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Performance evaluation method for read mapping tool in clinical panel sequencing

机译:临床面板测序中读取映射工具的性能评估方法

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摘要

In addition to the rapid advancement in Next-Generation Sequencing (NGS) technology, clinical panel sequencing is being used increasingly in clinical studies and tests. However, tools that are used in NGS data analysis have not been comparatively evaluated in performance for panel sequencing. This study aimed to evaluate the tools used in the alignment process, the first procedure in bioinformatics analysis, by comparing tools that have been widely used with ones that have been introduced recently. With the accumulated panel sequencing data, detected variant lists were cataloged and inserted into simulated reads produced from the reference genome (h19). The amount of unmapped reads and misaligned reads, mapping quality distribution, and runtime were measured as standards for comparison. As the most widely used tools, Bowtie2 and BWA-MEM each showed explicit performance with AUC of 0.9984 and 0.9970 respectively. Kart, maintaining superior runtime and less number of misaligned read, also similarly possessed high level of AUC (0.9723). Such selection and optimization method of tools appropriate for panel sequencing can be utilized for fields requiring error minimization, such as clinical application and liquid biopsy studies.
机译:除了下一代测序(NGS)技术的快速进步之外,临床研究和试验中越来越多地使用临床面板测序。但是,在面板测序的性能下,NGS数据分析中使用的工具尚未相互评估。本研究旨在评估对准过程中使用的工具,通过比较已广泛使用的工具,该方法是生物信息学分析中最近介绍的工具。利用累积的面板测序数据,检测到的变型列表被编目并插入由参考基因组(H19)产生的模拟读数。作为比较标准,测量了未映射的读取和错位读取,映射质量分布和运行时的数量。作为最广泛使用的工具,Bowtie2和BWA-MEM分别显示出0.9984和0.9970的AUC显式性能。卡丁车,维持卓越的运行时间和更少数量的错位阅读,也同样拥有高水平的AUC(0.9723)。适合面板测序的工具的这种选择和优化方法可用于需要误差最小化的字段,例如临床应用和液检研究。

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