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 2025
• Chosen participants will be notified by: 31st May 2025
• Course date: 30 June - 4 July 2025

Venue

University of Bari “Aldo Moro” Aula 4, “Vecchi Istituti Biologici”, Campus Ernesto Quagliarello, via Orabona 4, 70126, Bari. 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 2025.

(Invited) Speakers

• Duccio Cavalieri, University of Florence
• Eugenio Parente, University of Basilicata
• Antonella Bruno, University of Milan Bicocca
• Edoardo Pasolli, University of Naples

Organizers and Instructors

• 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
• Paolo Manghi, Fondazione Edmund Mach, ELIXIR-IT, Italy
• Marinella Marzano, Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, IBIOM-CNR, ELIXIR-IT, Italy
• Pierfrancesco Novielli, INFN-Bari, ELIXIR-IT, Italy
• Graziano Pesole, University of Bari “Aldo Moro”, ELIXIR-IT, Italy
• Monica Santamaria, University of Bari “Aldo Moro”, ELIXIR-IT, Italy
• Sabina Tangaro, University of Bari “Aldo Moro”, ELIXIR-IT, Italy
• Veronica Morea, Institute of Molecular Biology and Pathology, IBPM-CNR, ELIXIR-IT Training Platform, Italy
• Allegra Via, University of Rome “Sapienza, ”ELIXIR-IT Training Platform, 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 workshop

• 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.

Registration

Application Form

Programme