Detection of Genomic Structural Variants from Next-Generation Sequencing Data

利用新一代测序数据检测基因组结构变异

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Abstract

Structural variants are genomic rearrangements larger than 50 bp accounting for around 1% of the variation among human genomes. They impact on phenotypic diversity and play a role in various diseases including neurological/neurocognitive disorders and cancer development and progression. Dissecting structural variants from next-generation sequencing data presents several challenges and a number of approaches have been proposed in the literature. In this mini review, we describe and summarize the latest tools - and their underlying algorithms - designed for the analysis of whole-genome sequencing, whole-exome sequencing, custom captures, and amplicon sequencing data, pointing out the major advantages/drawbacks. We also report a summary of the most recent applications of third-generation sequencing platforms. This assessment provides a guided indication - with particular emphasis on human genetics and copy number variants - for researchers involved in the investigation of these genomic events.

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