---
title: "Test_exp"
output: html_document
---

```{r}
library(dplyr)
library(tidyverse)
library(cowplot)
library(ggpubr)
```


#Cell death frm three batches, WT2 (WT68)
```{r}
setwd("Z:/16-Our Papers/In Preparation/PD_Diabetes_Alise/Figures/FigureS2/originals/B,C")
data_LDH <- readr::read_csv("LDH_assay_Insulin_inputR.csv")
```

```{r}
#Data68<-subset(data_ins, data_ins$Cell_line %in% "WT_68")
data_LDH %>% mutate(Day= 'D30')%>% mutate(Area = pi*(data_LDH$Diameter/2)^2)%>% mutate(Cell_death=Lum_norm/Area*10000)->newData
#Luminescence is normalized to the mean RLU of the batch and multiply by 10000 factor to keep the scale

newData %>% 
  
  mutate(Treatment = case_when (str_detect(Condition, 'Ctrl') ~ 'Standard media',
                                str_detect(Condition, '430nM') ~ 'Self-made N2 +430nM ins',
                                str_detect(Condition, '-ins') ~ 'Self-made N2 w/o ins',
                               TRUE ~ 'none'))-> dataTr


dataTr$Treatment <- factor(dataTr$Treatment, levels=c("Standard media", "Self-made N2 +430nM ins","Self-made N2 w/o ins"))

ggplot(dataTr, aes(x=Treatment, y=Cell_death))+
    geom_boxplot(aes(fill=Treatment),width=0.5)+
    #geom_violin(aes(fill=Treatment),show.legend = T, trim=T)+
    scale_fill_manual(values=c('indianred','gold3','steelblue'))+ #RosyBrown
    geom_jitter(aes(color=Cell_line),position=position_jitter(0.2), cex=1)+
    scale_color_manual(values = c("black")) +
   #ylim(0,0.25)+
   geom_signif(comparisons = list(c("Standard media", "Self-made N2 +430nM ins")), test='t.test',#margin_top = 0.5,
                  vjust=0, size=0.3, textsize=3, map_signif_level=c("***"=0.001, "**"=0.01, "*"=0.05), y_position = 0.025 ) +
   geom_signif(comparisons = list(c("Standard media", "Self-made N2 w/o ins")), test='t.test',#margin_top = 0.5,
                  vjust=0, size=0.3, textsize=3, map_signif_level=c("***"=0.001, "**"=0.01, "*"=0.05), y_position = 0.028 ) +
  geom_signif(comparisons = list(c("Self-made N2 +430nM ins", "Self-made N2 w/o ins")), test='t.test',#margin_top = 0.5,
                  vjust=0, size=0.3, textsize=3, map_signif_level=c("***"=0.001, "**"=0.01, "*"=0.05), y_position = 0.022 ) +
 theme_minimal()+
  labs(title=" ", y = "LDH release, RLU/Area")+
   theme(plot.title=element_text(size=15, face="bold", hjust=0.5),
          axis.text.x=element_blank(), 
          axis.title.x=element_blank(), axis.title.y=element_text(size=20), axis.text.y=element_text(size=16, colour = "black"), legend.text = element_text(size=14), legend.title = element_text(size=15))->p

  print(p)
  
```

#ATP
```{r}
setwd("Z:/16-Our Papers/In Preparation/PD_Diabetes_Alise/Figures/FigureS2/originals/B,C")
dataATP <- readr::read_csv("ATP_assay_Insulin_treatment_inputR.csv")
```
```{r}
#data68<-subset(dataATP, dataATP$Cell_line %in% "WT_68")
dataATP %>% mutate(Day= 'D30')%>% mutate(Area = pi*(dataATP$Diameter/2)^2)%>% mutate(ATP = Lum_norm/Area*10000)->newDataATP
#Luminescence is normalized to the mean RLU of the batch and multiply by 10000 factor to keep the scale

newDataATP %>% 
  
  mutate(Treatment = case_when (str_detect(Condition, 'Ctrl') ~ 'Standard media',
                                str_detect(Condition, '430nM') ~ 'Self-made N2 +430nM ins',
                                str_detect(Condition, '-ins') ~ 'Self-made N2 w/o ins',
                               TRUE ~ 'none')) -> dataTrATP


dataTrATP$Treatment <- factor(dataTrATP$Treatment, levels=c("Standard media", "Self-made N2 +430nM ins","Self-made N2 w/o ins"))

ggplot(dataTrATP, aes(x=Treatment, y=ATP))+
    geom_boxplot(aes(fill=Treatment),width=0.5)+
    #geom_violin(aes(fill=Treatment),show.legend = T, trim=T)+
    scale_fill_manual(values=c('indianred','gold3','steelblue'))+ #RosyBrown
    geom_jitter(aes(color=Cell_line),position=position_jitter(0.2), cex=1)+
    scale_color_manual(values = c("black")) +
   #ylim(0,0.25)+
   geom_signif(comparisons = list(c("Standard media", "Self-made N2 +430nM ins")), test='t.test',#margin_top = 0.5,
                  vjust=0, size=0.3, textsize=3, map_signif_level=c("***"=0.001, "**"=0.01, "*"=0.05), y_position = 0.023 ) +
   geom_signif(comparisons = list(c("Standard media", "Self-made N2 w/o ins")), test='t.test',#margin_top = 0.5,
                  vjust=0, size=0.3, textsize=3, map_signif_level=c("***"=0.001, "**"=0.01, "*"=0.05), y_position = 0.026 ) +
  geom_signif(comparisons = list(c("Self-made N2 +430nM ins", "Self-made N2 w/o ins")), test='t.test',#margin_top = 0.5,
                  vjust=0, size=0.3, textsize=3, map_signif_level=c("***"=0.001, "**"=0.01, "*"=0.05), y_position = 0.02 ) +
  theme_minimal()+
  labs(title=" ", y = "ATP, RLU/Area")+
  theme(plot.title=element_text(size=15, face="bold", hjust=0.5),
          axis.text.x=element_blank(), 
          axis.title.x=element_blank(), axis.title.y=element_text(size=20), axis.text.y=element_text(size=16, colour = "black"), legend.text = element_text(size=14), legend.title = element_text(size=15))->p

  print(p)
  
