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

机译:用SPARC约束变体检测:稀疏性,亲本相关性和覆盖范围

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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(SVS)是DNA序列的重排,例如逆变,缺失,插入和易位。检测SVS的常用方法已经从测试基因组序列数据并将其映射到参考基因组。最近,DNA测序研究可能包括数百,甚至数千个人,其中一些可能与其中有关。为了提高我们识别SV的能力,通过同时分析父母和子基因组来提高真正的SV信号。我们的算法配方 - SPARC - 采用SVS的稀疏性等现实标准,在整个基因组中的个体和可变测序覆盖之间的相关性。

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