Erasmus Summer Programme Courses

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Microbiome Data Analysis in Population-based Studies [ESP81]

Course highlights

EC points

1.4

Start date

19 August 2024

End date

23 August 2024

Course days

Monday to Friday (5 full days)

Course time

From 8:45 till 16:00 CEST

Faculty

Dr, Carolina Medina Gomez, Dr. Robert Kraaij & others

Course fee

€ 1058

Location

Erasmus MC, Rotterdam NL

Level

Intermediate

Prerequisites

Basic understanding of statistics and use of R statistical software.

Disciplines

  • Genetic Epidemiology

Course Materials

Digitally, download instructions will be sent before the start of the course, by e-mail.

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Detailed information about this course:

Description

Faculty: Carolina Medina-Gomez, PhD, Luba Pardo-Cortes, PhD, Robert Kraaij, PhD & others

Our understanding of the link between the human gut microbiome and health outcomes is rapidly expanding. The different microbial communities within the human body affect cellular responses and shape many aspects of our physiology, starting to reveal critical roles in health and disease processes. From an epidemiological perspective, microbiome data analysis aims at elucidating the composition of microbial communities, their variation in response to environmental triggers and ultimately, their involvement in human health outcomes in the population. Thanks to the advances in next generation sequencing technology, microbiome profiling is now within reach of large epidemiological studies, bringing up new challenges for the analysis of microbiome data. This course seeks providing students with their first encounters with real microbiome datasets, learn about quality control requirements, preparing datasets for analysis, and finally, teach how to carry out typical analysis tasks, such as comparing microbial diversity and composition, clustering samples and computing associations. Uniquely, this course will also cover aspects of study design providing examples for population-based studies on gut, oral, vaginal and skin microbiome studies. The course will comprise theoretical lectures (by local experts and guest speakers) together with hands-on interactive practical sessions.

Participants of this course should be familiar or become familiar with R-programming language, before the start of the course.


Topics covered:

• Research question and study design of a microbiome study
• Technical and analytical applications for the analysis of gut, oral, vaginal and skin microbiome.
• Sequencing techniques, data types (16S, metagenomics)
• Sample size and power in context of multidimensional and dynamic microbiome data
• Creation and pre-processing of microbiome data
• Estimating microbial evenness and diversity
• Testing differential "relative" and "absolute" abundance, including compositional approaches
• Association analysis of microbiome data in relation to health outcomes in human populations
• Critical review of literature and real-life examples of disease (Acne, caries/periodontitis, diabetes, vaginosis)


Objectives

At the end of the course participants will be able to:
• Recognize the role of microbiome determinants in human health and disease processes
• Get acquainted with the methodology used for microbiome research in population-based settings
• Draw research questions and appraise the properties of microbiome study design
• Characterize methods used to sample the microbiome across distinct bodily systems
• Describe the process of microbiome dataset creation and quality control
• Understand how to extract species and function counts from sequencing data
• Comprehend the definitions of microbiome richness, evenness and diversity
• Correlate diversity and microbial composition with health and disease outcomes
• Understand how to perform and interpret associations with operational taxonomy units and function

Participant profile

Healthcare professionals, clinical and fundamental researchers working with microbiome profiling (e.g., skin, oral, gut, vaginal) and health and disease outcomes within population—based settings or planning to carry-out a project using these techniques and approaches.

Assessment

Attendance