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Training courses: Profiling of microbial communities using targeted and shotgun metagenomics



Course Description

This training course focuses on the study of the microbiota using Next Generation Sequencing (NGS) techniques. The course will introduce DNA metabarcoding and shotgun metagenomics and illustrate the major computational tools for the analysis of metagenomic data. In addition, the course will provide an introduction to Machine Learning methods applied to the analysis of metagenomic data. The course will include both a theoretical introduction to the topics and practical sessions with real data.



Important Dates

  • Deadline for applications: 20th May 2026
  • Chosen participants will be notified by: 31st May 2026
  • Course date: 29 June - 3 July 2026



Venue

University of Bari “Aldo Moro”
Aula 4, “Vecchi Istituti Biologici”, Campus Ernesto Quagliarello, via Orabona 4, 70126, Bari. google maps
The closest Campus entrance is on Via Giovanni Amendola 165/A



Fee

The course includes a fee of 250 Euros for academic attendees and 350 Euros for industry professionals, covering lunches and coffee breaks. Participants are expected to pay their own travel and accommodation costs (if any).



Selection procedure

A maximum of 25 candidates will be selected on a first-come first-served basis. Selected participants will be notified by 31st May 2026.



Institutional speaker

  • Prof. Graziano Pesole, Head of ELIXIR-IT, Italy



Invited speakers

  • Eugenio Parente (University of Basilicata, Potenza, Italy)
  • Mina Hojat Ansari (University of Freiburg, Georges-Koehler-Allee 079, 79110 Freiburg, Germany)



Instructors

  • Elisabetta Notario, Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, IBIOM-CNR, ELIXIR-IT, Italy
  • Pierfrancesco Novielli, INFN-Bari, ELIXIR-IT, Italy



Organizers

  • Giuseppe Defazio, University of Bari “Aldo Moro”, ELIXIR-IT, Italy
  • Claudio Donati, Fondazione Edmund Mach, ELIXIR-IT, Italy
  • Bruno Fosso, University of Bari “Aldo Moro”, ELIXIR-IT, Italy
  • Monica Santamaria, University of Bari “Aldo Moro”, ELIXIR-IT, Italy



Contacts

For all kinds of queries, please contact Claudio Donati at: claudio.donati@fmach.it, Bruno Fosso at: bruno.fosso@uniba.it or Monica Santamaria at: monica.santamaria@uniba.it



Target Audience

A maximum of 25 candidates will be selected on a first-come-first-served basis. The workshop is open to all biological or biomedical PhD and Post-Doc research scientists. The course requires basic knowledge of Unix and the command line (bash shell).



Aims of the Course

  • Introduce the principles of metabarcoding and shotgun metagenomics
  • Guide participants through all steps of data analysis, from quality controls to data reduction and visualization
  • Provide hands-on experience to develop practical analysis skills and enable the extraction and interpretation of biological insights from metabarcoding and metagenomic data



Resources and tools covered

  • MetaPhlAn, StrainPhLan, HUMANN, Kraken2, Bracken, Metabat2, kMetaShot
  • QIIME2, DADA2, BioMaS, ITSoneDB/ITSoneWB, GreenGenes2



Learning Outcomes

By the end of this course, the participants will be able to:

  • Use the common bioinformatics workflows for DNA-metabarcoding and shotgun metagenomics data analysis;
  • Analyse microbial communities using common ecological measures of biodiversity;
  • Apply methods of multivariate statistics and dimensionality reduction to microbiome data;
  • Use machine learning approaches for microbiota data analysis.

In summary, the course provides a comprehensive overview of modern microbiota analysis techniques, from sample preparation to bioinformatics analysis and machine learning applications.



Prerequisites

Participants are expected to have basic understanding of the UNIX shell and an active Google Account.



