Challenges of sequencing human genomes
Challenges of sequencing human genomes
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DOI：
10.1093/bib/bbq016
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发表时间：
2010-09-01
影响因子：
9.5
通讯作者：
Wilson, Richard K.
中科院分区：
文献类型：
--
作者：
Koboldt, Daniel C.;Ding, Li;Wilson, Richard K.
大规模并行测序技术继续改变人类遗传学的研究。随着测序成本的下降，下一代测序（NGS）仪器和数据集将越来越容易被更广泛的研究界所使用。可以理解，研究人员渴望利用这些新技术的力量。然而，在这些平台上测序人类基因组提出了许多生产和生物信息学挑战。在从技术开发实验室到生产车间的过渡过程中，样品污染、文库嵌合体和运行质量可变等生产问题变得越来越严重。NGS数据的分析也仍然具有挑战性，特别是考虑到短读取长度（35-250 bp）和数据量。开发精简、高度自动化的数据分析管道对于从技术采用到加速研究和出版的过渡至关重要。这篇综述旨在描述当前NGS技术的状态，以及使NGS用户能够表征人类DNA序列变异全谱的策略。
Massively parallel sequencing technologies continue to alter the study of human genetics. As the cost of sequencing declines, next-generation sequencing (NGS) instruments and datasets will become increasingly accessible to the wider research community. Investigators are understandably eager to harness the power of these new technologies. Sequencing human genomes on these platforms, however, presents numerous production and bioinformatics challenges. Production issues like sample contamination, library chimaeras and variable run quality have become increasingly problematic in the transition from technology development lab to production floor. Analysis of NGS data, too, remains challenging, particularly given the short-read lengths (35-250 bp) and sheer volume of data. The development of streamlined, highly automated pipelines for data analysis is critical for transition from technology adoption to accelerated research and publication. This review aims to describe the state of current NGS technologies, as well as the strategies that enable NGS users to characterize the full spectrum of DNA sequence variation in humans.