News: Course announcement: CSAMA 2015 (13th ed.) Statistics and Computing in Genome Data Science
gravatar for Wolfgang Huber
4.3 years ago by
EMBL European Molecular Biology Laboratory
Wolfgang Huber13k wrote:

CSAMA 2015 (13th edition)
Statistics and Computing in Genome Data Science
Bressanone-Brixen, Italy (South Tyrol Alps)
June 14-19, 2015

Registration for CSAMA 2015 is now open


  • Martin Morgan, Fred Hutchinson Cancer Research Center (USA)
  • Wolfgang Huber, European Molecular Biology Laboratory
  • Vincent J. Carey, Channing Laboratory, Harvard Medical School (USA)
  • Michael Love, Dana Farber Cancer Institute and the Harvard School of Public Health (USA)
  • Simon Anders, European Molecular Biology Laboratory
  • Mark Robinson, University of Zurich (CH)
  • Laurent Gatto, University of Cambridge (UK)
  • Paul Pyl, University of Copenhagen (DK)

The one-week intensive course “Statistics and Computing in Genome Data Science” 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). The course covers the primary analysis (“preprocessing”) of high-throughput sequencing based assays in functional genomics (transcriptomics, epigenetics, etc.) as well as integrative methods including efficiently operating with genomic intervals, statistical testing, linear models, machine learning, bioinformatic annotation and visualization. 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 Bioconductor
  • Elements of statistics: hypothesis testing, multiple testing, regression, regularization, clustering and classification (machine learning), visualization
  • Computing with sequences and genomic intervals
  • RNA-Seq data analysis and differential expression
  • ChIP-Seq and epigenetics
  • Integrating DNA variant calls with functional data, and large-scale efficient computation with genomic intervals
  • Working with annotation – genes, genomic features and variants
  • Metagenomics and proteomics primers
  • Single-cell RNA-Seq primer
  • Interactive displays with Shiny

The course consists of

  • morning lectures: 20 x 45 minutes: Monday to Friday 8:30am - 12:00am
  • 4 practical computer tutorials in the afternoons (2pm - 5pm) on Monday, Tuesday,Thursday and Friday


Visit our website at:


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