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HLA type inference via haplotypes identical by descent.

Manu N Setty1, Alexander Gusev, Itsik Pe'er

  • 1Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|March 10, 2011
PubMed
Summary

This study introduces a novel computational method for inferring human leukocyte antigen (HLA) types from single nucleotide polymorphism (SNP) data. The approach utilizes shared segments identical by descent (IBD) for accurate and efficient HLA imputation.

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Area of Science:

  • Immunogenetics
  • Computational Biology
  • Genomics

Background:

  • Human leukocyte antigen (HLA) genes are crucial for immune response and self/non-self discrimination.
  • HLA hypervariability impacts autoimmune disease susceptibility and organ transplant matching.
  • Traditional serological HLA typing is time-consuming and costly, contrasting with high-throughput SNP data.

Purpose of the Study:

  • To develop a computational method for inferring per-locus HLA types using SNP genotype data.
  • To leverage shared segments identical by descent (IBD) for HLA type imputation.
  • To compare the novel method's performance against existing tag SNP-based approaches.

Main Methods:

  • Inferred identical by descent (IBD) segments from SNP genotype data.
  • Modeled IBD information as a graph to explore shared haplotypes.
  • Applied the method to a subset of the HapMap population with known HLA types.

Main Results:

  • Achieved high accuracy in HLA type imputation: 96% (HLA-A), 94% (HLA-B), 95% (HLA-C), 77% (HLA-DR1), 93% (HLA-DQA1), and 90% (HLA-DQB1).
  • Demonstrated superior sensitivity and specificity compared to a tag SNP-based imputation method.
  • Validated the effectiveness of using shared haplotype segments for large-scale HLA imputation.

Conclusions:

  • The novel computational method accurately infers HLA types from SNP data using IBD sharing.
  • This approach offers a more efficient and cost-effective alternative to traditional HLA typing.
  • Shared haplotype analysis provides a powerful tool for large-scale HLA imputation in genomic studies.