Welcome to Oulu Summer School, June 2022
Figure source: Moreno-Indias et al. (2021) Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions. Frontiers in Microbiology 12:11.
You can render the book locally in R with:
bookdown::serve_book()
The miaverse (mia = MIcrobiome Analysis) is an R/Bioconductor framework for microbiome data science. It aims to extend the capabilities of another popular framework, phyloseq.
The miaverse framework consists of an efficient data structure, an associated package ecosystem, demonstration data sets, and open documentation. These are explained in more detail in the online book Orchestrating Microbiome Analysis.
This training material walks you through an example workflow that shows the standard steps of taxonomic data analysis covering data access, exploration, analysis, visualization and reporoducible reporting. You can run the workflow by simply copy-pasting the examples. For advanced material, you can test and modify further examples from the OMA book, or try to apply the techniques to your own data.
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 format allows adaptations according to the student’s learning speed.
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 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. The openly licensed teaching material will be available online during and after the course, following national recommendations on open teaching materials.
Target audience The course is primarily designed for advanced MSc and PhD students, Postdocs, and biomedical researchers who wish to learn 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 be given for local students from Oulu.
Venue University of Oulu. June 20-23, 2022.
Citation "Multi-omic data science with R/Bioconductor (2022). Tuomas Borman and Leo Lahti. URL: https://microbiome.github.io/course_2022_oulu/"
Contact
- Leo Lahti, University of Turku
- mia Collective
License All material is released under the open CC BY-NC-SA 3.0 License.
- Landing page (html): miaverse teaching material
- Source code (github): miaverse teaching material
The source code of this repository is fully 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.