Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios

María Luisa Matey-Hernandez, Lasse Maretty, Jacob Malte Jensen, Bent Petersen, Jonas Andreas Sibbesen, Siyang Liu, Palle Villesen, Laurits Skov, Kirstine Belling, Christian Theil Have, Jose Maria Gonzalez-Izarzugaza, Marie Grosjean, Jette Bork-Jensen, Jakob Grove, Thomas D. Als, Shujia Huang, Yuqi Chang, Ruiqi Xu, Weijian Ye, Junhua Rao & 41 others Xiaosen Guo, Jihua Sun, Hongzhi Cao, Chen Ye, Johan v. Beusekom, Thomas Espeseth, Esben N. Flindt, Rune M. Friborg, Anders Egerup Halager, Stephanie Le Hellard, Christina M. Hultman, Francesco Lescai, Shengting Li, Ole Lund, Peter Løngren, Thomas Mailund, María Luisa Matey-Hernandez, Ole Mors, Christian N. S. Pedersen, Thomas Sicheritz-Pontén, Patrick F. Sullivan, Syed Ali , David Westergaard, Rachita Yadav, Ning Li, Xun Xu, Torben Hansen, Anders Krogh, Lars Bolund, Thorkild I. A. Sørensen, Oluf Pedersen, Ramneek Gupta, Søren Besenbacher, Anders D. Børglum, Jun Wang, Hans Eiberg, Karsten Kristiansen, Søren Brunak, Mikkel Heide Schierup, Søren Brunak, Jose M. G. Izarzugaza*

*Corresponding author for this work

    Research output: Contribution to journalJournal articleResearchpeer-review

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    Abstract

    Background: The adaptive immune response intrinsically depends on hypervariable human leukocyte antigen (HLA) genes. Concomitantly, correct HLA phenotyping is crucial for successful donor-patient matching in organ transplantation. The cost and technical limitations of current laboratory techniques, together with advances in nextgeneration sequencing (NGS) methodologies, have increased the need for precise computational typing methods. Results: We tested two widespread HLA typing methods using high quality full genome sequencing data from 150 individuals in 50 family trios from the Genome Denmark project. First, we computed descendant accuracies assessing the agreement in the inheritance of alleles from parents to offspring. Second, we compared the locus-specific homozygosity rates as well as the allele frequencies; and we compared those to the observed values in related populations. We provide guidelines for testing the accuracy of HLA typing methods by comparing family information, which is independent of the availability of curated alleles. Conclusions: Although current computational methods for HLA typing generally provide satisfactory results, our benchmark – using data with ultra-high sequencing depth – demonstrates the incompleteness of current reference databases, and highlights the importance of providing genomic databases addressing current sequencing standards, a problem yet to be resolved before benefiting fully from personalised medicine approaches HLA phenotyping is essential
    Original languageEnglish
    Article number239
    JournalB M C Bioinformatics
    Volume19
    Number of pages12
    ISSN1471-2105
    DOIs
    Publication statusPublished - 2018

    Bibliographical note

    This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

    Keywords

    • HLA genotyping
    • NGS
    • Clinical genomics
    • Population genetics
    • Prediction

