A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to Select the Most Likely Human Leukocyte Antigen Genotype

Abstract

BackgroundHigh-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using next-generation sequencing (NGS) data are insufficiently accurate.Materials and MethodsWe compared availability, accuracy, correction score, and complementary ratio of eight HLA genotyping tools (OptiType, HLA-HD, PHLAT, seq2HLA, arcasHLA, HLAscan, HLA*LA, and Kourami) using 1,005 cases from the 1000 Genomes Project data. We created a new HLA-genotyping algorithm combining tools based on the precision and the accuracy of tools’ combinations. Then, we assessed the new algorithm’s performance in 39 in-house samples with normal whole-exome sequencing (WES) data and polymerase chain reaction–sequencing-based typing (PCR-SBT) results.ResultsRegardless of the type of tool, the calls presented by more than six tools concordantly showed high accuracy and precision. The accuracy of the group with at least six concordant calls was 100% (97/97) in HLA-A, 98.2% (112/114) in HLA-B, 97.3% (142/146) in HLA-C. The precision of the group with at least six concordant calls was over 98% in HLA-ABC. We additionally calculated the accuracy of the combination tools considering the complementary ratio of each tool and the accuracy of each tool, and the accuracy was over 98% in all groups with six or more concordant calls. We created a new algorithm that matches the above results. It was to select the HLA type if more than six out of eight tools presented a matched type. Otherwise, determine the HLA type experimentally through PCR-SBT. When we applied the new algorithm to 39 in-house cases, there were more than six matching calls in all HLA-A, B, and C, and the accuracy of these concordant calls was 100%.ConclusionsHLA genotyping accuracy using NGS data could be increased by combining the current HLA genotyping tools. This new algorithm could also be useful for preliminary screening to decide whether to perform an additional PCR-based experimental method instead of using tools with NGS data.

Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data

“…On the other hand, HLAminer, HLA-VBSeq and HLAScan performed rather poorly in our benchmark. Similar trends were observed in previous independent benchmarking studies [14,17,19– 23] that focused on a subset of tools and/or genes (Table S4), with the exception of xHLA where we obtained considerably higher accuracies on WES data than reported in a study by Chen et al [19]. The optimal strategy for HLA genotyping depends on a few factors: the availability of DNA or RNA data, the size of the dataset that needs to be analysed and the available computational resources.…”

“…On the other hand, HLAminer, HLA-VBSeq and HLAScan performed rather poorly in our benchmark. Similar trends were observed in previous independent benchmarking studies [14,17,[19][20][21][22][23]] that focused on a subset of tools and/or genes (Table S4), with the exception of xHLA where we obtained considerably higher accuracies on WES data than reported in a study by Chen et al [19].…”

“…For MHC-II genotyping there is currently no consensus about the best method. Several benchmarks have been performed previously [14,[16][17][18][19][20][21][22][23], but these were either not applied to MHC class II or did not include some recently published tools.…”

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

“…The 50 WES samples with the highest DOC from the 1000G dataset were used to simulate an aDNA dataset. Samples were High typing accuracy in previous studies (25,26,28).…”

Benchmarking freely available human leukocyte antigen typing algorithms across varying genes, coverages and typing resolutions

“…In these cases, predictions by the tools were counted as correct if they matched any combination of correct alleles. Some of the samples in this dataset were also used in the development of the HLA typing tools or at least included in the proof of concept study in the original articles introducing High typing accuracy in previous studies (20,21,36) Only offers typing of class I alleles and only considers the most frequent alleles, leading to certain typing errors when encountering rare alleles.…”