Computational Skills for Bioinformatics Data Analysis (Data Carpentry)

May 28-29, 2018

9:00 am - 5:00 pm

Instructors: Jason Williams, Tania Allard, Malvika Sharan

Helpers: Bérénice Batut, Danielle Quinn, Chiara Cotroneo, Benjamin Roques, TBA

General Information

Data Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. 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.

For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. Lecture hall: TBD. Get directions with OpenStreetMap or Google Maps.

When: May 28-29, 2018. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). They are also required to abide by Data Carpentry's Code of Conduct.

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:

Course materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you please get in touch (using contact details below) and we will attempt to provide them.

Registration: Please note that the course is primarily open for the academic researchers from UCD and UCD affiliated institutes. If you are from other research institute and would like to attend the course, please contact the organizers personally.


Each registration will be reviewed and applicants will be confirmed for their participation via email by the organisers.

Contact: Please email, for more information.



Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey

Day 1

Day-1 Introduction to Genomics Data, Data Organization, Unix/Shell and Cloud
09:00 Data Organization
10:30Cloud Genomics
12:00Lunch break
13:30Introduction to the command line
15:00Command line (continued)
16:30End of Day-1

Day 2

Day-2 Data Wrangling, Pipeline and R for Genomics
09:00 Data Wrangling and pipeline
10:30R for Genomics
12:00Lunch break
13:30R for Genomics (continued)
15:00Open session
16:30End of Day-2

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


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...


To participate in a Data Carpentry workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful 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.


  1. Download and install PuTTY for Windows .


The default shell in all versions of macOS is Bash, so no need to install anything. You access Bash from the Terminal (found in /Applications/Utilities). See the Git installation video tutorial for an example on how to open the Terminal. 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.


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


Video Tutorial

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.


Video Tutorial

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


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 dnf install R). Also, please install the RStudio IDE.

Course Affiliations