Prepare Data_in_R

Create a new RStudio project

Open RStudio and create a new project, for more info see https://support.rstudio.com/hc/en-us/articles/200526207-Using-Projects

• File > New Project > New Directory > New Project (name the new directory, Ex. Data_in_R) and check “use packrat with this project” if present.

Learn more about packrat see https://rstudio.github.io/packrat/

Set some options and make sure the packages ‘knitr’, ‘tidyverse’, ‘reshape2’, and ’gr are installed (if not install it), and then load

In the R console run the following commands

if (!any(rownames(installed.packages()) == "knitr")){
  install.packages("knitr")
}
library(knitr)

if (!any(rownames(installed.packages()) == "tidyverse")){
  install.packages("tidyverse")
}
library(tidyverse)

## ── Attaching packages ───────────────────────────── tidyverse 1.2.1 ──

## ✔ ggplot2 2.2.1     ✔ purrr   0.2.4
## ✔ tibble  1.4.2     ✔ dplyr   0.7.4
## ✔ tidyr   0.8.0     ✔ stringr 1.3.0
## ✔ readr   1.1.1     ✔ forcats 0.3.0

## ── Conflicts ──────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()

if (!any(rownames(installed.packages()) == "reshape2")){
  install.packages("reshape2")
}
library(reshape2)

## 
## Attaching package: 'reshape2'

## The following object is masked from 'package:tidyr':
## 
##     smiths

if (!any(rownames(installed.packages()) == "gridExtra")){
  install.packages("gridExtra")
}
library(gridExtra)

## 
## Attaching package: 'gridExtra'

## The following object is masked from 'package:dplyr':
## 
##     combine

Learn more about the tidyverse see https://www.tidyverse.org.

Open a new R Notebook

An R notebook is an R Markdown document with chunks that can be executed independently and interactively, with output visible immediately beneath the input. More info see https://rmarkdown.rstudio.com/r_notebooks.html

• File -> New File -> R Notebook
• Save the Notebook (Ex. test)

R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the preview or Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed R code and plots in chunks like this:

```{r chunk_name}
print('hello world!')
```

Review the R Markdown page and R Markdown cheat sheets.

Try ‘knitting’ to html, pdf, and doc as well as previewing the notebook. Open the resulting documents.

Try executing the code chunks in the R Notebook.

Download the data file for the workshop document and preview/open it

This is the stats file generated after running samtools stats on a bam file generated from running BWA MEM.

In the R console run the following command.

download.file("https://raw.githubusercontent.com/ucdavis-bioinformatics-training/2018-March-Bioinformatics-Prerequisites/master/Data_in_R/bwa_mem_Stats.log", "bwa_mem_Stats.log")

Download the template Markdown workshop document and open it

In the R console run the following command

download.file("https://raw.githubusercontent.com/ucdavis-bioinformatics-training/2018-March-Bioinformatics-Prerequisites/master/Data_in_R/data_in_R.Rmd", "data_in_R.Rmd")

Edit the file YAML portion

The top YAML (YAML ain’t markup language) portion of the doc tells RStudio how to parse the document.

---
title: "Data_in_R"
author: your_name
date: current_date
output:
    html_notebook: default
    html_document: default
---

What are we going to do?

We will recreate some of the plots generated with plot-bamstats on the same file

You can view the output of plot-bamstats -> https://rawgit.com/ucdavis-bioinformatics-training/2018-March-Bioinformatics-Prerequisites/master/Data_in_R/bwa_mem_Stats/bwa_mem_Stats.html