    Cite this

    Matey-Hernandez, María Luisa ; Maretty, Lasse ; Jensen, Jacob Malte ; Petersen, Bent ; Andreas Sibbesen, Jonas ; Liu, Siyang ; Villesen, Palle ; Skov, Laurits ; Belling, Kirstine ; Theil Have, Christian ; Gonzalez-Izarzugaza, Jose Maria ; Grosjean, Marie ; Bork-Jensen, Jette ; Grove, Jakob ; Als, Thomas D. ; Huang, Shujia ; Chang, Yuqi ; Xu, Ruiqi ; Ye, Weijian ; Rao, Junhua ; Guo, Xiaosen ; Sun, Jihua ; Cao, Hongzhi ; Ye, Chen ; Beusekom, Johan v. ; Espeseth, Thomas ; Flindt, Esben N. ; Friborg, Rune M. ; Halager, Anders Egerup ; Le Hellard, Stephanie ; Hultman, Christina M. ; Lescai, Francesco ; Li, Shengting ; Lund, Ole ; Løngren, Peter ; Mailund, Thomas ; Matey-Hernandez, María Luisa ; Mors, Ole ; Pedersen, Christian N. S. ; Sicheritz-Pontén, Thomas ; Sullivan, Patrick F. ; Ali , Syed ; Westergaard, David ; Yadav, Rachita ; Li, Ning ; Xu, Xun ; Hansen, Torben ; Krogh, Anders ; Bolund, Lars ; Sørensen, Thorkild I. A. ; Pedersen, Oluf ; Gupta, Ramneek ; Besenbacher, Søren ; Børglum, Anders D. ; Wang, Jun ; Eiberg, Hans ; Kristiansen, Karsten ; Brunak, Søren ; Schierup, Mikkel Heide ; Brunak, Søren ; Izarzugaza, Jose M. G. / Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios. In: B M C Bioinformatics. 2018 ; Vol. 19.
    @article{55a61db161984f9cb64c5e5303f7a519,
    title = "Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios",
    abstract = "Background: The adaptive immune response intrinsically depends on hypervariable human leukocyte antigen (HLA) genes. Concomitantly, correct HLA phenotyping is crucial for successful donor-patient matching in organ transplantation. The cost and technical limitations of current laboratory techniques, together with advances in nextgeneration sequencing (NGS) methodologies, have increased the need for precise computational typing methods. Results: We tested two widespread HLA typing methods using high quality full genome sequencing data from 150 individuals in 50 family trios from the Genome Denmark project. First, we computed descendant accuracies assessing the agreement in the inheritance of alleles from parents to offspring. Second, we compared the locus-specific homozygosity rates as well as the allele frequencies; and we compared those to the observed values in related populations. We provide guidelines for testing the accuracy of HLA typing methods by comparing family information, which is independent of the availability of curated alleles. Conclusions: Although current computational methods for HLA typing generally provide satisfactory results, our benchmark – using data with ultra-high sequencing depth – demonstrates the incompleteness of current reference databases, and highlights the importance of providing genomic databases addressing current sequencing standards, a problem yet to be resolved before benefiting fully from personalised medicine approaches HLA phenotyping is essential",
    keywords = "HLA genotyping, NGS, Clinical genomics, Population genetics, Prediction",
    author = "Matey-Hernandez, {Mar{\'i}a Luisa} and Lasse Maretty and Jensen, {Jacob Malte} and Bent Petersen and {Andreas Sibbesen}, Jonas and Siyang Liu and Palle Villesen and Laurits Skov and Kirstine Belling and {Theil Have}, Christian and Gonzalez-Izarzugaza, {Jose Maria} and Marie Grosjean and Jette Bork-Jensen and Jakob Grove and Als, {Thomas D.} and Shujia Huang and Yuqi Chang and Ruiqi Xu and Weijian Ye and Junhua Rao and Xiaosen Guo and Jihua Sun and Hongzhi Cao and Chen Ye and Beusekom, {Johan v.} and Thomas Espeseth and Flindt, {Esben N.} and Friborg, {Rune M.} and Halager, {Anders Egerup} and {Le Hellard}, Stephanie and Hultman, {Christina M.} and Francesco Lescai and Shengting Li and Ole Lund and Peter L{\o}ngren and Thomas Mailund and Matey-Hernandez, {Mar{\'i}a Luisa} and Ole Mors and Pedersen, {Christian N. S.} and Thomas Sicheritz-Pont{\'e}n and Sullivan, {Patrick F.} and Syed Ali and David Westergaard and Rachita Yadav and Ning Li and Xun Xu and Torben Hansen and Anders Krogh and Lars Bolund and S{\o}rensen, {Thorkild I. A.} and Oluf Pedersen and Ramneek Gupta and S{\o}ren Besenbacher and B{\o}rglum, {Anders D.} and Jun Wang and Hans Eiberg and Karsten Kristiansen and S{\o}ren Brunak and Schierup, {Mikkel Heide} and S{\o}ren Brunak and Izarzugaza, {Jose M. G.}",
    note = "This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.",
    year = "2018",
    doi = "10.1186/s12859-018-2239-6",
    language = "English",
    volume = "19",
    journal = "B M C Bioinformatics",
    issn = "1471-2105",
    publisher = "BioMed Central Ltd.",

