MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets
MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets
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DOI：
10.1093/bioinformatics/btv638
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发表时间：
2016-02-15
期刊：
影响因子：
5.8
通讯作者：
Singer, Steven W.
中科院分区：
文献类型：
--
作者：
Wu, Yu-Wei;Simmons, Blake A.;Singer, Steven W.
从宏基因组数据集中恢复基因组是确定潜在未培养群体功能作用的关键步骤。我们之前开发了MaxBin，这是一种用于从宏基因组中高通量回收微生物基因组的自动分箱方法。在这里，我们提出了一个扩展的分箱算法，MaxBin 2.0，它恢复基因组从一个集合的宏基因组数据集的共组装。在模拟数据集上的测试表明，MaxBin 2.0在恢复单个基因组方面具有高度准确性，MaxBin 2.0对环境样品中的几个宏基因组的应用表明，它可以实现两个互补的目标：与单个样品相比，恢复更多的细菌基因组以及比较不同采样环境之间的微生物群落组成。
The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments.