Genome‐wide associations studies have repeatedly identified the major histocompatibility complex genomic region (6p21.3) as key in immune pathologies. Researchers have also aimed to extend the biological interpretation of associations by focusing directly on human leukocyte antigen (HLA) polymorphisms and their combination as haplotypes. To circumvent the effort and high costs of HLA typing, statistical solutions have been developed to infer HLA alleles from single‐nucleotide polymorphism (SNP) genotyping data. Though HLA imputation methods have been developed, no unified effort has yet been undertaken to share large and diverse imputation models, or to improve methods. By training the HIBAG software on SNP + HLA data generated by the Consortium on Asthma among African‐ancestry Populations in the Americas (CAAPA) to create reference panels, we highlighted the importance of (a) the number of individuals in reference panels, with a twofold increase in accuracy (from 10 to 100 individuals) and (b) the number of SNPs, with a 1.5‐fold increase in accuracy (from 500 to 24,504 SNPs). Results showed improved accuracy with CAAPA compared to the African American models available in HIBAG, highlighting the need for precise population‐matching. The SNP‐HLA Reference Consortium is an international endeavor to gather data, enhance HLA imputation and broaden access to highly accurate imputation models for the immunogenomics community.

中文翻译：

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SNP-HLA参考协会（SHLARC）：HLA和SNP数据共享，可促进以MHC为中心的基因组学分析。

全基因组关联研究反复确定了主要的组织相容性复杂基因组区域（6p21.3）是免疫病理学的关键。研究人员还旨在通过直接关注人类白细胞抗原（HLA）多态性及其作为单倍型的组合来扩展关联的生物学解释。为了避免HLA分型的工作量和高昂的成本，已经开发了统计解决方案，可以从单核苷酸多态性（SNP）基因型数据推断HLA等位基因。虽然HLA归因方法已经开发出来，尚未采取统一的措施来共享大型多样的归因模型或改进方法。通过对HIBAG软件进行培训，以了解美洲非洲裔人口中的哮喘联合会（CAAPA）生成的SNP + HLA数据，以创建参考面板，我们强调了（a）参考面板中的人数，以及准确度增加了两倍（从10个人增加到100个人），并且（b）SNP的数量增加了1.5倍（准确度从500增加到24,504个SNP）。结果显示，与HIBAG中可用的非裔美国人模型相比，CAAPA的准确性有所提高，这凸显了对精确人口匹配的需求。SNP‐HLA参考协会是一项国际努力，旨在收集数据，增强HLA 归因，并为免疫基因组学界提供了更高精度的归因模型。