Immunogenetr: A comprehensive toolkit for clinical HLA informatics

There is significant interest in using modern informatics processes for clinical HLA data, but there are few resources developed for clinical use. To help clinical HLA laboratories make use of best practices in informatics and align with published data standards, we developed immunogenetr for the R programming language. immunogenetr was built with tidyverse functions and principles, and uses Genotype List (GL) string, which encodes complete HLA genotypes, including ambiguities, in a single human- and machine-readable object, as the primary data structure. The package includes functions to easily convert HLA genotyping data to and from GL strings, parse and rebuild GL strings, validate and truncate allele names, search for specific alleles within a GL string, and perform matching and mismatching. The functions are highly customizable, with matching and mismatching functions including options for host-versus-graft, graft-versus-host, and bidirectional comparisons, along with configurable homozygous mismatch counting, aligned with published guidelines. The package is open-source and available on CRAN and GitHub. This manuscript gives an overview of immunogenetr, with examples of how the functions can be used in informatics pipelines. Together, this package enables standardized HLA informatics analyses across clinical and research workflows.

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Publication Details

Journal
Human Immunology
Published
2025-12-03
DOI
https://doi.org/10.1016/j.humimm.2025.111619
Primary Topic
vaccines and immunoinformatics approaches
Type
article
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article

Immunogenetr: A comprehensive toolkit for clinical HLA informatics

Nicholas K. Brown, Busra Coskun
Human Immunology
vaccines and immunoinformatics approaches
article

Immunogenetr: A comprehensive toolkit for clinical HLA informatics

Nicholas K. Brown, Busra Coskun
article en

Abstract

There is significant interest in using modern informatics processes for clinical HLA data, but there are few resources developed for clinical use. To help clinical HLA laboratories make use of best practices in informatics and align with published data standards, we developed immunogenetr for the R programming language. immunogenetr was built with tidyverse functions and principles, and uses Genotype List (GL) string, which encodes complete HLA genotypes, including ambiguities, in a single human- and machine-readable object, as the primary data structure. The package includes functions to easily convert HLA genotyping data to and from GL strings, parse and rebuild GL strings, validate and truncate allele names, search for specific alleles within a GL string, and perform matching and mismatching. The functions are highly customizable, with matching and mismatching functions including options for host-versus-graft, graft-versus-host, and bidirectional comparisons, along with configurable homozygous mismatch counting, aligned with published guidelines. The package is open-source and available on CRAN and GitHub. This manuscript gives an overview of immunogenetr, with examples of how the functions can be used in informatics pipelines. Together, this package enables standardized HLA informatics analyses across clinical and research workflows.

Human ImmunologyVol. 87(1)
University of Pennsylvania (US), Philadelphia University (US)
Openalex Percentile: Top 65%
vaccines and immunoinformatics approaches
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