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CNV-seq, a new method to detect copy number variation using high-throughput sequencing

机译:CNV-seq,一种使用高通量测序检测拷贝数变异的新方法

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Background DNA copy number variation (CNV) has been recognized as an important source of genetic variation. Array comparative genomic hybridization (aCGH) is commonly used for CNV detection, but the microarray platform has a number of inherent limitations. Results Here, we describe a method to detect copy number variation using shotgun sequencing, CNV-seq. The method is based on a robust statistical model that describes the complete analysis procedure and allows the computation of essential confidence values for detection of CNV. Our results show that the number of reads, not the length of the reads is the key factor determining the resolution of detection. This favors the next-generation sequencing methods that rapidly produce large amount of short reads. Conclusion Simulation of various sequencing methods with coverage between 0.1× to 8× show overall specificity between 91.7 – 99.9%, and sensitivity between 72.2 – 96.5%. We also show the results for assessment of CNV between two individual human genomes.
机译:背景DNA拷贝数变异(CNV)被认为是遗传变异的重要来源。阵列比较基因组杂交(aCGH)通常用于CNV检测,但是微阵列平台具有许多固有的局限性。结果在这里,我们描述了一种使用shot弹枪测序CNV-seq检测拷贝数变异的方法。该方法基于描述完整分析过程的鲁棒统计模型,并允许计算用于检测CNV的基本置信度值。我们的结果表明,读取次数而不是读取长度是决定检测分辨率的关键因素。这有利于迅速产生大量短读的下一代测序方法。结论对覆盖范围在0.1倍至8倍之间的各种测序方法进行的仿真显示,总体特异性在91.7%至99.9%之间,灵敏度在72.2%至96.5%之间。我们还显示了两个单独的人类基因组之间的CNV评估结果。

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