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一个用于改进全基因组和外显子组测序数据变异检测的高效且可调节的参数。

An efficient and tunable parameter to improve variant calling for whole genome and exome sequencing data.

作者信息

Ahn Yong Ju, Markkandan Kesavan, Baek In-Pyo, Mun Seyoung, Lee Wooseok, Kim Heui-Soo, Han Kyudong

机构信息

Department of Nanobiomedical Science & BK21 PLUS NBM Global Research Center for Regenerative Medicine, Dankook University, Cheonan, Republic of Korea.

Theragen Etex Inc., Suwon, Republic of Korea.

出版信息

Genes Genomics. 2018 Jan;40(1):39-47. doi: 10.1007/s13258-017-0608-6. Epub 2017 Aug 29.

DOI:10.1007/s13258-017-0608-6
PMID:29892897
Abstract

Next generation sequencing (NGS) has traditionally been performed in various fields including agricultural to clinical and there are so many sequencing platforms available in order to obtain accurate and consistent results. However, these platforms showed amplification bias when facilitating variant calls in personal genomes. Here, we sequenced whole genomes and whole exomes from ten Korean individuals using Illumina and Ion Proton, respectively to find the vulnerability and accuracy of NGS platform in the GC rich/poor area. Overall, a total of 1013 Gb reads from Illumina and ~39.1 Gb reads from Ion Proton were analyzed using BWA-GATK variant calling pipeline. Furthermore, conjunction with the VQSR tool and detailed filtering strategies, we achieved high-quality variants. Finally, each of the ten variants from Illumina only, Ion Proton only, and intersection was selected for Sanger validation. The validation results revealed that Illumina platform showed higher accuracy than Ion Proton. The described filtering methods are advantageous for large population-based whole genome studies designed to identify common and rare variations associated with complex diseases.

摘要

下一代测序(NGS)传统上已在包括农业到临床等各个领域中进行,并且有许多测序平台可用于获得准确和一致的结果。然而,这些平台在促进个人基因组中的变异检测时表现出扩增偏差。在这里,我们分别使用Illumina和Ion Proton对十名韩国个体的全基因组和全外显子组进行测序,以发现NGS平台在富含/缺乏GC区域的易感性和准确性。总体而言,使用BWA-GATK变异检测流程分析了来自Illumina的总共1013Gb读数和来自Ion Proton的约39.1Gb读数。此外,结合VQSR工具和详细的过滤策略,我们获得了高质量的变异。最后,仅从Illumina、仅从Ion Proton以及两者交集的十个变异中各选择一个进行桑格验证。验证结果表明Illumina平台比Ion Proton具有更高的准确性。所描述的过滤方法对于旨在识别与复杂疾病相关的常见和罕见变异的基于大群体的全基因组研究是有利的。

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