iPyLAE

iPyLAE performs local ancestry estimation along genomes from whole-genome sequencing or high-density genotyping data to resolve ancestry segments in admixed populations.

Key Features:

• Local ancestry estimation: Determines local ancestry along genomes using whole-genome sequencing (WGS) or high-density genotyping data.
• Arbitrary ancestral populations: Handles an arbitrary number of ancestral populations, with or without informative priors.
• Phased and unphased support: Operates on both phased and unphased genomic data.
• Computational efficiency: Reported capability to process thousands of genomes within a single day.
• Implementation: Implemented in Python.
• Pathway enrichment sensitivity: Demonstrated detection of differentially enriched pathways with higher enrichment scores when using local ancestry versus whole-genome approaches.
• Benchmarking: Performance evaluated using the 1000 Genomes project and compared to aggregated predictions, global admixture results, and RFMix.

Scientific Applications:

• Local ancestry mapping: Delineating ancestry tracts within admixed populations for population genetics analyses.
• Pathway enrichment analysis: Identifying differentially enriched biological pathways between populations using local-ancestry-informed signals.
• Large-scale genomic studies: Scalable processing of thousands of genomes from WGS or high-density genotyping datasets.
• Method validation: Comparative evaluation of local ancestry inference against RFMix and global admixture or aggregated predictions using 1000 Genomes data.

Methodology:

Implemented in Python; accepts whole-genome sequencing and high-density genotyping input; supports phased and unphased data and an arbitrary number of ancestral populations with optional informative priors; benchmarked using the 1000 Genomes project and comparisons to aggregated predictions, global admixture results, and RFMix, with reported throughput on the order of thousands of genomes per day.