结构变异
基因组
生物
计算生物学
人类基因组
变化(天文学)
数据科学
DNA测序
基因组学
遗传学
计算机科学
进化生物学
基因
天体物理学
物理
作者
Steve S. Ho,Alexander E. Urban,Ryan E. Mills
标识
DOI:10.1038/s41576-019-0180-9
摘要
Identifying structural variation (SV) is essential for genome interpretation but has been historically difficult due to limitations inherent to available genome technologies. Detection methods that use ensemble algorithms and emerging sequencing technologies have enabled the discovery of thousands of SVs, uncovering information about their ubiquity, relationship to disease and possible effects on biological mechanisms. Given the variability in SV type and size, along with unique detection biases of emerging genomic platforms, multiplatform discovery is necessary to resolve the full spectrum of variation. Here, we review modern approaches for investigating SVs and proffer that, moving forwards, studies integrating biological information with detection will be necessary to comprehensively understand the impact of SV in the human genome.
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