Structural variation in the sequencing era

Steve S. Ho

doi:10.1038/s41576-019-0180-9

2019-11-15

349

Steve S. Ho

Alexander E. Urban

Ryan E. Mills *

DOI：10.1038/s41576-019-0180-9

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摘要

En 中文

识别结构变异 (SV) 对于基因组解释至关重要，但由于可用基因组技术固有的局限性，历史上一直很困难。使用集成算法和新兴测序技术的检测方法已经能够发现数千个sv，揭示有关它们的普遍性，与疾病的关系以及对生物机制的可能影响的信息。鉴于SV类型和大小的可变性，以及新兴基因组平台的独特检测偏差，多平台发现对于解决全谱变异是必要的。在这里，我们回顾了研究SV的现代方法，并提出，向前迈进，将生物信息与检测相结合的研究对于全面了解SV在人类基因组中的影响是必要的。为了绘制人类基因组中结构变异的全部范围，需要改进短读方法的检测方法。这篇综述讨论了集成算法和新兴测序技术如何帮助解决结构变异的全部问题。

Keyword:

COPY-NUMBER VARIATION

NEXT-GENERATION

SINGLE-MOLECULE

HUMAN GENOME

PAIRED-END

VARIANT DISCOVERY

CANCER

IMPACT

REARRANGEMENTS

TRANSCRIPTOME

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期刊

Nature Reviews Genetics

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论文数:

4.0K

被引数:

4.3W

机构

University of Michigan

学者数:

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论文数: 5.3W

被引数: 124

university of michigan system

学者数:

9.1W

论文数: 8.6W

被引数: 133

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