TY - JOUR
T1 - Review of the Current State of Freely Accessible Web Tools for the Analysis of 16S rRNA Sequencing of the Gut Microbiome
AU - Ibal, Jerald Conrad
AU - Park, Yeong Jun
AU - Park, Min Kyu
AU - Lee, Jooeun
AU - Kim, Min Chul
AU - Shin, Jae Ho
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022/9
Y1 - 2022/9
N2 - 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.
AB - 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.
KW - 16S rRNA
KW - gut microbiome
KW - microbiome analysis
KW - next-generation sequencing
KW - web-based tool
UR - http://www.scopus.com/inward/record.url?scp=85138382232&partnerID=8YFLogxK
U2 - 10.3390/ijms231810865
DO - 10.3390/ijms231810865
M3 - Review article
C2 - 36142775
AN - SCOPUS:85138382232
SN - 1661-6596
VL - 23
JO - International Journal of Molecular Sciences
JF - International Journal of Molecular Sciences
IS - 18
M1 - 10865
ER -