Conditions: Diabetes Mellitus, Diabetes Mellitus, Type 1
Division: DEM
Available Genotype Data: No
Image Summary: No
Transplant Type: None
Does it have dialysis patients: No
Data Package Version Number: 1 (June 1, 2015)
DOI: 10.58020/63vn-7d44
How to cite this dataset: Rich, Stephen (2023). T1DGC HLA Reference Panel for Imputation with SNP2HLA (V1) [Dataset]. NIDDK Central Repository. https://doi.org/10.58020/63vn-7d44
Data availability statement: Data from the T1DGC HLA Reference Panel for Imputation with SNP2HLA [(V1)/https://doi.org/10.58020/63vn-7d44] reported here are available for request at the NIDDK Central Repository (NIDDK-CR) website, Resources for Research (R4R), https://repository.niddk.nih.gov/.
The T1DGC Immunochip/HLA Reference Panel (described in Jia et al., PLoS ONE 2013; Jun 6;8(6):e64683) enables accurate imputation of classical HLA types starting from SNP genotype data. Exploiting long-range linkage disequilibrium between HLA loci and SNP markers across the major histocompatibility complex (MHC) region, a computational strategy, called SNP2HLA, has been developed to impute classical alleles and amino acid polymorphisms at class I (HLA-A, -B, -C) and class II (-DPA1, -DPB1, -DQA1, -DQB1, and -DRB1) loci. A European ancestry reference panel was constructed based on data collected by the Type 1 Diabetes Genetics Consortium (T1DGC, 5,225 individuals). For validation, HLA alleles were imputed in the British 1958 Birth Cohort (N = 918) with gold-standard four-digit HLA types and SNPs genotyped using the Affymetrix GeneChip 500K and Illumina ImmunoChip microarrays. Using the T1DGC reference panel, the average accuracy at four-digit resolution is 96.7% using the high-density Illumina Immunochip. For amino acid polymorphisms within HLA genes, accuracy was 99.3% using the Illumina ImmunoChip. A link to the SNP2HLA software via the Broad institute is located below. The T1DGC reference panel can be accessed by submitting a request from this page.
Note: The panel may only be used for research in the areas of diabetes, autoimmune diseases and diabetes complications.