R is a programming language, very good for statistics and for operating with huge datasets. As the community of R users and developers is growing fast, probably you'll find helpful tools for your favorite kind of analysis. If not, you can develop them yourself. Microarray-based gene expression and snp analysis, next generation sequencing and many other biological experiments may be analyzed with R.
This course consists of two parts:
If you have already some R experience, please check printouts and problem sets. If you can solve them all, spend Tuesday morning on something more profitable to you. This course is NOT about: statistics, gene expression etc. If you are not familiar with them, the very basics will be covered, but do not expect anything extensive.
We will meet all together once a week, on Tuesdays, at 9.30 in the lecture hall, for one hour. However, learning a language requires practicing it - so you should solve problem sets, posted for each course day.
I will post also solutions (in a separate file, so you won't be tempted).
In case of doubts and questions you can email me or come to my office on Friday morning.
Bring with you a laptop with installed R (see installation help). Check information about a given meeting - if there is a dataset posted, package to install sugested, download it before the course. Take printouts with you.
I strongly suggest also to go trough R tutorials (see tutorials) or just use them as a reference.