期刊
PHARMACOGENOMICS JOURNAL
卷 18, 期 3, 页码 367-376出版社
SPRINGERNATURE
DOI: 10.1038/tpj.2017.7
关键词
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资金
- Office of Naval Research (ONR) [N00014-08-1-1207]
- National Institutes of Health (NIH) - National Institute of Allergy and Infectious Diseases (NIAID) [U01AI067068, U19AI067152, R01GM109030, P01GM099568]
- National Institutes of Health (NIH) - National Institute of General Medical Sciences (NIGMS) [RO1NS076492, RO1NS046297, R01NS049477]
- National Institutes of Health (NIH) - National Institute of Neurological Disorders and Stroke (NINDS)
- National Multiple Sclerosis Society (NMSS) [RG 2899-D11]
- Race to Erase MS Junior Investigator Award
- European Federation for Immunogenetics Julia Bodmer Award
- Australian National Health and Medical Research Council (NHMRC) [1053756]
- Victorian Life Sciences Computation Initiative (VLSCI) [VR0240]
- Victorian Government's Operational Infrastructure Support Program
Four single nucleotide polymorphism (SNP)-based human leukocyte antigen (HLA) imputation methods (e-HLA, HIBAG, HLA*IMP:02 and MAGPrediction) were trained using 1000 Genomes SNP and HLA genotypes and assessed for their ability to accurately impute molecular HLA-A, -B, -C and -DRB1 genotypes in the Human Genome Diversity Project cell panel. Imputation concordance was high (>89%) across all methods for both HLA-A and HLA-C, but HLA-B and HLA-DRB1 proved generally difficult to impute. Overall, < 27.8% of subjects were correctly imputed for all HLA loci by any method. Concordance across all loci was not enhanced via the application of confidence thresholds; reliance on confidence scores across methods only led to noticeable improvement (+3.2%) for HLA-DRB1. As the HLA complex is highly relevant to the study of human health and disease, a standardized assessment of SNP-based HLA imputation methods is crucial for advancing genomic research. Considerable room remains for the improvement of HLA-B and especially HLA-DRB1 imputation methods, and no imputation method is as accurate as molecular genotyping. The application of large, ancestrally diverse HLA and SNP reference data sets and multiple imputation methods has the potential to make SNP-based HLA imputation methods a tractable option for determining HLA genotypes.
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