Sep 27–28, 2018
9:00 am - 4:30 pm
Instructors: Jenny Drnevich, Samniqueka Halsey, Jessica Holmes
Helpers: Neal Davis
Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. 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 "Good Enough 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.
When: Sep 27–28, 2018. Add to your Google Calendar.
Requirements: Participants may bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on OR they may use one of the PCs in the computer lab. If bringing a laptop, 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:
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 (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email email@example.com for more information.
Acknowledgments: Local Software Carpentry and Data Carpentry workshops are made possible by the generous support of Computational Science and Engineering, Technology Services, the National Center for Supercomputing Applications, HPCBio at the Roy J. Carver Biotechnology Center with support through the Office of the Vice Chancellor for Research, the Deloitte Center for Business Analytics at the Gies College of Business, and the home units of each of our instructors.
Please be sure to complete these surveys before and after the workshop.
|Morning||Data organization for genomics|
|Morning||Data analysis with R for genomics|
|Afternoon||Data visualization with R for genomics|
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
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 and a spreadsheet program such as Microsoft Excel or LibreOffice.
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.
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.
Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.
The default shell in all versions of macOS is Bash, so no
need to install anything. You access Bash from the Terminal
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
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 macOS 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 Data Carpentry Windows installer and double click on the file to run it. This installer requires an active internet connection.
nano is a basic editor and the default that instructors use in the workshop. See the Git installation video tutorial for an example on how to open nano. It should be pre-installed.