From b94d9a3fdb1cb6b1e1c66dac12197337c4c1c750 Mon Sep 17 00:00:00 2001
From: Tanushree Tunstall <tanu@tunstall.in>
Date: Mon, 2 Nov 2020 16:39:37 +0000
Subject: [PATCH] renamed file to reflect stats for linear graphs

---
 boxplot_stat_all.R => boxplot_stat_linear.R |   0
 boxplot_with_stats_test.R                   | 264 --------------------
 2 files changed, 264 deletions(-)
 rename boxplot_stat_all.R => boxplot_stat_linear.R (100%)
 delete mode 100755 boxplot_with_stats_test.R

diff --git a/boxplot_stat_all.R b/boxplot_stat_linear.R
similarity index 100%
rename from boxplot_stat_all.R
rename to boxplot_stat_linear.R
diff --git a/boxplot_with_stats_test.R b/boxplot_with_stats_test.R
deleted file mode 100755
index f513cc2..0000000
--- a/boxplot_with_stats_test.R
+++ /dev/null
@@ -1,264 +0,0 @@
-#!/usr/bin/Rscript   
-getwd()
-setwd("~/git/mosaic_2020/")
-getwd()
-############################################################
-# TASK: boxplots at T1
-# FIXME: currently not rendering, problem with NAs for stats?
-############################################################
-#=============
-# Input
-#=============
-source("plot_data.R")
-#######################################################
-med_names = c("eotaxin3", "il12p70", "itac", "il13")
-lf_test = lf_fp_npa[lf_fp_npa$mediator%in%med_names,]
-
-mediators = levels(as.factor(lf_test$mediator))
-mediators = levels(as.factor(lf_fp_npa$mediator))
-lf_test = lf_fp_npa
-
-plots <- list()
-
-for (i in mediators) {
-single=lf_test[lf_test$mediator==i,]
-
-max_y = max(single$value, na.rm = T)
-cat("Plotting:", i, "max_y:", max_y, "\n")
-
-p2 = ggplot(single)+ geom_boxplot(aes(x = timepoint
-                     , y = value
-                     , color = obesity
-                    #, palette = c("#00BFC4", "#F8766D")
-                    ))+
-  scale_colour_manual(values=c("blue", "red")) + 
-  theme(axis.text.x = element_text(size = 15)
-        #axis.text.x = element_blank()
-        , axis.text.y = element_text(size = 15
-                                     , angle = 0
-                                     , hjust = 1
-                                     , vjust = 0)
-        , axis.title.x = element_blank()
-        , axis.title.y = element_blank()
-        , legend.position = "none"
-        , plot.subtitle = element_text(size = 20, hjust = 0.5)
-        , plot.title = element_text(size = 20, hjust = 0.5)) +
-  labs(title = i
-       #, subtitle = "test2"
-       )
-
-stat_npa2 <- single %>%
-  group_by(timepoint, mediator) %>%
-  wilcox_test(value ~ obesity, paired = F) %>%
-  add_significance("p")
-stat_npa2
-
-stat_npa2 <- stat_npa2 %>%
-  add_xy_position(x = "timepoint", dodge = 0.8)
-
-p2 = p2 + stat_pvalue_manual(stat_npa2
-                             #, y.position = max_y
-                             , label = "{p} {p.signif}"
-                             , hide.ns=T
-                             , tip.length = 0)+
-  scale_y_continuous(expand = expansion(mult = c(0.05, 0.25))) +
-  
-plots[[i]] <- p2
-
-}
-#============================
-# combine: cowplot_plot_grid
-#============================
-#cowplot::plot_grid(plotlist=plots, align = 'hv', ncol=2, nrow=2)
-pdf("test.pdf", width = 22, height = 16)
-cowplot::plot_grid(plotlist=plots, align = 'hv', ncol=7, nrow=5)
-dev.off()
-#===========================
-# combine: ggpubr::ggarrange
-#===========================
-pdf("test2.pdf", width = 22, height = 16)
-npa_plot<- ggpubr::ggarrange(plotlist = plots, align = "hv"
-                             , ncol = 7
-                             , nrow = 5
-                             , common.legend = T)
-npa_plot
-annotate_figure(npa_plot,
-                top = text_grob("NPA", color = "purple", face = "bold", size = 14),
-                bottom = text_grob("Mosaic data\nFlu positive adults (n=133)"
-                                   , color = "blue",
-                                   hjust = 1, x = 0.98, face = "italic", size = 10),
-                left = text_grob("Levels (pg/ml)", color = "black", rot = 90, size = 18),
-                #right = "I'm done, thanks :-)!",
-                #fig.lab = "Figure 1", fig.lab.face = "bold"
-                )
-
-
-##################################################################
-#=======
-# facet
-#=======
-#--------
-# wilcox stats
-#--------
-stat_npa3 <- lf_test %>%
-  group_by(timepoint, mediator) %>%
-  wilcox_test(value ~ obesity, paired = F) %>%
-  add_significance("p")
-stat_npa3
-stat_npa3$p_format = round(stat_npa3$p, 3)
-
-stat_npa3 <- stat_npa3 %>%
-  add_xy_position(x = "timepoint", dodge = 0.8)
-head(stat_npa3)
-
-#--------
-# summary stats
-#--------
