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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
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Personalized Peptide Arrays for Detection of HLA Alloantibodies in Organ Transplantation
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Comparison of HLA allelic imputation programs.

Jason H Karnes1, Christian M Shaffer2, Lisa Bastarache3

  • 1Department of Pharmacy Practice and Science, University of Arizona College of Pharmacy, Tucson, Arizona, United States of America.

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|February 17, 2017
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Summary

Comparing human leukocyte antigen (HLA) imputation programs revealed SNP2HLA offers superior call rates and imputed allele counts. Concordance varied by race, with higher accuracy from genome-wide association study (GWAS) data.

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Area of Science:

  • Immunogenetics
  • Genomic Medicine
  • Bioinformatics

Background:

  • Human Leukocyte Antigen (HLA) alleles are crucial in disease and widely studied using genome-wide association study (GWAS) data.
  • HLA sequencing is complex, making imputation from single nucleotide polymorphism (SNP) data an attractive alternative.
  • Comprehensive evaluations of HLA imputation tools are limited.

Purpose of the Study:

  • To compare the performance of three HLA imputation programs: HIBAG, SNP2HLA, and HLA*IMP:02.
  • To evaluate imputation accuracy against four-digit HLA sequencing in a large cohort.
  • To identify factors influencing imputation accuracy, including genotyping platform and race/ethnicity.

Main Methods:

  • Compared HLA imputation results from HIBAG, SNP2HLA, and HLA*IMP:02 against 4-digit HLA sequencing in 3,265 BioVU samples.
  • Utilized long-read sequencing for HLA-A, -B, -C, -DRB1, -DPB1, and -DQB1.
  • Genotyped samples using Illumina HumanExome BeadChip and a GWAS platform, comparing call and concordance rates.

Main Results:

  • Overall concordance rates were similar across programs for European Americans (approx. 97%).
  • SNP2HLA demonstrated a significant advantage in call rate and the number of imputed alleles.
  • Concordance rates were lower for African Americans, and higher accuracy was achieved using GWAS platforms compared to the HumanExome BeadChip.

Conclusions:

  • SNP2HLA shows superior performance in HLA imputation, particularly regarding call rates and imputed allele numbers.
  • Genotyping platform choice significantly impacts HLA imputation accuracy, with high genomic coverage being preferable.
  • Findings offer guidance for selecting HLA imputation methods and highlight their current limitations, especially across diverse ancestries.