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

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Benchmarking freely available HLA typing algorithms across varying genes, coverages and typing resolutions. / Thuesen, Nikolas Hallberg; Klausen, Michael Schantz; Gopalakrishnan, Shyam; Trolle, Thomas; Renaud, Gabriel.

In: Frontiers in Immunology, Vol. 13, 987655, 2022.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Thuesen, NH, Klausen, MS, Gopalakrishnan, S, Trolle, T & Renaud, G 2022, 'Benchmarking freely available HLA typing algorithms across varying genes, coverages and typing resolutions', Frontiers in Immunology, vol. 13, 987655. https://doi.org/10.3389/fimmu.2022.987655

APA

Thuesen, N. H., Klausen, M. S., Gopalakrishnan, S., Trolle, T., & Renaud, G. (2022). Benchmarking freely available HLA typing algorithms across varying genes, coverages and typing resolutions. Frontiers in Immunology, 13, [987655]. https://doi.org/10.3389/fimmu.2022.987655

Vancouver

Thuesen NH, Klausen MS, Gopalakrishnan S, Trolle T, Renaud G. Benchmarking freely available HLA typing algorithms across varying genes, coverages and typing resolutions. Frontiers in Immunology. 2022;13. 987655. https://doi.org/10.3389/fimmu.2022.987655

Author

Thuesen, Nikolas Hallberg ; Klausen, Michael Schantz ; Gopalakrishnan, Shyam ; Trolle, Thomas ; Renaud, Gabriel. / Benchmarking freely available HLA typing algorithms across varying genes, coverages and typing resolutions. In: Frontiers in Immunology. 2022 ; Vol. 13.

Bibtex

@article{9eaa731856ab4a9aa783d11841cc7f7e,
title = "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.",
keywords = "human leukycote antigen, next-generation sequencing (NGS), whole exome sequencing, depth of coverage, algorithm, benchmark, typing resolution, MHC CLASS-I, ANTIGEN, ALIGNMENT, DONOR",
author = "Thuesen, {Nikolas Hallberg} and Klausen, {Michael Schantz} and Shyam Gopalakrishnan and Thomas Trolle and Gabriel Renaud",
year = "2022",
doi = "10.3389/fimmu.2022.987655",
language = "English",
volume = "13",
journal = "Frontiers in Immunology",
issn = "1664-3224",
publisher = "Frontiers Research Foundation",

}

RIS

TY - JOUR

T1 - Benchmarking freely available HLA typing algorithms across varying genes, coverages and typing resolutions

AU - Thuesen, Nikolas Hallberg

AU - Klausen, Michael Schantz

AU - Gopalakrishnan, Shyam

AU - Trolle, Thomas

AU - Renaud, Gabriel

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - human leukycote antigen

KW - next-generation sequencing (NGS)

KW - whole exome sequencing

KW - depth of coverage

KW - algorithm

KW - benchmark

KW - typing resolution

KW - MHC CLASS-I

KW - ANTIGEN

KW - ALIGNMENT

KW - DONOR

U2 - 10.3389/fimmu.2022.987655

DO - 10.3389/fimmu.2022.987655

M3 - Journal article

C2 - 36426357

VL - 13

JO - Frontiers in Immunology

JF - Frontiers in Immunology

SN - 1664-3224

M1 - 987655

ER -

ID: 329699999