LAVAA

LAVAA visualizes multi-dimensional genome-wide association study (GWAS) results for single-nucleotide polymorphisms (SNPs) across thousands of traits to aid interpretation of biobank-scale genetic association data.

Key Features:

• Multi-dimensional visualization: Integrates P-value, effect size, case counts, trait class, and fine-mapping posterior probability for SNPs into combined representations.
• Genetic volcano plots: Extends traditional volcano plots by plotting statistical significance (P-value) against effect size while encoding additional dimensions such as case counts, trait class, and fine-mapping posterior probability.
• Cross-trait comparison: Supports simultaneous visualization and comparison of associations across thousands of traits from biobank-scale datasets.
• Locus-level interpretation: Presents multiple association metrics together to enable interpretation and prioritization of individual loci.

Scientific Applications:

• GWAS interpretation: Facilitates interpretation of GWAS signals by combining effect size and statistical significance with study-specific metrics.
• Cross-trait analysis: Enables identification of shared or distinct genetic associations across many traits.
• Fine-mapping assessment: Assists evaluation of fine-mapping posterior probabilities in the context of association strength and trait-specific parameters.

Methodology:

Uses volcano-plot-based visualizations that plot statistical significance (P-value) versus effect size and encode additional dimensions such as case counts, trait class, and fine-mapping posterior probability.