Winnow-tax: sensitive and precise taxonomic profiling of low-coverage organisms in shotgun metagenomes

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.