The course, found at the website https://r-cubed-intro.rostools.org/, is designed as a series of participatory live-coding lessons, where the instructor and learner code together, along with hands-on exercises interspersed throughout the course and a final group assignment to do a simple data analysis project. In the course we will describe the fundamentals of what an open and reproducible data analysis looks like and then create a project that applies some of the basics of these concepts using R. The learning objectives are:

1. Explain what an open and reproducible data analysis workflow is, what it looks like, and why it is important.
2. Explain and demonstrate why R is rapidly becoming the standard program of choice for doing modern data analysis in science.
3. Demonstrate and apply collaborative tools and techniques when working in team settings (including working with your future self).
4. Show and apply the fundamental tools and skills for conducting a reproducible and modern analysis for a research project.
5. Show where to go to get help and to continue learning modern data analysis skills.

Because learning and coding is ultimately not just a solo activity, in addition to the group project work, during this course we also aim to provide opportunities to chat with fellow participants, learn about their work and how they do analyses, and to build networks of support and collaboration.

The course will place particular emphasis on research in diabetes, health, and metabolism; it will be (mostly) taught by instructors working in this field and it will use relevant examples where possible.

The specific software and technologies we will cover in this course are R, RStudio, Git, GitHub, and Quarto, while the specific R packages are dplyr and ggplot2 packages.

Instructors:

Luke Johnston, Team Leader, Steno Diabetes Center Aarhus (DK)

Participants will be selected based on a motivational statement provided via the registration form. We will select participants with a clear, relevant motivation.

To participate in the course, you will have to be a PhD Student or Postdoc working in the fields of diabetes, metabolism or classical endocrinology. Priority is given to participants employed at Danish research and health institutions or in the life science industry.

To help manage expectations and develop the material for this course, we make a few assumptions about who you are as a participant in the course:

• You currently or will soon do some quantitative data analysis.
• You:
  • know nothing or little about R (or computing in general);
  • haven’t used code-based programs for doing data analysis (e.g. have used SPSS);
  • have used coding programs before (e.g. used SAS or Stata), but not R;
  • or know how to use R, but haven’t used the tidyverse or RStudio.

While we have these assumptions to help focus the content of the course, if you have an interest in learning R but don’t fit any of the above assumptions, you are still welcome to attend the course!

In addition to the assumptions, we also have a fairly focused scope for teaching and expectations for learning. So this may also help you decide if this course is for you.

• We do teach how to use R, starting from the very basics and targeted to beginners.
• We do not teach statistics (these are already covered by most university curriculums).
• We do teach from a team science, reproducible research, and open scientific perspective (i.e. by including a collaborative group project that uses a transparent and reproducible analysis workflow).
• We do teach using practical, applied, and hands-on lessons and exercises, with a few short lectures that introduce a topic.

Please note that you are not guaranteed a seat at the event if you do not meet the target group requirements. Priority may be given to participants employed at Danish research and health institutions or life science industry. Early-career researchers from abroad are welcome to apply. If the event is overbooked, DDEA reserves the right to select participants based on the defined requirements.

Pre-workshop instructions:

To attend the course, you will have to complete the pre-course tasks no later than 8 January 2025.
You find the pre-course tasks here: https://r-cubed-intro.rostools.org/preamble/pre-course.html

Bring your own laptop
Make sure to bring your own laptop, since the course includes hands-on learning.

Dinner registration

DDEA organizes a networking dinner on 14 and 15 January. Participation in the dinner is free of charge. Please sign up for the dinner upon registration, and indicate whether you have any dietary requirements.

Accommodation

DDEA offers accommodation for participants living outside the Aarhus area from 14 (check in) to 16 (check out) January.

Please sign up for accommodation when you register for the event.

You will be informed about your overnight accommodation by DDEA after the registration deadline.

Certificate of Attendance
A course certificate of attendance and participation can be issued upon request at the end of the course. Full participation in the course is required to receive the certificate. Apply to your PhD school with the certificate and course programme.

Latest cancellation date & no-show fee
Please note that it is free of charge to participate in the event however the DDEA will charge a no-show fee of 1000 DKK if you do not show up and have not unregistered from the event by 8 January 2025, except in the case of illness or emergencies.