One Size Doesn't Fit All - RefEditor: Building Personalized Diploid Reference Genome to Improve Read Mapping and Genotype Calling in Next Generation Sequencing Studies.
One Size Doesn't Fit All - RefEditor: Building Personalized Diploid Reference Genome to Improve Read Mapping and Genotype Calling in Next Generation Sequencing Studies.
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DOI：
10.1371/journal.pcbi.1004448
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发表时间：
2015-08
影响因子：
4.3
通讯作者：
Qin ZS
中科院分区：
文献类型：
--
作者：
Yuan S;Johnston HR;Zhang G;Li Y;Hu YJ;Qin ZS
随着测序成本的快速下降，研究人员今天急于接受全基因组测序（WGS）或全外显子组测序（WES）方法作为将遗传变异与人类疾病和表型联系起来的下一个强大工具。分析WGS和WES数据的基本步骤是将短测序读数映射回参考基因组。这是一个重要的问题，因为不正确映射的读段影响下游变体发现、基因型识别和关联分析。尽管已经开发了许多读段作图算法，但它们中的大多数使用通用参考基因组并且不考虑序列变体。鉴于遗传变异是普遍存在的，如果它们可以被考虑到读段作图程序中，则是非常期望的。在这项工作中，我们开发了一种新的策略，利用先验获得的基因型将通用的单倍体参考基因组定制为个性化的二倍体参考基因组。新策略在名为RefEditor的程序中实现。当将RefEditor应用于真实的数据时，我们在读段作图、变体发现和基因型调用方面取得了令人鼓舞的改进。与标准方法相比，RefEditor可以显着提高基因型调用一致性（在4X覆盖率下从43%提高到61%;在20 X覆盖率下从82%提高到92%），并减少不同测序深度的孟德尔不一致性。由于许多WGS和WES研究是在先前或同时使用基于阵列的基因分型平台进行基因分型的队列中进行的，因此我们相信所提出的策略在实践中具有很高的价值，这也可以应用于在同一队列中进行多个NGS实验的情况。RefEditor源代码可在https://github.com/superyuan/refeditor上获得。
With rapid decline of the sequencing cost, researchers today rush to embrace whole genome sequencing (WGS), or whole exome sequencing (WES) approach as the next powerful tool for relating genetic variants to human diseases and phenotypes. A fundamental step in analyzing WGS and WES data is mapping short sequencing reads back to the reference genome. This is an important issue because incorrectly mapped reads affect the downstream variant discovery, genotype calling and association analysis. Although many read mapping algorithms have been developed, the majority of them uses the universal reference genome and do not take sequence variants into consideration. Given that genetic variants are ubiquitous, it is highly desirable if they can be factored into the read mapping procedure. In this work, we developed a novel strategy that utilizes genotypes obtained a priori to customize the universal haploid reference genome into a personalized diploid reference genome. The new strategy is implemented in a program named RefEditor. When applying RefEditor to real data, we achieved encouraging improvements in read mapping, variant discovery and genotype calling. Compared to standard approaches, RefEditor can significantly increase genotype calling consistency (from 43% to 61% at 4X coverage; from 82% to 92% at 20X coverage) and reduce Mendelian inconsistency across various sequencing depths. Because many WGS and WES studies are conducted on cohorts that have been genotyped using array-based genotyping platforms previously or concurrently, we believe the proposed strategy will be of high value in practice, which can also be applied to the scenario where multiple NGS experiments are conducted on the same cohort. The RefEditor sources are available at https://github.com/superyuan/refeditor.