RBV

RBV validates and prioritizes copy number variants (CNVs) in whole-exome and whole-genome sequencing datasets by analyzing allele-level read balance to assess candidate deletions and duplications.

Key Features:

• Read balance analysis: Uses the relative proportion of reads for each allele at genomic positions to inform CNV assessment.
• CNV prioritization and validation: Assigns likelihoods to putative CNVs to prioritize genuine events for further analysis.
• Nominated-region interrogation: Examines user-nominated genomic regions for evidence of deletions or duplications (multiplications).
• Simultaneous regional interrogation: Performs concurrent analysis of multiple genomic regions to evaluate CNV signals.
• Deletion and duplication detection: Differentiates putative deletions and duplications based on allele balance patterns.
• Distinguishing large CNVs from diploid regions: Identifies larger CNVs and discriminates them from diploid background signal.
• Inheritance testing: Supports testing for inheritance patterns of CNVs in familial or hereditary contexts.
• Complementary evidence integration: Provides read-balance-based evidence that complements read depth, split reads, and assembly-based methods.
• Sequencing technology compatibility: Applicable to whole exome sequencing (WES) and whole genome sequencing (WGS) datasets.

Scientific Applications:

• Germline CNV validation in clinical diagnostics: Provides allele-balance evidence to validate candidate CNVs in diagnostic sequencing data.
• CNV prioritization in research cohorts: Ranks putative CNVs in WES/WGS studies to focus downstream validation efforts.
• Familial segregation and inheritance studies: Tests inheritance patterns of CNVs to support studies of hereditary conditions.
• Integration with other CNV detection methods: Serves as an orthogonal source of evidence alongside read depth, split-read, and assembly-based approaches.
• Reduction of false positives from diploid regions: Helps distinguish true large CNVs from diploid variation to improve specificity.

Methodology:

Computationally analyses allele-specific read balance (relative read proportions per allele) at genomic positions across nominated regions, interrogates regions simultaneously to assess likelihoods of deletions or duplications, and supports inheritance testing while providing evidence complementary to read depth, split reads, and assembly-based methods.