| Detailed information |
| Original study plan |
Bachelor's programme Bioinformatics 2015W |
| Objectives |
The scientific computing platform (and programming language) R was originally designed for statistical analyses but has quickly emerged as a de facto standard in bioinformatics and is also rapidly becoming important in machine learning. In this regard, R is a platform of the future. Knowing R well is a great plus in statistics and machine learning, and a must in bioinformatics. The goal of this course is to provide an in-depth view of the R platform and programming language. Students should be enabled to implement and document their own R programs and packages making use of advanced concepts, such as, S4 classes and foreign language interfaces.
Students should further be made able to identify and avoid performance bottlenecks. This course is complemented by a practical introduction to applications of R in bioinformatics, mainly focussing on packages that are part of the Bioconductor project.
|
| Subject |
The course is divided into two parts:
1. The R platform and programming language
* Introduction
* The R programming language
* R graphics
* Sweave
* Object-oriented programming in R
* Foreign language interfaces
* Packaging
2. Applications in bioinformatics
* Bioconductor
* Sequence handling and alignment
* Phylogeny
* Analyzing gene expression data
* Genome analysis
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| Criteria for evaluation |
Marking is based on homework.
|
| Methods |
Slide presentations complemented by R demos
|
| Language |
English |
| Study material |
Electronic course material is made available for download
|
| Changing subject? |
No |
| Corresponding lecture |
875VINFITRK12: KV Introduction to R (3 ECTS) or BIMWNKVIRAB: KV Introduction to R with applications to bioinformatics (3 ECTS)
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