Department of Microbiology, University of Innsbruck, Innsbruck, Austria.
Department of Horticultural Science, School of Agriculture, Shiraz University, Shiraz, Iran.
PLoS One. 2020 Dec 2;15(12):e0243241. doi: 10.1371/journal.pone.0243241. eCollection 2020.
In recent years, there has been a veritable boost in next-generation sequencing (NGS) of gene amplicons in biological and medical studies. Huge amounts of data are produced and need to be analyzed adequately. Various online and offline analysis tools are available; however, most of them require extensive expertise in computer science or bioinformatics, and often a Linux-based operating system. Here, we introduce "CoMA-Comparative Microbiome Analysis" as a free and intuitive analysis pipeline for amplicon-sequencing data, compatible with any common operating system. Moreover, the tool offers various useful services including data pre-processing, quality checking, clustering to operational taxonomic units (OTUs), taxonomic assignment, data post-processing, data visualization, and statistical appraisal. The workflow results in highly esthetic and publication-ready graphics, as well as output files in standardized formats (e.g. tab-delimited OTU-table, BIOM, NEWICK tree) that can be used for more sophisticated analyses. The CoMA output was validated by a benchmark test, using three mock communities with different sample characteristics (primer set, amplicon length, diversity). The performance was compared with that of Mothur, QIIME and QIIME2-DADA2, popular packages for NGS data analysis. Furthermore, the functionality of CoMA is demonstrated on a practical example, investigating microbial communities from three different soils (grassland, forest, swamp). All tools performed well in the benchmark test and were able to reveal the majority of all genera in the mock communities. Also for the soil samples, the results of CoMA were congruent to those of the other pipelines, in particular when looking at the key microbial players.
近年来,在生物和医学研究中,对基因扩增子的下一代测序(NGS)出现了真正的热潮。产生了大量的数据,需要进行充分的分析。有各种各样的在线和离线分析工具,但大多数都需要计算机科学或生物信息学方面的专业知识,并且通常需要基于 Linux 的操作系统。在这里,我们介绍“CoMA-比较微生物组分析”,这是一种用于扩增子测序数据的免费且直观的分析管道,可与任何常见的操作系统兼容。此外,该工具还提供了各种有用的服务,包括数据预处理、质量检查、聚类为操作分类单元(OTU)、分类分配、数据后处理、数据可视化和统计评估。该工作流程生成高度美观且适合出版的图形,以及以标准化格式(例如,制表符分隔的 OTU 表、BIOM、NEWICK 树)输出的文件,可用于更复杂的分析。CoMA 的输出通过使用具有不同样本特征(引物集、扩增子长度、多样性)的三个模拟群落进行基准测试进行了验证。性能与用于 NGS 数据分析的流行工具包 Mothur、QIIME 和 QIIME2-DADA2 进行了比较。此外,还通过一个实际示例展示了 CoMA 的功能,该示例调查了来自三种不同土壤(草地、森林、沼泽)的微生物群落。所有工具在基准测试中表现良好,并且能够揭示模拟群落中大多数属。对于土壤样本,CoMA 的结果与其他管道的结果一致,特别是在观察关键微生物参与者时。