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Single haplotype admixture models using large scale HLA genotype frequencies to reproduce human admixture

机译:使用大规模HLA基因型频率来复制人类混合物的单倍单倍型混合物模型

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摘要

The human leukocyte antigen (HLA) is the most polymorphic region in humans. Anthropologists use HLA to trace populations' migration and evolution. However, recent admixture between populations can mask the ancestral haplotype frequency distribution. We present a statistical method based on high-resolution HLA haplotype frequencies to resolve population admixture using a non-negative matrix factorization formalism and validated using haplotype frequencies from 56 world populations. The result is a minimal set of source components (SCs) decoding roughly 90% of the total variance in the studied admixtures. These SCs agree with the geographical distribution, phylogenies, and recent admixture events of the studied groups. With the growing population of multi-ethnic individuals, or individuals that do not report race/ethnic information, the HLA matching process for stem-cell and solid organ transplants is becoming more challenging. The presented algorithm provides a framework that facilitates the breakdown of highly admixed populations into SCs, which can be used to better match the rapidly growing population of multi-ethnic individuals worldwide.
机译:人白细胞抗原(HLA)是人类中最多态性的区域。人类学家使用HLA追踪人口的迁移和演变。然而,最近群体的混合物可以掩盖祖先的单倍型频率分布。我们介绍了一种基于高分辨率HLA单倍型频率的统计方法,以解决使用非负矩阵分解形式主义和使用56个世界人群的单倍型频率进行验证的人口混合物。结果是最小的源组件(SCS)解码了所研究的混合器总方差的大约90%。这些SCS与学习群体的地理分布,文学和最近的混合物事件一致。随着越来越多的多民族人口,或者没有报告种族/民族信息的个人,干细胞和固体器官移植的HLA匹配过程变得越来越具有挑战性。呈现的算法提供了一种框架,便于将高度混合群体分解为SCS的框架,这可以用于更好地匹配全世界的多族裔人群。

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