CSAMA 2016 Statistics and Computing in Genome Data Science

CSAMA 2016 (14th edition)
Statistics and Computing in Genome Data Science
Bressanone-Brixen, Italy (South Tyrol Alps)
July 10-15, 2016


  • Simon Anders, Institute for Molecular Medicine, Helsinki
  • Jennifer Bryan, University of British Columbia, Vancouver
  • Vincent J. Carey, Channing Laboratory, Harvard Medical School
  • Wolfgang Huber, European Molecular Biology Laboratory (EMBL), Heidelberg
  • Michael Love, Dana Farber Cancer Institute and the Harvard School of Public Health
  • Martin Morgan, Roswell Park Cancer Institute, Buffalo, New York.
  • Charlotte Soneson, University of Zurich
  • Levi Waldron, CUNY School of Public Health at Hunter College, New York

Teaching Assistants:

  • Simone Bell, EMBL, Heidelberg
  • Alejandro Reyes, EMBL, Heidelberg
  • Mike L. Smith, EMBL, Heidelberg

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 of high-throughput sequencing based assays in functional genomics and 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
  • Integrating multiple layers of ‘omic data
  • Working with annotation – genes, genomic features and variants
  • RNA-Seq data analysis and differential expression
  • Single-cell RNA-Seq
  • Proteomics primers
  • Interactive displays with Shiny

The course consists of

  • morning lectures: 20 x 45 minutes: Monday to Friday 8:30h – 12:00h
  • 4 practical computer tutorials in the afternoons (14:00h – 17:00h) on Monday, Tuesday, Thursday and Friday

The registration for CSAMA 2016 closed on June 15th 2016

Visit the course’s website at: http://www.huber.embl.de/csama