---
title: "Validation_HCN2_OLIG2_Basescope"
author: "Luise A. Seeker"
date: "03/08/2022"
output: html_document
---
This is based on only a single staining of one BA4 and one CSC tissue samples to
see if I can detect HCN2 positive oligodendrocytes in both tissues. C1(blue) 
probe target was HCN2, C2 (red) target Olig2.

```{r}

library(ggplot2)
library(lme4)
library(lmerTest)
library(here)
library(tidyr)
library(ggsci)
```

```{r, echo = F}
mypal <- pal_npg("nrc", alpha = 0.7)(10)
mypal2 <-pal_tron("legacy", alpha = 0.7)(7)
mypal3 <- pal_lancet("lanonc", alpha = 0.7)(9)
mypal4 <- pal_simpsons(palette = c("springfield"), alpha = 0.7)(16)
mypal5 <- pal_rickandmorty(palette = c("schwifty"), alpha = 0.7)(6)
mypal6 <- pal_futurama(palette = c("planetexpress"), alpha = 0.7)(5)
mypal7 <- pal_startrek(palette = c("uniform"), alpha = 0.7)(5)

mycoloursP<- c(mypal, mypal2, mypal3, mypal4, mypal5, mypal6, mypal7)

```


```{r}
hcn2_data <- read.csv(here("data", 
                   "validation_data", 
                   "20220808_HCN2_OLIG2.csv"))

```


```{r}
names(hcn2_data)

hcn2_data$tissue <- as.factor(hcn2_data$Tissue)


```

Convert from wide to long format to see how many single, double and triple
positive cells are in each sample

```{r}

keycol <- "sample_id"
valuecol <- "count"
gathercols <- c("HCN2_C1_blue",
                "Olig2_C2_red", 
                "HCN2_Olig2")

long_data <- gather(hcn2_data, keycol, valuecol, gathercols)

head(long_data)
nrow(long_data)
names(long_data)
```






```{r}


ggplot(long_data, aes(x = sample_id , 
                          y = valuecol, 
                          fill = keycol)) +
  geom_bar(position="stack", stat="identity")+ theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))+scale_fill_manual(values= mycoloursP[25:30])





ggplot(long_data, aes(x = sample_id , 
                          y = valuecol, 
                          fill = keycol)) +
  geom_bar(position="fill", stat="identity")+ theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +scale_fill_manual(values= mycoloursP[25:30])


```



```{r}

hcn2_data$HCN2_Olig2 <- as.numeric(hcn2_data$HCN2_Olig2)


ggplot(hcn2_data, aes(x = tissue, y = perc_HCN2_pos_olig2)) + geom_boxplot() + 
  geom_jitter(width = 0.2, height = 0, aes(colour = sample_id)) +
  theme_bw() + ylab("HCN2+ OLIG2+ (%)") + xlab("Tissue")


ggplot(hcn2_data, aes(x = tissue, y = HCN2_Olig2)) + geom_boxplot() + 
  geom_jitter(width = 0.2, height = 0, aes(colour = sample_id)) +
  theme_bw() + ylab("HCN2+ OLIG2+") + xlab("Tissue")




```


Conclusion:
In accordance to the snRNAseq data, HCN2 positive oligodendrocytes (Olig2+)
can be found in both BA4 and spinal cord. It is only one sample each and 
therefore not enough to comment, but based in what I see here, more samples 
may be able to show that there are more HCN2 positive oligodendrocytes
in the spinal cord compared to the brain. 

```{r}
sessionInfo()

```