NANOTAXI: A Shiny-Based GUI for Real-Time Classification and Analysis of 16S rRNA Nanopore Reads
Abstract
Real-time taxonomic classification of nanopore amplicon sequencing data enables rapid insights into microbial communities, with applications in clinical diagnostics, environmental monitoring, and outbreak surveillance. However, bridging the gap between long-read data and interpretable results often requires specialised bioinformatics expertise. There remains a need for integrated, user-friendly software that combines live data acquisition with downstream microbiome analysis. Here we present NANOTAXI, a fully automated Shiny-based GUI for the classification of barcoded 16S rRNA gene sequences generated by Oxford Nanopore sequencing. The platform supports four taxonomic classifiers, integrated with five reference databases, enabling flexible selection of classification strategies based on user requirements and available computational resources. In addition to real-time monitoring, NANOTAXI performs cohort-level analyses, including alpha and beta diversity, ordination, differential abundance testing, and functional inference using PICRUSt2. Validation using barcoded synthetic communities comprising pooled genomic DNA from clinically relevant bacterial species and the ZymoBIOMICS mock community demonstrated that NANOTAXI generated biologically coherent taxonomic and functional profiles. Benchmarking revealed clear trade-offs between computational performance and taxonomic specificity. Emu provided the lowest observed species-level false-positive rate, whereas Kraken2 offered the fastest classification and enabled continuous near-real-time monitoring across all tested databases. NANOTAXI is open source and freely available at https://github.com/Nirmal2310/NANOTAXI under the GPL version 3 license.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 0
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- NanoVI: a Bayesian variational inference Nextflow pipelinefor species-level taxonomic classification from full-length16S rRNA Nanopore reads
Carolina Curiqueo, Francisco Fuentes-Santander, Juan Antonio Ugalde·bioRxiv·Mar 10, 2026
- A novel barcoded nanopore sequencing workflow of high-quality, full-length bacterial 16S amplicons for taxonomic annotation of bacterial isolates and complex microbial communities
Julian Dommann, Jakob Kerbl-Knapp, … Pierre H. H. Schneeberger·mSystemsPeer-reviewed·Sep 10, 2024
- NanoCLUST: a species-level analysis of 16S rRNA nanopore sequencing data
Hector Rodríguez‐Pérez, Laura Ciuffreda, Carlos Flores·BioinformaticsPeer-reviewed·Oct 5, 2020
- High-accuracy meets high-throughput for microbiome profiling with near full-length 16S rRNA amplicon sequencing on the Nanopore platform
- NAP: an open-source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data
Luke B. Jones, Stefan Bagby·BMC BioinformaticsPeer-reviewed·Jun 29, 2026
- Evaluation of Oxford Nanopore MinION Sequencing for 16S rRNA Microbiome Characterization
Xiao Ma, Elyse Stachler, Kyle Bibby·bioRxiv·Jan 29, 2017