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A Flow Procedure for the Linearization of Genome Sequence Graphs

机译:基因组序列图线性化的流程

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Efforts to incorporate human genetic variation into the reference human genome have converged on the idea of a graph representation of genetic variation within a species, a genome sequence graph. A sequence graph represents a set of individual haploid reference genomes as paths in a single graph. When that set of reference genomes is sufficiently diverse, the sequence graph implicitly contains all frequent human genetic variations, including transloca-tions, inversions, deletions, and insertions. In representing a set of genomes as a sequence graph one encounters certain challenges. One of the most important is the problem of graph linearization, essential both for efficiency of storage and access, as well as for natural graph visualization and compatibility with other tools. The goal of graph linearization is to order nodes of the graph in such a way that operations such as access, traversal and visualization are as efficient and effective as possible. A new algorithm for the linearization of sequence graphs, called the flow procedure, is proposed in this paper. Comparative experimental evaluation of the flow procedure against other algorithms shows that it outperforms its rivals in the metrics most relevant to sequence graphs.
机译:将人类遗传变异纳入参考人类基因组的努力集中在一个物种内遗传变异的图形表示即基因组序列图的思想上。序列图将一组单个单倍体参考基因组表示为单个图中的路径。当该组参考基因组足够多样化时,序列图将隐式包含所有常见的人类遗传变异,包括易位,倒位,缺失和插入。在将一组基因组表示为序列图时,会遇到某些挑战。最重要的问题之一是图形线性化问题,这对于存储和访问的效率以及自然图形可视化和与其他工具的兼容性都是必不可少的。图形线性化的目的是对图形的节点进行排序,以使诸如访问,遍历和可视化之类的操作尽可能高效。本文提出了一种用于序列图线性化的新算法,称为流过程。与其他算法相比,对流程的比较实验评估表明,在与序列图最相关的指标上,它的表现优于竞争对手。

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