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Constrained variant detection with SPaRC: Sparsity, parental relatedness, and coverage

机译:SPaRC的受限变体检测:稀疏性,父母亲相关性和覆盖率

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Structural variants (SVs) are rearrangements of DNA sequences such as inversions, deletions, insertions and translocations. The common method for detecting SVs has been to sequence data from a test genome and map it to a reference genome. More recently, DNA sequencing studies may consist of hundreds, or even thousands of individuals, some of which may be related. In order to improve our ability to identify SVs, we boost the true SV signals by simultaneously analyzing parent and child genomes. Our algorithmic formulation - SPaRC - employs realistic criteria such as sparsity of SVs, relatedness between individuals and variable sequencing coverage throughout the genome.
机译:结构变体(SV)是DNA序列的重排,例如倒位,缺失,插入和易位。检测SV的常用方法是对来自测试基因组的数据进行测序并将其映射到参考基因组。最近,DNA测序研究可能由数百个甚至数千个个体组成,其中一些可能是相关的。为了提高我们识别SV的能力,我们通过同时分析父和子基因组来增强真正的SV信号。我们的算法公式-SPaRC-采用现实的标准,例如SV的稀疏性,个体之间的相关性以及整个基因组的可变测序范围。

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