A Unified Approach to Genotype Imputation and Haplotype-Phase Inference for Large Data Sets of Trios and Unrelated Individuals
A Unified Approach to Genotype Imputation and Haplotype-Phase Inference for Large Data Sets of Trios and Unrelated Individuals
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DOI：
10.1016/j.ajhg.2009.01.005
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发表时间：
2009-02-13
影响因子：
9.8
通讯作者：
Browning, Sharon R.
中科院分区：
文献类型：
--
作者：
Browning, Brian L.;Browning, Sharon R.
我们提出了在无关个体和亲子三人组的大数据集中输入非基因分型标记的数据和推断单倍型阶段的方法。我们的方法利用了已知的单倍型阶段，并且我们的方法在计算上是有效的，因此可以利用拥有数千个个体的大型参考板中的全部信息。我们证明，随着参考板大小的增加，尤其是当输入低频A变异体时，推算准确度显著提高，并且非阶段性参考板能提供高精度的基因推算。我们将我们的方法放在一个统一的框架中，允许在单一分析中同时使用来自三个人和无关个人的非阶段性和阶段性数据。对于不相关的个体，我们的归罪方法产生了校准良好的后验基因概率和高精度的等位基因频率估计。对于三人组，我们的单倍型推断方法比黄金标准阶段程序14快四个数量级，并具有极好的准确性。我们的方法能够用非阶段性的三组或不相关的参照组进行基因归属，从而解释参照组中单倍型阶段的不确定性。我们提出了一个有用的估算准确度的指标，等位基因R-2，并表明该指标可以从后验的基因概率中准确地估计出来。我们的方法在Beagle软件包的3.0版中实现。
We present methods for imputing data for ungenotyped markers and for inferring haplotype phase in large data sets of unrelated individuals and parent-offspring trios. Our methods make use of known haplotype phase when it is available, and our methods are computationally efficient so that the full information in large reference panels with thousands of individuals is utilized. We demonstrate that substantial gains in imputation accuracy accrue with increasingly large reference panel sizes, particularly when imputing low-frequency A variants, and that unphased reference panels can provide highly accurate genotype imputation. We place our methodology in a unified framework that enables the simultaneous use of unphased and phased data from trios and unrelated individuals in a single analysis. For unrelated individuals, our imputation methods produce well-calibrated posterior genotype probabilities and highly accurate allele frequency estimates. For trios, our haplotype-inference method is four orders of magnitude faster than the gold-standard PHASE program 14 and has excellent accuracy. Our methods enable genotype imputation to be performed with unphased trio or unrelated reference panels, thus accounting for haplotype-phase uncertainty in the reference panel. We present a useful measure of imputation accuracy, allelic R-2, and show that this measure can be estimated accurately from posterior genotype probabilities. Our methods are implemented in version 3.0 of the BEAGLE software package.