Reads Binning Improves Alignment-Free Metagenome Comparison
Reads Binning Improves Alignment-Free Metagenome Comparison
复制标题
读取分箱改进了无比对宏基因组比较
DOI：
10.3389/fgene.2019.01156
复制
发表时间：
2019-11-21
影响因子：
3.7
通讯作者：
Sun, Fengzhu
中科院分区：
文献类型：
--
作者：
Song, Kai;Ren, Jie;Sun, Fengzhu
比较宏基因组样本是了解微生物群落之间关系的关键一步。最近，下一代测序（NGS）技术已经产生了来自不同环境的微生物群落的大量短读段数据。然而，这些短读段的组装可能是耗时且具有挑战性的。此外，基于测序的宏基因组比较方法受到不完整基因组和/或途径数据库的限制。相比之下，用于宏基因组比较的无干扰方法不依赖于基因组或途径数据库的完整性。尽管如此，现有的无标记方法，和，其仅使用一个马尔可夫链为每个样品建模元组模式，忽略了宏基因组数据内的异质性，其中潜在的数千种类型的微生物被测序。为了解决和中的这种缺陷，我们将NGS序列组织到不同的读取箱中，并构建了几个相应的马尔可夫模型。接下来，我们修改了我们以前的无干扰方法的定义，并且，为了使它们与使用所提出的读数箱的分析方案更兼容。然后，我们使用两个模拟的和三个真实的宏基因组数据集，以测试的效果的k元组的大小和马尔可夫顺序的背景序列上的这些新的无约束的方法的性能。为了可靠地比较宏基因组样品，我们新开发的具有读数分箱的无干扰方法在检测微生物群落之间的关系方面优于没有读数分箱的无干扰方法，包括它们是否形成群体或根据一些环境梯度而变化。
Comparing metagenomic samples is a critical step in understanding the relationships among microbial communities. Recently, next-generation sequencing (NGS) technologies have produced a massive amount of short reads data for microbial communities from different environments. The assembly of these short reads can, however, be time-consuming and challenging. In addition, alignment-based methods for metagenome comparison are limited by incomplete genome and/or pathway databases. In contrast, alignment-free methods for metagenome comparison do not depend on the completeness of genome or pathway databases. Still, the existing alignment-free methods,and, which modelk-tuple patterns using only one Markov chain for each sample, neglect the heterogeneity within metagenomic data wherein potentially thousands of types of microorganisms are sequenced. To address this imperfection inand, we organized NGS sequences into different reads bins and constructed several corresponding Markov models. Next, we modified the definition of our previous alignment-free methods,and, to make them more compatible with a scheme of analysis which uses the proposed reads bins. We then used two simulated and three real metagenomic datasets to test the effect of thek-tuple size and Markov orders of background sequences on the performance of thesede novoalignment-free methods. For dependable comparison of metagenomic samples, our newly developed alignment-free methods with reads binning outperformed alignment-free methods without reads binning in detecting the relationship among microbial communities, including whether they form groups or change according to some environmental gradients.