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MULKSG: MULtiple K Simultaneous Graph Assembly

机译:mulksg:多k同步图组装

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This work shows how to parallelize multi K de Bruijn graph genome assembly simultaneously, removing the bottleneck of iterative multi K assembly. The expected execution time on a single node with 40 cores is variable, with the average execution time for the entire pipeline over 16 datasets tested being 1613 s for SPAdes vs. 1581 s for MULKSG, with the MULKSG graph creation and traversal averaging 15% faster than SPAdes. We implement a multi-node implementation for the graph creation and traversal portions of the assembly, showing the speedups in Fig. 4. We show that when implemented correctly with correction phases performed per graph in parallel, the expected outcome is very close to the original method, in some cases having less errors while keeping the same NGA50 and genome coverage %. We show this works in practice, implementing with the popular genome assembler SPAdes. Further, this algorithmic change gets rid of the single node sequential bottleneck on multi K genome assembly, allowing for the use of parallel error correction, graph building, graph correction, and graph traversal. We implement a parallel version of the assembly and show the statistics are the same as when run on a single node. The code is open source and can be found at https://github.com/cwright7101/mulksg.
机译:这项工作显示了如何同时并行化多k de Bruijn曲线图基因组组件,从而消除迭代多K组件的瓶颈。具有40个核心的单个节点上的预期执行时间是可变的,具有超过16个数据集的整个流水链的平均执行时间,用于Mulksg的Spades与SPADES与SPADS与1581s)进行1613秒,Mulksg图创建和遍历平均速度较快15%而不是黑桃。我们为组装的图形创建和遍历部分实现了多节点实现,示出了图4中的加速。我们表明,当用每格并行执行的校正阶段正确实现时,预期结果非常接近原始结果方法,在某些情况下具有较少的误差,同时保持相同的NGA50和基因组覆盖率%。我们在实践中展示了这项工作,利用流行的基因组汇编器黑桃实施。此外,该算法变化将在多k基因组组件上摆脱单节点顺序瓶颈,允许使用并行误差校正,图形构建,图形校正和图形遍历。我们实现了程序集的并行版本,并显示统计信息与在单个节点上运行时的统计信息相同。代码是开源,可以在https://github.com/cwright7101/mulksg找到。

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