Reproducible Research in R: An introductory course on modern data analyses and workflows for PhD students & Postdocs

1. Time & place
2. Who can attend?
3. Detailed description
4. Programme & speakers
5. Organisers 
6. Registration 
7. Additional information
   
   

TIME & PLACE

Dates: 22-24 June 2020
Place: Sinatur Hotel Storebælt, Østerøvej 121, 5800 Nyborg

WHO CAN ATTEND?

The course is targeted PhD students and Postdocs, who fit the assumptions:

• You are a researcher working in the fields of diabetes and metabolism.
• You currently or will soon do quantitative data analysis.
• You either:
• know nothing or little about R (or computing in general);
• haven’t used coding programs for doing data analysis (e.g. used SPSS);
• have used coding programs before (e.g. used SAS or Stata), but not R;
• know how to use R, but haven’t used the tidyverse or RStudio.

If you don’t fit the above assumptions, we reserve the right to cancel your registration.

We 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.

To further develop your R skills and knowledge, we are having an advanced R course from September 8-9, 2020 that will build off of this course (though it isn't dependent on this course). Keep an eye on DDA announcements to register and learn more about it!

DETAILED DESCRIPTION

Using a practical approach based mostly on code-along sessions (instructor and learner coding together), the course will:

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

We’ll be addressing the following questions:

• What is R, why should I use it, and how do I use it?
• What does a modern data analysis setup and workflow look like?
• What is reproducibility and how is it different from replicability?
• How can I ensure my data analysis project is reproducible?
• How can I import and work with my data in R?
• How can I visualize my data and make publication-quality figures?
• Why should I keep track of changes to my analysis files? How can I do this?
• How can I write reports to document, describe, and present analyses in a reproducible way?

Pre-workshop instructions

1. Check out the course website https://dda-rcourse.lwjohnst.com/
2. See the learning material website https://r-cubed.rostools.org/ for pre-workshop tasks and instructions (check it 2-3 weeks before the workshop).
3. Make sure to bring your own laptop, since we do hands-on learning.
4. Read and abide by the Code of Conduct found at the learning material website. 

PROGRAMME & SPEAKERS

See the tentative programme

Lead instructor and organiser:

• Luke Johnston, Postdoc, Aarhus University (DK), lwjohnst@ph.au.dk

Instructors:

• Daniel Witte, Professor, Aarhus University
• Bettina Lengger, PhD student, Technical University of Denmark
• Helene Bæk Juel, Postdoc, University of Copenhagen
  

Helpers:

• Malene Revsbech Christiansen, PhD student, University of Copenhagen
• Anders Aasted Isaksen, PhD student, Aarhus University 

ORGANISERS

Luke Johnston, Postdoc, Aarhus University, lwjohnst@ph.au.dk

REGISTRATION 

This course replaces the fully booked course we had to cancel in March. The seats were at first offered to the participants who were enrolled at the cancelled course. We have five open seats for other applicants.

Registration deadline: 10 May 2020 

Please be aware that the course will only be held if it is possible according to the COVID-19 restrictions imposed by the authorities. 

ADDITIONAL INFORMATION

Certification
A course certificate will be sent to all participants on request at the end of the course. Full participation is required to attain 2.6 ECTS points. 

No-show fee 
Please note that it is free of charge to participate in the course however the DDA will charge a no-show fee of 150 DKK if you do not show up and have not unregistered from the course prior to its start.