diff --git a/boxplot.R b/boxplot.R
new file mode 100644
index 0000000..e7d4e99
--- /dev/null
+++ b/boxplot.R
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+#!/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 + stat_compare_means(comparisons = my_comparisons
+                         , method = "wilcox.test"
+                         , paired = F
+                         , label = "p.format") 
+
+
+########################################################################
+# Output plots as one pdf
+cat("Output plots will be in:", output_boxplot)
+pdf(output_boxplot, width=15, height=12)
+
+y_value = "value"
+my_title1 = "Boxplots"
+
+p1 = ggplot(lf, aes(x = factor(timepoint), y = eval(parse(text=y_value)), fill = factor(obesity) ))  + 
+  scale_fill_manual(values=c("#00BFC4", "#F8766D")) +
+  facet_wrap(~ mediator, nrow = 9, ncol = 4, scales = "free_y") + 
+  geom_boxplot(width = 0.5, outlier.colour = NA) +
+  #geom_point(position = position_jitterdodge(dodge.width=0.5)
+  #           , aes(colours = factor(obesity))) + 
+             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 = 10)
+                   , legend.text = element_text(size = 15)
+                   , legend.direction = "vertical") +
+               labs(title = my_title1
+                    , x = ""
+                    , y = "Levels")+
+  stat_compare_means(comparisons = my_comparisons
+                     , method = "wilcox.test"
+                     , paired = F
+                     , label = "p.format") 
+#p1
+shift_legend2(p1)     
+dev.off()