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Updated: Jul 21, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease.

Saori Sakaue1,2,3, Saisriram Gurajala1,2,3, Michelle Curtis1,2,3

  • 1Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Nature Protocols
|July 26, 2023
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Summary
This summary is machine-generated.

This tutorial provides essential guidelines for imputing human leukocyte antigen (HLA) alleles from genotype data. It details best practices for association testing and fine-mapping to understand HLA

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Area of Science:

  • Genomics
  • Immunogenetics
  • Computational Biology

Background:

  • The human leukocyte antigen (HLA) locus significantly influences complex diseases, often explaining more heritability than other genetic loci combined.
  • In silico HLA imputation methods allow accurate estimation of HLA alleles from existing microarray data, facilitating large-scale genetic studies.
  • Existing research highlights HLA imputation's utility in identifying causal variations in autoimmune diseases and HIV infection control.

Purpose of the Study:

  • To provide comprehensive guidelines for performing human leukocyte antigen (HLA) imputation from genotype data.
  • To offer best practice recommendations for association testing and fine-mapping of HLA alleles, amino acids, and haplotypes.
  • To establish a standardized pipeline and online resource for HLA imputation analyses applicable to large-scale genotyping data.

Main Methods:

  • Detailed guidance on quality control for input genotyping data.
  • Description of local and web-based (Michigan Imputation Server) HLA allele and amino acid imputation methods.
  • Inclusion of a multi-ancestry HLA imputation reference panel for improved accuracy.

Main Results:

  • A comprehensive tutorial with step-by-step instructions and scripts for HLA imputation.
  • Best practice recommendations for association testing to identify trait-associated HLA variations.
  • An accessible online guide and software repository (https://github.com/immunogenomics/HLA_analyses_tutorial) for practical application.

Conclusions:

  • This tutorial addresses the need for standardized guidelines in HLA imputation, association testing, and fine-mapping.
  • The provided resources will enable researchers to effectively utilize large-scale genotyping data for HLA-related disease research.
  • The work aims to advance the understanding of HLA's role in human diseases across diverse global populations.