CNVnator: An approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing
CNVnator: An approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing
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DOI：
10.1101/gr.114876.110
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发表时间：
2011-06-01
期刊：
影响因子：
7
通讯作者：
Gerstein, Mark
中科院分区：
文献类型：
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作者：
Abyzov, Alexej;Urban, Alexander E.;Gerstein, Mark
基因组中的拷贝数变异（CNV）是一种复杂的现象，尚未被完全理解。我们开发了一种名为CNVnator的方法，用于从个人基因组测序的读长深度（RD）分析中发现CNV并进行基因分型。我们的方法基于将已有的均值漂移方法与其他改进措施（多带宽划分和GC校正）相结合，以扩大所发现CNV的范围。我们利用1000基因组计划所进行的广泛验证对CNVnator进行了校准。因此，我们可以使用CNVnator在人群中发现CNV并进行基因分型，以及对非典型CNV（如新生和多等位基因事件）进行特征描述。总体而言，对于可通过RD检测到的CNV，CNVnator具有高灵敏度（86% - 96%）、低假发现率（3% - 20%）、高基因分型准确性（93% - 95%）以及在断点发现方面的高分辨率（
Copy number variation (CNV) in the genome is a complex phenomenon, and not completely understood. We have developed a method, CNVnator, for CNV discovery and genotyping from read-depth (RD) analysis of personal genome sequencing. Our method is based on combining the established mean-shift approach with additional refinements (multiple-bandwidth partitioning and GC correction) to broaden the range of discovered CNVs. We calibrated CNVnator using the extensive validation performed by the 1000 Genomes Project. Because of this, we could use CNVnator for CNV discovery and genotyping in a population and characterization of atypical CNVs, such as de novo and multi-allelic events. Overall, for CNVs accessible by RD, CNVnator has high sensitivity (86%-96%), low false-discovery rate (3%-20%), high genotyping accuracy (93%-95%), and high resolution in breakpoint discovery (