MarViN

MarViN refines genotype calls using linkage-disequilibrium modeling to improve genotype inference from low-coverage whole-genome sequencing data.

Key Features:

• Efficient Modeling of Linkage-Disequilibrium: Uses a multivariate Gaussian distribution to model linkage-disequilibrium for genotype refinement from sequencing data.
• Speed and Scalability: Operates hundreds of times faster than traditional methods such as hidden Markov models and scales linearly with the number of samples.
• Applicability to Diverse Coverage Levels: Validated on both low- and high-coverage sequencing datasets for robust genotype refinement across coverage regimes.

Scientific Applications:

• Large-scale cohort genotyping: Enables cost-effective and rapid genotype inference across large genomic cohorts.
• Population genetics: Facilitates analysis of linkage patterns and allele frequency variation within populations.
• Disease association studies: Improves genotype accuracy for downstream association testing in genetic epidemiology.
• Evolutionary biology: Supports studies of genetic variation and LD structure relevant to evolutionary inference.

Methodology:

Models linkage-disequilibrium using a multivariate Gaussian distribution to refine genotypes from sequencing-derived data.