05_pcp-proteins.Rmd

---
title: "Wnt genes"
output: 
  html_document:
    toc: true
    toc_float: true
    theme: flatly
---

# Setup 

Libraries required
```{r libraries, message=FALSE, warning=FALSE}
library(dplyr)
library(here)
library(tibble)
library(tidyr)
library(HGNChelper)
library(ggplot2)
library(ggrepel)
```


# Data input

```{r data-input, message=FALSE, warning=FALSE}
load(here('data', 'data-preprocessed.RData'))
```

Import the wnt proteins
```{r pcp-proteins-import}
vec <- c("LRP6", "FZD3", "ROR1", "ROR2", "CELSR1", "CELSR2", "VANGL1", "VANGL2")
```

Transform to long format
```{r data-long}
data.filt <- subset %>%
  select(Suggested.Symbol,
         ends_with("adj.P.Val"),
         ends_with("logFC"))

data.filt <- data.filt %>%
  rename('logFC_PRK1' = 'PRK1.CTRL.logFC',
         'logFC_PRK2' = 'PRK2.CTRL.logFC',
         'logFC_PRK3' = 'PRK3.CTRL.logFC',
         'padj_PRK1' = 'PRK1.CTRL.adj.P.Val',
         'padj_PRK2' = 'PRK2.CTRL.adj.P.Val',
         'padj_PRK3' = 'PRK3.CTRL.adj.P.Val')

data.long <- pivot_longer(data.filt, 
                          cols = !Suggested.Symbol,
                          names_to = c(".value", "Var"),
                          names_sep = "_")
```

# PCP proteins

```{r pcp-proteins}
myColors <- c("#94C96E", "#315D00", "#90005D")
names(myColors) <- levels(factor(data.long$Var))
colScale <- scale_color_manual(name = "PRICKLE_isoform",values = myColors)

for (i in 1:length(vec)){
p <- data.long %>%
  filter(Suggested.Symbol == vec[i]) %>%
  ggplot(aes(x = logFC, y = -log10(padj), col = Var, label = Var))+
  geom_point()+
  geom_label_repel()+
  theme_minimal()+
  labs(title = vec[i])+
  colScale

print(p)
}