---
title: "CellROX Dopaminergic neurons"
author: "Claudia Saraiva"
date: "2023-07-24"
output: html_document
---
```{r}
library(tidyverse)
library(ggforce)
library(ggsignif)
library(shiny)
library(ggpubr)

library(ggplot2)
library(dplyr)

#install.packages("hrbrthemes")
#installr::check.for.updates.R()

library(hrbrthemes)

#install.packages("viridisLite")
library(viridisLite)
library(viridis)
library(gdata)
library(readxl)
library(tidyverse)
library(ggsignif)
#install.packages("janitor")
library(janitor)
#install.packages("xgboost")
library(xgboost)
#install.packages("vioplot")
library(vioplot)
#install.packages("outliers")
library(outliers)
library(ggpubr)
library(rstatix)
```


```{r}
#work directory and data loading
setwd("Z:/16-Our Papers/In Preparation/Miro1_AxPD_Claudia/Figures/Figure2/Partials/e")

dataDAN <- readr::read_csv("RplottingCellRox2D.csv")


#Checking for data normality within the dataset

#30days
shapiro.test(dataDAN$`CellroxMean normalized to isogenic control`)

#If shapiro test is significant, then data is not normal and Kruskal Willis test is done

#30days
kruskal.test(`CellroxMean normalized to isogenic control` ~ Condition, data = dataDAN)
stat.test.dunn  <- dunn_test(dataDAN, `CellroxMean normalized to isogenic control` ~ Condition, p.adjust.method = "BH")
stat.test.dunn


```

```{r}

```
```{r}

#Ploting the feature of interest 30days
dataDAN$Condition <- factor (dataDAN$Condition, level=c("Ctrl", "PD", "iCtrl"))
dataDAN$NomenclatureManuscript <- factor (dataDAN$NomenclatureManuscript, level=c("Ctrl1", "PD", "iCtrl"))

dataDAN %>%
    ggplot( aes(x = factor(Condition), y=`CellroxMean normalized to isogenic control`) ) +
    geom_boxplot(aes(fill=Condition),width=0.5,outlier.shape=NA) +
      scale_fill_manual(values= c(alpha("#008176",0.7),"#c1272d",alpha("#0000a7",0.7)),name = "Condition") +
    geom_jitter(aes(colour = NomenclatureManuscript), position=position_jitter(0), cex=2)+
      scale_color_manual(values= (c(alpha("black", 0.8), alpha("black", 0.8), alpha("black", 0.8))))+
     stat_compare_means()  + #default Kruskall-Wallis
   stat_pvalue_manual(
    stat.test.dunn,
    y.position = 3.4, step.increase = 0.1,
    label = "p.adj.signif", hide.ns =T
    )+
  labs(x     = "Ctrl", "PD", "iCtrl",
       y     = "MFI CellROX \n Normalized iCtrl (set to 1)",
       fill  = "Conditions",
       title = "") +
     scale_y_continuous(limits=c(0, 4)) +
  
  theme_classic() +
  theme(
    axis.line = element_line(colour = 'black', size = 0.1) ,
    axis.title.x = element_blank(),
    axis.text.x = element_blank(),
    axis.title.y = element_text(size = 14),
    axis.text.y = element_text(size=12, color="black"),
    axis.ticks.y = element_line(),
    legend.position="right",
    legend.text = element_text(size = 12, face = "bold") ,
    legend.title = element_blank(),
    legend.key.size = unit(0.7, "cm"),
    legend.key.width = unit(0.6,"cm"),
    plot.title = element_text(size = 15, 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"),
    panel.grid.major = element_blank(), 
    panel.grid.minor = element_blank(),
    panel.background = element_blank()
  )+
  theme(aspect.ratio = 1.25 / 0.75) -> p

print(p)
ggsave("CellROX_DAN_30days.pdf", useDingbats=FALSE, plot=p,  height = 4, width = 5)
ggsave("CellROX_DAN_30days.tiff", plot=p)

```