The course provides a gentle introduction to microbiome and multi-omic data science with R/Bioconductor, focusing on:
reproducible data analysis workflows
standardized data containers for biomedical data integration
how to approach new analysis tasks using documentation + existing tools
Instructors and organizers
Instructors: Leo Lahti, Tuomas Borman Coordinator: Anna Kaisanlahti Organizers: HBS-DP (University of Oulu Graduate School) Computing support: CSC (cloud services)
Target audience
For MSc students, PhD candidates, postdocs, and researchers who want to build skills in:
statistical programming in R
omics data analysis and visualization
reproducible reporting
Learning goals
After the course, you will be able to:
use Bioconductor data infrastructure for omics data analysis
work with standardized containers for single-omics and multi-omics
build reproducible workflows with Quarto
continue learning independently using the OMA documentation
Day 1: Reproducible workflows with R/Bioconductor and Quarto Day 2: Tabular data analysis (working with single ’omics) Day 3: Multi-assay data integration (multi-omics methods)
Day 1 — Open data science
Day 1 — Open data science
Time
Activity
9:00–10:00
Coffee, welcome & practicalities
10:00–11:00
Introduction to CSC RStudio notebook
11:00–12:00
Lecture: open & reproducible workflows
12:00–13:00
Lunch break
13:00–16:00
Working with data containers and workflows
Evening
Informal course dinner (own cost)
Learning goals
Understand principles of open & reproducible microbiome/omics analysis
Become familiar with the Bioconductor ecosystem
Learn the role of standardized data containers for omics data
Microbiome research
Microbiome: community of microbes and their genes in certain habitat (e.g., human gut)
Vital role
Data typically sequencing profiles, along with additional molecular layers
