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GCB Academy - Introduction to Scientific Computing for Genomics

October 29 - November 2, 2018

8:30 am - 12:00 pm

Instructors: Hilmar Lapp (GCB), Dan Leehr (GCB)

Helpers: Gregory Steffen (GCB)

General Information

Computing has become an integral and indispensable part of genomic biology. This course teaches basic skills in scientific computing, with a focus on applications for genomic science, aimed at making you more productive, your computational work more reliable, and your research easier to reproduce and extend, including by your future self. The course includes introductions to

  1. using Unix shell commands to efficiently find, organize, and stage data for analysis;
  2. basic data types, control flows, functions, and 3rd party packages for the Python programming language commonly encountered in scientific computing;
  3. using version control to manage with confidence the numerous directions research code takes from inception to publication; and
  4. learning best practices for running your computational analyses on a shared high-performance computing cluster.
The format of the course is inspired by the acclaimed Software Carpentry-style bootcamps. Hence, this is a fully hands-on workshop, and students are expected to bring a laptop.

Who: The course is aimed at graduate students, postdocs, early career faculty, and other researchers.

Where: CIEMAS, Room 2240. 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.

Contact: Please mail for more information.


Oct 29, 8.30am-12pm

08:30 Automating tasks with the Unix shell
10:00 Break
12:00 Wrap-up

Oct 30, 8.30am-12pm

08:30 Building programs with Python
10:00 Break
12:00 Wrap-up

Oct 31, 8.30am-12pm

08:30 Version control with Git
10:00 Break
12:00 Wrap-up

Nov 2, 8.30am-12pm

08:30 Running programs on an HPC cluster
10:00 Break
12:00 Wrap-up

We will use this Etherpad for chatting, taking notes, and sharing URLs and bits of code.


Automating tasks with the Unix shell

  • Introducing the shell
  • Navigating files and directories
  • Working with files and directories
  • Pipes and redirection
  • Writing scripts
  • Project organization
  • Reference...

Building programs with Python

  • Data types and variables
  • Loops and conditionals
  • Creating and using functions
  • Working with files
  • Scripts and command-line
  • Libraries and packages
  • 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
  • Open licenses
  • Where to host work, and why
  • Reference...

Running programs on an HPC cluster

  • Why you need a cluster
  • How a cluster works
  • Running a job: srun
  • Running a batch job: sbatch
  • Monitoring your jobs: squeue, sacct, scancel
  • Moving files in/out: scp
  • Finding/getting software
  • Helpful Resources


Programming w/ Python

Git version control

Running programs on an HPC cluster


To participate in this workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser. Installation instructions will become available here closer to the date of the course.

We maintain a list of common issues that occur during installation as a reference for instructors and learners on the Configuration Problems and Solutions wiki page.

The Bash Shell

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


Download the Git for Windows installer. Run the installer. Important: on the 6th page of the installation wizard (the page titled `Configuring the terminal emulator...`) select `Use Windows' default console window`. If you forgot to do this programs that you need for the workshop will not work properly. If this happens rerun the installer and select the appropriate option. On the dialog titled "Adjusting your PATH environment", we recommend you choose the option labeled "Use Git from the Windows Command Prompt". This will allow RStudio to work with Git out of the box. We teach Python, not R, in this course, but R is frequently used in computational genomics as well, including for RNAseq analysis.

This will provide you with both Git and Bash in the Git Bash program.

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.


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 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 You will need a supported web browser (current versions of Chrome, Firefox or Safari, or Internet Explorer version 9 or above).


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

Mac OS X

For OS X 10.9 and higher, install Git for Mac by downloading and running the most recent "mavericks" installer from this list. 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 (10.5-10.8) use the most recent available installer labelled "snow-leopard" available here.


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.

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.


nano is a basic editor and the default that instructors use in the workshop. To install it, download the Software Carpentry Windows installer and double click on the file to run it. This installer requires an active internet connection.

Others editors that you can use are Notepad++ or Sublime Text. Be aware that you must add its installation directory to your system path. Please ask your instructor to help you do this.

Mac OS X

nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.

Others editors that you can use are Text Wrangler or Sublime Text.


nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.

Others editors that you can use are Gedit, Kate or Sublime Text.


Python is a popular language for research computing, and great for general-purpose programming as well. Installing all of its research packages individually can be a bit difficult, so we recommend Anaconda, an all-in-one installer.

Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.7 is fine).

We will teach Python using the Jupyter notebook, a programming environment that runs in a web browser. For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9 and below, are not).


Video Tutorial
  1. Open with your web browser.
  2. Download the Python 3 installer for Windows.
  3. Install Python 3 using all of the defaults for installation except make sure to check Add Anaconda to the system PATH environment variable and Make Anaconda the default Python.


Video Tutorial
  1. Open with your web browser.
  2. Download the Python 3 installer for OS X.
  3. Install Python 3 using all of the defaults for installation.


  1. Open with your web browser.
  2. Download the Python 3 installer for Linux.
    (The installation requires using the shell. If you aren't comfortable doing the installation yourself stop here and request help at the workshop.)
  3. Open a terminal window.
  4. Type
    bash Anaconda3-
    and then press tab. The name of the file you just downloaded should appear. If it does not, navigate to the folder where you downloaded the file, for example with:
    cd Downloads
    Then, try again.
  5. Press enter. You will follow the text-only prompts. To move through the text, press the space key. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).
  6. Close the terminal window.

Once you are done installing the software listed above, please go to this page, which has instructions on how to test that everything was installed correctly.