Introduction to Reproducible Publications with RStudio

Participants will build on their research and analytical skills with R Studio by learning how to create reproducible documents that combine code, analysis and narrative. RStudio makes it possible to work on a complete research project in a more efficient, integrated and organized manner: from data upload, cleaning, and analysis, to writing and styling a manuscript in R Markdown. It allows users to add code, figures, citations, and bibliography, as well as to generate outputs in various formats (e.g., html, pdf, doc). Rstudio also connects with Git and Github and learners will have a chance to experiment with this integration and understand its advantages for collaboration and version control. This workshop will involve lectures and demos alternating with hands-on exercises and challenges, so by the end of the workshop, learners will have “authored” a reproducible paper of your own with the data and narrative we provide.

Prerequisites:

Experience in R/RStudio is recommended but not required. Experience, if not, familiarity, with using Version Control with Git is required. You will need a GitHub Account to pull the example repo.

Schedule

	Setup	Download files required for the lesson
00:00	1. Scientific reproducibility: What is it for?	What is reproducible research? How can RStudio help research to be more reproducible? What are the benefits of using RStudio for writing academic essays and papers?
00:20	2. Navigating RStudio and R Markdown Documents	How do you find your way around RStudio? How do you start an R Markdown document in Rstudio? How is an R Markdown document configured and how do I work with it?
00:50	3. Introduction to Working with R Markdown Files	What is the breakdown of an R Markdown file? What are templates in R Markdown? How can you render the input file to the specified output format? How can you find existing templates for R Markdown files?
01:15	4. Good Practices for Managing Projects in RStudio	What are good research project management practices? What is an R Project file? How do you start a new or open an existing R Project? How do you use version control to keep track of your work?
01:55	5. Getting Your project set up with Version Control in RStudio	How do I start or continue a project with Git versioning? What are the features in the RStudio Interface for working with Git? What are the basics of the Git versioning workflow?
02:35	6. Writing and Styling Rmd Documents	What is the Visual Editor in Rstudio? Which features does the Visual Editor have? How can I can apply styling and formatting to Rmd documents in Rstudio more easily? How to add inline code?
02:55	7. Adding Code-Generated Plots and Figures	What is Knitr? What are code chunks and how they are structured? How can you run code from your rmd document? What are global knitr options? What are global chunk options?
04:05	8. Reproducible & Efficient Methods of Using Code Chunks	How do I run external scripts in an R Markdown document? How can I avoid issues with relative paths? How can I get my R Markdown document to render faster? What is inline code and when to use it?
05:15	9. Bibliography, Citations & Cross-Referencing	How can you insert citations to your manuscripts using RStudio’s visual editor? How can you change citation styles? What are the options to display cited and uncited bibliography? How can you cross-reference content?
05:50	10. Collaborating via Github	How do I authenticate with Github? How do I put my project on Github? How do I "push" my latest changes to Github ?
06:15	11. Publishing your project	What are the options for you to publish your project? What free and open publishing resources are available? What aspects should guide your choice?
06:25	Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.