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University of Virginia

Apr 15-16, 2015

8:00 am - 4:00 pm

Instructors: Jessica Bonnie, Zhuo Fu, Alex Koeppel

Helpers: Stephen Turner, Bart Ragon

General Information

Software Carpentry's mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

This workshop is sponsored by the UVA Data Science Institute.

Who: The course is aimed at graduate students and other researchers in the biomedical sciences.

Where:

Day 1: MR5, Room 3005.

Day 2: Jordan Hall Conference Center, Room G1/G2.

Get directions with OpenStreetMap or Google Maps.

Requirements: Participants must bring a laptop with a few specific software packages installed (listed below). They are also required to abide by Software Carpentry's Code of Conduct.

Pre-Assessment: Before attending the first session, please fill out a short pre-assessment.

Post-Assessment: After the last session, please fill out a short post-assessment.

Contact: Please mail br5n@virginia.edu for more information.

Schedule

Day 1

08:00 Coffee/Setup
8:30 Introduction
9:00 Meet the Unix Shell
12:30 Lunch (Provided! Thanks Data Science Institute!)
13:30 Version control with Git
14:00 Coffee
16:00 Wrap-up

Day 2

08:00 Coffee
8:30 R for Beginners
12:30 Lunch (Provided! Thanks Data Science Institute!)
13:30 R: Loops and Conditionals
14:00 Coffee
16:00 Wrap-up

Etherpad: https://etherpad.mozilla.org/uvaswc.
We will use this Etherpad for chatting, taking notes, and sharing URLs and bits of code. If there is a something that you would like clarified, or a code snippet that you would like to get, please ask over etherpad.

Syllabus

The Unix Shell

  • Files and directories
  • History and tab completion
  • Pipes and redirection
  • Looping over files
  • Creating and running shell scripts
  • Finding things
  • Reference...

Programming in R

  • Working with vectors and data frames
  • Reading and plotting data
  • Creating and using functions
  • Loops and conditionals
  • Using R from the command line
  • Reference...

Version Control with Git

  • Creating a repository
  • Recording changes to files: add, commit, ...
  • Viewing changes: status, diff, ...
  • Ignoring files
  • Working on the web: clone, pull, push, ...
  • Resolving conflicts
  • Reference...

Setup

Text Editor

When you're writing code, it's nice to have a text editor that is optimized for writing code, with features like automatic color-coding of key words. The default text editor on Mac OS X and Linux is usually set to Vim, which is not famous for being intuitive. if you accidentally find yourself stuck in it, try typing the escape key, followed by ':q!' (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell.

Windows

nano is the editor installed by the Software Carpentry Installer, it is a basic editor integrated into the lesson material.

Notepad++ is a popular free code editor for Windows. Be aware that you must add its installation directory to your system path in order to launch it from the command line (or have other tools like Git launch it for you). Please ask your instructor to help you do this.

Mac OS X

We recommend Text Wrangler or Sublime Text. In a pinch, you can use nano, which should be pre-installed.

Linux

Kate is one option for Linux users. In a pinch, you can use nano, which should be pre-installed.

The Bash Shell

Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.

Windows

Install Git for Windows by download and running the installer. This will provide you with both Git and Bash in the Git Bash program.

Software Carpentry Installer

This installer requires an active internet connection.

After Git Bash:

  • Download the installer.
  • Double click on the file to run it.

Information about the SWC Windows Installer, including the source code, can be found at https://github.com/swcarpentry/windows-installer.

Mac OS X

The default shell in all versions of Mac OS X is bash, so no need to install anything. You access bash from the Terminal (found in /Applications/Utilities). You may want to keep Terminal in your dock for this workshop.

Linux

The default shell is usually bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.

Git

Git is a version control system that lets you track who made changes to what when and has options for easily updating a shared or public version of your code on github.com.

Windows

Git should be installed on your computer as part of your Bash install (described above).

Mac OS X

For OS X 10.8 and higher, install Git for Mac by downloading and running the installer. After installing Git, there will not be anything in your /Applications folder, as Git is a command line program. For older versions of OS X (10.5-10.7) use the most recent available installer for your OS available here. Use the Leopard installer for 10.5 and the Snow Leopard installer for 10.6-10.7.

Linux

If Git is not already available on your machine you can try to install it via your distro's package manager. For Debian/Ubuntu run sudo apt-get install git and for Fedora run sudo yum install git.

R

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Windows

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE.

Mac OS X

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.

Linux

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R). Also, please install the RStudio IDE.

Virtual Machine

Part of the lesson will require that learners use a virtual machine (VM). In order to set up the VM please:

  1. Install VirtualBox.
  2. Download our VM image. Warning: This file is 2.23 GByte, so please download it before coming to your workshop.
  3. Load the VM into VirtualBox by selecting File --> Import Appliance and choosing the swc_biomedical.ova file you just downloaded. Warning: If you open this image before the workshop, it might ask you to update. Say No.