Wolfgang Huber, Mike Smith, Simone Bell, Katharina Imkeller, Britta Velten (HD-HuB) Laurent Gatto, Robert Gentleman, Martin Morgan, Johannes Rainer, Lori Shepherd, Charlotte Soneson, Davide Risso, Levi Waldron
21 to 26 June 2020
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).
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 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.
Statistics, biology, RNASeq, Bioconductor, R, RStudio human genetics.
R / Bioconductor