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    Matey-Hernandez, ML, Maretty, L, Jensen, JM, Petersen, B, Andreas Sibbesen, J, Liu, S, Villesen, P, Skov, L, Belling, K, Theil Have, C, Gonzalez-Izarzugaza, JM, Grosjean, M, Bork-Jensen, J, Grove, J, Als, TD, Huang, S, Chang, Y, Xu, R, Ye, W, Rao, J, Guo, X, Sun, J, Cao, H, Ye, C, Beusekom, JV, Espeseth, T, Flindt, EN, Friborg, RM, Halager, AE, Le Hellard, S, Hultman, CM, Lescai, F, Li, S, Lund, O, Løngren, P, Mailund, T, Matey-Hernandez, ML, Mors, O, Pedersen, CNS, Sicheritz-Pontén, T, Sullivan, PF, Ali , S, Westergaard, D, Yadav, R, Li, N, Xu, X, Hansen, T, Krogh, A, Bolund, L, Sørensen, TIA, Pedersen, O, Gupta, R, Besenbacher, S, Børglum, AD, Wang, J, Eiberg, H, Kristiansen, K, Brunak, S, Schierup, MH, Brunak, S & Izarzugaza, JMG 2018, 'Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios', B M C Bioinformatics, vol. 19, 239. https://doi.org/10.1186/s12859-018-2239-6

    Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios. / Matey-Hernandez, María Luisa; Maretty, Lasse; Jensen, Jacob Malte; Petersen, Bent; Andreas Sibbesen, Jonas; Liu, Siyang; Villesen, Palle ; Skov, Laurits; Belling, Kirstine ; Theil Have, Christian; Gonzalez-Izarzugaza, Jose Maria; Grosjean, Marie; Bork-Jensen, Jette ; Grove, Jakob; Als, Thomas D.; Huang, Shujia ; Chang, Yuqi ; Xu, Ruiqi; Ye, Weijian ; Rao, Junhua ; Guo, Xiaosen ; Sun, Jihua; Cao, Hongzhi ; Ye, Chen ; Beusekom, Johan v.; Espeseth, Thomas; Flindt, Esben N.; Friborg, Rune M. ; Halager, Anders Egerup; Le Hellard, Stephanie; Hultman, Christina M.; Lescai, Francesco; Li, Shengting; Lund, Ole; Løngren, Peter; Mailund, Thomas; Matey-Hernandez, María Luisa; Mors, Ole; Pedersen, Christian N. S.; Sicheritz-Pontén, Thomas; Sullivan, Patrick F.; Ali , Syed; Westergaard, David; Yadav, Rachita; Li, Ning ; Xu, Xun; Hansen, Torben; Krogh, Anders; Bolund, Lars; Sørensen, Thorkild I. A.; Pedersen, Oluf; Gupta, Ramneek; Besenbacher, Søren; Børglum, Anders D.; Wang, Jun; Eiberg, Hans; Kristiansen, Karsten; Brunak, Søren; Schierup, Mikkel Heide; Brunak, Søren; Izarzugaza, Jose M. G.

    In: B M C Bioinformatics, Vol. 19, 239, 2018.

    Research output: Contribution to journalJournal articleResearchpeer-review

    TY - JOUR

    T1 - Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios

    AU - Matey-Hernandez, María Luisa

    AU - Maretty, Lasse

    AU - Jensen, Jacob Malte

    AU - Petersen, Bent

    AU - Andreas Sibbesen, Jonas

    AU - Liu, Siyang

    AU - Villesen, Palle

    AU - Skov, Laurits

    AU - Belling, Kirstine

    AU - Theil Have, Christian

    AU - Gonzalez-Izarzugaza, Jose Maria

    AU - Grosjean, Marie

    AU - Bork-Jensen, Jette

    AU - Grove, Jakob

    AU - Als, Thomas D.

    AU - Huang, Shujia

    AU - Chang, Yuqi

    AU - Xu, Ruiqi

    AU - Ye, Weijian

    AU - Rao, Junhua

    AU - Guo, Xiaosen

    AU - Sun, Jihua

    AU - Cao, Hongzhi

    AU - Ye, Chen

    AU - Beusekom, Johan v.

    AU - Espeseth, Thomas

    AU - Flindt, Esben N.

    AU - Friborg, Rune M.

