Microbiome data science and multi-omics with R/Bioconductor
Oulu, September 2026
2026-04-23
1 Course overview
Contents and learning goals: The course will provide a gentle introduction to multi-omic data analysis with R/Bioconductor, a popular open source environment for scientific data analysis. Participants get an overview of the reproducible data analysis workflow and learn to use standardized data containers that support the integration and analysis of biomedical data. After the course you will know how to approach new tasks in biomedical data analysis by utilizing available documentation and R/Bioconductor tools.
Target audience: MSc students, PhD, postdoctoral, and other researchers who wish to learn new skills in statistical programming and data analysis. Academic students and researchers from Finland and abroad are welcome and encouraged to apply.
Teaching material: We will follow open online documentation created by the course teachers, primarily the Orchestrating Microbiome Analysis (OMA) book. The training material walks you through the standard steps of omics data analysis covering data access, exploration, analysis, visualization, and reproducible workflows. Preparatory material and video clips, and online support are available before the course. All teaching material will be shared openly.
1.1 Schedule
The course is organized in a live format.
Venue: University of Oulu. September 28-30, 2026 (Mon-Wed).
Accommodation: Housing tips can be found at https://visitoulu.fi/en/arrival-overnight/.
Schedule: Contact teaching daily between 9am – 4pm, including lectures, demonstrations, hands-on sessions, and breaks.
- 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)
For a detailed schedule, see Section 2.
1.2 Instructions for registration
Fee: Course is free of charge for participants having a study right in University of Oulu and for doctoral researchers in Universities belonging to Doctoral+ affiliate network (Aalto University, Hanken School of Economics, University of Eastern Finland, University of Jyväskylä, University of Lapland, LUT University, University of Oulu, Tampere University, University of Turku, University of Vaasa, Åbo Akademi). Other participants are asked to apply for non-degree study right that involves an enrolment fee of 40e. Participants are expected to cover their own travel and accommodation.
Participants having a study right to University of Oulu can register directly in PEPPI to Microbiome data science and multi-omics with R/Bioconductor under course code DP00BE40.
Doctoral researchers with a study right in University belonging to Doctoral+ affiliate network can register through https://www.doctoralcourses.fi/.
Otherwise, participants are asked to apply for a non-degree study right. Please email anna.kaisanlahti@oulu.fi for further instructions.
Registration for the course is open 1.5.–31.5.2026. Enrolment is confirmed in June.
1.3 Teachers and organizers
Teachers: Leo Lahti is the main teacher and Professor in Data Science at the University of Turku. Tuomas Borman is a co-teacher and Anna Kaisanlahti is a coordinator . The course is organized by Health and Biosciences Doctoral Programme (HBS-DP) University of Oulu Graduate School, Research Unit of Clinical Medicine, University of Oulu. The Finnish IT Center for Science (CSC) supports the course by providing cloud computing services.
1.4 Code of Conduct
The Bioconductor community values an open approach to science that promotes the
- sharing of ideas, code, software and expertise
- collaboration
- diversity and inclusivity
- a kind and welcoming environment
- community contributions
More details on its enforcement are available here.
1.5 Acknowledgments
Citation: We thank all developers and contributors who have contributed open resources that supported the development of the training material. Kindly cite the course material as Tuomas Borman and Leo Lahti (2026).
Contact: Refer to https://microbiome.github.io.
License and source code:
All material is released under the open CC BY-NC-SA 3.0 License and available online during and after the course, following the recommendations on open teaching materials of the national open science coordination in Finland.