Microbiome data science with R/Bioconductor
Welcome to Radboud Summer School, July 2022
2022-07-11
1 Overview
1.1 Contents and learning goals
This course will focus on microbiome data analysis with R/Bioconductor, a popular open source environment for scientific data analysis. You will get an overview of the reproducible data analysis workflows in microbiome research, with a focus on gut-brain axis studies.
After the course you will know how to approach new tasks in the analysis of taxonomic profiling data by taking advantage of available documentation and R tools.
The teaching follows the 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 Finnish 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.
1.2 Schedule and organizers
Format In-person course. For detailed schedule, see the course website.
Venue University of Radboud. July 11-15, 2022.
Expected background
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 encouraged to apply. Priority will be given for local students. Some earlier experience with R or another programming language is recommended.
Preparation Advance preparation is expected. Online support is available. See section 3 for instructions.
1.3 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 Borman et al. (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. See README.