BOA: A partitioned view of genome assembly.
BOA: A partitioned view of genome assembly.
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DOI：
10.1016/j.isci.2022.105273
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发表时间：
2022-11-18
期刊：
影响因子：
5.8
通讯作者：
Kalyanaraman, Ananth
中科院分区：
文献类型：
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作者：
An, Xiaojing;Ghosh, Priyanka;Keppler, Patrick;Kurt, Sureyya Emre;Krishnamoorthy, Sriram;Sadayappan, Ponnuswamy;Rajam, Aravind Sukumaran;Catalyurek, Umit V;Kalyanaraman, Ananth
从头基因组组装是计算分子生物学中的一个基本问题，旨在从基因组获得的一组短 DNA 序列（或读数）重建未知的基因组序列。沿着目标基因组的读数的相对顺序是事先未知的，这是组装过程复杂性增加的主要原因之一。在本文中，出于提高装配质量和暴露高度并行性的双重目标，我们提出了一种基于分区的方法。我们的框架 BOA（桶顺序组装）使用分桶以及基于图和超图的分区技术来生成读取的部分排序。这种部分排序使我们能够将读取集划分为不相交的块，这些块可以使用任何最先进的串行汇编器进行独立并行组装。实验结果表明，BOA 提高了整体装配质量和性能。基于图/超图分区的方法，可提高组装质量和运行时间 分桶和图/超图分区将读取分区为块 然后使用任何独立汇编器独立组装每个块 Hypergraph 变体可产生更精确的重叠群，并且比最先进的组装器 Genomics 更快；生物信息学；生物信息学中的高性能计算；算法。
De novo genome assembly is a fundamental problem in computational molecular biology that aims to reconstruct an unknown genome sequence from a set of short DNA sequences (or reads) obtained from the genome. The relative ordering of the reads along the target genome is not known a priori, which is one of the main contributors to the increased complexity of the assembly process. In this article, with the dual objective of improving assembly quality and exposing a high degree of parallelism, we present a partitioning-based approach. Our framework, BOA (bucket-order-assemble), uses a bucketing alongside graph- and hypergraph-based partitioning techniques to produce a partial ordering of the reads. This partial ordering enables us to divide the read set into disjoint blocks that can be independently assembled in parallel using any state-of-the-art serial assembler of choice. Experimental results show that BOA improves both the overall assembly quality and performance. A graph/hypergraph partitioning based method to improve assembly quality and runtime Bucketing and graph/hypergraph partitioning to partition reads into blocks Each block is then independently assembled using any standalone assembler Hypergraph variant produces more precise contigs and is faster than state-of-the-art assemblers Genomics; Bioinformatics; High-performance computing in bioinformatics; Algorithms.