Winnow-tax: sensitive and precise taxonomic profiling of low-coverage organisms in shotgun metagenomes
- 1University of North Carolina at Charlotte
Abstract
Accurate species-level profiling of shotgun metagenomes becomes difficult when an organism is represented by only sparse sequence coverage. Per-read k-mer classifiers can retain sensitivity under these conditions, but short reads from conserved or shared genomic regions can generate false-positive calls among closely related references. More conservative marker-gene and genome-containment approaches generally provide stronger species-level specificity but may lose sensitivity as genomic sampling becomes sparse. We present winnow-tax, a two-stage taxonomic profiling pipeline that separates sensitive candidate nomination from genome-level confirmation. Candidate species are nominated using sylph, Kraken2, and a branch-rescue procedure, then reads are competitively recruited to a sample-specific reference set. Species presence is evaluated using read support, observed genome breadth, and a Lander-Waterman-based breadth ratio that compares observed breadth with the breadth expected at the measured mean depth. In a controlled synthetic community of 82 genomes with human DNA background, winnow-tax maintained a stronger precision-sensitivity balance than Kraken2/Bracken, sylph, and MetaPhlAn 4 as genome coverage decreased, with its advantage concentrated near the low-coverage detection boundary. In the CAMI III Toy Longitudinal Human Gut benchmark, winnow-tax had higher sensitivity than sylph (0.803 versus 0.672), lower precision (0.923 versus 0.970), and a modestly but significantly higher F1 score (0.858 versus 0.793). In a clinical enteric stool cohort with culture/PCR reference testing, winnow-tax achieved the best performance for Salmonella, detecting 33 of 43 culture-positive samples with two false-positive calls (F1 0.846 versus 0.811 for sylph). Together, these results support the advantage of a profiling strategy in which read-level classifications are accepted only when their genomic evidence is distributed as broadly as expected given the sequencing depth.
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BibTeX
@misc{sun2026winnowtax,
title = {{Winnow-tax: sensitive and precise taxonomic profiling of low-coverage organisms in shotgun metagenomes}},
author = {S. Sun and A. A. Fodor},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.02.756312},
url = {https://www.biorxiv.org/content/10.64898/2026.10.02.756312v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Winnow-tax: sensitive and precise taxonomic profiling of low-coverage organisms in shotgun metagenomes
AU - S. Sun
AU - A. A. Fodor
PY - 2026
DA - 2026/10/02
PB - bioRxiv
DO - 10.64898/2026.10.02.756312
UR - https://www.biorxiv.org/content/10.64898/2026.10.02.756312v1
AB - Accurate species-level profiling of shotgun metagenomes becomes difficult when an organism is represented by only sparse sequence coverage. Per-read k-mer classifiers can retain sensitivity under these conditions, but short reads from conserved or shared genomic regions can generate false-positive calls among closely related references. More conservative marker-gene and genome-containment approaches generally provide stronger species-level specificity but may lose sensitivity as genomic sampling becomes sparse. We present winnow-tax, a two-stage taxonomic profiling pipeline that separates sensitive candidate nomination from genome-level confirmation. Candidate species are nominated using sylph, Kraken2, and a branch-rescue procedure, then reads are competitively recruited to a sample-specific reference set. Species presence is evaluated using read support, observed genome breadth, and a Lander-Waterman-based breadth ratio that compares observed breadth with the breadth expected at the measured mean depth. In a controlled synthetic community of 82 genomes with human DNA background, winnow-tax maintained a stronger precision-sensitivity balance than Kraken2/Bracken, sylph, and MetaPhlAn 4 as genome coverage decreased, with its advantage concentrated near the low-coverage detection boundary. In the CAMI III Toy Longitudinal Human Gut benchmark, winnow-tax had higher sensitivity than sylph (0.803 versus 0.672), lower precision (0.923 versus 0.970), and a modestly but significantly higher F1 score (0.858 versus 0.793). In a clinical enteric stool cohort with culture/PCR reference testing, winnow-tax achieved the best performance for Salmonella, detecting 33 of 43 culture-positive samples with two false-positive calls (F1 0.846 versus 0.811 for sylph). Together, these results support the advantage of a profiling strategy in which read-level classifications are accepted only when their genomic evidence is distributed as broadly as expected given the sequencing depth.
ER -