Containers for Reproducible Computational Environments (QCIF) [webinar]
This is a QCIF course and places are highly limited as Graduate School is paying the fee. If you are unable to attend, please de-register (or email graduateschool@uq.edu.au if you are unable to do so). An unexplained absence could result in all your future QCIF registrations becoming Waitlisted. You may only attend the workshop once. Repeat bookings will be removed and placed on the Waitlist.
Containers are self-contained pieces of software that allow you to run applications easily across all sorts of different computing hardware – from your laptop to your institutional high-performance computing system – without the need for a complicated installation process. Containers are also an effective way of achieving a reproducible analysis pipeline, allowing researchers to ensure that the same version of an application and consistent computational environment are used each time. This short introductory course will show you how to find and use containers in a typical research computing context.
Recommended Participants
Anyone interested in finding out more about containers and learning how to run research software from containers. Basic experience with Unix or Linux is required.
Syllabus
- What are containers, and where to find them
- How to load and run containers using Singularity
- Accessing local datafiles from a container
About Research software and programming
Library workshops
The library offers a range of workshops under the headings below including:
R with RStudio Excel for research data NVivo Pro
Useful links
- Library's software training resources
- Software carpentry: The open-source movement to teach basic lab skills for research computing.
- REDCap consortium: A secure web application for building and managing online surveys and databases. UQ is a member of the consortium
- RStudio cheat sheets
- Hacky Hour (supported by RCC, QCIF, IMB and wonderful volunteer helpers!): RCC runs consultations every Tuesday at Cafe Nano. Come and ask IT questions such as: getting started with Python and R, stats, machine learning, bio-image, software tools, research data management (RDM), how to access high performance computing, cloud data storage and tools for data cleaning and data visualisation. Bring your project's IT problems or come along as a helper! Very occasionally Hacky Hour may not run; follow us on Twitter (@HackyHourStLuc) to get the latest announcements. Aside from the usual IT research questions,
- First Tuesday of the month: Bioinformatics Hacky Hour, ask bioinformatics analysis, software and pipeline questions
- Last Tuesday of the month: BioLab Hacky Hour, ask about experimental design and technical sample processing questions to get started in the lab