R is a complete and flexible system for statistical analysis which has become a tool of choice for biologists and biomedical scientists, who need to analyze and visualize large amounts of data. One reason for this success is the availability of many contributed packages, which are available freely and can be installed and run directly from R. In bioinformatics, in particular, most published papers include a link to an R package implementing the methods described in the article. This "First Steps with R" course is addressed to beginners wanting to become familiar with the R environment and master the most common commands to be able to start exploring their own datasets.

The course will focus on learning and internalizing the practices of unit testing, refactoring, and version control through hands-on experience. The first morning will start with an introduction into these concepts and tools used to support them. In the afternoon, we will transition to a code clinic and work together in small groups applying these practices to make improvements to code brought by participants. The second day will continue with the code clinic.

The aim of this course is to familiarise the participants with long read (also called “third generation”) sequencing technologies, their applications and the bioinformatics tools used to assemble this kind of data. Multiple sequencing platforms, including Pacific Biosciences and Oxford Nanopore MinION, are now available to generate reads that are several kilobases-long. It is also possible to assemble Illumina reads to generate in-silico long reads. These improvements have greatly facilitated the assembly of genomes but some other applications are emerging, for example, for haplotype phasing, or for the study of alternative splicing using RNA-seq.

This course will be composed of an introduction to the techniques and data analysis methods, a minisymposium and a hands-on session. The minisymposium will consist of short presentations by SIB researchers on the applications of these technologies. It will be followed by a panel discussion between speakers and the audience, letting the opportunity to debate on the advantages and pitfalls of these technologies for research projects. The hands-on session will consist of computer exercises that will enable the participants to familiarize with real datasets from different technologies and the bioinformatics tools to assemble genomes.

Several research groups are dealing with very sensitive human data, and learning how to properly manage them, from acquisition to storage and sharing, has become urgent.
This course will introduce the general steps needed to avoid public leaks of sensitive data, protecting by the same time your reputation and that of your institution. The course will cover best practices for the management of sensitive human data, from the technical aspects of how the data should be stored and shared, to practical guidelines of how to manage such data in an an analysis setting.