This book provides resources for instructors to engage students in a cloud-based Galaxy activity on AnVIL, focused on SARS-CoV-2 variant detection.

There is a growing need for undergraduate students to learn cutting-edge concepts in genomics data science, including performing analysis on the cloud instead of a personal computer. This lesson aims to introduce a mutant detection bioinformatics pipeline based on a publicly available genetic sample of SARS-CoV-2. Students will be introduced to the sequencing revolution, variants, genetic alignments, and essentials of cloud computing prior to the lab activity. During the lesson, students will work hands-on with the point-and-click Galaxy interface on the AnVIL cloud computing resource to check data, perform an alignment, and visualize their results.

Skills Level

Novice: no genetics knowledge needed

Programming skills
Novice: no programming experience needed

Learning Objectives

Learning objectives for this activity come from the Genetics Core Competencies:

  • Gather and evaluate experimental evidence, including qualitative and quantitative data
  • Generate and interpret graphs displaying experimental results
  • Critique large data sets and use bioinformatics to assess genetics data
  • Tap into the interdisciplinary nature of science

GDSCN Collection

This exercise is part of a collection of teaching resources developed through the Genomic Data Science Community Network (GDSCN). GDSCN works towards a vision where researchers, educators, and students from diverse backgrounds are able to fully participate in genomic data science research. Learn more about GDSCN by visiting https://www.gdscn.org/home or reading the article in Genome Research.

Please check out our full collection of AnVIL and related resources: https://hutchdatascience.org/AnVIL_Collection/