Background: Advances in high-throughput sequencing accessibility have democratized small subunit ribosomal RNA gene sequence data collection, coincident with an increasing availability of computational tools for sequence data processing, multivariate statistics, and data visualization. However, existing tools often require programming ability and frequent user intervention that may not be suitable for fast-paced and large-scale data analysis by end user microbiologists who are unfamiliar with the Linux command line environment or who prefer interactions with a GUI. Here we present AXIOME3, which is a completely redeveloped AXIOME pipeline that streamlines small subunit ribosomal RNA data analysis by managing QIIME2, R, and Python-associated analyses through an interactive web interface.
Findings: AXIOME3 comes with web GUI to improve usability by simplifying configuration processes and task status tracking. Internally, it uses an automated pipeline that is wrapped around QIIME2 to generate a range of outputs including amplicon sequence variant tables, taxonomic classifications, phylogenetic trees, biodiversity metrics, and ordinations. The extension module for AXIOME3 provides advanced data visualization tools such as principal coordinate analysis, bubble plots, and triplot ordinations that can be used to visualize interactions between a distance matrix, amplicon sequence variant taxonomy, and sample metadata.
Conclusions: Because repeat analysis of small subunit ribosomal RNA amplicon sequence data is challenging for those who have limited experience in command line environments, AXIOME3 now offers rapid and user-friendly options within an automated pipeline, with advanced data visualization tools and the ability for users to incorporate additional analyses easily through extension. AXIOME3 is completely open source (https://github.com/neufeld/AXIOME3, https://github.com/neufeld/AXIOME3-GUI), and researchers are encouraged to modify and redistribute the package.
Keywords: 16S rRNA genes; QIIME2; SSU rRNA; interactive pipeline; microbial ecology.
© The Author(s) 2021. Published by Oxford University Press GigaScience.