---
title: "Introduction To Markdown"
author: "Your Name"
date: "September 9, 2017"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## Complete the steps below
This is the rmarkdown file for the genviz.org tutorial series, complete the steps below and delete this section when complete.

* add your name in the yaml header
* load in the data
* create a code chunk in the section "Data visualization"
* create a plot matching the description in the section "Data visualization"
* create a code chunk in the section "Data mean"
* Set the code chunk to not display this last block of code in the final document.

## Data description
The data used in this section is from the manuscript entitled "Recurrent somatic mutations affecting B-cell receptor signaling pathway genes in follicular lymphoma" (PMID: [28064239](https://www.ncbi.nlm.nih.gov/pubmed/28064239)).
```{r}
fl_data <- read.delim("ggplot2ExampleData.tsv")
```

## Data visualization
using geom_density() from the ggplot2 package we can see that the discovery cohort has an average tumor variant allele fraction (tumor_VAF) somewhere around 20%. The extension cohort has a wider distribution with an average variant allele fraction somewhere around 30-45%.

## Data mean
More precisely we can see that the mean variant allele fraction for these cohorts are as follows: