01
  ) 
  scale_y_continuous(expand = expansion(mult = c(0.01, 0.1)))