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Description:The course will present intermediate to advanced R programming using the object-oriented programming paradigm. It will cover how to document code and data to produce a fully functional R package. Further information is available.
The Course Web Site providing links to the course materials is here.
Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.
Target audience:
- Our courses are open to all who might benefit
- Booking priority is given to people from Cambridge University and Collaborating Institutes
- Individual Course fees are required only from External participants not from Collaborating Institutes
Duration:One full day session
Sessions:
Number of sessions: 1
| Date | Time | Venue | Trainer |
|---|---|---|---|
| Wed 19 Jun | 09:30 - 17:30 | Department of Genetics, Room G12 | Robert Stojnic , Laurent Gatto |
Format:Presentation and demonstrations
Frequency:A number of times per year
Prerequisites:
- Only attending Bioinformatics: Introduction to R would not provide sufficient background for this course
- A substantial period of active programming experience in R will be assumed
- Familiarity with object-oriented programming and Latex would be an advantage, but not essential
Aims:
- To help users advance their R programming skills to be able to begin writing object-oriented code and/or developing R packages
Topics covered:
- Introduction: what is object-oriented programming; description of the working example; R programming best practices: tips and tricks, environments, coding standards
- R object-oriented programming: the S3 and S4 OO systems
- Documentation: documenting functions, methods and data, providing executable examples; documentation using Roxygen; executing R code inside Latex document (Vignettes)
- Writing R packages: minimum package structure; combining the written classes/generics/methods and documentation to create a package; building, checking and installing packages
- Other advanced R programming topics: testing code, unit testing; profiling and debugging; calling C code inside R
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