Galaxy Training: A Powerful Framework for Teaching!

Abstract

There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis and stewardship are still rarely taught in life science educational programs, resulting in a skills gap in many of the researchers tasked with analysing these big datasets. In order to address this skills gap and empower researchers to perform their own data analyses, the Galaxy Training Network (GTN) has previously developed the Galaxy Training Platform (https://training.galaxyproject.org); an open access, community-driven framework for the collection of FAIR training materials for data analysis utilizing the user-friendly Galaxy framework as its primary data analysis platform. Since its inception, this training platform has thrived, with the number of tutorials and contributors growing rapidly, and the range of topics extending beyond life sciences to include topics such as climatology, cheminformatics and machine learning. While initially aimed at supporting researchers directly, the GTN framework has proven to be an invaluable resource for educators as well. We have focused our efforts in recent years on adding increased support for this growing community of instructors. New features have been added to facilitate the use of the materials in a classroom setting, simplifying the contribution flow for new materials, and have added a set of train-the-trainer lessons. Here, we present the latest developments in the GTN project, aimed at facilitating the use of the Galaxy Training materials by educators, and its usage in different learning environments

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease

“…Comprehensive training, such as basic computational skills and data analysis, remains a requirement for understanding data analyses and result interpretation (6). However, even as the life sciences are continually evolving to be more computational in nature and bioinformatics becoming more prevalent in research studies, life science educational programs do not commonly include comprehensive computational training in their curricula (6).…”

“…Comprehensive training, such as basic computational skills and data analysis, remains a requirement for understanding data analyses and result interpretation (6). However, even as the life sciences are continually evolving to be more computational in nature and bioinformatics becoming more prevalent in research studies, life science educational programs do not commonly include comprehensive computational training in their curricula (6). To address this training deficit, the GTN (https://training.galaxyproject.org/) was created to provide learners and instructors, regardless of expertise and experience, with free online training materials and access to a global community, while promoting open data analysis practices (6).…”

“…To demonstrate the effectiveness of our clinical metaproteomics workflow, here we analyze MS/MS data from Pap test fluid (PTF) samples collected from ovarian cancer (OC) and non-OC patients. The bioinformatics workflow is accessible via the Galaxy ecosystem, which offers access to powerful bioinformatic tools for metaproteomic data analysis that facilitate the development and execution of complex workflows necessary for complete clinical metaproteomics (6). Galaxy is a free, browser-based, scalable platform that is maintained by a thriving community keeping it current to meet emerging needs in bioinformatics analysis across 'omic domains (7,8).…”

“…Galaxy is a free, browser-based, scalable platform that is maintained by a thriving community keeping it current to meet emerging needs in bioinformatics analysis across 'omic domains (7,8). New users can also access online and on-demand training resources, such as step-by-step instructions, access to workflows, and example datasets via Galaxy Training Network (GTN) resources (6,9). We envision these collective bioinformatic resources will find use in many clinical studies, such as potential secondary infections during COVID-19 infection, and other broad research questions regarding host-microbe interactions underlying human disease underlying human disease (10).…”

Catching the Wave: Detecting Strain-Specific SARS-CoV-2 Peptides in Clinical Samples Collected during Infection Waves from Diverse Geographical Locations

“…These are deployed within the Galaxy bioinformatics ecosystem [ 16 ], providing a workbench wherein scientists can share, analyze, and visualize their results in a reproducible manner, carrying out analyses on scalable computer resources accessed through a web browser interface. The ecosystem also provides extensive online and on-demand training material via the Galaxy Training Network [ 17 ], including guidance on the usage of the platform for SARS-CoV-2 studies [ 18 ].…”