2 Program

The course takes place daily from 9am – 5pm (CEST), including coffee and lunch breaks.

We expect that participants will prepare for the course in advance, see section 4. Online support is available.

The material follows open online book created by the course teachers, Orchestrating Microbiome Analysis https://microbiome.github.io/OMA. This is R/Bioconductor framework for multi-omic data science.

ML4microbiome

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.

2.1 Day 1 - Open data science

Morning session

9-10 Coffee, Welcome & Practicalities

10-11 Lecture: Open & reproducible workflows

11-12 Demo & hands-on: Introduction to CSC RStudio notebook

12-13 Lunch break

Afternoon hands-on session

13-15 Demo: Data science framework

15-17 Hands-on: microbiome data summaries & exploration

17-18 Presentations & Discussion


2.2 Day 2 - Tabular data

Morning session

9-10 Lecture: Analysis & visualization of tabular data

10-12 Demo & hands-on: Univariate methods

12-13 Lunch break

Afternoon hands-on session

13-14 Demo: Multivariate data analysis & visualization

14-17 Hands-on: Multivariate data analysis & visualization

17-18 Presentations & Discussion


2.3 Day 3 - Multi-assay data

Morning session

9-10 Lecture: multi-omic data integration

10-12 Demo & hands-on: multi-assay data container

12-13 Lunch break

Afternoon hands-on session

13-15: Demo & hands-on: association analysis

13-17: Demo & hands-on: machine learning

17-18 Presentations & Discussion


2.4 Day 4 - Advanced topics

Morning session

9-10 Summary of the learning material

10-12 Demo & hands-on: custom data & advanced tools

12-13 Q & A session

Afternoon session

13-14 Lunch

14-16 Wrap-up