cnvScan: a CNV screening and annotation tool to improve the clinical utility of computational CNV prediction from exome sequencing data.
cnvScan: a CNV screening and annotation tool to improve the clinical utility of computational CNV prediction from exome sequencing data.
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DOI：
10.1186/s12864-016-2374-2
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发表时间：
2016-01-14
期刊：
影响因子：
4.4
通讯作者：
Lyle R
中科院分区：
文献类型：
--
作者：
Samarakoon PS;Sorte HS;Stray-Pedersen A;Rødningen OK;Rognes T;Lyle R
随着下一代测序技术和分析方法的进步，单核苷酸变异（snv）和indel可以在外显子组测序数据中具有较高的灵敏度和特异性。最近的研究已经证明了在外显子组测序数据中检测致病拷贝数变异（CNVs）的能力。然而，外显子CNV预测程序显示出高假阳性CNV计数，这是这些程序在临床研究中适用性的主要限制因素。我们开发了一种工具（cnvScan）来提高外显子组数据中计算CNV预测的临床实用性。cnvScan可以接受来自任何CNV预测程序的输入。cnvScan包括两个步骤：CNV筛选和CNV标注。CNV筛选使用质量分数评估CNV预测，并使用内部CNV数据库对其进行改进，从而大大降低了假阳性率。注释步骤使用多个源数据集提供功能和临床相关信息。我们使用来自原发性免疫缺陷（PIDD）患者的64个外显子组，评估了cnvScan对来自5个不同预测程序的CNV预测的性能，并在来自两个不同家庭的3个个体中鉴定了引起PIDD的CNV。总之，cnvScan通过减少假阳性计数和提供注释，减少了检测致病CNVs所需的时间和精力。这提高了外显子组数据中CNV检测的临床实用性。本文的在线版本（doi:10.1186/s12864-016-2374-2）包含补充材料，可供授权用户使用。
With advances in next generation sequencing technology and analysis methods, single nucleotide variants (SNVs) and indels can be detected with high sensitivity and specificity in exome sequencing data. Recent studies have demonstrated the ability to detect disease-causing copy number variants (CNVs) in exome sequencing data. However, exonic CNV prediction programs have shown high false positive CNV counts, which is the major limiting factor for the applicability of these programs in clinical studies. We have developed a tool (cnvScan) to improve the clinical utility of computational CNV prediction in exome data. cnvScan can accept input from any CNV prediction program. cnvScan consists of two steps: CNV screening and CNV annotation. CNV screening evaluates CNV prediction using quality scores and refines this using an in-house CNV database, which greatly reduces the false positive rate. The annotation step provides functionally and clinically relevant information using multiple source datasets. We assessed the performance of cnvScan on CNV predictions from five different prediction programs using 64 exomes from Primary Immunodeficiency (PIDD) patients, and identified PIDD-causing CNVs in three individuals from two different families. In summary, cnvScan reduces the time and effort required to detect disease-causing CNVs by reducing the false positive count and providing annotation. This improves the clinical utility of CNV detection in exome data. The online version of this article (doi:10.1186/s12864-016-2374-2) contains supplementary material, which is available to authorized users.