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CNV-seq,一种利用高通量测序检测拷贝数变异的新方法。

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

作者信息

Xie Chao, Tammi Martti T

机构信息

Department of Biological Sciences, National University of Singapore, Singapore.

出版信息

BMC Bioinformatics. 2009 Mar 6;10:80. doi: 10.1186/1471-2105-10-80.

Abstract

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 0.1x to 8x 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.

摘要

背景

DNA拷贝数变异(CNV)已被公认为遗传变异的一个重要来源。阵列比较基因组杂交(aCGH)常用于CNV检测,但微阵列平台存在一些固有局限性。

结果

在此,我们描述了一种使用鸟枪法测序检测拷贝数变异的方法,即CNV-seq。该方法基于一个强大的统计模型,该模型描述了完整的分析过程,并允许计算检测CNV所需的置信值。我们的结果表明,读取的数量而非读取的长度是决定检测分辨率的关键因素。这有利于快速产生大量短读取的新一代测序方法。

结论

对覆盖度在0.1x至8x之间的各种测序方法进行模拟,结果显示总体特异性在91.7%至99.9%之间,灵敏度在72.2%至96.5%之间。我们还展示了评估两个人类个体基因组之间CNV的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/087b/2667514/ce31f1467c0f/1471-2105-10-80-1.jpg

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