...
首页> 外文期刊>Scientific reports. >OpEx - a validated, automated pipeline optimised for clinical exome sequence analysis
【24h】

OpEx - a validated, automated pipeline optimised for clinical exome sequence analysis

机译:OPEX - 针对临床exome序列分析优化的验证,自动化管道

获取原文
   

获取外文期刊封面封底 >>

       

摘要

We present an easy-to-use, open-source Optimised Exome analysis tool, OpEx (http://icr.ac.uk/opex) that accurately detects small-scale variation, including indels, to clinical standards. We evaluated OpEx performance with an experimentally validated dataset (the ICR142 NGS validation series), a large 1000 exome dataset (the ICR1000 UK exome series), and a clinical proband-parent trio dataset. The performance of OpEx for high-quality base substitutions and short indels in both small and large datasets is excellent, with overall sensitivity of 95%, specificity of 97% and low false detection rate (FDR) of 3%. Depending on the individual performance requirements the OpEx output allows one to optimise the inevitable trade-offs between sensitivity and specificity. For example, in the clinical setting one could permit a higher FDR and lower specificity to maximise sensitivity. In contexts where experimental validation is not possible, minimising the FDR and improving specificity may be a preferable trade-off for slightly lower sensitivity. OpEx is simple to install and use; the whole pipeline is run from a single command. OpEx is therefore well suited to the increasing research and clinical laboratories undertaking exome sequencing, particularly those without in-house dedicated bioinformatics expertise.
机译:我们提供了易于使用的开源优化Exome分析工具,OPEX(http://icr.ac.uk/opex),可准确地检测临床标准的小规模变化,包括indels。我们使用实验验证的数据集(ICR142 NGS验证系列)评估了OPEX性能,这是一个大型1000个Exome数据集(ICR1000英国Exome系列)和临床先验父母Trio数据集。 OPEX对小型和大型数据集中的高质量基取代和短吲哚的性能优异,总灵敏度为95%,特异性为97%,低误报率(FDR)为3%。根据个人性能要求,OPEX输出允许其中优化灵敏度和特异性之间的不可避免的权衡。例如,在临床环境中,可以允许更高的FDR和更低的特异性来最大化敏感性。在不可能的实验验证的背景下,最小化FDR并提高特异性可能是稍微较低的敏感性的优选权衡。 OPEX易于安装和使用;整个管道从一个命令运行。因此,OPEX完全适用于越来越多的研究和临床实验室,特别是那些没有内部专用生物信息学专业知识的研究和临床实验室。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号