NGS Core Facility, Kyungpook National University, Daehak-ro 80, Daegu 41566, Korea.
Department of Applied Biosciences, Kyungpook National University, Daehak-ro 80, Daegu 41566, Korea.
Int J Mol Sci. 2022 Sep 17;23(18):10865. doi: 10.3390/ijms231810865.
Owing to the emergence and improvement of high-throughput technology and the associated reduction in costs, next-generation sequencing (NGS) technology has made large-scale sampling and sequencing possible. With the large volume of data produced, the processing and downstream analysis of data are important for ensuring meaningful results and interpretation. Problems in data analysis may be encountered if researchers have little experience in using programming languages, especially if they are clinicians and beginners in the field. A strategy for solving this problem involves ensuring easy access to commercial software and tools. Here, we observed the current status of free web-based tools for microbiome analysis that can help users analyze and handle microbiome data effortlessly. We limited our search to freely available web-based tools and identified MicrobiomeAnalyst, Mian, gcMeta, VAMPS, and Microbiome Toolbox. We also highlighted the various analyses that each web tool offers, how users can analyze their data using each web tool, and noted some of their limitations. From the abovementioned list, gcMeta, VAMPS, and Microbiome Toolbox had several issues that made the analysis more difficult. Over time, as more data are generated and accessed, more users will analyze microbiome data. Thus, the availability of free and easily accessible web tools can enable the easy use and analysis of microbiome data, especially for those users with less experience in using command-line interfaces.
由于高通量技术的出现和改进以及相关成本的降低,下一代测序 (NGS) 技术已经可以实现大规模的采样和测序。随着产生的大量数据,数据的处理和下游分析对于确保有意义的结果和解释非常重要。如果研究人员对编程语言的使用经验很少,特别是如果他们是临床医生并且是该领域的初学者,那么在数据分析中可能会遇到问题。解决此问题的策略涉及确保轻松访问商业软件和工具。在这里,我们观察了当前可用于微生物组分析的免费网络工具的现状,这些工具可以帮助用户轻松地分析和处理微生物组数据。我们将搜索范围限制在免费的基于网络的工具上,并确定了 MicrobiomeAnalyst、Mian、gcMeta、VAMPS 和 Microbiome Toolbox。我们还强调了每个网络工具提供的各种分析,用户如何使用每个网络工具分析他们的数据,并指出了它们的一些限制。在上述列表中,gcMeta、VAMPS 和 Microbiome Toolbox 存在一些问题,使得分析更加困难。随着时间的推移,随着更多的数据生成和访问,将有更多的用户分析微生物组数据。因此,免费且易于访问的网络工具的可用性可以实现微生物组数据的轻松使用和分析,特别是对于那些使用命令行界面经验较少的用户。