ASHG 2026 Fine-mapping and Colocalization with Structural Variants: Practical Workflows Using GWAS and Multi-omic Summary Statistics

Description

Instructors: Yann Le Guen, Tanner Jensen

Structural variants are frequently causal at GWAS loci but are often missed in standard fine-mapping and colocalization analyses. This interactive workshop will teach practical workflows for incorporating structural variants into fine-mapping and multi-omic colocalization using GWAS and QTL summary statistics. Through guided hands-on exercises, live demonstrations, and small-group discussions, participants will learn how to evaluate candidate structural variants, interpret credible sets and posterior probabilities, and use population frequency data to prioritize variants.

Session Details:

1. Conceptual Overview and Orientation (20 minutes | interactive lecture + live polling)
   1. Brief refresher on statistical fine-mapping (credible sets, posterior inclusion probabilities) and Bayesian colocalization, with emphasis on why SVs frequently underlie GWAS signals but are missed in SNV-only analyses.
2. Guided Hands-on Activity: Identifying SV Candidates at GWAS Loci (30 minutes | guided workflow + individual and small-group exercise)
   1. Participants work through a step-by-step workflow to query GWAS summary statistics and identify nearby SVs. Activities include hands-on exploration of linkage disequilibrium, tagging quality, and SV allele frequency using provided datasets.
3. Applied Fine-mapping and Colocalization Exercise (30 minutes | guided tutorial + applied analysis)
   1. Participants follow a structured tutorial demonstrating fine-mapping and colocalization analyses that integrate SVs alongside SNVs and multi-omic QTL summary statistics. Examples highlight scenarios in which SVs enter credible sets or emerge as lead variants.
4. Practical Application and Case-Based Discussion (25 minutes | applied problem-solving + group discussion)
   1. Participants apply the learned workflows to case studies illustrating SV-driven GWAS loci, as well as rare-disease filtering scenarios. Emphasis is placed on using population SV frequency data from healthy aging cohorts to rapidly deprioritize likely benign SVs and prioritize rare or unseen variants.
5. Synthesis, Quiz, and Q&A (15 minutes | interactive quiz + discussion)
   1. Key methodological takeaways and best-practice workflows are summarized. A short quiz reinforces core concepts, followed by open discussion addressing participant questions, common pitfalls, and next steps for applying the methods to participants’ own data.

Learning Objectives:

1. Explain why structural variants are missed in SNV-only GWAS fine-mapping and colocalization analyses.
2. Identify and evaluate candidate structural variants at GWAS loci using LD, allele frequency, and annotation data.
3. Apply fine-mapping and colocalization methods that integrate structural variants with multi-omic QTL summary statistics.
4. Evaluate structural variants using population-scale frequency data from healthy aging cohorts to prioritize rare variants.

Additional Information:

Basic level; All materials required for hands-on activities—including compressed GWAS and QTL summary statistics, example datasets used during the workshop, and a containerized computing environment—will be made available to participants in advance of the session. A Docker container will be provided with all required binaries, software tools, and package dependencies pre-installed. All resources (datasets and the Docker container) will be hosted in a shared Google Drive folder, enabling participants to download materials prior to or during the workshop.