Keywords: assembly, climate, galaxy-interface, introduction, microbiome, proteomics, single-cell, statistics, variant-analysis

Learning objectives:

• Assess long reads FASTQ quality using Nanoplot and PycoQC
• Assess short reads FASTQ quality using FASTQE 🧬😎 and FastQC
• Become comfortable converting text-based files in a variety of ways.
• Connect different parts of the Research Object using identifiers
• Construct an RO-Crate by hand using JSON
• Construct phylogenetic tree for TAPs
• Describe each part of the Research Object
• Explain what is a BAM file and what it contains
• Extract FASTA sequences using sequence ID/header
• Familiarize yourself with data manipulation tools in Galaxy
• Familiarize yourself with the basics of Galaxy
• Gain understanding on navigating and manipulating histories
• Generate a workflow test using Planemo
• Learn about how Galaxy handles NGS data using Illumina data derived from patients infected with Plasmodium
• Learn basic JSON-LD to create FAIR metadata
• Learn how histories work
• Learn how to create a workflow
• Learn how to extract and run a workflow
• Learn how to identify TAPs from a given proteome using TAPScan
• Learn how to obtain data from external sources
• Learn how to run tools
• Learn how to share a history
• Learn how to share your work
• Learn how to upload a file
• Learn how to use a tool
• Learn how to view histories
• Learn how to view results
• Perform basic text manipulation tasks in Galaxy
• Perform quality correction with Cutadapt (short reads)
• Perform sequence alignment using MAFFT
• Process single-end and paired-end data
• Reason about the expected outcome of tools
• Run a tool to map reads to a reference genome
• Summarise quality metrics MultiQC
• Understand and master dataset collections
• Understand how testing can be automated with GitHub Actions
• Understand most common types of NGS-related datatypes
• Understand the role of TAPs
• Use genome browser to understand your data

Organizer: Armin Dadras (https://orcid.org/0000-0001-7649-2388), Delphine Lariviere (https://orcid.org/0000-0001-6421-3484), Diana Chiang Jurado (https://orcid.org/0000-0002-5857-1477), Natalie Whitaker-Allen (https://training.galaxyproject.org/training-material/hall-of-fame/natalie-wa/), Saskia Hiltemann (https://orcid.org/0000-0003-3803-468X), Scott Cain (https://training.galaxyproject.org/training-material/hall-of-fame/scottcain/), Teresa Müller (https://orcid.org/0000-0003-1252-9684)

Event types:

• Workshops and courses

Sponsors: ABRomics, ELIXIR Europe, EOSC | FAIR2Adapt, German Network for Bioinformatics Infrastructure Service, Training, Cooperations & Cloud Computing, Institut Français de Bioinformatique, Ministry of Science, Research and Arts

Instructors: Ahmed Hamid Awan, Anna Syme, Anne Fouilloux, Anup Kumar, Anthony Bretaudeau, Anton Nekrutenko, Armin Dadras, Amirhossein Naghsh Nilchi, Bérénice Batut, Björn Grüning, Clea Siguret, Daniela Schneider, Dannon Baker, Diana Chiang Jurado, Deepti Varshney, Delphine Lariviere, Elifsu Filiz, Eli Chadwick, Engy Nasr, Emmanuel Augustine, Even Moa Myklebust, Gareth Price, Hans-Rudolf Hotz, Helena Vela, Igor Makunin, Khaled Jum'ah, John Davis, Jean Iaquinta, Jennifer Hillman-Jackson, Julian Hahnfeld, Jochen Blom, Lisanna Paladin, Linda Fenske, Matthias Bernt, Max Pfister, Melanie Föll, Meltem Kutnu, Michael Schatz, Michelle Terese Savage, Eduardo Jacobo Miranda Ackerman, Natalie Whitaker-Allen, Nate Coraor, Oliver Rupp, Oliver Schwengers, Paul De Geest, Paul Zierep, Pavankumar Videm, Polina Polunina, Krzysztof Poterlowicz, Pratik Jagtap, Rand Zoabi, Romane LIBOUBAN, Saim Momin, Sanjay Kumar Srikakulam, Scott Cain, Silvia Di Giorgio, Stéphanie Robin, Subina Mehta, Teresa Müller, Timothy J. Griffin, Tyler Collins, Wendi Bacon, Wolfgang Maier, Reyhaneh Tavakoli-Koopaei

Scientific topics: Mapping