Taxonova

Taxonova assigns 16S rRNA and rRNA operon amplicon sequences to a lineage from domain to species, with a confidence at each rank, and stops at the deepest rank it is confident about.

Classify your sequences

No installation: upload a FASTA file to the web app.

Command line (Python 3.10 or later):

pip install taxonova
taxonova classify reads.fasta --model v4

The model is downloaded on first use (about 240 MB, once). Results are written to reads.taxonova.tsv.

Models

Species names follow GTDB. Other references, as preview models: RDP 19 (v4-rdp, v3v4-rdp, v5v7-rdp) and SILVA 138.2 (v3v4-silva), for example --model v3v4-silva; their output uses that reference's names (model cards). Run taxonova models to see all models and which are downloaded.

Output

One row per sequence: a label and a confidence for each rank (columns for phylum to family not shown here).

sequence_id   domain    domain_confidence  ...  genus       genus_confidence  species                 species_confidence
f1eb3726...   Bacteria  1.0000             ...  Prevotella  0.9988            Prevotella pectinovora  0.9988

A rank below its confidence threshold, and every rank below it, reads Unclassified.

Options you may want

taxonova classify reads.fasta -m v3v4 -o results.tsv   # model and output file
taxonova classify reads.fasta -m v4 --confidence 0.9   # stricter (default 0.8)
taxonova classify reads.fasta -m v4 --threads 8        # more CPU threads
taxonova classify reads.fasta -m v4 --genus-threshold 0.6   # set one rank

--confidence sets the species threshold, and the other ranks scale with it. From Python: taxonova.classify("reads.fasta", model="v4") returns a pandas DataFrame.

Links

• Documentation: models, output and thresholds, Python, training your own model
• Changelog
• Paper and the benchmark used in it, TaxoBench
• Report a problem or ask for a model

Citation

If you use Taxonova, please cite:

Kakabra K, Patel S, Temko A, Claesson MJ. Taxonova: deep learning enables fast and confidence-aware microbiome species-level amplicon classification. PLoS Comput Biol. 2026;22(10):e1014912. doi:10.1371/journal.pcbi.1014912

Taxonova is developed in the Claesson Lab, University College Cork and APC Microbiome Ireland, and released under the MIT licence.