Galaxy as a gateway to bioinformatics: Multi-Interface Galaxy Hands-on Training Suite (MIGHTS) for scRNA-seq

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Mastering bioinformatics presents a steep learning curve for bench biologists and clinicians.
• Analyzing data while learning to code is challenging, hindering effective bioinformatics training.
• Single-cell analysis is in high demand, but unstandardized pipelines and iterative analyses complicate training.

Purpose of the Study:

• To address challenges in bioinformatics training for single-cell RNA sequencing (scRNA-seq) analysis.
• To provide a training suite that separates coding from data analysis, offering intermediate steps.
• To facilitate smooth transitions between graphical and code-based analysis environments for diverse learners.

Main Methods:

• Developed the Multi-Interface Galaxy Hands-on Training Suite (MIGHTS) for scRNA-seq analysis.
• MIGHTS offers parallel analytical methods using a graphical interface (buttons) or code.
• Leveraged Galaxy interfaces for analyses, supporting both Python (Scanpy) and R (Seurat & Monocle) based workflows.

Main Results:

• MIGHTS provides clear, interoperable materials facilitating transitions between analysis environments.
• The suite bridges the biologist-programmer gap, emphasizing interdisciplinary communication.
• Real-world data analysis in MIGHTS promotes critical thinking, best practices, and FAIR data principles.

Conclusions:

• MIGHTS comprises 11 tutorials with diverse learning materials and a history of sustainability.
• Parallel pathways in MIGHTS cater to scientists at all programming levels, addressing heterogeneous needs.
• The training suite supports concurrent learning for novice bioinformaticians in both graphical and code-based settings.