RAVAQ

RAVAQ performs region-based rare variant association analysis on next-generation sequencing (NGS) data by applying quality-control steps that account for case-control status to mitigate batch effects across sequencing platforms.

Key Features:

• Pipeline structure: A five-step pipeline organized for region-based rare variant association analysis.
• Quality control (QC): A QC workflow comprising three explicit steps that account for case-control status to maintain comparability across datasets.
• Batch-effect mitigation: Methods to mitigate batch effects and comparability issues between case-control datasets generated on different sequencing platforms.
• VQSR comparison: QC approach reported to remove inflation caused by spurious signals and to outperform Variant Quality Score Recalibration (VQSR) in this respect.
• Variant qualification: Support for defining and selecting qualifying variants according to research-specific criteria.
• Association testing: Performs rare variant association tests on a per-genomic-region basis.
• Implementation: Implemented as an R package with configurable analysis arguments.

Scientific Applications:

• Region-based rare variant studies: Analysis of rare variant associations aggregated by genomic regions.
• Cross-platform case-control studies: Genetic association analyses involving case-control datasets generated on different sequencing platforms.
• Phenotype and disease association: Identification of associations between rare genetic variants and phenotypic traits or diseases.
• Genetic epidemiology: Applications in genetic epidemiology and related disciplines requiring stringent QC and region-based testing.

Methodology:

A five-step pipeline with a three-step QC that accounts for case-control status, user-defined selection of qualifying variants, and per-genomic-region rare variant association testing, implemented as an R package.