Multi-Population Classical HLA Type Imputation
Multi-Population Classical HLA Type Imputation
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DOI：
10.1371/journal.pcbi.1002877
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发表时间：
2013-02-01
影响因子：
4.3
通讯作者：
McVean, Gil
中科院分区：
文献类型：
--
作者：
Dilthey, Alexander;Leslie, Stephen;McVean, Gil
在病例对照研究中，经典的HLA等位基因的统计归因已成为识别和精细定位MHC疾病关联信号的有价值的工具。然而，对不同群体的归因仍然具有挑战性，主要是因为结合不同来源的参考小组引入了额外的单倍型异质性。我们提出了一个HLA型归因模型，HLAIMP：02，设计用于在多群体参考小组上操作。HL A*IMP：02基于单倍型结构的图形表示。我们提出了一种概率算法来为HLA区域建立这样的模型，考虑了基因分型错误、单倍型异质性和对HLA基因座最大精度的需求，推广了Browning和Browning 2007)和Ron等人的工作。1998年)。HL*IMP：02在不同的欧洲小组上实现了平均4位数的归因准确性，呼叫率为97%)。在非欧洲样本中，对于大多数可获得数据的基因座和种族，两位数的性能超过90%。HL A*IMP：02支持HLA-DPB1和HLA-DRB3-5的拼接，高度容忍拼接面板中的缺失数据，并使用流行的基因芯片的标准基因数据。它以源代码的形式公开提供，并且是一个用户友好的Web服务框架。
Statistical imputation of classical HLA alleles in case-control studies has become established as a valuable tool for identifying and fine-mapping signals of disease association in the MHC. Imputation into diverse populations has, however, remained challenging, mainly because of the additional haplotypic heterogeneity introduced by combining reference panels of different sources. We present an HLA type imputation model, HLA*IMP:02, designed to operate on a multi-population reference panel. HLA*IMP:02 is based on a graphical representation of haplotype structure. We present a probabilistic algorithm to build such models for the HLA region, accommodating genotyping error, haplotypic heterogeneity and the need for maximum accuracy at the HLA loci, generalizing the work of Browning and Browning 2007) and Ron et al. 1998). HLA*IMP:02 achieves an average 4-digit imputation accuracy on diverse European panels of 97% call rate 97%). On non-European samples, 2-digit performance is over 90% for most loci and ethnicities where data available. HLA*IMP: 02 supports imputation of HLA-DPB1 and HLA-DRB3-5, is highly tolerant of missing data in the imputation panel and works on standard genotype data from popular genotyping chips. It is publicly available in source code and as a user-friendly web service framework.