首页> 外文期刊>The American Journal of Human Genetics >Simultaneous genotype calling and haplotype phasing improves genotype accuracy and reduces false-positive associations for genome-wide association studies.
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Simultaneous genotype calling and haplotype phasing improves genotype accuracy and reduces false-positive associations for genome-wide association studies.

机译:同时进行基因型调用和单倍体定相可提高基因型准确性,并减少全基因组关联研究的假阳性关联。

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摘要

We present a novel method for simultaneous genotype calling and haplotype-phase inference. Our method employs the computationally efficient BEAGLE haplotype-frequency model, which can be applied to large-scale studies with millions of markers and thousands of samples. We compare genotype calls made with our method to genotype calls made with the BIRDSEED, CHIAMO, GenCall, and ILLUMINUS genotype-calling methods, using genotype data from the Illumina 550K and Affymetrix 500K arrays. We show that our method has higher genotype-call accuracy and yields fewer uncalled genotypes than competing methods. We perform single-marker analysis of data from the Wellcome Trust Case Control Consortium bipolar disorder and type 2 diabetes studies. For bipolar disorder, the genotype calls in the original study yield 25 markers with apparent false-positive association with bipolar disorder at a p < 10(-7) significance level, whereas genotype calls made with our method yield no associated markers at this significance threshold. Conversely, for markers with replicated association with type 2 diabetes, there is good concordance between genotype calls used in the original study and calls made by our method. Results from single-marker and haplotypic analysis of our method's genotype calls for the bipolar disorder study indicate that our method is highly effective at eliminating genotyping artifacts that cause false-positive associations in genome-wide association studies. Our new genotype-calling methods are implemented in the BEAGLE and BEAGLECALL software packages.
机译:我们提出了一种同时进行基因型调用和单倍型阶段推断的新方法。我们的方法采用了计算有效的BEAGLE单倍型-频率模型,该模型可用于具有数百万个标记和数千个样本的大规模研究。我们使用Illumina 550K和Affymetrix 500K阵列的基因型数据,比较使用我们的方法进行的基因型调用与使用BIRDSEED,CHIAMO,GenCall和ILLUMINUS基因型调用方法进行的基因型调用。我们表明,与竞争方法相比,我们的方法具有更高的基因型调用准确度,并产生更少的未调用基因型。我们对来自Wellcome Trust病例对照协会双相情感障碍和2型糖尿病研究的数据进行单标记分析。对于双相情感障碍,原始研究中的基因型调用在p <10(-7)显着性水平上产生了25个与双相情感障碍明显假阳性关联的标记,而在我们的方法阈值下,用我们的方法进行的基因型调用没有相关标记。相反,对于与2型糖尿病有重复关联的标记物,原始研究中使用的基因型调用与我们方法进行的调用之间存在良好的一致性。对我们方法的基因型进行单标记和单倍型分析的结果要求进行双相情感障碍研究,这表明我们的方法在消除引起全基因组关联研究中假阳性关联的基因分型伪影方面非常有效。我们的新基因型调用方法在BEAGLE和BEAGLECALL软件包中实现。

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