GRANVIL

GRANVIL performs gene- or region-based association analysis of variants of intermediate and low frequency by aggregating minor alleles from rare or uncommon markers in dense genotyping or resequencing data to test associations with binary and quantitative phenotypes.

Key Features:

• Gene- or region-based aggregation: Conducts association analyses within pre-defined gene regions.
• Mutational-load approach: Implements an approach based on mutational load that aggregates minor alleles across genes to test for association.
• Phenotype support: Handles both binary (dichotomous) and quantitative phenotypes.
• Variant frequency focus: Targets rare and uncommon markers, i.e., variants of intermediate and low frequency.
• Input data types: Operates on dense genotyping and resequencing data.
• Robustness to missing data: Retains adequate power in the presence of missing genotypes for genome-wide association studies.
• Evaluation: Has been evaluated using simulated data from the Genetic Analysis Workshop 17 (GAW17).

Scientific Applications:

• Rare-variant association studies: Detect associations between aggregated rare variants and complex trait phenotypes.
• Missing heritability investigations: Investigate contributions of rare variation to the missing heritability of complex diseases and traits.
• Resequencing data analysis: Identify gene-level variant burdens from human genome resequencing datasets.
• Gene-level GWAS scans: Perform gene- or region-level scans in genome-wide association study contexts.

Methodology:

Aggregates minor alleles across genes using a mutational-load framework to test for association with phenotypes; method performance was evaluated on simulated data from Genetic Analysis Workshop 17 and shown to maintain power despite missing genotypes.