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Exploiting sparseness in de novo genome assembly

机译:在De Novo基因组组装中利用稀疏性

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BackgroundThe very large memory requirements for the construction of assembly graphs for de novo genome assembly limit current algorithms to super-computing environments.MethodsIn this paper, we demonstrate that constructing a sparse assembly graph which stores only a small fraction of the observed k-mers as nodes and the links between these nodes allows the de novo assembly of even moderately-sized genomes (~500 M) on a typical laptop computer.ResultsWe implement this sparse graph concept in a proof-of-principle software package, SparseAssembler, utilizing a new sparse k-mer graph structure evolved from the de Bruijn graph. We test our SparseAssembler with both simulated and real data, achieving ~90% memory savings and retaining high assembly accuracy, without sacrificing speed in comparison to existing de novo assemblers.
机译:背景技术对于De Novo基因组组装将电流算法限制为超级计算环境的大量存储器要求。本文的方法,我们证明构建稀疏组装图,该图仅将观察到的K-MERS的小部分存储在一起这些节点之间的节点和链接允许在典型的笔记本电脑上甚至是典型的型基因组(〜500米)的DE Novo组装在典型的笔记本电脑上。方法在原则上的校样软件包,Sparseassembler中实现这个稀疏的图形概念,利用新的稀疏的k-mer图结构从de bruijn图表演变。我们用模拟和实际数据测试我们的sparseasembler,实现〜90%的内存节省并保持高装配精度,而不是与现有的De Novo装配商相比牺牲速度。

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