BIGMAC : breaking inaccurate genomes and merging assembled contigs for long read metagenomic assembly
BIGMAC : breaking inaccurate genomes and merging assembled contigs for long read metagenomic assembly
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DOI：
10.1186/s12859-016-1288-y
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发表时间：
2016-10-28
影响因子：
3
通讯作者：
Rao, Satish
中科院分区：
文献类型：
--
作者：
Lam, Ka-Kit;Hall, Richard;Rao, Satish
背景：仅使用长读长进行宏基因组从头组装的问题正在引起人们的关注。我们研究使用原始输入长读长进行后处理宏基因组组装是否可以提高质量。以前的方法主要集中在预处理读取和优化汇编程序。 BIGMAC 采用另一种视角来关注后处理步骤。结果：使用组装的重叠群和原始长读作为输入，BIGMAC 首先在可能错误组装的位置破坏重叠群，然后支架重叠群。我们对长读段组装的宏基因组进行的实验表明，BIGMAC 可以通过减少错误组装的数量来提高组装质量，同时保持或增加 N50 和 N75。此外，与其他后处理工具相比，BIGMAC 在所有测试数据集上显示出最大的 N75 与错误组装数量的比率。结论：BIGMAC 证明了后处理方法在提高宏基因组组装质量方面的有效性。
Background: The problem of de-novo assembly for metagenomes using only long reads is gaining attention. We study whether post-processing metagenomic assemblies with the original input long reads can result in quality improvement. Previous approaches have focused on pre-processing reads and optimizing assemblers. BIGMAC takes an alternative perspective to focus on the post-processing step.Results: Using both the assembled contigs and original long reads as input, BIGMAC first breaks the contigs at potentially mis-assembled locations and subsequently scaffolds contigs. Our experiments on metagenomes assembled from long reads show that BIGMAC can improve assembly quality by reducing the number of mis-assemblies while maintaining or increasing N50 and N75. Moreover, BIGMAC shows the largest N75 to number of mis-assemblies ratio on all tested datasets when compared to other post-processing tools.Conclusions: BIGMAC demonstrates the effectiveness of the post-processing approach in improving the quality of metagenomic assemblies.