Jan 31–Feb 1, 2019
9:00 am - 4:30 pm
Instructors: Neal Davis, Jessica Holmes, Jenny Drnevich
Helpers: Ghana Challa, Samniqueka Halsey, Kavya Kannan
The focus of this two-day workshop is on working with genomics data and data management and analysis for genomics research. It covers data management and analysis for genomics research including: best practices for organization of bioinformatics projects and data, use of command line utilities, use of command line tools to analyze sequence quality and perform variant calling, connecting to and using cluster computing resources, and R for data analysis and visualization.
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: 607 Institute for Genomic Biology. Get directions with OpenStreetMap or Google Maps.
When: Jan 31–Feb 1, 2019. 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 organisers 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.
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, and the home units of each of our instructors.
Contact: Please email training@cse.illinois.edu for more information.
Surveys
Please be sure to complete these surveys before and after the workshop.
| Morning | Data organization for genomics |
| Morning | Introduction to the command line |
| Afternoon | Wrangling genomics data |
| 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.
Supplementary materials for the workshop are available at go.illinois.edu/dc-genomics-supp.
add, commit, ...status, diff, ...clone, pull, push, ...wherejoinTo 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.
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
(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.
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.
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.