Genome Technology Branch, NHGRI/NIH, Bethesda, MD 20892-9400, USA.
Bioinformatics. 2013 Jun 15;29(12):1498-503. doi: 10.1093/bioinformatics/btt183. Epub 2013 Apr 24.
Extensive DNA sequencing of tumor and matched normal samples using exome and whole-genome sequencing technologies has enabled the discovery of recurrent genetic alterations in cancer cells, but variability in stromal contamination and subclonal heterogeneity still present a severe challenge to available detection algorithms.
Here, we describe publicly available software, Shimmer, which accurately detects somatic single-nucleotide variants using statistical hypothesis testing with multiple testing correction. This program produces somatic single-nucleotide variant predictions with significantly higher sensitivity and accuracy than other available software when run on highly contaminated or heterogeneous samples, and it gives comparable sensitivity and accuracy when run on samples of high purity.
利用外显子组和全基因组测序技术对肿瘤和匹配的正常样本进行广泛的 DNA 测序,使人们能够发现癌细胞中反复出现的遗传改变,但基质污染和亚克隆异质性的可变性仍然对现有检测算法构成了严峻挑战。
在这里,我们描述了一款名为 Shimmer 的公开可用软件,它使用带有多重检验校正的统计假设检验准确地检测体细胞单核苷酸变异。与其他可用软件相比,当运行于高度污染或异质性样本时,该程序产生的体细胞单核苷酸变异预测具有显著更高的灵敏度和准确性,而当运行于高纯度样本时,它具有可比的灵敏度和准确性。