mutation_and_cnv_breakdown.Rmd

---
title: "Breakdown of Mutation and CNV Files"
author: "Ted Laderas"
date: "9/15/2019"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(ggplot2)
library(here)
library(data.table)
library(dplyr)
mutation_file <- fread(here("data/TCGA.HNSC.mutect.84c7a87a-9dcc-48fb-bd69-ba9d6e6f3ca2.DR-7.0.somatic_cleaned.maf"))

hpv_pos_file <- fread(here("data/TCGA.HNSC.HPV-negative.maf"))

hpv_neg_file <- fread(here("data/TCGA.HNSC.HPV-negative.maf"))

cnv_file <- fread(here("data/gistic_long_file.maf"))
```

# Breakdown of Main Mutation File

```{r}
top20 <- mutation_file %>% group_by(Hugo_Symbol) %>% summarize(count = n()) %>% top_n(20) %>% arrange(desc(count)) %>% pull(Hugo_Symbol)

mutation_file %>% filter(Hugo_Symbol %in% top20) %>%
  mutate(gene = ordered(Hugo_Symbol, levels = top20)) %>% ggplot(aes(x=gene, fill= Variant_Classification)) + geom_bar() + theme_minimal() + theme(axis.text.x = element_text(angle = 90)) + ggtitle("Breakdown of Mutation by Variant Type")
```

# Breakdown of CNV File

```{r}
top20 <- cnv_file %>% group_by(Hugo_Symbol) %>% summarize(count = n()) %>% top_n(20) %>% arrange(desc(count)) %>% pull(Hugo_Symbol)

cnv_file %>% filter(Hugo_Symbol %in% top20) %>%
  mutate(gene = ordered(Hugo_Symbol, levels = top20)) %>% ggplot(aes(x=gene, fill= Variant_Type)) + geom_bar() + theme_minimal() + theme(axis.text.x = element_text(angle = 90)) + ggtitle("Breakdown of CNV by Variant Type")
```

# Breakdown of HPV Positive by Variant Type

```{r}
top20 <- hpv_pos_file %>% group_by(Hugo_Symbol) %>% summarize(count = n()) %>% top_n(20) %>% arrange(desc(count)) %>% pull(Hugo_Symbol)

hpv_pos_file %>% filter(Hugo_Symbol %in% top20) %>%
  mutate(gene = ordered(Hugo_Symbol, levels = top20)) %>% ggplot(aes(x=gene, fill= Variant_Classification)) + geom_bar() + theme_minimal() + theme(axis.text.x = element_text(angle = 90)) + ggtitle("Breakdown of Mutations in HPV+ \nby Variant Type")
```

# Breakdown of HPV Positive by Variant Type

```{r}
top20 <- hpv_pos_file %>% group_by(Hugo_Symbol) %>% summarize(count = n()) %>% top_n(20) %>% arrange(desc(count)) %>% pull(Hugo_Symbol)

hpv_pos_file %>% filter(Hugo_Symbol %in% top20) %>%
  mutate(gene = ordered(Hugo_Symbol, levels = top20)) %>% ggplot(aes(x=gene, fill= Variant_Classification)) + geom_bar() + theme_minimal() + theme(axis.text.x = element_text(angle = 90)) + ggtitle("Breakdown of Mutations in HPV- \nby Variant Type")
```