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.
This course is designed to provide researchers in biomedical sciences with experience in the application of basic statistical analysis techniques to a variety of biological problems.
The course will combine lectures on statistics and practical exercises. The participants will learn how to work with the widely used "R" language and environment for statistical computing and graphics.
Topics covered during the course include: reminders about numerical and graphical summaries, and hypothesis testing; multiple testing, linear models, correlation and regression, and other topics. Participants will also have the opportunity to ask questions about the analysis of their own data.
With a constant evolution of technologies, laboratory biologists are faced with an increasing need of bioinformatics skills to deal with high-throughput data storage, retrieval and analysis.
Although several resources developped for such tasks have a web interface (most of the time, the first choice of biologists), many operations can be more efficiently handled with command lines (CLI).
During the first part of this workshop, researchers and professionals
involved in Big Data management at VitalIT/SIB as well as in Data
Management Plan preparation at UNIL/CHUV will teach you best practices
in data management and how to collect, describe, store, secure and
archive research data. You will be introduced to the need for a Data
Management Plan (DMP) preparation, an evolving document reporting how
the research data will be managed during and after a research project.
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.
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.