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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.

More information Original publication

DOI

10.1038/s41467-021-21541-5

Type

Journal article

Publication Date

2021-02-24T00:00:00+00:00

Volume

12

Keywords

Alleles, Asian People, Diabetes Mellitus, Type 1, Genome, Human, Genome-Wide Association Study, Genotype, HLA Antigens, Humans, Models, Theoretical, Phenotype, Polymorphism, Single Nucleotide