#!/usr/bin/Rscript   
getwd()
setwd("~/git/mosaic_2020/")
getwd()
############################################################
# TASK: boxplots at T1
# FIXME: currently not rendering, problem with NAs for stats?
############################################################
my_sample_type = "serum"
#=============
# Input
#=============
source("data_extraction_formatting.R")

# check: adult variable and age variable discrepancy!
metadata_all$mosaic[metadata_all$adult==1 & metadata_all$age<=18]

#=============
# Output:
#=============
outfile_bp = paste0("boxplots_", my_sample_type, ".pdf")
output_boxplot = paste0(outdir_plots, outfile_bp); output_boxplot

#===============================
# data assignment for stats
#================================
wf = serum_wf[serum_wf$flustat == 1,]
lf = serum_lf[serum_lf$flustat == 1,]
lf$timepoint = paste0("t", lf$timepoint)

#==================
# Data for plotting
#==================
# convert these to factor
lf$obesity = as.factor(lf$obesity)
lf$timepoint = as.factor(lf$timepoint)

########################################################################
my_comparisons <- list( c("0", "1") )
########################################################################
lf_test = lf[lf$mediator == "eotaxin",]

str(lf_test)
p = ggplot(lf_test, aes(x = timepoint, y = value, fill = obesity  ))  + 
  geom_boxplot(width = 0.5)
p
# see default ggplot palette
ggplot_build(p)$data

p + stat_compare_means(comparisons = my_comparisons
                       , method = "wilcox.test"
                       , paired = F
                       , label = "p.format") 

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

# stats
stat.test <- lf_test %>%
  group_by(timepoint) %>%
  wilcox_test(value ~ obesity) %>%
  adjust_pvalue(method = "bonferroni") %>%
  add_significance("p.adj")
stat.test


# add stats to grouped boxplots
str(lf_test)
lf_test$obesity = as.factor(lf_test$obesity) # ensure factor

bxp <- ggboxplot(lf_test, x = "timepoint", y = "value", 
  color = "obesity", palette = c("#00BFC4", "#F8766D"))
bxp

stat.test <- stat.test %>%
  add_xy_position(x = "timepoint", dodge = 0.8)
bxp + stat_pvalue_manual(
  stat.test,  label = "p", tip.length = 0
)
################################
lf_test2 = lf[order(lf$mediator),] # 2 meds
lf_test2 = lf_test2[1:798,]
table(lf_test2$mediator)
str(lf_test2)

stat.test <- lf_test2 %>%
  group_by(timepoint, mediator) %>%
  wilcox_test(value ~ obesity, paired = F) %>%
  #adjust_pvalue(method = "bonferroni") %>%
  #add_significance("p.adj")
  add_significance("p")

stat.test

bxp <- ggboxplot(lf_test2, x = "timepoint", y = "value", 
                 color = "obesity", palette = c("#00BFC4", "#F8766D")) +
  facet_wrap(~mediator, scales = "free_y")

bxp

stat.test <- stat.test %>%
  add_xy_position(x = "timepoint", dodge = 0.8)
bxp + stat_pvalue_manual(stat.test,  label = "p.signif", tip.length = 0)

########################################################################
lf_comp = lf[-which(is.na(lf$value)),]
lf_test_comp = lf_comp[lf_comp$mediator == "eotaxin",]
str(lf_comp)

p2 = ggplot(lf_test_comp, aes(x = timepoint, y = value, fill = obesity ))  + 
  geom_boxplot(width = 0.5)
p2 

########################################################################
# Output plots as one pdf
cat("Output plots will be in:", output_boxplot)
pdf(output_boxplot, width = 25, height = 15)

#stats data
str(lf)
stat.test <- lf %>%
  group_by(timepoint, mediator) %>%
  wilcox_test(value ~ obesity, paired = F) %>%
  #adjust_pvalue(method = "bonferroni") %>%
  #add_significance("p.adj")
  add_significance("p")
stat.test

bxp <- ggboxplot(lf, x = "timepoint", y = "value", 
                 color = "obesity", palette = c("#00BFC4", "#F8766D")) +
  facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
  scale_y_log10()
bxp

bxp + stat.test <- stat.test %>%
  add_xy_position(x = "timepoint", dodge = 0.8)

bxp + stat_pvalue_manual(stat.test,  label = "p.signif", tip.length = 0)

dev.off()

######output 

# Output plots as one pdf
cat("Output plots will be in:", output_boxplot)
pdf(output_boxplot, width = 20, height = 15)
my_title1 = "Boxplots: serum"

bxp <- ggboxplot(lf, x = "timepoint", y = "value", 
                 color = "obesity", palette = c("#00BFC4", "#F8766D")) +
  facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
  scale_y_log10()

bxp + theme(axis.text.x = element_text(size = 15)
            , axis.text.y = element_text(size = 15
                                         , angle = 0
                                         , hjust = 1
                                         , vjust = 0)
            , axis.title.x = element_text(size = 15)
            , axis.title.y = element_text(size = 15)
            , plot.title = element_text(size = 20, hjust = 0.5)
            , strip.text.x = element_text(size = 15, colour = "black")
            , legend.title = element_text(color = "black", size = 20)
            , legend.text = element_text(size = 15)
            , legend.direction = "horizontal") +
  labs(title = my_title1
       , x = ""
       , y = "Levels (Log10)") 
#shift_legend2(bxp)
dev.off()