index.Rmd

---
title: "GDSCN Book: SARS with Galaxy on AnVIL"
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description: "This book provides resources for instructors to engage students in a cloud-based Galaxy activity on AnVIL, focused on SARS-CoV-2 variant detection."
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---

# Overview {-}

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](https://anvilproject.org/) cloud computing resource to check data, perform an alignment, and visualize their results.

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<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/OFGa6x2bGHs" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

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## Skills Level {-}

<div class = "notice">
_Genetics_  
**Novice**: no genetics knowledge needed
 
_Programming skills_  
**Novice**: no programming experience needed
</div>

## Learning Objectives {-}

Learning objectives for this activity come from the [Genetics Core Competencies](https://genetics-gsa.org/education/genetics-learning-framework/):

- 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](https://doi.org/10.1101/gr.276496.121).

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

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