SABER

SABER infers locus-specific ancestry in admixed individuals using a Markov-hidden Markov Model (MHMM) that incorporates background linkage disequilibrium (LD) from ancestral populations.

Key Features:

• Markov-Hidden Markov Model (MHMM): SABER employs an MHMM to delineate ancestry blocks along chromosomes while explicitly accounting for background LD in ancestral populations.
• Support for multiple ancestral groups: SABER handles scenarios with more than two ancestral populations and allows distinct admixture times for each ancestral population.
• Simulation-based validation: SABER uses simulations to validate ancestry inference accuracy and to demonstrate the impact of modeling background LD, including cases relevant to indigenous populations.
• High-density SNP panels: SABER utilizes high-density single-nucleotide polymorphism (SNP) panels to identify genomic ancestry blocks without requiring ancestry-informative-marker panels.

Scientific Applications:

• Population genetics: Delineating ancestry blocks to infer gene-flow patterns, genetic structure, human evolution, and migration in admixed populations.
• Admixture mapping: Identifying genomic regions associated with traits or diseases in admixed individuals without requiring specialized ancestry-informative markers.

Methodology:

Constructs a Markov-hidden Markov Model (MHMM) that integrates background LD from ancestral populations, supports multiple ancestral groups with distinct admixture times, and uses high-density SNP genotype data; the model is validated through simulations.