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.

Cloud-based analysis of genomic datasets is increasingly vital for portability, reproducibility, and multi-institution collaboration, but transitioning to the cloud can be daunting. We will offer a workshop that will serve to eliminate some of the barriers to the adoption of these tools. Specifically, we will teach researchers how to access and utilize The Analysis, Visualization, and Informatic Lab-space (AnVIL), an environment that provides access to hosted data, reproducible tools, and collaborative workspaces, and comprehensive documentation to enable users to conduct research in the cloud. This workshop will demonstrate how to access and explore data in AnVIL. Participants will also learn to search for analysis tools in Dockstore, a platform for sharing portable, container-based tools and workflows written to be interoperable across local and cloud environments. Finally, they will analyze data in a Terra workspace, which is a dedicated space where researchers can access and organize the same data and tools and run analyses.

This workshop will specifically explore and demonstrate open-access data from the Human Pangenome Reference Consortium (HPRC), an NHGRI funded effort to create a more diverse and comprehensive reference human pangenome. We will present the data and methods produced and utilized within the first year of this project, which ultimately aims to release the assembly of high-quality diploid genomes from >350 ethnically diverse individuals across five years. Currently, raw data and assemblies from 45 individuals and associated Docker-based analysis workflows written in the Workflow Description Language (WDL) are available in the AnVIL for researchers to explore and utilize. Data and workflows will continue to be publicly released as early as possible to promote open science. These data make an excellent substrate for interaction with these data types and new workspaces and methods.

Using data and workflows from the HPRC, participants of this workshop will follow along with instructors to learn how to:

1. Register for a Terra account and set up a project using $300 in free Google Cloud credits
2. Set up a collaborative cloud workspace in Terra
3. Access and explore Human Pangenome Data hosted by AnVIL
4. Search for bioinformatics workflows in Dockstore and export them to a Terra workspace
5. Configure and launch a Docker-based WDL workflow to conduct a parallel analysis
6. Monitor cloud costs associated with an analysis

After completing the workshop, attendees will be able to leverage AnVIL to analyze hosted datasets and launch analyses that are reproducible and scalable. Attendees will also be familiar with Human Pangenome data and resources.

In this interactive workshop, we aim at introducing some state-of-art population genetics tools that are most useful for the general ASHG community and provide hands-on experiences for attendees to learn and understand these tools. The audience will learn population genetic simulations, global and local ancestry inference, genealogy and tree inference, advanced demographic history inference from experts on these topics. Each topic takes 20 minutes, with 10 minutes discussion in the end.

In the first half of this workshop, we will instruct how to perform forward simulations with SLiM and backward simulation with msPrime for simulating a large number of genomes (and phenotypes) under mutation, recombination, selection, and population structure. Data from realistic simulations are useful for understanding genomic patterns, benchmarking new methods, and testing hypotheses.

We will then introduce global ancestry (i.e., the proportion of a genome that comes from each population) and local ancestry (i.e., genomic segments come from each population) inference methods. Ancestry information is useful for understanding population history, identifying selection, and mapping disease loci. In the second part of this workshop, we will instruct recently developed methods for constructing whole-genome genealogies. These new methods opened up possibilities to utilize the genomic information efficiently and opportunities to understand selection and demography more accurately. We will then instruct various methods for inferring complex demographic history and best practices for a given dataset

We will collect questions the audience is interested in tackling during the workshop, and our instructors will host a short discussion at the end to discuss how these tools could be used to address their specific questions.

The UCSC Genome Browser has been a workhorse providing data and visualization for genetics research and clinical professionals for more than 20 years.  The Browser continues to grow and add new features, and even experienced users frequently disclose that they have missed important innovations.  The proposed workshop will feature some of the newest Browser offerings.

 We have recently revised our presentations of data important to the interpretation of variants in the clinical context.  Working with ClinVar, ClinGen, gnomAD and others, we now make the details of items displayed in the Browser more available via mouseover in the main Browser graphic.  In this way, multiple variants in a region can be investigated more quickly, without a required click-through. 

 We have also implemented a new feature called "Recommended Track Sets" -- one each for copy-number variants and single nucleotide variants.  Using this feature, users may, from any location in the genome, launch a pre-configured session with important data automatically displayed.

 A new data type has been introduced to aid in the display of ClinVar SNV variants with phenotypes in the five clinical classes (pathogenic > benign), simultaneously showing the variant classes and the number of reports of the variant in each class.

 We also now display a data track of exon-capture kits from various manufacturers. This allows users to evaluate the coverage of the genome both when choosing kits for use and to assist in the interpretation of whole exome sequencing experiments.  

 We will also briefly present our coronavirus resources, both as GWAS data on the genome and viral genome data.

 Participants should have experience with the Genome Browser and are encouraged to follow along with the presentation on a separate device.  Attendees with limited experience with the Browser should view the video tutorials at http://bit.ly/ucscBasics before attending.