Course 1. Introduction to Tidyverse
R is a popular language and environment that allows powerful and fast manipulation of data, offering many statistical and graphical options. This course aims to introduce R as a tool for statistics and graphics, with the main aim being to become comfortable with the R environment. As well as introducing core R language concepts this course also provides the basics of using the Tidyverse for data maniupulation, and ggplot for plotting. It will focus on entering and manipulating data in R and producing simple graphs. A few functions for basic statistics will be briefly introduced, but statistical functions will not be covered in detail.
Course 2. Advanced Tidyverse
The 'Tidyverse' is a set of add-in R packages for data loading, modelling, manipulation and plotting. It is an attempt to make data analysis and plotting cleaner, simpler and more consistent by addressing some poor design decisions in the original language. This course follows on from our Introduction to R with tidyverse and focusses on the manipulation and restructuring of data using the tidyverse packages. The course shows how to do complex transformations on large data structures and how to deal efficiently with data which is both large and sometimes not well behaved.
Course 3. Introduction to ggplotThis course is normally taught as part of the R with Tidyverse bootcamp. Ggplot is the most popular plotting extension to R and replicates many of the graph types found in the core plotting libraries. This course provides an introduction to the ggplot2 libraries and gives a practical guide for how to use these to create different types of graphs.
Course 4. Introduction to Core R
R is a popular language and environment that allows powerful and fast manipulation of data, offering many statistical and graphical options. This course aims to introduce R as a tool for statistics and graphics, with the main aim being to become comfortable with the R environment. It will focus on entering and manipulating data in R and producing simple graphs. A few functions for basic statistics will be briefly introduced, but statistical functions will not be covered in detail.
Course 5. Advanced Core R
This course follows on from the introductory course. It goes into more detail on practical guides to filtering and combining complex data sets. It also looks at other core R concepts such as looping with apply statements and using packages. Finally, it looks at how to document your R analyses and generate complete analysis reports.
Course 6. Plotting complex figures with Core R
This course is a comprehensive guide to the use of the built-in R plotting functionality to construct everything from customised simple plots to complex multi-layered figures. It follows on from the material in our introductory R course and participants are expected to have a basic understanding of R - enough to load and do basic manipulation of datasets.
Course 7. Introduction to Shiny
Shiny is an R package that enables interactive web applications to be built using R. They are a great way of allowing users to explore a dataset and make use of the graphical and statistical functionality of R without having to write any code.
Course 8. Using R Notebooks
This course is designed for people who are already familiar with R and are ready for a more integrated way to perform and report their analyses. It will show the use of R Notebooks for interactive analysis and then demonstrate how to apply this to the production of complete reports.
Course 9. Writing R Packages
R packages are the best way to create robust re-usable code, either for internal use or for sharing with the wider community. In this course we will look at how to write functions which are robust for use by others. We will then go through the process of authoring function based R packages with the help of the recommended development tools.
Course 10. Using git and GitHub with RStudio
RStudio has embedded tools to facilitate the use of git with RProjects. This short course explores this functionality.
Babraham Institute