In contrast to the Bulk RNA sequencing used to quantify the abundance of gene and transcript expression at a whole population level, single-cell RNA sequencing (scRNAseq) allows researchers to study gene expression profile at a single cell resolution while enabling the discovery of tissue specific sub populations and markers. For example, contrasting different sample conditions i.e. disease vs. normal using scRNAseq can help identify sub-cellular differential behaviours and thus target specific gene markers. This 2-days course will cover the main technologies as well main aspects to consider while designing a scRNAseq experiment including a hands-on practical data analysis session applied to droplet-based methods.

This workshop aims to present several computer-aided drug design tools developed at SIB. Several examples are taken from different therapeutical fields. The exercises are available to a wide audience.

CAS-PMO 2018-2019

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.

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.