Material for the course about RMarkdown at ISGlobal 2017/02/02 ⌚️ 9:30-12:30
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RMarkdown course ISGlobal

In this course (note: language to be decided based on the audience), we will learn how to use RMarkdown, a powerful reporting tool in R. Instead of copy-pasting tables, figures, number of patients into Word documents, you will be able to embed the corresponding code directly in your report.

We will prepare a scientific manuscript together, including citations. We will also discuss collaboration for manuscripts written in RMarkdown.

Producing a .docx/.pdf is only one of the many things you can do with RMarkdown. Based on the RMarkdown knowledge adquired in this course, you should be able to start exploring other RMarkdown outputs. We will have a look at reveal.js which is a framework for producing slides.

All course material will live in this repository, and you're welcome to open issues.

What should I install before coming to the course?

You will need

  • R and RStudio

  • the rmarkdown package (install.packages("rmarkdown"))

  • the broom package (install.packages("broom"))

  • the revealjs package (install.packages("revealjs"))

  • the knitcitations package (install.packages("knitcitations"))

  • the citr package (install.packages("citr"))

  • the rmdTemplates package

# If you don't have devtools installed
# first install.packages("devtools")
  • the ezknitr package (install.packages("ezknitr"))

  • A tex installation (for pdf output), see this website

Don't hesitate to send me an email or come to my office (campus Mar, sala B) if you have any installation issue.

How much do I need to know about R?

You just need to know that R exists, how to load data into R, and for instance do a linear regression with R. Don't hesitate to contact me via maelle dot salmon at yahoo dot se if you're not too sure about whether you should come.

We are not going to write any advanced code in the chunks, and starting to learn RMarkdown could be of the first steps of your R journey.


Further resources

Other courses at ISGlobal

The material of the course from April 2016 about data wrangling in R with dplyr and tidyr lives here.