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Accurate imputation of human leukocyte antigens with CookHLA

Author

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  • Seungho Cook

    (Seoul National University College of Medicine
    University of Ulsan College of Medicine & Asan Institute for Life Sciences, Asan Medical Center)

  • Wanson Choi

    (Seoul National University College of Medicine)

  • Hyunjoon Lim

    (Seoul National University)

  • Yang Luo

    (Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School
    Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School
    Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School
    Program in Medical and Population Genetics, Broad Institute of MIT and Harvard)

  • Kunhee Kim

    (Seoul National University College of Medicine
    University of Ulsan College of Medicine & Asan Institute for Life Sciences, Asan Medical Center)

  • Xiaoming Jia

    (University of California San Francisco)

  • Soumya Raychaudhuri

    (Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School
    Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School
    Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School
    Program in Medical and Population Genetics, Broad Institute of MIT and Harvard)

  • Buhm Han

    (Seoul National University College of Medicine
    University of Ulsan College of Medicine & Asan Institute for Life Sciences, Asan Medical Center
    Seoul National University)

Abstract

The recent development of imputation methods enabled the prediction of human leukocyte antigen (HLA) alleles from intergenic SNP data, allowing studies to fine-map HLA for immune phenotypes. Here we report an accurate HLA imputation method, CookHLA, which has superior imputation accuracy compared to previous methods. CookHLA differs from other approaches in that it locally embeds prediction markers into highly polymorphic exons to account for exonic variability, and in that it adaptively learns the genetic map within MHC from the data to facilitate imputation. Our benchmarking with real datasets shows that our method achieves high imputation accuracy in a wide range of scenarios, including situations where the reference panel is small or ethnically unmatched.

Suggested Citation

  • Seungho Cook & Wanson Choi & Hyunjoon Lim & Yang Luo & Kunhee Kim & Xiaoming Jia & Soumya Raychaudhuri & Buhm Han, 2021. "Accurate imputation of human leukocyte antigens with CookHLA," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21541-5
    DOI: 10.1038/s41467-021-21541-5
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    Cited by:

    1. Pooja Middha & Rohit Thummalapalli & Michael J. Betti & Lydia Yao & Zoe Quandt & Karmugi Balaratnam & Cosmin A. Bejan & Eduardo Cardenas & Christina J. Falcon & David M. Faleck & Matthew A. Gubens & S, 2024. "Polygenic risk score for ulcerative colitis predicts immune checkpoint inhibitor-mediated colitis," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    2. Zeynep Demir & Marc Raynaud & Gillian Divard & Kevin Louis & Agathe Truchot & Matthias Niemann & Renata Ponsirenas & Olivier Aubert & Arnaud Del Bello & Alexandre Hertig & Dany Anglicheau & Bethany Da, 2025. "Impact of HLA evolutionary divergence and donor-recipient molecular mismatches on antibody-mediated rejection of kidney allografts," Nature Communications, Nature, vol. 16(1), pages 1-11, December.

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