RADIA：用于体细胞突变检测的RNA和DNA集成分析
RADIA: RNA and DNA Integrated Analysis for Somatic Mutation Detection
摘要：
体细胞单核苷酸变异的检测是表征癌症基因组的关键组成部分。到目前为止，突变识别算法主要集中在比较来自同一个体的正常和肿瘤基因组。近年来，像癌症基因组图谱（TCGA）这样的项目也对肿瘤RNA进行测序已经成为常规。在这里，我们提出了RADIA（RNA和DNA集成分析），一种将患者匹配的正常和肿瘤DNA与肿瘤RNA相结合以检测体细胞突变的方法。RNA的包含增加了检测体细胞突变的能力，特别是在低DNA等位基因频率下。通过整合DNA和RNA，我们能够挽救传统的突变调用算法所错过的回调，这些算法只检查DNA。RADIA被开发用于使用来自同一个体的DNA和RNA来鉴定体细胞突变。我们在TCGA的子宫内膜癌和肺腺癌的真实数据中证明了高灵敏度（84%）和非常高的特异性（98%和99%）。具有高DNA和RNA读段支持的突变具有超过99%的最高验证率。我们还介绍了一个模拟包，它将人工突变尖峰到真实数据，而不是模拟来自参考基因组的测序数据。我们评估敏感性的模拟数据，并证明我们的能力，包括RNA救援回叫在低DNA等位基因频率。最后，我们强调了由于RNA的掺入而被挽救回来的重要癌症基因的突变。软件可在https://github.com/aradenbaugh/radia/上获得
英文摘要：
The detection of somatic single nucleotide variants is a crucial component to the characterization of the cancer genome. Mutation calling algorithms thus far have focused on comparing the normal and tumor genomes from the same individual. In recent years, it has become routine for projects like The Cancer Genome Atlas (TCGA) to also sequence the tumor RNA. Here we present RADIA (RNA and DNA Integrated Analysis), a method that combines the patient-matched normal and tumor DNA with the tumor RNA to detect somatic mutations. The inclusion of the RNA increases the power to detect somatic mutations, especially at low DNA allelic frequencies. By integrating the DNA and RNA, we are able to rescue back calls that would be missed by traditional mutation calling algorithms that only examine the DNA. RADIA was developed for the identification of somatic mutations using both DNA and RNA from the same individual. We demonstrate high sensitivity (84%) and very high specificity (98% and 99%) in real data from endometrial carcinoma and lung adenocarcinoma from TCGA. Mutations with both high DNA and RNA read support have the highest validation rate of over 99%. We also introduce a simulation package that spikes in artificial mutations to real data, rather than simulating sequencing data from a reference genome. We evaluate sensitivity on the simulation data and demonstrate our ability to rescue back calls at low DNA allelic frequencies by including the RNA. Finally, we highlight mutations in important cancer genes that were rescued back due to the incorporation of the RNA. Software available at https://github.com/aradenbaugh/radia/
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