To foster international participation, this course will be held online

This course will survey the most advanced methodologies for the study of microbial communities from shotgun metagenomics data. Through a balanced approach of lectures and hands-on lab sections, students will be faced with the most important challenges in the metagenomics scientific practice, which include: tools for data preprocessing, taxonomic profiling, strain-level characterization, microbial genome reconstruction, functional potential characterization, and integrative statistical data analysis. At the end of the course the participants will acquire familiarity with the theory and practice of the most important bioinformatics approaches for metagenomics, including tools for visualisation of results.

This course is intended for researchers and students whose desire is to gather the necessary knowledge to analyse high-throughput microbiome data from different sources. The course will overview the basics of the most important metagenomic approaches and will provide the critical knowledge to apply these in future contexts. A particular focus will be given to the long-standing challenges that have allowed the design of the described tools, to provide a general perspective about the application of these methodologies in the future.

Having basic command line knowledge will be beneficial for the course. If you're new to the command line, we recommend completing this online tutorial before the course starts.

●    Familiarity with the goals of studying microbial communities, and with the approaches that are used to pursue these.
●    Taxonomic, gene-related, and strain-level characterization of communities using reproducible workflows, with related case studies.
●    Workflows to address the study of unknown microbial communities.
●    Univariate and multivariate statistical analyses for microbiome studies, applied on a single cohort and in multi-population studies.
●    Visualisation tools for exploring microbiome data and deploying scientific reports.

Day1– Classes from 2-8 pm BERLIN TIME

General introduction
Introduction to microbiome data analysis
Raw data pre-processing
Taxonomic profiling
Taxonomic profiling (MetaPhlAn)
Strain-level profiling
Open discussion/wrap-up

Day2– Classes from 2-8 pm BERLIN TIME

GraPhlAn
Microbiome study design    
Strain-level profiling (StrainPhlan)
Strain-level profiling (PanPhlAn)
Functional profiling        
Functional profiling (HUMAnN)
Open discussion/wrap-up   

Day3– Classes from 2-8 pm BERLIN TIME

Metagenomic assembly        
Metagenomic assembly (Megahit + Prokka)
MAG reconstruction and taxonomic assignment    
MAG reconstruction and taxonomic assignment (Metabat + PhyloPhlAn)
Phylogenetic analysis (PhyloPhlAn)    
Open discussion/wrap-up   

Day4– Classes from 2-8 pm BERLIN TIME

Data reuse (curatedMetagenomicData)
Statistics for metagenomics    
Diversity analysis
High dimensional testing
Machine learning in metagenomics    
Regression analysis
Classification analysis
Reproducibility in microbiome studies    
Open discussion/wrap-up