HapReads

HapReads infers haplotypes from short reads generated by high-throughput sequencing to support population genomics analyses.

Key Features:

• Direct haplotype inference: Uses a probabilistic model tailored for short read data to infer haplotypes directly from reads without prior genotype calling.
• Integer Linear Programming (ILP): Applies integer linear programming for datasets with absent or minimal recombination, approximating local genealogical history as a perfect phylogeny to identify optimal haplotypes.
• Heuristic method for larger datasets: Employs a heuristic approach to extend applicability to larger datasets and scenarios with recombination.

Scientific Applications:

• Population genomics: Infers haplotype structure from short reads to support analyses of population-level genetic variation.
• Genetic diversity and evolutionary biology: Enables investigation of haplotype patterns relevant to diversity and evolutionary inference.
• Disease-associated variant mapping: Supports identification and phasing of variants from short-read data for studies of disease-associated loci.
• Analyses across dataset complexities: Applicable to modest-sized datasets without recombination and to larger datasets that include recombination.

Methodology:

HapReads implements a probabilistic model for short reads; uses integer linear programming under an assumed perfect phylogeny when recombination is absent or minimal; and applies a heuristic method for larger datasets and recombinant regions.