SomVarIUS: somatic variant identification from unpaired tissue samples
SomVarIUS: somatic variant identification from unpaired tissue samples
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DOI：
10.1093/bioinformatics/btv685
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发表时间：
2016-03-15
期刊：
影响因子：
5.8
通讯作者：
De, Subhajyoti
中科院分区：
文献类型：
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作者：
Smith, Kyle S.;Yadav, Vinod K.;De, Subhajyoti
动机：体细胞变异识别通常需要配对的肿瘤-正常组织样品。然而，配对的正常组织并不总是可在临床设置或存档samples.Results：我们提出SomVarIUS，一种计算方法，用于检测体细胞变异体使用高通量测序数据从未配对的组织样本。我们使用来自合成和真实的肿瘤样品的基因组数据来评估该方法的性能。与真实的肿瘤样本中的配对组织体细胞变异调用相比，SomVarIUS在与150 x覆盖率相似的exome-seq数据中识别出体细胞变异，精确度至少为67.7%，召回率至少为64.6%。我们通过识别福尔马林固定样本中的体细胞突变，并跟踪治疗前和治疗后白血病样本的靶向深度测序数据中致癌突变的克隆动力学，证明了SomVarIUS的实用性。
Motivation: Somatic variant calling typically requires paired tumor-normal tissue samples. Yet, paired normal tissues are not always available in clinical settings or for archival samples.Results: We present SomVarIUS, a computational method for detecting somatic variants using high throughput sequencing data from unpaired tissue samples. We evaluate the performance of the method using genomic data from synthetic and real tumor samples. SomVarIUS identifies somatic variants in exome-seq data of similar to 150 x coverage with at least 67.7% precision and 64.6% recall rates, when compared with paired-tissue somatic variant calls in real tumor samples. We demonstrate the utility of SomVarIUS by identifying somatic mutations in formalin-fixed samples, and tracking clonal dynamics of oncogenic mutations in targeted deep sequencing data from pre- and post-treatment leukemia samples.