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Detecting very low allele fraction variants using targeted DNA sequencing and a novel molecular barcode-aware variant caller

机译:使用靶向DNA测序和新型分子条形码识别变体调用程序检测非常低的等位基因片段变体

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摘要

BackgroundDetection of DNA mutations at very low allele fractions with high accuracy will significantly improve the effectiveness of precision medicine for cancer patients. To achieve this goal through next generation sequencing, researchers need a detection method that 1) captures rare mutation-containing DNA fragments efficiently in the mix of abundant wild-type DNA; 2) sequences the DNA library extensively to deep coverage; and 3) distinguishes low level true variants from amplification and sequencing errors with high accuracy. Targeted enrichment using PCR primers provides researchers with a convenient way to achieve deep sequencing for a small, yet most relevant region using benchtop sequencers. Molecular barcoding (or indexing) provides a unique solution for reducing sequencing artifacts analytically. Although different molecular barcoding schemes have been reported in recent literature, most variant calling has been done on limited targets, using simple custom scripts. The analytical performance of barcode-aware variant calling can be significantly improved by incorporating advanced statistical models.
机译:背景技术以非常低的等位基因分数检测DNA突变具有很高的准确性,将显着提高精准药物对癌症患者的有效性。为了通过下一代测序实现这一目标,研究人员需要一种检测方法:1)在丰富的野生型DNA混合物中有效捕获含有罕见突变的DNA片段; 2)对DNA文库进行广泛的测序以达到深层覆盖; 3)准确地将低水平的真实变异与扩增和测序错误区分开。使用PCR引物的靶向富集为研究人员提供了一种方便的方法,可使用台式测序仪对较小但最相关的区域进行深度测序。分子条形码(或索引编制)提供了一种独特的解决方案,可以从分析上减少测序伪像。尽管在最近的文献中已经报道了不同的​​分子条形码方案,但是大多数变体调用是使用简单的自定义脚本在有限的目标上完成的。通过合并高级统计模型,可以大大提高条形码识别变量调用的分析性能。

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