Workshop: Structural variant discovery from long-read sequencing data on the cloud with Galaxy in Terra

Description

Growing evidence that structural variants (SVs) are responsible for many types of diseases and traits is fueling interest in taking a fresh look at different disease types using long-read sequencing. Although short-read technologies have long been cheaper and more readily available, long-read sequencing produces data that can yield significantly more accurate results for identifying SVs.

However, the large amounts of data and complexity of the computational methods involved can make it difficult for newcomers to access this exciting area of research, particularly in the context of the traditional computing environments that are provided by default to academic researchers.

In this workshop, we will guide you through an end-to-end SV identification journey using Galaxy, a platform designed to facilitate access to computational methods for researchers without a programming background. Specifically, we will use Galaxy in Terra, in the context of the NHGRI Genomic Data Science Analysis, Visualization and Informatics Lab-space (AnVIL). This cloud-based environment enables you to analyze large genomic datasets with familiar tools and reproducible workflows securely.

Through live demonstrations and interactive exercises, you will learn how to:

1. Bring data into a project workspace in Terra
2. Combine data (your own or controlled-access) with an open-access dataset
3. Launch a Galaxy instance in Terra and run a complete workflow to identify SVs
4. Visualize results and identify potentially pathogenic variants

The skills you will learn in this workshop will extend to other scientific use cases, datasets and tools beyond the examples shown.