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Mon 11 Apr 2016
09:30 - 17:30

Venue: Bioinformatics Training Room

Provided by: Bioinformatics


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R object-oriented programming and package development

Mon 11 Apr 2016


The course will teach intermediate R object-oriented programming and how to build a fully functional R package.

The course page includes slides and handouts; other relevant teaching materials are available here) and the sequences example package used as template in the course can be found here.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book register Interest by linking here.

Target audience
  • Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
  • Further details regarding eligibility criteria are available here
  • Further details regarding the charging policy are available here
  • A good knowledge of R and some active programming experience is required.
  • Only attending Introduction to R would not provide sufficient background for this course.
  • Familiarity with object-oriented programming would be an advantage, but is not essential.

Number of sessions: 1

# Date Time Venue Trainers
1 Mon 11 Apr 2016   09:30 - 17:30 09:30 - 17:30 Bioinformatics Training Room map Robert Stojnic,  Laurent Gatto

After this course you should be able to:

  • use object-oriented programming in R and build your own packages

During this course you will learn about:

  • 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 *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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