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Profiling of microbial communities using targeted and shotgun metagenomics

Course Program

The lectures are available at the following link.

Day 1 - Welcome and general Introduction

Time	Learning Experience	Topic
10:00 - 12:00		Welcome and registration
12:00 - 14:00		Welcome cocktail
14:00 - 14:30	Lecture	Welcome and short intro on ELIXIR Introduction to the course
14:30 - 17:30	Lecture	What is metagenomics - metabarcoding vs shotgun - Prof. Monica Santamaria Intro on sequencing technologies - Second Generation Technologies - Third Generation Technologies - Dott. Elisabetta Notario Introduction to DNA-metabarcoding - Historical notes- Applications: from the gut microbiome to food traceability - Prof. Monica Santamaria

Day 2 - Analysis of microbiome biodiversity through DNA metabarcoding

Time	Learning Experience	Topic
09:00 - 09:45	Lecture	Amplicon sequencing: Variable regions vs full length - Prof. Bruno Fosso
10:00 - 10:30	Hands-On	Access to virtual machines and upload/download tests of files and folders
09:45 - 10:30	Hands-On	Dott. Giuseppe Defazio Characteristics of the raw sequencing data Data visualization Data quality: fastqc/multiqc Data import into qiime Data pre-processing
10:30 - 11:00		Coffee Break
11:00 - 12:00	Lecture	Prof. Bruno Fosso Denoising vs OTU-clustering & Chimera removal Taxonomic classification: Approaches based on similarity analysis vs Bayesian classifiers
12:00 - 13:00	Hands-On	Dott. Giuseppe Defazio Data Denoising Taxonomic classification of data and visualization of relative abundances
13:00 - 14:00		Lunch Break
14:30 - 15:30	Lecture	Prof. Bruno Fosso & Dott. Giuseppe Defazio Theoretical notes on the concept of Diversity and Diversity measures Data normalization for Rarefaction and CLR Dimensional reduction approaches (PCoA/PCA) and permANOVA tests Statistical tests on alpha diversity and beta diversity metrics Differential Abundance Analysis
15:30 - 15:45		Coffee Break
15:30 - 17:00	Hands-On	Prof. Bruno Fosso & Dott. Giuseppe Defazio Rarefaction and diversity metrics Statistical Comparison Differential Abundance Analysis

Day 3 - Artificial Intelligence and the Microbiome

Time	Learning Experience	Topic
09:00 - 10:30	Lecture	Dott. Pierfrancesco Novielli & Dott. Pierpaolo Di Bitonto Fundamentals of Machine Learning and AI Introduction to Python for microbiome data analysis Types of Machine Learning (Supervised vs Unsupervised) Microbiome data and their specificity- Compositional data and log-ratio transformations (clr, ilr, alr) Sparsity and over-dispersion problems Need for normalization and scalingDimensionality reduction PCA, t-SNE, UMAP (advantages and limitations in microbiomial analysis) Considerations on normalization, data balancing and cross-validation
10:30 - 11:00		Coffee Break
11:00 - 12:30	Hans-On	Dott. Pierfrancesco Novielli & Dott. Pierpaolo Di Bitonto Data preprocessing and preparation for ML Data import and visualization Transformations for compositional data Normalization and management of relative abundances Implementation of PCA and t-SNE to explore the structure of microbiome data
12:30 - 13:30		Lunch Break
13:00 - 15:00	Lecture	Dott. Pierfrancesco Novielli & Dott. Pierpaolo Di Bitonto Machine Learning Models and Interpretability Machine Learning for the Microbiome Classification vs Regression Common algorithms: Logistic Regression, Decision Trees, Random Forest, SVM, Gradient Boosting Performance evaluation- Accuracy, Precision, Recall, F1-score, AUC-ROC Confusion Matrix and importance of the choice of metric Explainable AI (XAI) and model interpretability (SHAP and LIME) for feature interpretation Importance of features and their role in prediction XAI applications in the microbiome: identification of relevant microbial markers
15:00 - 15:15		Coffee Break
15:15 - 16:15	Lecture	The human microbiome and the Holobiont theory of evolution - Duccio Cavalieri - University of Florence
16:15 - 17:30	Hands-On	Dott. Pierfrancesco Novielli & Dott. Pierpaolo Di Bitonto Construction and interpretation of an ML model on metagenomic data- Training a classification model on abundance data Hyperparameter optimization with cross-validation Hyperparameter optimization with cross-validation Discussion of the results and comparison with traditional methods

Day 4 - Analysis of the taxonomic and functional composition of the microbiome through shotgun metagenomics

Time	Learning Experience	Topic
09:00 - 10:30	Lecture	Dott. Claudio Donati & Dott. Paolo Manghi Brief introduction to the main analysis techniques: Taxonomic profiling Functional profiling Metagenome assembly and binning Computational tools for metagenomics operating systems hardware requests software tools (nextflow-docker, etc)
10:30 - 11:00		Coffee Break
11:00 - 12:30	Lecture	Dott. Claudio Donati & Dott. Paolo Manghi Taxonomic and functional profiling using shotgun dataRaw data preprocessing: read filtering and host elimination Taxonomic profiling:- MetaPhlAn- Kraken2/Bracken Functional profiling: HUMANN Taxonomic profiling beyond the species level: Strain level analysis The species concept in bacteria Genomic variability within the species: strain, genome, pangenome Strain level profiling: StrainPhlAn
12:30 - 13:30		Lunch Break
13:30 - 15:30	Hands-On	Dott. Paolo Manghi MetaPhlAn Kraken2/Bracken HUMANN
15:00 - 15:30		Coffee Break
15:30 - 16:00	Hands-On	Dott. Paolo Manghi StrainPhlAn
16:00 - 17:00	Lecture	Dott. Claudio Donati & Dott. Paolo Manghi Metagenome assembly and binning Binning- Quality measures for MAGs Dereplication of MAGS- Taxonomic classification of MAGs Taxonomic classification of MAGs MAGs Taxonomic Classification with kMetaShot Functional annotation of MAGs
20:30		Social Beer

Day 5 - Case Studies

Time	Learning Experience	Topic
09:00-10:00	Question Time
10:00-11:00	Lecture	The Food Microbiome - Eugenio Parente, University of Basilicata
11:00-11:15	Coffee Break
11:15-12:15	Lecture	Living with microbes: The microbiome of the built environment and its implications in human wellbeing - Antonia Bruno, University of Milan Bicocca
12:15-13:15	Lecture	Strain-resolved metagenomics of the human and food microbiomes - Edoardo Pasolli, University of Naples