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RBV: Read balance validator, a tool for prioritising copy number variations in germline conditions

机译:RBV:读取平衡验证器,一种用于优先考虑种系条件的拷贝数变化的工具

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The popularisation and decreased cost of genome resequencing has resulted in an increased use in molecular diagnostics. While there are a number of established and high quality bioinfomatic tools for identifying small genetic variants including single nucleotide variants and indels, currently there is no established standard for the detection of copy number variants (CNVs) from sequence data. The requirement for CNV detection from high throughput sequencing has resulted in the development of a large number of software packages. These tools typically utilise the sequence data characteristics: read depth, split reads, read pairs, and assembly-based techniques. However, the additional source of information from read balance (defined as relative proportion of reads of each allele at each position) has been underutilised in the existing applications. Here we present Read Balance Validator (RBV), a bioinformatic tool that uses read balance for prioritisation and validation of putative CNVs. The software simultaneously interrogates nominated regions for the presence of deletions or multiplications, and can differentiate larger CNVs from diploid regions. Additionally, the utility of RBV to test for inheritance of CNVs is demonstrated in this report. RBV is a CNV validation and prioritisation bioinformatic tool for both genome and exome sequencing available as a python package from https://github.com/whitneywhitford/RBV.
机译:基因组重构的普及和降低成本导致分子诊断的使用增加。虽然存在许多建立和高质量的生物族工具,用于识别小型遗传变体,包括单核苷酸变体和诱导,目前没有建立从序列数据检测拷贝数变体(CNV)的标准。从高吞吐量测序中的CNV检测要求导致了大量软件包的开发。这些工具通常利用序列数据特性:读取深度,分流读取,读对和基于组装的技术。然而,来自读取余额的附加信息来源(定义为每个位置的每个等位基因的读取的相对比例)已经未充分利用现有应用程序。在这里,我们呈现读取平衡验证器(RBV),一种生物信息工具,它使用读取余额来优先考虑和验证推定的CNV。该软件同时询问指定区域是否存在删除或乘法,并且可以从二倍体区域区分更大的CNV。此外,在本报告中,证明了RBV对CNV的遗传测试的效用。 RBV是一种CNV验证和优先级,用于基因组和外壳序列的优先级序列,作为来自HTTPS://github.com/WhitneyWhitford/RBV的Python包。

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