Registration form

Application Form



Programme

Day 1, June 29

Time Learning Experience Topic
11:00-14:00 Welcome and registration
14:00-14:30 Welcome and short intro on ELIXIR
Introduction to the course
14:30-17:00 Lecture What is metagenomics - metabarcoding vs shotgun
Intro on sequencing technologies
- Second Generation Technologies
- Third Generation Technologies
Introduction to DNA-metabarcoding
- Historical notes
- Applications: from the gut microbiome to food traceability
Experimental design
17:00-18:00 Hands-On Access to virtual machines and upload/download tests of files and folders
Setup of Colab account and Colab fundamentals

Day 2 - June 30th, Analysis of microbiome biodiversity through DNA metabarcoding

Time Learning Experience Topic
09:00-09:45 Lecture Amplicon sequencing
Variable regions vs full length
09:45-10:30 Hands-On 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 Denoising vs OTU-clustering & Chimera removal
Taxonomic classification: Approaches based on similarity analysis vs. Approaches based on Bayesian classifiers
12:00-13:00 Hands-On - Data denoising
- Taxonomic classification of data and visualization of relative abundances
13:00-14:00 Lunch Break
14:00-14:30 Questions and answers
14:30-15:30 Lecture 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
15:30-17:00 Hands-On - Rarefaction and diversity metrics.
- Statical Comparison
- Differential Abundance Analysis

Day 3, July 1st - Analysis of the taxonomic and functional composition of the microbiome through shotgun metagenomics

Time Learning Experience Topic
09:00-10:30 Lecture Sequencing technologies
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 Taxonomic and functional profiling using shotgun data
Raw 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
13:30-15:00 Hands On - MetaPhlAn
- Kraken2/Bracken
- Humann
15:00-15:30 Coffee Break
15:30-16:00 Hands On StrainPhlAn
16:00-17:00 Lecture Metagenome assembly and binning
- Binning
- Quality measures for MAGs
- Dereplication of MAGS
- Taxonomic classification of MAGs
- Hands On kMetaShot
- Functional annotation of MAGs

Day 4 - July 2nd - Machine Learning and Network Inference for Microbiome Data: Methods and Practice

Time Learning Experience Topic
09:00-10:30 Lecture Fundamentals of Machine Learning: problem formulations, model inputs/outputs, and the concept of learning from data
From data tables to model-ready features: representation choices and core preprocessing principles
Model assessment and validation: data splitting strategies, cross-validation, performance metrics, and control of leakage/confounding factors
Exploratory analyses: dimensionality reduction techniques and appropriate interpretation of embedded representations
Model explainability: global versus local explanations, feature importance, and SHAP (scope, assumptions, and limitations)
10:30-11:00 Coffee Break
11:00-12:30 Exercise Practical workflow: from data tables to modelling and interpretation
- Data import and initial inspection (feature table and metadata)
- Construction of model inputs: basic QC, representation choices, and preprocessing within a reproducible pipeline
- Baseline modelling and validation (cross-validation and performance metrics)
- Model interpretation using explainability tools (feature importance and SHAP)
12:30-13:30 Lunch Break
13:30-15:00 Lecture Eugenio Parente - Inference of microbial association networks from metataxonomic data.
Associations vs interactions in microbiome science
A primer on network science terminology
Measuring networks: networks, node and edge statistics
Methods for the inference of association networks
Statistical and graphical tools for the analysis of microbial association networks
15:00-15:30 Coffee Break
15:30-17:00 Exercise Inference of microbial association networks with R:
- Data preparation and package installation
- Inference of networks with NetCoMi and SpiecEasi
- Calculation of network statistics
- Postprocessing with tidygraph and ggraph
20:30 Social Dinner

Day 5 - July 3rd - Galaxy Project and usegalaxy.eu

Time Learning Experience Topic
09:00-09:30 Lecture Introduction to Galaxy Project: Galaxy concepts & logic
09:30-10:00 Hands-on Galaxy hands-on: sign-in, log-in, how-to
10:00-11:00 Hands-on FAIRyMAGs workflow - part 1
11:00-11:15 Coffee Break
11:15-13:15 Hands on FAIRyMAGs workflow - part 2
13:15-13:30 Closing remarks Closing remarks from Summer School committee