Accurate imputation of human leukocyte antigens with CookHLA

Seungho Cook, Wanson Choi, Hyunjoon Lim, Yang Luo, Kunhee Kim, Xiaoming Jia, Soumya Raychaudhuri and Buhm Han ()
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Seungho Cook: Seoul National University College of Medicine
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
Kunhee Kim: Seoul National University College of Medicine
Xiaoming Jia: University of California San Francisco
Soumya Raychaudhuri: Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School
Buhm Han: Seoul National University College of Medicine

Nature Communications, 2021, vol. 12, issue 1, 1-11

Abstract: 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.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21541-5

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DOI: 10.1038/s41467-021-21541-5

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