    AU - Halager, Anders Egerup

    AU - Le Hellard, Stephanie

    AU - Hultman, Christina M.

    AU - Lescai, Francesco

    AU - Li, Shengting

    AU - Lund, Ole

    AU - Løngren, Peter

    AU - Mailund, Thomas

    AU - Matey-Hernandez, María Luisa

    AU - Mors, Ole

    AU - Pedersen, Christian N. S.

    AU - Sicheritz-Pontén, Thomas

    AU - Sullivan, Patrick F.

    AU - Ali , Syed

    AU - Westergaard, David

    AU - Yadav, Rachita

    AU - Li, Ning

    AU - Xu, Xun

    AU - Hansen, Torben

    AU - Krogh, Anders

    AU - Bolund, Lars

    AU - Sørensen, Thorkild I. A.

    AU - Pedersen, Oluf

    AU - Gupta, Ramneek

    AU - Besenbacher, Søren

    AU - Børglum, Anders D.

    AU - Wang, Jun

    AU - Eiberg, Hans

    AU - Kristiansen, Karsten

    AU - Brunak, Søren

    AU - Schierup, Mikkel Heide

    AU - Brunak, Søren

    AU - Izarzugaza, Jose M. G.

    N1 - This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

    PY - 2018

    Y1 - 2018

    N2 - Background: The adaptive immune response intrinsically depends on hypervariable human leukocyte antigen (HLA) genes. Concomitantly, correct HLA phenotyping is crucial for successful donor-patient matching in organ transplantation. The cost and technical limitations of current laboratory techniques, together with advances in nextgeneration sequencing (NGS) methodologies, have increased the need for precise computational typing methods. Results: We tested two widespread HLA typing methods using high quality full genome sequencing data from 150 individuals in 50 family trios from the Genome Denmark project. First, we computed descendant accuracies assessing the agreement in the inheritance of alleles from parents to offspring. Second, we compared the locus-specific homozygosity rates as well as the allele frequencies; and we compared those to the observed values in related populations. We provide guidelines for testing the accuracy of HLA typing methods by comparing family information, which is independent of the availability of curated alleles. Conclusions: Although current computational methods for HLA typing generally provide satisfactory results, our benchmark – using data with ultra-high sequencing depth – demonstrates the incompleteness of current reference databases, and highlights the importance of providing genomic databases addressing current sequencing standards, a problem yet to be resolved before benefiting fully from personalised medicine approaches HLA phenotyping is essential

    AB - Background: The adaptive immune response intrinsically depends on hypervariable human leukocyte antigen (HLA) genes. Concomitantly, correct HLA phenotyping is crucial for successful donor-patient matching in organ transplantation. The cost and technical limitations of current laboratory techniques, together with advances in nextgeneration sequencing (NGS) methodologies, have increased the need for precise computational typing methods. Results: We tested two widespread HLA typing methods using high quality full genome sequencing data from 150 individuals in 50 family trios from the Genome Denmark project. First, we computed descendant accuracies assessing the agreement in the inheritance of alleles from parents to offspring. Second, we compared the locus-specific homozygosity rates as well as the allele frequencies; and we compared those to the observed values in related populations. We provide guidelines for testing the accuracy of HLA typing methods by comparing family information, which is independent of the availability of curated alleles. Conclusions: Although current computational methods for HLA typing generally provide satisfactory results, our benchmark – using data with ultra-high sequencing depth – demonstrates the incompleteness of current reference databases, and highlights the importance of providing genomic databases addressing current sequencing standards, a problem yet to be resolved before benefiting fully from personalised medicine approaches HLA phenotyping is essential

    KW - HLA genotyping

    KW - NGS

    KW - Clinical genomics

    KW - Population genetics

    KW - Prediction

    U2 - 10.1186/s12859-018-2239-6

    DO - 10.1186/s12859-018-2239-6

    M3 - Journal article

    VL - 19

    JO - B M C Bioinformatics

    JF - B M C Bioinformatics

    SN - 1471-2105

    M1 - 239

    ER -

    Matey-Hernandez ML, Maretty L, Jensen JM, Petersen B, Andreas Sibbesen J, Liu S et al. Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios. B M C Bioinformatics. 2018;19. 239. https://doi.org/10.1186/s12859-018-2239-6