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Integrative pipeline for profiling DNA copy number and inferring tumor phylogeny

机译:用于分析DNA拷贝数和推断肿瘤的综合管线

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摘要

Copy number variation is an important and abundant source of variation in the human genome, which has been associated with a number of diseases, especially cancer. Massively parallel next-generation sequencing allows copy number profiling with fine resolution. Such efforts, however, have met with mixed successes, with setbacks arising partly from the lack of reliable analytical methods to meet the diverse and unique challenges arising from the myriad experimental designs and study goals in genetic studies. In cancer genomics, detection of somatic copy number changes and profiling of allele-specific copy number (ASCN) are complicated by experimental biases and artifacts as well as normal cell contamination and cancer subclone admixture. Furthermore, careful statistical modeling is warranted to reconstruct tumor phylogeny by both somatic ASCN changes and single nucleotide variants. Here we describe a flexible computational pipeline, MARATHON, which integrates multiple related statistical software for copy number profiling and downstream analyses in disease genetic studies.
机译:拷贝数变异是人类基因组的重要和丰富的变异来源,这与许多疾病有关,尤其是癌症。大规模并行的下一代测序允许使用精细分辨率复制数字分析。然而,这种努力已经满足了混合成功,挫折部分来自缺乏可靠的分析方法,以满足无数的实验设计产生的多样化和独特的挑战,并在遗传学研究中研究目标。在癌症基因组学中,检测体细胞拷贝数变化和等位基因特异性拷贝数(ASCN)的分析是通过实验偏差和伪影以及正常细胞污染和癌症亚旋塞混合物复杂化。此外,需要仔细的统计建模以通过体细胞ASCN变化和单核苷酸变异来重建肿瘤系统发生。在这里,我们描述了一个灵活的计算管道,马拉松,它集成了多种相关统计软件,用于疾病遗传研究中的拷贝数分析和下游分析。

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