```

#Organoid developmentfrom the same three batches
```{r}
setwd("Z:/16-Our Papers/In Preparation/PD_Diabetes_Alise/Figures/FigureS2/originals/B,C")
dataB1 <- readr::read_csv("Summary_size_B1.csv")
dataB3 <- readr::read_csv("Summary_size_B3.csv")
dataB4 <- readr::read_csv("Summary_size_B4.csv")
```
#Clean data to analyze the shared time pints between batches
```{r}
dataB1[!grepl("D12", dataB1$Day),]->dataB1
dataB1[!grepl("D18", dataB1$Day),]->dataB1
dataB3[!grepl("D12", dataB3$Day),]->dataB3

dataB1[!grepl("Annas_protocol", dataB1$Treatment),]->dataB1

data<-rbind(dataB1, dataB3, dataB4)

data[!grepl("WT_K7", data$Cell_line),]->data

data[!grepl("Insulin_10nM", data$Treatment),]->data

data %>% 
  
  mutate(Condition = case_when (str_detect(Treatment, 'Optimized') ~ 'Standard media',
                                str_detect(Treatment, 'Self_made_N2') ~ 'Self-made N2 +430nM ins',
                                str_detect(Treatment, 'W/o_insulin') ~ 'Self-made N2 w/o ins',
                               TRUE ~ 'none'))%>%
 
  mutate(Cell = case_when(str_detect(Cell_line, 'WT_68') ~ 'WT2',
                               
                               TRUE ~ 'none'))->dataSize

 dataSize$Condition <- factor(dataSize$Condition, levels=c("Standard media", "Self-made N2 +430nM ins","Self-made N2 w/o ins"))

 dataSize$Day <- factor(dataSize$Day, levels=c("D2","D6","D9", "D16"))
 
ggplot(dataSize, aes(x=Condition, y=Area))+
    geom_boxplot(aes(fill=Batch),width=1)+
    scale_fill_manual(values=c('DarkGray','RosyBrown',"lightblue"))+
    geom_jitter(aes(color=Cell_line),position=position_jitter(0.5))+
   # scale_color_manual(values = c("SteelBlue","DarkGreen")) +
    facet_grid(~Day)+
  theme_bw()+
  labs(title="Organoid size", y = "Area, um")+
  theme(plot.title=element_text(size=15, face="bold", hjust=0.5),
          axis.text.x=element_text(size = 12, angle=45, vjust = 1, hjust = 1), 
          axis.title.x=element_blank(), axis.title.y=element_text(size=12)) -> p


 t<- cowplot::ggdraw(cowplot::add_sub(p, "Objective: D2-D6:4x, D9-D16:2.5x",hjust=-0.5, size=9))
  print(t)
  

#ggsave('Size comparison2.png', height = 6 , width = 9)
```
#take D30 Area from LDH Diameter (ATP and LDH Area is the same, bc both experiments done fr the same MOs)
```{r}
data_ins2<-dataTr[,c("Batch","Cell_line","Day","Treatment", "Area")]

dataSize2<-dataSize[,c("Batch","Cell","Day","Condition", "Area")]
colnames(dataSize2)<-c("Batch","Cell_line","Day","Treatment","Area")

data3<-rbind(data_ins2,dataSize2)

data3$Day <- factor(data3$Day, levels=c("D2","D6","D9", "D16", "D30"))
```
```{r}
data3 %>%
  group_by(Day,  Treatment) %>%
  dplyr::mutate(av = mean(Area, na.rm=TRUE)) %>%
  unique() %>%
  ggplot(aes(x=Day, y=av, group=Treatment, color=Treatment)) +
  scale_color_manual(values=c('indianred','gold3','steelblue'))+
  stat_smooth(method='loess', formula ='y ~ x')+
  labs(x="Days of organoid culture",
       y = "Area, μm",
       fill = "Treatment",
      title = " ") +
   theme_minimal() +
   theme(
    #axis.line = element_line(colour = 'black', size = 0.1) ,
    axis.title.x = element_text(size = 20),
    axis.text.x = element_text(size = 16, colour = "black"),
    axis.title.y = element_text(size = 20),
    axis.text.y = element_text(size=16, color="black"),
    axis.ticks.y = element_line(),
    legend.position="right",
    legend.text = element_text(size = 14),
    legend.title = element_text(size=15),
    legend.key.size = unit(0.7, "cm"),
    legend.key.width = unit(0.6,"cm"),
    plot.title = element_text(size = 16, hjust=0.5, vjust= 1, face = "bold"),
    plot.subtitle = element_blank(),#element_text(size = 2, hjust=0.5)
    strip.text = element_text(size=12, vjust=0.5),
    strip.background = element_rect(fill="lightgray"),
    #panel.border = element_rect(fill = NA, color = "black"),
    panel.spacing.y = unit(0.8, "lines"),
    strip.switch.pad.wrap=unit(20, "lines")
  )  -> p
 print(p)
#  ggsave(paste0(Sys.Date(), "_Timeline.pdf"), p)
```