HiFiTaxa: a reproducible analysis pipeline for full length 16S rRNA gene and ITS amplicon sequencing from PacBio reads
- 1The University of Sydney
Abstract
Long-read amplicon sequencing profiles communities at high resolution, but taxonomic accuracy depends on the reference, classifier and the parameters used. Here, we present HiFiTaxa, a reproducible, single command Nextflow pipeline for PacBio HiFi 16S rRNA gene and fungal ITS amplicons. It builds versioned references from current GTDB and UNITE releases and supports Bayesian lowest common ancestor (BLCA) and naive Bayes (NB) classifiers and the read level profilers Emu (16S rRNA gene) and EMITS (ITS). We benchmarked them on mock communities and on holdouts with 10% of GTDB or UNITE databases sequences withheld. On the 16S rRNA gene mock of 20 species, BLCA detected all 20 species and reported two false positives, NB detected 17 and reported none, and Emu detected all 20 and reported eight. In the GTDB holdout, for taxa represented in the reference, BLCA reached 80.0% species level accuracy against 48.1% for the exact matching species step of NB. However, NB produced fewer incorrect assignments for taxa absent from the reference. On fungal ITS, BLCA had slightly higher holdout accuracy at species level(54.7%) against 52.2% for NB. NB was more conservative for novel taxa, and EMITS detected the most mock species. HiFiTaxa therefore offers a single reproducible workflow that uses current GTDB and UNITE releases and enables users to choose between different classifier algorithms depending on their needs.
Related
- POAnoise: A Graph-based Denoising Pipeline for Amplicon Sequencing Data
- SeCAT (Sequence Consensus Amplicon Trimming): a simulation-informed Nextflow pipeline for cross-study harmonisation of 16S rRNA metabarcoding datasets
- ASPIRE: the Amplicon Sequencing Profiler for Investigating Respiratory Ecosystems
- A Reproducible MRI‐Based Pipeline for Longitudinal Tracking of Laser‐Assisted Bioprinted Cells in Three‐Dimensional Constructs
- Comparison of long and short 16S rRNA gene amplicon sequencing for agricultural soil and grain microbiomes using custom Kinnex libraries
BibTeX
@misc{garritano2026hifitaxa,
title = {{HiFiTaxa: a reproducible analysis pipeline for full length 16S rRNA gene and ITS amplicon sequencing from PacBio reads}},
author = {A. N. Garritano and F. Modolon and C. R. Warren},
howpublished = {bioRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.03.763332},
url = {https://www.biorxiv.org/content/10.64898/2026.11.03.763332v1},
note = {CC BY-ND},
}
RIS
TY - UNPB
TI - HiFiTaxa: a reproducible analysis pipeline for full length 16S rRNA gene and ITS amplicon sequencing from PacBio reads
AU - A. N. Garritano
AU - F. Modolon
AU - C. R. Warren
PY - 2026
DA - 2026/11/03
PB - bioRxiv
DO - 10.64898/2026.11.03.763332
UR - https://www.biorxiv.org/content/10.64898/2026.11.03.763332v1
AB - Long-read amplicon sequencing profiles communities at high resolution, but taxonomic accuracy depends on the reference, classifier and the parameters used. Here, we present HiFiTaxa, a reproducible, single command Nextflow pipeline for PacBio HiFi 16S rRNA gene and fungal ITS amplicons. It builds versioned references from current GTDB and UNITE releases and supports Bayesian lowest common ancestor (BLCA) and naive Bayes (NB) classifiers and the read level profilers Emu (16S rRNA gene) and EMITS (ITS). We benchmarked them on mock communities and on holdouts with 10% of GTDB or UNITE databases sequences withheld. On the 16S rRNA gene mock of 20 species, BLCA detected all 20 species and reported two false positives, NB detected 17 and reported none, and Emu detected all 20 and reported eight. In the GTDB holdout, for taxa represented in the reference, BLCA reached 80.0% species level accuracy against 48.1% for the exact matching species step of NB. However, NB produced fewer incorrect assignments for taxa absent from the reference. On fungal ITS, BLCA had slightly higher holdout accuracy at species level(54.7%) against 52.2% for NB. NB was more conservative for novel taxa, and EMITS detected the most mock species. HiFiTaxa therefore offers a single reproducible workflow that uses current GTDB and UNITE releases and enables users to choose between different classifier algorithms depending on their needs.
ER -