CSAMA 2018 (16th edition)
Statistical Data Analysis for Genome Scale Biology
Bressanone-Brixen, Italy (South Tyrol Alps)
July 8-13, 2018
Lecturers:
- Vincent J. Carey, Harvard Medical School
- Laurent Gatto, University of Cambridge
- Robert Gentleman, 23andMe, Mountain View
- Laleh Haghverdi, European Molecular Biology Laboratory (EMBL), Heidelberg
- Wolfgang Huber, European Molecular Biology Laboratory (EMBL), Heidelberg
- Michael I. Love, University of North Carolina-Chapel Hill
- Martin Morgan, Roswell Park Comprehensive Cancer Center, Buffalo
- Johannes Rainer, European Academy of Bozen (EURAC)
- Charlotte Soneson, University of Zurich
- Levi Waldron, CUNY School of Public Health at Hunter College, New York
Teaching Assistants:
- Simone Bell, EMBL, Heidelberg
- Vladislav Kim, EMBL, Heidelberg
- Lori Shepherd, RPCCC, Buffalo
- Mike L. Smith, EMBL, Heidelberg
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.
Topics include:
- Introduction to R and Bioconductor
- The elements of statistics: hypothesis testing, multiple testing, regression, regularization, clustering and classification, parallelization and performance (machine learning), visualisation
- RNA-Seq data analysis
- Computing with sequences and genomic intervals
- Working with annotation – genes, genomic features, variants, transcripts and proteins
- Gene set enrichment analysis
- Mass spec proteomics and metabolomics
- Basis of microbiome analysis
- Experimental design, batch effects and confounding
- Reproducible research and workflow authoring with R markdown
- Package development, version control and developer tools (incl. git, github, RStudio)
- Working with large data: performance parallelisation and cloud computing
The course consists of
- morning lectures: 20 x 45 minutes: Monday to Friday 8:30h – 12:00h
- 4 practical computer tutorials in the afternoons (13:30h – 16:30h) on Monday, Tuesday, Thursday and Friday
Visit the course’s website at: http://www.huber.embl.de/csama