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Mon 16 Feb - Tue 17 Feb 2015
09:30 - 17:30

Venue: Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Provided by: Bioinformatics


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An Introduction to Solving Biological Problems with R
BeginnersPrerequisites

Mon 16 Feb - Tue 17 Feb 2015

Description

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
  • Graduate students, Postdocs and Staff members from the University of Cambridge and Affiliated Institutions
  • Graduate students, Postdocs and Staff members from all other external Institutions
  • Individual Course fees are required only from external participants not from Affiliated Institutions
  • Further details regarding eligibility criteria are available here
  • Further details regarding the charging policy are available here
Prerequisites
  • 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
Sessions

Number of sessions: 2

# Date Time Venue Trainers
1 Mon 16 Feb 2015   09:30 - 17:30 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site map Robert Foy,  John Davey
2 Tue 17 Feb 2015   09:30 - 17:30 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site map Robert Foy,  John Davey
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
Aims

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

Format

Presentations, demonstrations and practicals

Notes

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

Duration

Two full day sessions

Frequency

A number of times per year

Related courses
Theme
Core skills

Booking / availability