library(ggpubr)
###################################################################

my_unpaired_stats <- function(lf_data
                              , lf_stat_value = "param_value"
                              , lf_stat_group = "mutation_info"
                              , lf_col_statvars = "param_type"
                              , my_paired = FALSE
                              , stat_adj = "none"){
  
  stat_formula = as.formula(paste0(lf_stat_value, "~", lf_stat_group))
  
  my_stat_df = compare_means(stat_formula
                             , group.by = lf_col_statvars
                             , data = lf_data
                             , paired = my_paired
                             , p.adjust.method =  stat_adj)  
  
  
  return(my_stat_df)
}
  
#####################
# call stat function
#####################
stat_results_df <- my_unpaired_stats(lf_data =  lf_duet
                  , lf_stat_value = "param_value"
                  , lf_stat_group = "mutation_info"
                  , lf_col_statvars = "param_type"
                  , my_paired = FALSE
                  , stat_adj = "none"
)

y_value = "param_value"

#################################
my_comparisons <- list( c("DM", "OM") )

my_ats = 22 # axis text size
my_als = 20 # axis label size
my_fls = 20 # facet label size
my_pts = 22 # plot title size

####################################


stat_bp_mut <- function(df
                        , x_bp_cateog = "mutation_info"
                        , y_var = "param_value"
                        , facet_var = "param_type"
                        , scales = "free_y"
                        , title = ""
                        , col_categ = "duet_outcome"
                        , grp_comp = "my_comparisons"
                        , stat_method = "wilcox.test"
                        , my_paired = FALSE
                        #, stat_label = "p.format")
                        , stat_label = "p.signif" )


#############################
y_value = "param_value"


p1 = ggplot(lf_duet, aes(x = mutation_info
                          , y = eval(parse(text = y_value)) ))  + 
  facet_wrap(~ param_type
             , nrow = 1
             , scales = "free_y") + 
  geom_boxplot(fill = "white", outlier.colour = NA
               #, position = position_dodge(width = 0.9)
               , width = 0.2) +
  geom_point(position = position_jitterdodge(dodge.width=0.01)
             , alpha = 0.5
             , show.legend = FALSE
             , aes(colour = factor(duet_outcome))) +
  theme(axis.text.x = element_text(size = my_ats)
        , axis.text.y = element_text(size = my_ats
                                     , angle = 0
                                     , hjust = 1
                                     , vjust = 0)
        , axis.title.x = element_text(size = my_ats)
        , axis.title.y = element_text(size = my_ats)
        , plot.title = element_text(size = my_pts , hjust = 0.5, colour = "black", face = "bold")
        , strip.background = element_rect(fill = "khaki2")
        , strip.text.x = element_text(size = my_fls, colour = "black")
        , legend.title = element_text(color = "black", size = my_als)
        , legend.text = element_text(size = my_ats)
        , legend.direction = "vertical") +
  labs(title = "DUET"
       , x = ""
       , y = "")+ 
  stat_compare_means(comparisons = my_comparisons
                     , method = "wilcox.test"
                     , paired = FALSE
                     #, label = "p.format")
                     , label = "p.signif")

p1