normal_tissue_hpa.Rmd

---
title: "HPA Normalalized Tissue Expression Notebook"
output: html_notebook
---

```{r setup}
library(tidyverse)
library(here)
library(janitor)
library(cowplot)
#rm(list = ls())
```

#import RNA consensus tissue gene data
Consensus transcript expression levels summarized per gene in 74 tissues based on transcriptomics data from three sources: HPA, GTEx and FANTOM5. The consensus normalized expression ("NX") value is calculated as the maximum NX value for each gene in the three data sources. For tissues with multiple sub-tissues (brain regions, blood cells, lymphoid tissues and intestine) the maximum of all sub-tissues is used for the tissue type. The tab-separated file includes Ensembl gene identifier ("Gene"), analysed sample ("Tissue") and normalized expression ("NX"). The data is based on The Human Protein Atlas version 19.2 and Ensembl version 92.38.

You can either download the file and place it in the data folder
1. Download https://www.proteinatlas.org/download/rna_tissue_consensus.tsv.zip to the data folder  
2. Unzip (double-click)  
3. Confirm you see rna_tissue_consensus.tsv  

Or you can run the code below to download the file each time

```{r}

url <- "https://www.proteinatlas.org/download/rna_tissue_consensus.tsv.zip"
zip_file <- tempfile(fileext = ".zip")
download.file(url, zip_file, mode = "wb")
normalized_tissue <- read_tsv(zip_file) %>% 
  clean_names()

#uncomment this line to import from saved location
#normalized_tissue <- read_tsv(here::here("data", "rna_tissue_consensus.tsv")) %>% clean_names()

head(normalized_tissue)

count(normalized_tissue, nx, sort = TRUE)

ggplot(normalized_tissue) +
  geom_histogram(aes(x = log10(nx)))
```

#yfg
```{r}
normalized_tissue %>% 
  filter(gene_name == "NOS2") %>% 
  arrange(desc(nx))

normalized_tissue %>% 
  filter(tissue == "amygdala") %>% 
  top_n(20) %>% 
  arrange(desc(nx)) %>% 
  ggplot() +
  geom_col(aes(x = fct_reorder(gene_name, nx), y = nx)) +
  coord_flip() + 
  labs(title = "Tissue distribution of amygdala expression", x = "Normalized Expression", y = "") +
  theme_cowplot()


```