1 Overview

1.1 Schedule

The schedule is summarized as follows.

Day 1 (Tue) - Symposium; online lectures and no hands-on session
Day 2 (Wed) - Online lectures; hands-on session on R/Bioconductor framework
Day 3 (Thu) - Online lectures; hands-on session on microbiome data analysis methods
Day 4 (Fri) - Online lectures; advanced microbiome data analysis methods

1.2 Learning goals

This course will teach the basics of microbiome data analysis and integration with R/Bioconductor, a popular open source environment for scientific data analysis.

You will get an overview of the reproducible data analysis workflow, with recent examples from published studies.

After the course you will know how to approach new tasks in microbiome data science by utilizing the available R tools and documentation. In particular, you understand the concepts of data containers, reproducible workflows, and standard concepts in microbiome data analysis.

1.3 Target audience

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 microbiome data science. Academic students and researchers from Finland and abroad are welcome and encouraged to apply. The course has limited capacity, and priority will given for local students.

Expected background Earlier experience with R or another programming language is expected. The teaching format allows adaptations according to the student’s learning speed.

1.4 Learning material

The teaching builds on the open online tutorial, Orchestrating Microbiome Analysis (https://microbiome.github.io/OMA). The openly licensed teaching material will be available online during and after the course, following recommendations on open education.

The training material walks you through the standard steps of microbiome data analysis covering data import, processing, exploration, analysis, visualization, reproducible reporting, and best practices in open science. We 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.

Link to online Gitter chat: https://microbiome.github.io

Microbiome data science with R/Bioconductor