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EXCAVATOR: detecting copy number variants from whole-exome sequencing data

机译:挖掘机:从全外显子组测序数据中检测拷贝数变异

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摘要

We developed a novel software tool, EXCAVATOR, for the detection of copy number variants (CNVs) from whole-exome sequencing data. EXCAVATOR combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number states. We validate EXCAVATOR on three datasets and compare the results with three other methods. These analyses show that EXCAVATOR outperforms the other methods and is therefore a valuable tool for the investigation of CNVs in largescale projects, as well as in clinical research and diagnostics. EXCAVATOR is freely available at http://sourceforge.net/projects/excavatortool/ webcite.
机译:我们开发了一种新颖的软件工具EXCAVATOR,用于从全外显子组测序数据中检测拷贝数变异(CNV)。 EXCAVATOR将三步归一化过程与新颖的异构隐马尔可夫模型算法和将基因组区域分为五个拷贝数状态的调用方法结合在一起。我们在三个数据集上验证了EXCAVATOR,并将结果与​​其他三个方法进行了比较。这些分析表明,EXCAVATOR优于其他方法,因此是在大型项目以及临床研究和诊断中研究CNV的宝贵工具。可从http://sourceforge.net/projects/excavatortool/ webcite免费获得EXCAVATOR。

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