Multi-omic data science with R/Bioconductor
Welcome to Oulu Summer School, June 2022
This course will teach the basics of biomedical data analysis with R/Bioconductor, a popular open source environment for scientific data analysis. The participants get an overview of the reproducible data analysis workflow in modern multi-omics, with a focus on recent examples from published microbiome studies. After the course you will know how to approach new tasks in biomedical data analysis by utilizing available documentation and R tools.
The teaching will follow open online documentation created by the course teachers, extending the online book Orchestrating Microbiome Analysis (https://microbiome.github.io/OMA). The openly licensed teaching material will be available online during and after the course, following national recommendations on open education.
The training material walks you through the standard steps of biomedical data analysis covering data access, exploration, analysis, visualization, reproducible reporting, and best practices in open science. We will teach generic data analytical skills that are applicable to common data analysis tasks encountered in modern omics research. The teaching format allows adaptations according to the student’s learning speed.
The course will be organized in a live format (Flyer)
Venue University of Oulu. June 20-23, 2022.
Schedule Contact teaching daily between 9am – 5pm, including lectures, demonstrations, hands-on sessions, and breaks. A detailed schedule is available at the course website: (https://microbiome.github.io/course_2022_oulu).
Teachers and organizers
Leo Lahti is the main teacher and Associate Professor in Data Science at the University of Turku, with specialization on biomedical data analysis. Course assistants are Tuomas Borman (University of Turku) is one of the main developers of the open training material covered by the course, Jenni Hekkala, a PhD researcher at the University of Oulu, in the group of the course coordinator Docent Justus Reunanen, and Rajesh Shigdel who has supported the writing of the course material.
The course is jointly organized by
- Health and Biosciences Doctoral Programme University of Oulu Graduate School
- Cancer & Translational Medicine Research Unit, University of Oulu
- Department of Computing, University of Turku, Finland
- Finnish IT Center for Science (CSC) supports the course with cloud computing services
The course is primarily designed for advanced MSc and PhD students, Postdocs, and biomedical researchers who wish to learn and develop new skills in scientific programming and biomedical data analysis. Academic students and researchers from Finland and abroad are welcome and encouraged to apply. The course has limited capacity of max 20 participants, and priority will given for local students from Oulu.
Expected background Some earlier experience with R or another programming language is recommended. However, this can be compensated by familiarizing with the course material in advance, if necessary. The teaching format allows adaptations according to the student’s learning speed.
- Send a brief motivation letter to Jenni Hekkala email@example.com
- Applications sent before May 20 will be given priority
The course fee covers contact teaching and teaching material.
- 285 euros with registration by May 20, 2022
- 350 euros with registration after May 20, 2022
- Local students are exempted from the fee
Accommodation and travel costs are not included in the registration fee. For accommodation tips, see https://visitoulu.fi/en/arrival-overnight/
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 (2022)
Contact See 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**.
The source code of this repository is reproducible and contains the Rmd files with executable code. All files can be rendered at one go by running the file main.R. You can check the file for details on how to clone the repository and convert it into a gitbook, although this is not necessary for the training.