T19 – Analysis of Compositional Microbiome Data
Tag, Uhrzeit, Dauer
Donnerstag, 9–18 Uhr, 8h
Angebotene Sprache
Englisch
Kurzbeschreibung
Since the development of modern next-generation sequencing (NGS) techniques, collecting data to describe microbial communities has become more efficient, and an increasing number of studies strive to investigate the interaction of bacterial communities colonizing the human body with health and disease of the host. Reproducibility, however, remains a major issue in microbiome research. Heterogeneity arises not only from biological variations, but also from the complex nature of microbiome data, such as compositionality, high-dimensionality and zero-inflation, and the challenges to adequately accommodate for those characteristics in the study design and statistical analyses. The aim of this tutorial is to equip all participants with the necessary skills and tools to interpret and critically question the results of microbiome studies, to be able to perform their own basic microbiome analyses and to be able to critically revise the assumptions and the possible advantages and disadvantages of common and novel methodology. The tutorial will be a combination of mini lectures to introduce the core concepts of microbiome research and hands-on tutorials to reinforce and apply the concepts covered. After completing the course, the participants will (1) have a basic understanding of the microbiome data collection process covering amplicon sequencing and shotgun metagenomics, bioinformatics processing, clustering into operational taxonomic units (OTUs) or amplicon sequence variants (ASVs) and taxonomic classification and annotation. The participants will be able to (2) import microbiome data into common data formats (phyloseq / TreeSummarizedExperiment) in R, apply common data transformations (relative abundances, log-ratio transformations) and to (3) calculate and understand the most widely applied ecological parameters such as alpha (i.e., Shannon diversity) and beta diversity (i.e., Bray-Curtis dissimilarity). The participants will further (4) understand the concepts of differential abundance analyses and will be able to perform differential abundance
Fachliche Voraussetzungen
For this tutorial, you will need a basic understanding of R to follow along. The tutorial will cover all necessary concepts and provide examples for you to learn from.
Technische Voraussetzungen
To participate in this tutorial, you will need a laptop with the latest version of R and R Studio installed. In addition, make sure to install the following packages to follow along with the analyses: tidyverse, phyloseq, mia, MiaViz, vegan and microbiome. If you encounter any difficulties with these preparations, please don’t hesitate to contact the organizers for assistance.
Organisator*in
Sven Kleine Bardenhorst
Institution
Institut für Epidemiologie und Sozialmedizin, Universität Münster, Münster
Kontakt
kleineba [at] uni-muenster.de
Zusätzliche*r Referent*in
Nicole Rübsamen, PhD
Institution
Institut für Epidemiologie und Sozialmedizin, Universität Münster, Münster