Tools for building, analyzing and evaluating HLA haplotypes from families

Area of Science:

• Immunogenetics
• Population Genetics
• Bioinformatics

Background:

• Human leukocyte antigen (HLA) genes are highly polymorphic and exhibit strong linkage disequilibrium (LD), forming conserved multi-locus haplotypes.
• Estimating HLA haplotype frequencies in populations typically uses the expectation-maximization (EM) method for unrelated individuals.
• Constructing HLA haplotypes from nuclear family data allows for direct observation of allele segregation and identification of genotyping inconsistencies or crossover events.

Purpose of the Study:

• To develop standardized computational tools for building and validating HLA haplotypes from family-based allele segregation data.
• To automate the identification of HLA genotyping errors and crossover events within nuclear families.
• To facilitate accurate estimation of HLA haplotype frequencies and linkage disequilibrium (LD) measures.

Main Methods:

• Development of the HaplObserve program for automated haplotype construction and crossover event detection using family HLA allele segregation.
• Adaptation and utilization of the HLA Haplotype Validator (HLAHapV) program to compare observed and imputed haplotypes and resolve uninformative genotypes.
• Creation of the 'pould' R package for calculating HLA haplotype frequencies and estimating locus-level LD from both observed and computationally derived haplotypes.

Main Results:

• HaplObserve provides a standardized and automated method for building HLA haplotypes from family data, improving efficiency and consistency.
• HLAHapV effectively compares observed and estimated haplotypes, aiding in validation and imputation of phase for complex family structures.
• The 'pould' R package enables comprehensive analysis of HLA haplotype frequencies and LD, supporting population genetic studies.

Conclusions:

• The developed software (HaplObserve, HLAHapV, and pould) offers robust solutions for accurate HLA haplotype analysis in family-based studies.
• These tools enhance the reliability of HLA genotyping, haplotype construction, and subsequent genetic analyses.
• The improved methods contribute to a better understanding of HLA diversity, population genetics, and disease association studies.