-my_summary = lf_test %>%
-  group_by(timepoint, mediator) %>%
-  get_summary_stats(value)
-my_summary
-my_max_df = subset(my_summary
-                   , select = c("mediator", "timepoint"
-                                #, "obesity"
-                                , "max"))
-
-head(my_max_df); head(stat_npa3)
-
-#-----------------------------
-# merge my_max and stat_npa3
-#-----------------------------
-head(my_max_df)
-merging_cols = intersect(names(stat_npa3), names(my_max_df)); merging_cols
-
-stat_npa3_v2 = merge(stat_npa3, my_max_df, by = merging_cols, all.x = T)
-stat_npa3_v2$my_y_pos = (stat_npa3_v2$max)*1.2
-stat_npa3_v2$my_y_pos
-
-head(stat_npa3_v2); head(stat_npa3)
-
-p3 = ggplot(lf_test)+ geom_boxplot(aes(x = timepoint
-                                      , y = value
-                                      , color = obesity))+
-  scale_colour_manual(values=c("blue", "red")) + 
-  
-  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_blank()
-        , axis.title.y = element_blank()
-        , strip.text.x = element_text(size = 20,margin = margin(0.05,0,0.07,0, "cm"))
-        , legend.position = "top" 
-        , legend.title = element_text(color = "black", size = 20)
-        , legend.text = element_text(size = 15)
-        , plot.subtitle = element_text(size = 20, hjust = 0.5)
-        , plot.title = element_text(size = 20, hjust = 0.5)) +
-  labs(title ="NPA")+
-  facet_wrap(~mediator, scales = "free", nrow = 2, ncol = 2)
-#p3
-p4 = p3 + stat_pvalue_manual(stat_npa3_v2
-                             , y.position = "my_y_pos"
-                             #, y.position = 50
-                             , label = "{p_format} {p.signif}"
-                             , hide.ns=T
-                             , tip.length = 0)+
-  scale_y_continuous(expand = expansion(mult = c(0.05, 0.25)))
-
-p4
-#=======================================
-p3_build = ggplot_build(p3)
-p3_build$layout$panel_scales_y
-
-get_facet_ymax <- function (x){
-  ret <- x$layout$panel_scales_y
-  y_max =  NULL
-  
-  for (i in 1:length(ret)){
-    print(i)
-    y_max_i <- max(x$layout$panel_scales_y[[i]]$range$range)
-    y_max = c(y_max, y_max_i)
-  }
-  
-  return(y_max)
-}
-
-y_max_l = get_facet_ymax(p3_build); y_max_l
-#===============================================
-# facet wrap on actual data
-pdf("boxplot_stats.pdf", width = 20, height = 15)
-#=======
-# facet
-#=======
-#--------
-# wilcox stats
-#--------
-stat_npa3 <- lf_fp_npa %>%
-  group_by(timepoint, mediator) %>%
-  wilcox_test(value ~ obesity, paired = F) %>%
-  add_significance("p")
-stat_npa3 
-stat_npa3$p_format = round(stat_npa3$p, 3)
-
-stat_npa3 <- stat_npa3 %>%
-  add_xy_position(x = "timepoint", dodge = 0.8)
-head(stat_npa3)
-
-#--------
-# summary stats
-#--------
-my_summary = lf_fp_npa %>%
-  group_by(timepoint, mediator) %>%
-  get_summary_stats(value)
-my_summary
-my_max_df = subset(my_summary
-                   , select = c("mediator", "timepoint", "max"))
-
-head(my_max_df); head(stat_npa3)
-
-#-----------------------------
-# merge my_max and stat_npa3
-#-----------------------------
-head(my_max_df)
-merging_cols = intersect(names(stat_npa3), names(my_max_df)); merging_cols
-
-stat_npa3_v2 = merge(stat_npa3, my_max_df, by = merging_cols, all.x = T)
-stat_npa3_v2$my_y_pos = (stat_npa3_v2$max)*1.2
-stat_npa3_v2$my_y_pos
-
-head(stat_npa3_v2); head(stat_npa3)
-
-
-p3 = ggplot(lf_fp_npa)+ geom_boxplot(aes(x = timepoint
-                                         , y = value
-                                         , color = obesity))+
-  scale_colour_manual(values=c("blue", "red")) + 
-  #scale_y_log10()+
-  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_blank()
-        , axis.title.y = element_blank()
-        , strip.text.x = element_text(size = 20,  margin = margin(2,0,2,0, "cm"))
-        , legend.position = "top" 
-        , legend.title = element_text(color = "black", size = 20)
-        , legend.text = element_text(size = 15)
-        , plot.subtitle = element_text(size = 20, hjust = 0.5)
-        , plot.title = element_text(size = 20, hjust = 0.5)) +
-  labs(title ="NPA")+
-  facet_wrap(~mediator, scales = "free", nrow = 5, ncol = 7)
-#p3
-p4 = p3 + stat_pvalue_manual(stat_npa3_v2
-                             , y.position = "my_y_pos"
-                             , step.increase = 0.08
-                             #, y.position = 50
-                             , label = "{p_format} {p.signif}"
-                             , hide.ns=T
-                             , tip.length = 0) #+
-  #scale_y_continuous(expand = expansion(mult = c(0.05, 0.25)))
-
-p4
-dev.off()
\ No newline at end of file