Brixen, Italy

2015-06-15 ~ 2015-06-15



The one-week intensive course Statistics and Computing in Genome Data Science teaches statistical and computational analysis of multi-omics studies in biology and biomedicine. It covers the underlying theory and state of the art (the morning lectures), and practical hands-on exercises based on the R / Bioconductor environment (the afternoon labs). The course covers the primary analysis ("preprocessing") of high-throughput sequencing based assays in functional genomics (transcriptomics, epigenetics, etc.) as well as integrative methods including efficiently operating with genomic intervals, statistical testing, linear models, machine learning, bioinformatic annotation and visualization. At the end of the course, you should be able to run analysis workflows on your own (multi-)omic data, adapt and combine different tools, and make informed and scientifically sound choices about analysis strategies. The course is intended for researchers who have basic familiarity with the experimental technologies and their applications in biology, and who are interested in making the step from a user of bioinformatics software towards adapting or developing their own analysis workflows. The four practical sessions of the course will require you to follow (and hopefully, modify) scripts in the computer language R.


See the Programme for details of the course. Course material is available; a github repository contains additional resources.

Packages »

Bioconductor's stable, semi-annual release:

Bioconductor is also available via Docker and Amazon Machine Images.

Documentation »


R / CRAN packages and documentation