Educators:
Wolfgang Huber, Mike Smith, Vincent J. Carey, Laurent Gatto, Robert Gentleman, Martin Morgan, Johannes Rainer, Lori Shepherd, Charlotte Soneson, Levi Waldron Simone Bell (HD-HuB)

Date:
21 to 26 July 2019

Location:
Brixen, Italy

Contents:
The one-week intensive course Statistical Data Analysis for Genome-Scale Biology 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).

Learning goals:
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.

Prerequisites:
The course is intended 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.

Keywords:
Statistics, biology, RNASeq, Bioconductor, R, RStudio human genetics.

Tools:
R / Bioconductor