The one-week intensive course Statistical Data Analysis for Genome-Scale Biology teaches statistical and computational data analysis of multi-omics studies in biology and biomedicine. It comprises lectures covering underlying theory and state of the art, and practical hands-on exercises based on the R / Bioconductor environment. 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 skills, see below for some links.
- 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 – bulk and single cell
- Computing with sequences and genomic intervals
- Working with annotation – genes, genomic features, variants, transcripts and proteins
- Gene set enrichment analysis
- MS-based proteomics and metabolomics
- Basics of microbiome analysis
- Experimental design, batch effects and confounding
- Reproducible research and workflow authoring with R markdown
- Package development, version control and developer tools
- Working with large data: performance parallelisation and cloud computing
The course consists of
- Morning lectures: 20 x 45 minutes: Monday to Friday 8:30 – 12:00
- Practical computer tutorials in the afternoons: Mon, Tue, Thu, Fri 13:30 – 16:30
- Evening sessions: Mon, Tue 20:30-22:00
- A hike in the mountains and networking opportunity: Wed 14:30 – 22:00
Download the course materials for the labs.
Download the course materials for the lectures.
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 and Bioconductor installed: R-3.5.x and Bioconductor 3.6 installed (details will be provided). Please make sure that your computer’s hardware is sufficiently powered (>8 GB RAM, > 2 GB free disk space) and that you have administrator rights. The course material will be provided by a local network wireless network – however, this not connected to the internet. Please set up your computer beforehand; internet connections at the course venue can be slow and unreliable.
One of the afternoons is for a joint cultural and outdoors activity. We plan a guided tour at one of the Brixen area’s impressive cultural / historical sites and, weather permitting, a trip into the mountains with a (light) walk in the high-alpine area and delicious local dinner.
2:55 pmWe meet at “Casa della Gioventù” and walk 1 min to the bus waiting for us in Via Dante.
Please take the underpass to cross “Via Peter Mayr.”
3:00 pmThe bus leaves towards the cable car for Mount Plose.
3:30 pmThe cable car takes us to the top of Mount Plose in about 20-30 min.
45-60 minHiking to RossAlm at 2200 m altitude.
6:00 pmSocial dinner at RossAlm.
8:00 pmTime to leave! We walk back to the bus from RossAlm.
9:00 pmThe bus takes us back to Brixen.
- Solid footwear (ideal: hiking shoes or boots)
- Jacket or warm sweater for the descent (it may get quite fresh)
If you don’t attend the social programme, please let us know at the latest on Monday 9th July via email to simone.bell [at] embl.de
No Internet Access
Please note: The course venue does not provide stable internet access. The course provides a local network with the course material.