Immunogenetic variation in humans is important in research, clinical diagnosis and increasingly a target for therapeutic intervention. Two highly polymorphic loci play critical roles, namely the human leukocyte antigen (HLA) system, which is the human version of the major histocompatibility complex (MHC), and the Killer-cell immunoglobulin-like receptors (KIR) that are relevant for responses of natural killer (NK) and some subsets of T cells. Their accurate classification has typically required the use of dedicated biological specimens and a combination of in vitro and in silico efforts. Increased availability of next generation sequencing data has led to the development of ancillary computational solutions. Here, we report an evaluation of recently published algorithms to computationally infer complex immunogenetic variation in the form of HLA alleles and KIR haplotypes from whole-genome or whole-exome sequencing data. For both HLA allele and KIR gene typing, we identified tools that yielded >97% overall accuracy for four-digit HLA types, and >99% overall accuracy for KIR gene presence, suggesting the readiness of in silico solutions for use in clinical and high-throughput research settings.

中文翻译：

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用于从临床测序数据中准确推断 HLA 和 KIR 的计算机工具支持个体患者和人群规模的免疫遗传学。

人类的免疫遗传变异在研究、临床诊断中很重要，并且越来越成为治疗干预的目标。两个高度多态性位点起着关键作用，即人类白细胞抗原 (HLA) 系统，它是主要组织相容性复合体 (MHC) 的人类版本，以及与免疫球蛋白反应相关的杀伤细胞免疫球蛋白样受体 (KIR)。自然杀伤 (NK) 和一些 T 细胞亚群。它们的准确分类通常需要使用专用的生物标本以及体外和计算机模拟的组合努力。下一代测序数据可用性的增加导致了辅助计算解决方案的发展。在这里，我们报告了对最近发表的算法的评估，以从全基因组或全外显子组测序数据中计算推断 HLA 等位基因和 KIR 单倍型形式的复杂免疫遗传变异。对于 HLA 等位基因和 KIR 基因分型，我们确定的工具对四位 HLA 类型产生了 >97% 的总体准确度，对 KIR 基因存在产生了 >99% 的总体准确度，这表明计算机解决方案已准备好用于临床和高-吞吐量研究设置。