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). 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.
The course is intended for 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. The four practical sessions of the course will require you to follow and modify scripts in the computer language R. To freshen up your R, see below for some links.
- Introduction to Bioconductor
- Elements of statistics: hypothesis testing, multiple testing, regression, regularization, clustering and classification, parallelization and performance (machine learning), visualisation
- Reproducible research and R authoring with markdown and knitr
- RNA-Seq data analysis and differential expression
- New workflows for RNA-seq
- Computing with sequences and genomic intervals
- End-to-end RNA-Seq workflow
- Experimental design, batch effects and confounding
- Working with annotation – genes, genomic features and variants
- Visualization, the grammar of graphics and ggplot2
- Use of Git and GitHub with R, RStudio, and R Markdown
- Gene set enrichment analysis
The course consists of
- Morning lectures: 20 x 45 minutes: Monday to Friday 8:30 – 12:00
- Practical computer tutorials in the afternoons (14:00 – 17:00) on Monday, Tuesday, Thursday and Friday
You will work on the labs at your own pace in small groups with expert guidance (all lecturers from the morning sessions plus teaching assistants).
Participants are required to bring their own laptop with the most recent release versions of R (i.e. 3.3) and Bioconductor (i.e. 3.3) installed. If its hardware is sufficiently powered for ‘real work’, you will enjoy the course more. A WiFi network card is welcome to connect to our local network, however, no connections to the internet will be possible from the WLAN at the course venue.
Wednesday afternoon is for a joint cultural and outdoors activity. We plan a guided tour at one of the Brixen area’s impressive cultural / historical sites, followed by a trip into the mountains, a (light) walk in the high-alpine area and delicious local dinner.
No Internet Access
Please note: the course venue does not provide stable internet access. The course provides a local network with the course material.