Benchmarking freely available HLA typing algorithms across varying genes, coverages and typing resolutions

Abstract

Identifying the specific human leukocyte antigen (HLA) allele combination of an individual is crucial in organ donation, risk assessment of autoimmune and infectious diseases and cancer immunotherapy. However, due to the high genetic polymorphism in this region, HLA typing requires specialized methods. We investigated the performance of five next-generation sequencing (NGS) based HLA typing tools with a non-restricted license namely HLA*LA, Optitype, HISAT-genotype, Kourami and STC-Seq. This evaluation was done for the five HLA loci, HLA-A, -B, -C, -DRB1 and -DQB1 using whole-exome sequencing (WES) samples from 829 individuals. The robustness of the tools to lower depth of coverage (DOC) was evaluated by subsampling and HLA typing 230 WES samples at DOC ranging from 1X to 100X. The HLA typing accuracy was measured across four typing resolutions. Among these, we present two clinically-relevant typing resolutions (P group and pseudo-sequence), which specifically focus on the peptide binding region. On average, across the five HLA loci examined, HLA*LA was found to have the highest typing accuracy. For the individual loci, HLA-A, -B and -C, Optitype’s typing accuracy was the highest and HLA*LA had the highest typing accuracy for HLA-DRB1 and -DQB1. The tools’ robustness to lower DOC data varied widely and further depended on the specific HLA locus. For all Class I loci, Optitype had a typing accuracy above 95% (according to the modification of the amino acids in the functionally relevant portion of the HLA molecule) at 50X, but increasing the DOC beyond even 100X could still improve the typing accuracy of HISAT-genotype, Kourami, and STC-seq across all five HLA loci as well as HLA*LA’s typing accuracy for HLA-DQB1. HLA typing is also used in studies of ancient DNA (aDNA), which is often based on sequencing data with lower quality and DOC. Interestingly, we found that Optitype’s typing accuracy is not notably impaired by short read length or by DNA damage, which is typical of aDNA, as long as the DOC is sufficiently high.

An immunogenetic basis for lung cancer risk

“…To provide additional confidence in the robustness of our association results using imputed HLA genotypes, we assessed the concordance of HLA genotypes called from whole-exome sequencing data with imputed genotypes, both assessed in the same individuals from the UK Biobank. We used two independent, well-validated tools for genotyping of HLA -I and HLA -II—HLA*LA ( 59 ) and HLA-HD ( 60 )—both of which have strong performance relative to other methods ( 61 ). Using these methods, we genotyped HLA -I and HLA -II from 43,000 individuals from the UK Biobank on the basis of whole-exome sequencing data available from blood.…”

Full resolution HLA and KIR genes annotation for human genome assemblies

“…We in parBcular focused on the results from T1K (Song et al 2023). We did not evaluate other genotypers because most of them only work for classical HLA genes, could not genotype KIR genes, and have been evaluated in other benchmark studies (Klasberg et al 2019;Liu et al 2021;Thuesen et al 2022;Yu et al 2023). We carefully evaluated T1K for each of HLA and KIR genes (Figure 6), and also summarized in different categories (Supplemental Table S5).…”

A novel framework for human leukocyte antigen (HLA) genotyping using probe capture-based targeted next-generation sequencing and computational analysis

“…In the contemporary landscape, multiple NGS data types are amenable to HLA typing analysis via a range of software tools, including HLAminer [34] , HLAforest [35] , ATHLATES [36] , seq2HLA [37] , OptiType [38] , HLAssign [39] , HLAreporter [40] , Polysolver [41] , HLA-VBseq [42] , HLA*PRG [43] , xHLA [44] , HLA-HD [45] , HLAscan [46] , PHLAT [47] , Kourami [48] , STC-Seq [49] , OncoHLA [50] , HLA*LA [51] , HISAT-genotype [52] , arcasHLA [53] , SpecHLA [54] , T1K [55] , DRAGEN [56] , and QzType (TBG Biotechnology Corp., Taipei, Taiwan) ( http://www.tbgbio.com/en/product/product_analysis_software ) (supplementary-1). Several studies have addressed systematic comparisons [33] , [50] , [57] , [58] , [59] , however a definitive assessment, particularly considering both probe capture-based and whole-genome sequencing (WGS) approaches, remain elusive. This study explored and compared multiple HLA genotyping tools using whole-genome and capture-based sequencing data, an aspect that has not been thoroughly addressed in the literature.…”