PyPop

PyPop performs population-genetic analyses on highly polymorphic multi-locus genotype and allele data to estimate haplotype frequencies, test Hardy–Weinberg equilibrium, detect selection, measure linkage disequilibrium (including asymmetric LD), and aggregate results across populations.

Key Features:

• Multi-locus genotype handling: Processes highly polymorphic multi-locus genotype and allele datasets.
• Data Conformity Testing: Tests conformity to Hardy–Weinberg equilibrium expectations.
• Selection Analysis: Performs Ewens–Watterson tests for selection at genetic loci.
• Haplotype Frequency Estimation: Estimates haplotype frequencies from multi-locus genotype data.
• Linkage Disequilibrium Measurement: Measures linkage disequilibrium and implements asymmetric LD measures introduced in PyPop 1.0.0.
• Significance Testing: Provides comprehensive significance testing to validate genetic analyses.
• Modern Nomenclature Support: Supports colon-delimited allele nomenclature used in immunogenetics.
• Meta-Analysis Features: Aggregates outputs across multiple populations to support meta-analysis.

Scientific Applications:

• Evolutionary Biology: Analyzes genetic variation and population structure in evolutionary studies.
• Population Genetics: Performs standard population-genetic analyses on polymorphic loci.
• Disease Association Studies: Supports disease association analyses via haplotype estimation and linkage disequilibrium measurement.
• Immunogenetics: Enables analysis of immunogenetic datasets that use colon-delimited allele names.

Methodology:

Implements Hardy–Weinberg conformity testing, Ewens–Watterson selection tests, haplotype frequency estimation, linkage disequilibrium measurement including asymmetric LD measures, significance testing, and meta-analysis aggregation across populations.