Park Tae-Joon, Heo Lyong, Moon Sanghoon, Kim Young Jin, Oh Ji Hee, Han Sohee, Kim Bong-Jo
Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Centers for Disease Control and Prevention, Chungcheongbuk-do 363-700, Republic of Korea.
Int J Genomics. 2015;2015:421715. doi: 10.1155/2015/421715. Epub 2015 Dec 27.
Exome-based genotyping arrays are cost-effective and have recently been used as alternative platforms to whole-exome sequencing. However, the automated clustering algorithm in an exome array has a genotype calling problem in accuracy for identifying rare and low-frequency variants. To address these shortcomings, we present a practical approach for accurate genotype calling using the Illumina Infinium HumanExome BeadChip. We present comparison results and a statistical summary of our genotype data sets. Our data set comprises 14,647 Korean samples. To solve the limitation of automated clustering, we performed manual genotype clustering for the targeted identification of 46,076 variants that were identified using GenomeStudio software. To evaluate the effects of applying custom cluster files, we tested cluster files using 804 independent Korean samples and the same platform. Our study firstly suggests practical guidelines for exome chip quality control in Asian populations and provides valuable insight into an association study using exome chip.
基于外显子组的基因分型阵列具有成本效益,最近已被用作全外显子组测序的替代平台。然而,外显子组阵列中的自动聚类算法在识别罕见和低频变异的基因型调用准确性方面存在问题。为了解决这些缺点,我们提出了一种使用Illumina Infinium HumanExome BeadChip进行准确基因型调用的实用方法。我们展示了比较结果和基因型数据集的统计摘要。我们的数据集包含14,647个韩国样本。为了解决自动聚类的局限性,我们对使用GenomeStudio软件识别的46,076个变异进行了手动基因型聚类,以进行靶向识别。为了评估应用自定义聚类文件的效果,我们使用804个独立的韩国样本和相同平台测试了聚类文件。我们的研究首先提出了亚洲人群外显子组芯片质量控制的实用指南,并为使用外显子组芯片的关联研究提供了有价值的见解。