Sunbeam: an extensible pipeline for analyzing metagenomic sequencing experiments
Sunbeam: an extensible pipeline for analyzing metagenomic sequencing experiments
复制标题
DOI：
10.1186/s40168-019-0658-x
复制
发表时间：
2019-03-22
期刊：
影响因子：
15.5
通讯作者：
Bittinger, Kyle
中科院分区：
文献类型：
--
作者：
Clarke, Erik L.;Taylor, Louis J.;Bittinger, Kyle
背景使用宏基因组测序实验分析混合微生物群落需要多个预处理和分析步骤来解释样品的微生物和遗传组成。分析步骤包括质量控制，适配器修剪，主机去污，宏基因组分类，读取组装，并对齐参考genomes.ResultsWe提出了一个模块化的和用户可扩展的管道称为阳光，执行这些步骤中的一致性和可重复的方式。它可以在单个步骤中安装，不需要对主机系统的管理访问，并且可以与大多数集群计算框架一起工作。我们还介绍了Komplexity，一个软件工具，以消除潜在的问题，低复杂性的核苷酸序列从宏基因组数据。Sunbeam管道的一个独特组件是一个易于使用的扩展框架，使用户能够将自定义处理或分析步骤直接添加到工作流程中。管道及其扩展框架有据可查，在日常使用，并定期updated.ConclusionsSunbeam提供了一个基础，建立更深入的分析，并通过删除有问题的，低复杂性的读取和标准化后处理和分析步骤，使宏基因组测序实验中的比较。Sunbeam是使用Snakemake工作流管理软件用Python编写的，可以在github.com/sunbeam-labs/sunbeam上根据GPL v3免费获得。
BackgroundAnalysis of mixed microbial communities using metagenomic sequencing experiments requires multiple preprocessing and analytical steps to interpret the microbial and genetic composition of samples. Analytical steps include quality control, adapter trimming, host decontamination, metagenomic classification, read assembly, and alignment to reference genomes.ResultsWe present a modular and user-extensible pipeline called Sunbeam that performs these steps in a consistent and reproducible fashion. It can be installed in a single step, does not require administrative access to the host computer system, and can work with most cluster computing frameworks. We also introduce Komplexity, a software tool to eliminate potentially problematic, low-complexity nucleotide sequences from metagenomic data. A unique component of the Sunbeam pipeline is an easy-to-use extension framework that enables users to add custom processing or analysis steps directly to the workflow. The pipeline and its extension framework are well documented, in routine use, and regularly updated.ConclusionsSunbeam provides a foundation to build more in-depth analyses and to enable comparisons in metagenomic sequencing experiments by removing problematic, low-complexity reads and standardizing post-processing and analytical steps. Sunbeam is written in Python using the Snakemake workflow management software and is freely available at github.com/sunbeam-labs/sunbeam under the GPLv3.