An Introduction to Solving Biological Problems with R BeginnersPrerequisites
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.
- 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
- 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 | Mon 16 Feb 2015 09:30 - 17:30 | 09:30 - 17:30 | Bioinformatics Training Room, Craik-Marshall Building | map | Robert Foy, John Davey |
| 2 | Tue 17 Feb 2015 09:30 - 17:30 | 09:30 - 17:30 | Bioinformatics Training Room, Craik-Marshall Building | map | Robert Foy, John Davey |
- 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
- 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
Two full day sessions
A number of times per year
- An Introduction to R: Software For Statistical Analysis [Provided by Graduate School of Life Sciences]
- Bioinformatics: R object-oriented programming and package development [Provided by Graduate School of Life Sciences]
- Bioinformatics: Microarray Analysis with Bioconductor [Provided by Graduate School of Life Sciences]
- Bioinformatics: Analysis of High-throughput sequencing data with Bioconductor [Provided by Graduate School of Life Sciences]
Booking / availability