R User for >10 years

Co-ordinator, Bioinformatics Hub
Level 4, Santos Petroleum Engineering Building

Also Today:

• Jimmy Breen & Hien To (Bioinformatics Hub)
• Reuben Buckley (Centre For Computational Genetics)
• Mohammad Kamruzzaman (Centre for Water Management and Reuse)

Later This Week:

• Joey Gerlach (eRSA)
• Steve Delean (Biological Sciences)

Slack

Please join the #radelaide-2016 channel

R Drop In

• Previously Wed 12:30 - 2:30
• Now Tues 11am - 1:00pm

• The main software/language used for analysis of biological data (along with Python)
• Can handle extremely large datasets
  
• We can easily perform complex analytic procedures
• Many processes come as inbuilt functions
  
• Huge user base of biological researchers

• Avoids common Excel pitfalls
• Reproducible Research

Excel is notorious for converting values from one thing to another inappropriately.

• Gene names are often converted to dates (e.g. SEPT9)

• Genotypes can be converted into numeric values (e.g. the homozygote "1/1")

In R we generally work with plain text files.

• Research is littered with mistakes from Excel
• Studies have made Phase III trials
• We have code to record and exactly repeat our analysis
• We can find and correct errors more easily than if they are copy/paste errors

With power comes great responsibility - Uncle Ben

With this extra capability, we need to understand a little about:

1. Data Types
   
2. Data Structures

That's tomorrow's content

Today we will start with:

1. An Introduction to RStudio
2. Reading data into R
3. Manipulating and cleaning data
4. Visualising data
5. Writing Reports

1. Open RStudio then
2. File > New File > R Script
   
3. Save As Introduction.R

• This is just a text editor.
• We enter our commands here but they are not executed
  • We can keep a record of everything we've done
  • We can also add comments to our code
  • Comments start with the # symbol

• Where we execute commands
• Is essentially the "engine"
• We can execute commands directly in the Console or send from the Script Window

Enter the following in the Script Window

# Create our first R object
x <- 5

• Lines of code are sent to the Console by either:
  • Ctrl + Enter
  • Copy & Paste into the Console
  • Clicking the Run button at the top right

We can view the contents of the object x by:

• entering it's name directly in the Console, or
• entering it's name in the Script Window & sending it to the Console

x
print(x)

Where have we created the object x?

• Is it on your hard drive somewhere?
• Is it in a file somewhere?

• We have placed x in our R Workspace
• More formally known as your Global Environment

• The Environment is like your desktop
• We keep all our relevant objects here and can save all the objects in your workspace as an .RData object

save.image()

• In the R Environment, we can create objects of multiple types.
• We first give them a name (e.g. x) and then assign a value to it using the <- symbol.
• This is like an arrow putting the value into the object.
• Can also work the other way, but is rarely done

# Using the reverse assignment operator
5 -> x

• Next to the Environment Tab is the History Tab
  • Contains everything executed in the Console
  • Useful for when we've been lazy
• Best coding practice is still to enter code in the Script Window and execute

In the bottom right are a series of tabs

1. Files: This shows your current working directory
2. Plots: Every time you make a graph it appears here
3. Packages: NEVER CLICK OR UN-CLICK ANYTHING HERE
4. Help: We'll explore this later

• Every tab can be resized using the buttons in the top right
• Window separators can also be be moved

Help > Cheatsheets > RStudio IDE Cheat Sheet

Page 2 has lots of hints:

• Ctrl + 1 places focus on the Script Window
• Ctrl + 2 places focus on the Console
• Ctrl + 3 places focus on the Help Tab

• Projects help keep an analysis organised
• Very useful for managing multiple analyses
• Integrated with Git and SVN version control
• Always goes back to "where-you-were-last-time"

Let's set one up for this course: File > New Project

• Choose either a New or Existing Directory
• Navigate to where you think is suitable for keeping the course notes
• The project name will automatically be assigned as the directory name