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Thu 6 Mar - Fri 7 Mar 2014
09:30 - 17:30

Venue: Department of Genetics, Room G12

Provided by: Graduate School of Life Sciences


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Bioinformatics: An Introduction to Solving Biological Problems with R

Thu 6 Mar - Fri 7 Mar 2014


This course provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented. Further information is available here.

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 or register Interest by linking here.

Target audience
  • No prior knowledge of R, or of programming in general, will be assumed
  • Some familiarity with command line UNIX would be an advantage but not essential

Number of sessions: 2

# Date Time Venue Trainers
1 Thu 6 Mar 2014   09:30 - 17:30 09:30 - 17:30 Department of Genetics, Room G12 map David Molnar,  Ines de Santiago
2 Fri 7 Mar 2014   09:30 - 17:30 09:30 - 17:30 Department of Genetics, Room G12 map David Molnar,  Ines de Santiago
Topics covered (session 1)
  • R environment
  • Informal introduction to R basics
  • Introducing R data objects
  • Understanding data types
  • Manipulating data in R
  • Basic build-in function for data manipulation
  • Loops and branching as useful data handling technique
  • A guide to using R for everyday data analysis
  • Reading and writing data tables
  • Data manipulation
  • Starting out with statistical tests
Topics covered (session 2)
  • Data analysis and R automation with examples
  • Data analysis 'Stepwise'. Interactive R scripting
  • Structuring an R progam'
  • Functions as procedures
  • Functions with arguments
  • Advanced data analysis and integration
  • Basic R graphics
  • High level plotting functions
  • Customized plotting functions

To enable bench scientists with no previous programming background to perform simple statistical analyses with R


Presentations, demonstrations and practicals


Participants may find it useful to look over the R tutorial from the computational biology group, Department of Oncology




A number of times per year

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