Quarto (RMarkdown)

In the two day WGS course you will be introduced to the basics of starting an R Project in RMarkdown: how to setup a decent file structure, how to import data and how to process them and how to export the results. Some example data will be used but it will also be possible to work on your own data. The course will have many practical assignments.

Requirements: knowledge about R, e.g. the VLAG course “Introduction to R” by Jos Hageman or the PE&RC course “Ïntroduction to R and R Studio”.

What is open science?

Open Science is the movement to make scientific research and data accessible to all. With Open Science decisions in experimental design, data collection, data processing, statistical analysis, and reporting should be transparent and reproducible for everybody. It is basically the old idea that scientific results should be reproducible by everyone and open to criticism.

What is the problem?

Many PhD students and other researchers use tools like Excel or SPSS to collect & store data from their experiments. They even use it for calculations and visualizations. Finally, results are transferred to Word for writing a paper and/or PowerPoint for creating a presentation. What is eventually communicated to the outside world as a final product in the form of a thesis, paper or presentation is hard to unravel for an outsider, let alone to reproduce it. In the process of transferring data, graphs, results of statistical analysis from one software program to another, it is not unlikely that errors will be made and some of them will go unnoticed (see this publication in Nature: d41586-022-00563-z.pdf (nature.com)). The results have become irreproducible and the scientific path has become obscured (even for yourself and your team). Commercial software programs may not be accessible to everyone and therefore results may never be reproducible. This goes against the idea of open science.

RMarkdown

RMarkdown is a freely available software program that combines text, statistical analysis, and graphics into one file. Data storage, analysis, and presentation of results (in a paper or presentation) takes places in a single computer program. This has advantages like e.g. changes in a dataset are immediately processed in statistical models, graphs and reports. Workflows in RMarkdown can be considerably more efficient and therefor faster. Multiple RMarkdown files (e.g. each file being a paper) can easily be combined to form a thesis. RMarkdown documents can be converted into:

• Html pages
• Word files
• Pdf
• E-books
• Websites
• Presentation slides

The core of RMarkdown is the freely available software program R that runs on every computer platform. In practice, it is most convenient to use RStudio, also freely available. RStudio can be linked to version control systems like GIT and GITHub. In fact, you can use RMarkdown in RStudio just as a word processor without any knowledge of R but its strength is, of course, the combination of text with data processing, statistical analysis, graphing and reporting, so in practice it only makes sense if you master R to some extent.

The course will also pay attention to the newest software development from Rstudio, namely a tool called Quarto. It has the same purpose as Rmarkdown, namely to integrate text, calculations, graphics, tables and bibliographies. Quarto has more possibilities and is more user-friendly than Rmarkdown. Next to R, Quarto can also work with Python and Julia, but the course will only pay attention to R applications. Therefore, basic knowledge of R is required. Like Rmarkdown, Quarto has many output options: html, pdf, e-book, presentations (ppt, revealjs), books, documents, reports, blogs, theses. In short, Quarto is yet another step forward in achieving Open Science, a tool every PhD student and postdoc should know about!

General Information

Target Group:	PhDs, postdocs
Group size:	max. 20 participants
Course duration:	2 days
Language:	English
Credit points:	0.6 ECTS
Self-study hours:
Name lecturer:	Jos Hageman (Biometris) and Tiny van Boekel (FQD)
Venue:	to be announced

 

Fee

Reduced fee: • PhD candidates of Wageningen University with an approved Training and Supervision Plan (TSP) who are registered at one of the WU graduate schools (EPS, PE&RC, VLAG, WASS, WIAS, WIMEK) • Postdocs of Wageningen University who are registered at one of the WU graduate schools	€ 160
University fee: All other PhD candidates / Wageningen University postdocs and staff	€ 320
External fee: All other participants	€ 640

Fee includes study and training material, coffee/tea and lunches.

Cancellation condition

You may cancel free of charge up to four weeks before the start of the course. After this date you will be charged the University fee. Unless:

• You can find someone to replace you in the course and supply the course coordinator with the name and contact information of your replacement.
  In this case you will only be charged a € 50,- cancellation fee.
• You (PhDs and postdocs of Wageningen University) have a valid reason to cancel (illness or death in the family 1st or 2nd degree).
  In this case you will be charged the reduced fee and your supervisor/PI must send a mail indicating the reason for cancellation.

Information 

For more information please contact Yvonne Smolders (yvonne.smolders@wur.nl)