• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>GMDS 2018, Annual Meeting >Using RNA-Seq Data for the Detection of a Panel of Clinically Relevant Mutations
【24h】

Using RNA-Seq Data for the Detection of a Panel of Clinically Relevant Mutations

机译：使用RNA-SEQ数据检测临床相关突变面板

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Somatic single nucleotide variants (SNVs) are genomic events with increasing implications in cancer treatment. The clinical standard for SNVs detection is whole genome/exome sequencing (WGS/WES) in matched tumor-normal samples. Yet, this is a very costly approach both economically and biologically and very often only tumor samples are sequenced. On the other hand, RNA sequencing (RNA-Seq) is the most popular technology to study gene expression, and has also the potential for a cost-effective identification of SNVs as an alternative to tumor-only WES. Here we present a method for the identification of SNVs in tumor-only RNA-Seq data putting a special focus on a small panel of clinically relevant SNVs. For evaluation purposes, we analyzed matched tumor-normal WES and tumor-only RNA-Seq data from 14 cancer patients. We compared SNVs detected in i) RNA-Seq by our method, ii) WES tumor-only by Mutect2 and iii) WES matched tumor-normal by Mutect2. We did a detailed evaluation for a reduced panel of clinically relevant SNVs and reliably identified in RNA-Seq data a subset of mutations for which we had pathological annotation. Hence, RNA-Seq rises as a cost-effective option to detect in parallel gene expression as well as a small panel of clinically relevant SNVs in research.
机译：体细胞单核苷酸变体（SNV）是具有越来越多的癌症治疗影响的基因组事件。 SNV检测的临床标准是匹配的肿瘤正常样品中的全基因组/外壳测序（WGS / WES）。然而，这是一种经济和生物学上的一种非常昂贵的方法，并且通常只测量肿瘤样品。另一方面，RNA测序（RNA-SEQ）是研究基因表达的最流行的技术，并且还具有成本效益鉴定SNV的潜力作为肿瘤的替代品。在这里，我们提出了一种用于鉴定肿瘤RNA-SEQ数据中SNV的方法，将特别重点放在一个临床相关的SNV面板上。为了评估目的，我们分析了来自14名癌症患者的肿瘤正常WES和肿瘤的RNA-SEQ数据。我们通过我们的方法，II）通过我们的方法进行比较II）RNA-SEQ检测到的SNVs，仅通过蛋白肿瘤 - 仅通过蛋白质匹配肿瘤正常。我们对临床相关的SNV的减少面板进行了详细的评估，并在RNA-SEQ数据中可靠地识别我们有病理注释的突变子集。因此，RNA-SEQ作为经常有效的选择，以检测并行基因表达以及在研究中的临床相关SNV小组中。

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